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AMD vs Intel, der ultimative Gaming-Showdown: 5GHz FX-9590 vs i7-4960X Als AMD angekündigt, es würde eine 5GHz-Version seiner FX-Klasse Prozessoren im vergangenen Sommer zu bauen, war die Reaktion aus der Enthusiastengemeinschaft gemischt. Einerseits erreichte AMD gleichzeitig seine Wurzeln und bot einen Chip deutlich schneller als alles andere in seinem eigenen Produktstapel an. Auf der anderen Seite, sogar bei 5 GHz, würde die CPU eine harte Zeit im Wettbewerb mit Intel8217s Haswell und Ivy Bridge-E haben. Vor kurzem verbrachten wir einige Zeit mit einem Maingear Shift, der mit dem FX-9590 ausgestattet war, und beschlossen, den Chip in einem Kopf-an-Kopf-Gaming-Showdown gegen Intel8217s Core i7-4960X durchzusetzen. We8217ve gewählt, um auf Gaming aus zwei Gründen zu konzentrieren. Zuerst war Spiel immer einer der Bereiche, in denen die ursprünglichen FX-Prozessoren leuchteten, und es8217s eine Frage that8217s kommen oben mehrmals in unseren letzten Piledriver Bewertungen. Mehrere Leser haben für einen Kopf-an-Kopf-Gaming-Artikel gefragt, und die FX-95908217s starten, kombiniert mit dem R9 290X8217s Debüt in diesem Monat. Machte es eine ideale Zeit, um die Frage zu prüfen, wie gut Intel und AMD-Plattformen vergleichen. Der zweite Grund ist, dass außerhalb der Gaming-Arena, die FX-9590 zugegebenermaßen kämpft. Während es mit einer höheren Taktrate läuft, hat es immer noch Probleme bei leichten Thread-Workloads, wo Haswell und Ivy Bridge auf bessere Single-Threaded-Performance und überlegene Skalierung über 2-4 Kerne verlassen können. Preis, Verfügbarkeit und die Intel Ivy Bridge-E Als ich diese Geschichte begann, war die FX-9590 nur von OEMs und zum Preis von 800. Frame-Treiber-Treiber Fragen verzögert meine Tests, wie mehrere GPU startet von AMD im Oktober. Die Preislücke, die zwischen der Ivy Bridge-E und der FX-9590 geöffnet wurde, bedeutet, dass die 1000 Intel CPU nicht mehr der beste Vergleichspunkt ist. Dies wird letztlich in Betracht gezogen. Auf der anderen Seite erlaubte uns die Verzögerung, Leistungsdaten für den R9 290X hinzuzufügen und gegen den Radeon 7990 zu vergleichen, den die Shift standardmäßig mitgeliefert hat. Apropos der Shift, Maingear8217s vertikalen Gehäuse mit einem benutzerdefinierten Rosso Scuderia Farbauftrag ist ein schön gestaltetes System, das mit einem benutzerdefinierten 180mm Maingear Epic CPU-Kühler und so eng wie eine Verkabelung Job, wie Sie fragen konnte. In der beträchtlichen Zeit, die wir mit dem Rigg verbrachten, hatten wir keine Probleme 8212 keine Lockups, keine Abstürze, keine Hardwareprobleme irgendwelcher Art. Offensichtlich, wenn Sie Top-Dollar für ein Boutique-System bezahlen, erwarten Sie diese Art von benutzerdefinierten Geräten und Aufmerksamkeit zum Detail, aber wir waren mit der Konfiguration des systems8217s gut zufrieden. Dieser Artikel konzentriert sich in erster Linie auf die FX-9590 CPU 8212 für alle Details über die Shift selbst, traf unsere PC-Magazin-Überprüfung der Maingear Shift. Unsere hohe Meinung über die Verschiebung änderte sich, nachdem sie wesentlich mehr Zeit damit verbracht hatte. Wir bauten ein Intel Core i7-4960X Ivy Bridge-E Vergleichssystem mit 16 GB leichten Mushkin DDR3-2133, einem identischen SSD (Samsung 840 Evo) und getestet beide Systeme auf einer Radeon 7990 und Radeon 290X. Jedes Spiel wurde bei 19202151080 getestet, aber wir variierten die visuellen Einstellungen etwas abhängig von dem Spiel in Frage. Wir brechen diese ab, wie wir gehen. Das Ziel war, eine Testumgebung zu bewahren, die nicht vollständig GPU-gebunden sein sollte, sondern um Spiele auf Grafik-Ebenen zu testen, die repräsentativ waren, wie High-End-Gamer jedes System konfigurieren würden. We8217ve untersuchte auch die Leistung in Bezug auf Frame-Raten und Frame-Latenz mit dem handlichen Open-Source-Tool FRAFS, die Fraps-Ausgang analysiert. Frame-Timing ist ein Metrik verwendet, um Latenz und Stottern in einem Spiel zu untersuchen, und es8217s ein Bereich, in dem AMD8217s Radeon-Karten hatte eine grobe Zeit von ihm Anfang dieses Jahres. (Siehe: Nach fast 20 Jahren bewegt sich das GPU-Benchmarking an Frames pro Sekunde vorbei.) AMD hat in diesem Sommer einen Frame-Pacing-Treiber herausgebracht und seither regelmäßig aktualisiert, so dass wir auch sehen können, was für ein Leistungsunterschied es ist Macht im Vergleich zu der Single-GPU Radeon R9 290X. Dazu haben wir ein Diagramm der schlechtesten 1 der Frames enthalten, die wir getestet haben. Dies ist eine untere Grenze für die Rahmenlatenz. Hierbei handelt es sich um die Faustregel, wenn es darum geht, Frame-Latenzwerte zu bewerten. Lower ist besser als höher, 16.7ms ist die Grenze für 60 fps Gaming, und 33.3ms ist die 30 fps Marke. Aber 8212 und dies ist der Schlüssel 8212 die Unterschiede mehr, desto höher die Figur. Der Unterschied zwischen 12ms und 16ms ist viel weniger als die Lücke zwischen 25ms und 33ms 8212, obwohl der Unterschied ist nur 1,33x. Frame-Tropfen unter 30 fps sind bemerkenswerter als 60 fps, und alles, was Sie in die Teens oder unter 10 fps schiebt, ist besonders ungeheuerlich. Sie denken nicht voran. Amd verbraucht viel mehr Power um dorthin zu gelangen. Dies ist der Grund, warum Intel hat eine solche Kante über amd überall atm. In Ordnung für AMD zu bekommen, wo Intel ist, müssen sie cpus overclock zu 5ghz und über verbrauchend 220W, wo ein normales i7 nicht mehr als 95W true, hat Intel einen Vorteil, aber sehr klein (im Gaming sind die gleichen) Nur FX (octa Core) Prozessoren verbrauchen so viel Leistung und nicht alle FXs8230 aber, wenn ich aussehe, kümmere ich mich nicht für den Stromverbrauch .. Ich habe PSU für 5 FX-CPU von 220W. Wenn Sie nicht über eine gute Stromversorgung, ist der gesamte PC Mist. Das Netzteil ist der Computer 8220heart8221. Ok, AMD verbraucht viel Watt (nur FX), aber Intel ist ungewöhnlich teuer. 8220perfomance per dollar82218230 Wenn ich so viel Geld gebe, dann erwarte ich eine Menge abendliche Vorstellungen8230 hier ist GREAT Beispiel, 860K (verbrauchen nur 95W) Hexe kosten nur 56 auf Amazon. Hier ist Intel i5 4430 (TDP ist das gleiche) und kosten 187 auf Amazon. Jetzt, schauen Sie die Benchmark, haben die gleiche Punktzahl wie ultra billig 860K (sehr viel ist, wie es ist mit i5 2500k und mit extra teuren i7 2600k, Link unten) hier ist Link von 860k vs i5 4430: cpubosscpusIntel-Core-i5-4430 - VS-AMD-Athlon-X4-860K hier ist Link 860k vs i7 2600k: jetzt sehen sehr gut, wie ist klein Unterschied in Perfomance und wie hughe ist anders im Preis. Warum dann kaufe ich ex. I5 4430 ist die gleiche Leistung wie 860K und kosten viel mehr als 860K8230 natürlich werde ich für die gleiche Leistung zahlen viel weniger und kaufen 860K. I8217m nicht für die gleiche Leistung bezahlen 3 mal mehr bezahlen. Aber das ist kein Thema, das wir reden. Wir reden über neue ZEN CPUs Hexe kommt mit 20 besseren Hyperthreadind von Intel HT, mit niedrigem TDP und wie Sie sehen, kommt mit 16 Kerne und 32 Fäden. Mit DDR4-Speicher. HBM etc. ist genug, um zu sehen, wie es leistungsstarke CPUs und dies ist nicht Server-CPUs. Diese CPUs kommt mit neuen AM4-Buchse. Up Ich veröffentlichte einen Kommentar, wo schreiben alle Details, sehen Sie diese. Wenn Sie seethis, dann sagen Sie mir, Hexe Intel CPU wird bettter und stärker von dieser Bestie Sie nicht vordenken, nicht me8230 Ich würde sagen, für Leute, die don8217t haben die extra 300 oder so für die i7and erhalten die AMD statt, IS Denken vorne vergessen 3-5 extra fps, wenn einige Leute don8217t sogar den Preisunterschied in einer Woche bezahlen. Und that8217s nur die 8220difference8221 im Preis. Dude, ich habe 4 Computer (ein Laptop) whitch Ich benutze und Teile für mindestens 5 oder 6 Computer zu do8230 dies ist mein Job, ich bin Computer-Techniker und habe meinen eigenen Service. Ich täglich verbringen mehr Geld auf dem Computer, als Sie in 3 months8230 ausgeben und ich habe und AMD PCs und Intel PCs8230 aber ich spreche über Preis-Leistung. Dies ist Beispiel, 860k und i5 4430 oder i7 2600k8230 860K und 4430 haben die gleiche Leistung, die gleiche Punktzahl (Link unten), 2600k ist LITTLE besser und kostet 5-6 mal mehr als 860k8230 4430 ist 3 mal teuer und haben die gleiche perfomanse . PERFOMANZ FÜR DOLLAR. Sie verstehen, was I8217m sagen oder ich habe, um Sie für viel, viel weniger Geld Sie bekam das gleiche oder besser perfomanse8230 Ich weiß sehr gut über ich reden. Und wie ich sagte, ich habe und AMD und Intel und für Spiele ist besser AMD8230 AMD ist nicht für Benchmark Seine Stärke sehen Sie, wenn Sie es verwenden. Und AMD ist voll für Spiele optimiert und Intel not8230 ist auch sehr gut für Spiele, ist aber nicht für Spiele optimiert. Jetzt zeige ich dir AMD vs AMD (link unten) ex. 860K VS 8320E (neuere Version von 8320, haben niedrigere TDP) und 860K vs 83008230 perfomance ist auch das gleiche und alle diese CPUs haben 8 Kerne und 860K nur 48230 dann warum ist besser oder die gleiche SINGLE CORE PERFOMANCE. Und jetzt genießen in benchmark8230 (Ich habe vergessen, was Sie sagen, auf neue AMD-CPUs mit ZEN-Architektur und mit Hyperthreading-Technologie. 16 Kerne und 32 Thread, niedrige TDP, mit DDR4-Speicher etc8230 und das ist nicht Server CPUs8230 kommt im Jahr 2016. Ich frage mich, Die Intel-CPUs werden stärker als diese AMD-CPUs .. hmmmm ..) LINKS (schauen Preis von beiden CPUs): 860K vs i5 4430: cpubosscpusIntel-Core-i5-4430-vs-AMD-Athlon-X4-860K Jetzt verstehen Sie Was I8217m sagen, wie sind Sie dumm und nicht informiert, OMG8230 welche Art von Schule Sie fertig Klempner vielleicht. Es wäre interessant zu sehen, sie im Vergleich zu 2k-Auflösungen, jetzt testen sie bei dieser Auflösung wird es mehr Druck auf die Grafikkarte und die CPU sowie What8217s die tdp der fx und der 4960x Nun, wenn sie ein Setup von IntelAMD testen können Vs AMDAMD gegen AMDNVIDIA gegen INTELNVIDIA. Die 9590 hat eine TDP von 220W. Der 4960X verfügt über einen 130W TDP. Aber wenn you8217re Kauf einer 3500 8211 5500 Computer, Sie wahrscheinlich don8217t Pflege. ) Auch eine Betrachtung der Nvidia Leistung auf beiden Plattformen war weit außerhalb des Bereichs dieses Projektes. Das ist wahr, ein 3500-5500 PC wird ein Overkill für mich und viele andere, I8217m glücklich mit meinem 700 pc. Hoffe, dass die 2k Bewertungen bald zu sehen. Sind Sie wissen, andere CPU. In allen Beiträgen, sagen Sie nur über FX 9590 und 4960X. Auf allen Post. Nein Ihr Post mit einer anderen CPU dies lernen Sie 2 Jahre über diese beiden CPU. D OMG. Shut up niemand hört Sie Don8217t Sie bekommen es Ihnen ungebildetes Stück Scheiße wer doesn8217t wissen, wie man mit anderen reden gehen fuck ein Schwein. Dont lesen, wenn Sie dont like it8230 fck Inttel Fanboy. Bist du jealuos Intel sinkt wie Titanic8230 Warum sind Sie gestört, wenn niemand mir zuhört. Kleine Schwein ist gestört: D LOL und ficken Sie. Fuck off out8230 taliban AMD-Chip kosten 400 Intel-Chip kosten 1.000 Eine 2,5-fache Erhöhung des Preises ist gleichbedeutend mit einem Vergleich eines Chevy Volt mit einem Tesla-Modell S Die 5 Leistungssteigerung des Intel-Chips ist völlig keine Relevanz für die 250 erhöhen In Kosten. Während die Tesla Model S Leistung und User Experience 2,5 fach besser ist als ein Chevy Volt. Als I8217ve sagte: Dieser Artikel wurde etwas verzögert durch unvermeidliche Umstände. Als ich anfing, war der 1000-Intel-Chip der beste Preis-Komparator für den 800 FX-Prozessor. Das ist jetzt nicht mehr der Fall. Ich hatte zwei Möglichkeiten: Halten Sie die HD 7990 und vergleichen Sie gegen die 4960X, oder testen Sie das Intel-System mit einem Quad-Core von geeigneter Wahl. Ich entschied, dass Leser eher schneidende Einzel-GPU Resultate mit einer Erklärung sehen würden, daß die Intel-CPU nicht mehr der beste Vergleich war, anstatt, zu einem anderen Intel-Span zurückzugehen (wo das Leistungsdelta vernachlässigbar wäre), aber das gleiche 7990 behaltend. Joel, ich habe Ihren Artikel nicht kritisiert. Ich war einfach feststellen, dass AMD8217s Chip bei 400 ist ein weit besserer Wert für die Leistung als ein Chip, der 250 mehr kostet. Das ist eine schlechte Nachricht für Intel. In Zukunft wird PC-Typ Ausrüstung verkauft werden vor allem für seine GRAPHIC Fähigkeiten. In der Cloud-Paradigma gibt es wirklich keinen Grund für den durchschnittlichen Verbraucher oder Unternehmen benötigen eine teure Intel-CPU-basierte Maschine. Die nächste Ära des Rechnens ist ganz über die GPU AMD hat einen langfristigen Plan, um von den enormen Trends zu profitieren, die ihre GPU - und Serverfähigkeiten bevorzugen, die ich eine Anzahl Artikel geschrieben habe, die den Zusammenhang von einigen wenigen enormen langfristigen Tendenzen besprechen, und AMDs einzigartige Fähigkeiten zu Profitieren. 4) AMDs Pipeline von Semi-Custom und Cloud-Design gewinnt 4) AMD und die HSA-Stiftung entfesseln die Macht der GPU 5) Das Fortschreiten der natürlichen Benutzeroberflächen begünstigt AMD Laut Fudzilla bietet die neue CPU bis zu 16 Zen-Kerne an, wobei jeder Kern bis zu zwei Threads für insgesamt 32 Threads unterstützt. Weve hörte Gerüchte, dass dieser neue Kern Simultane Multithreading verwendet, im Gegensatz zu den Clustered Multi-Threading, dass AMD debütierte in der Bulldozer-Familie und hat die letzten vier Jahre verwendet. Jeder CPU-Kern wird durch 512K L2-Cache, mit 32MB L3-Cache über den gesamten Kern gesichert. Interessanterweise ist der L3-Cache als 8 MB benachbarte Blöcke und nicht als ein einheitliches Design dargestellt. Dies deutet darauf hin, dass Zen erbt seine L3-Struktur von Bulldozer, die einen ähnlichen Ansatz verwendet, obwohl hoffentlich der Cache wurde für eine verbesserte Leistung überholt. Die integrierte GPU soll auch mit doppelter Genauigkeit Gleitkomma bei 12 Einzel-Präzision Geschwindigkeit. Der Kern unterstützt bis zu 16 GB angeschlossenen HBM (High Bandwidth Memory) bei 512 GB und einen Quad DDR4 Controller mit integrierter DDR4-3200-Fähigkeit, PCIe 3.0 und SATA Express Unterstützung. Zu gut um wahr zu sein Das oben dargestellte CPU-Layout macht viel Sinn. AMD hat ein Zen-Modul bestehend aus vier CPU-Kernen, acht Threads, 2 MB L2 und einem zweifelsfrei optionalen L3-Cache definiert. Aber es ist die HBM-Schnittstelle, Quad-Kanal-DDR4 und 64 Lanes von PCIe 3.0, die meine Augenbrauen heben. Heres, warum: Gerade jetzt, die höchsten End-Server können Sie von Intel Pack nur 32 PCI-Express Lanes kaufen. Quad-Kanal DDR4 ist sicherlich verfügbar, aber wieder, Intels High-End-Server unterstützen 4x DDR4-2133. Server-Speicherstandards liegen typischerweise hinter den Desktops durch einen fairen Spielraum. Es ist nicht klar, wann ECC DDR4-3200 zur Primetime bereit sein wird. Das ist, bevor wir zu den HBM-Zahlen kommen. Machen Sie keinen Fehler, HBM kommt, und die Integration auf dem Desktop und in Servern wäre ein großer Unterschied machen, aber 16 GB HBM-Speicher ist eine Menge. Darüber hinaus ist der Aufbau einer 512GBs Speicher-Schnittstelle in einem Server-Prozessor auf der Chip-Ebene eine weitere Augenbraue-Wölbung Leistung. Für all das Potenzial von HBM und machen keinen Fehler, es hat eine Menge Potenzial, das ist ein extrem ehrgeiziges Ziel für eine CPU, die in 12 bis 18 Monaten debütieren soll, auch auf dem Server-Raum. Nichts in dieser Folie ist unmöglich, und wenn AMD tatsächlich zog es ausschalten, während Sie die erforderlichen IPC und Stromverbrauch Ziele, würde es einen absolut Mammut-Kern haben. Aber die Zahlen auf dieser Folie sind so ehrgeizig, es sieht so aus, als ob jemand ein Diagramm von allen optimistischsten Prognosen, die über den Computing-Markt im Jahr 2016 gemacht wurden, schlug sie zusammen auf einem Deck, und nannte es gut. Ich bin echt überrascht, wenn AMD einen 16-Core-Chip mit einem massiven integrierten Grafikprozessor und 16 GB HBM-Speicher und 64 Lanes PCI-Express sowie einen neu gestalteten CPU-Kern und einen neuen Quad-Channel-DDR4-Speichercontroller vorstellt Ein TDP, der nicht 200W für einen gesockelten Prozessor knackt. AMD ist billiger, aber haben die gleiche oder sogar besser perfomance als CPU witchcost 1000. auch auf perfomance pro Dollar schauen) WAS SIE SAGEN AUF DIESE. 1000 BESSER ALSER 1000 INTEL CPU Laut Fudzilla bietet die neue CPU bis zu 16 Zen-Kerne an, wobei jeder Kern bis zu zwei Threads für insgesamt 32 Threads unterstützt. Weve hörte Gerüchte, dass dieser neue Kern Simultane Multithreading verwendet, im Gegensatz zu den Clustered Multi-Threading, dass AMD debütierte in der Bulldozer-Familie und hat die letzten vier Jahre verwendet. Jeder CPU-Kern wird durch 512K L2-Cache, mit 32MB L3-Cache über den gesamten Kern gesichert. Interessanterweise ist der L3-Cache als 8 MB benachbarte Blöcke und nicht als ein einheitliches Design dargestellt. Dies deutet darauf hin, dass Zen erbt seine L3-Struktur von Bulldozer, die einen ähnlichen Ansatz verwendet, obwohl hoffentlich der Cache wurde für eine verbesserte Leistung überholt. Die integrierte GPU soll auch mit doppelter Genauigkeit Gleitkomma bei 12 Einzel-Präzision Geschwindigkeit. Der Kern unterstützt bis zu 16 GB angeschlossenen HBM (High Bandwidth Memory) bei 512 GB und einen Quad DDR4 Controller mit integrierter DDR4-3200-Fähigkeit, PCIe 3.0 und SATA Express Unterstützung. Zu gut um wahr zu sein Das oben dargestellte CPU-Layout macht viel Sinn. AMD hat ein Zen-Modul bestehend aus vier CPU-Kernen, acht Threads, 2 MB L2 und einem zweifelsfrei optionalen L3-Cache definiert. Aber seine die HBM-Schnittstelle, Quad-Kanal-DDR4 und 64 Lanes von PCIe 3.0, die meine Augenbrauen heben. Heres, warum: Gerade jetzt, die höchsten End-Server können Sie von Intel Pack nur 32 PCI-Express Lanes kaufen. Quad-Kanal DDR4 ist sicherlich verfügbar, aber wieder, Intels High-End-Server unterstützen 4x DDR4-2133. Server-Speicherstandards liegen typischerweise hinter den Desktops durch einen fairen Spielraum. Es ist nicht klar, wann ECC DDR4-3200 zur Primetime bereit sein wird. Das ist, bevor wir zu den HBM-Zahlen kommen. Machen Sie keinen Fehler, HBM kommt, und die Integration auf dem Desktop und in Servern wäre ein großer Unterschied machen, aber 16 GB HBM-Speicher ist eine Menge. Darüber hinaus ist der Aufbau einer 512GBs Speicher-Schnittstelle in einem Server-Prozessor auf der Chip-Ebene eine weitere Augenbraue-Wölbung Leistung. Für all das Potenzial von HBM und machen keinen Fehler, es hat eine Menge Potenzial, das ist ein extrem ehrgeiziges Ziel für eine CPU, die in 12 bis 18 Monaten debütieren soll, auch auf dem Server-Raum. Nichts in dieser Folie ist unmöglich, und wenn AMD tatsächlich zog es ausschalten, während Sie die erforderlichen IPC und Stromverbrauch Ziele, würde es einen absolut Mammut-Kern haben. Aber die Zahlen auf dieser Folie sind so ehrgeizig, es sieht so aus, als ob jemand ein Diagramm von allen optimistischsten Prognosen, die über den Computing-Markt im Jahr 2016 gemacht wurden, schlug sie zusammen auf einem Deck, und nannte es gut. Ich bin echt überrascht, wenn AMD einen 16-Core-Chip mit einem massiven integrierten Grafikprozessor und 16 GB HBM-Speicher und 64 Lanes PCI-Express sowie einen neu gestalteten CPU-Kern und einen neuen Quad-Channel-DDR4-Speichercontroller vorstellt Ein TDP, der nicht 200W für einen gesockelten Prozessor knackt. Ich denke, im gonna zu holen einer dieser mit 2 oder 3 290x Karten im nächsten Jahr8230I kaufte um und Intel und nvidias Preise waren zu hoch für die Spitze der Linie Produkte Pentium haben GPU in (was ist nicht vorteilhaft), sondern beacuse Sie Bekam wenig bessere Punktzahl 860K dont haben UND DIESES IST ADVANTAGE8230hier ist nur ein Benchmark von GameDebate: game-debatecpuindex. phppid2160038pid22112038compareathlon-ii-x4-860k-vs-pentium-g3258-3-2ghz WOOOW :) HAT IST DIES. Dies ist fake haaa-haaaa :) OMG8230 POOR DUAL Kern Pentium vs 860K, die in i5 rank8230 ist, wenn Sie nicht glauben, hier ist einer der PassMasrk, Rang mit Intel CPUs. Sterben bitte nicht, wenn Sie dieses sehen: cpubenchmark. netcpu. phpcpuAMDAthlonX4860KQuadCore bitte, sagen Sie mir, was Sie sehen. Ich kann nicht sehen: (; LOL, was ist dieser 3DMARK-Benchmark, schau DIES aus und sage dann etwas: PS LEARN SOMETHING ÜBER CPUs diese schlechte Dual-Core haben GPU innen und nur beacuse, dass auf einigen Benchmark (NN Benchmark-Sites) gibt ihm wenig besser Und das ist ein großer Vorteil8230 Blick echte Benchmarks: cpu-worldCompare41AMDAthlonX4860KvsIntelPentiumDual-CoreG3258.html LOL :)))) WAS IST DIESE. Bitte nicht weinen (((g3258.HAAAAA-HAAAAA :) GREAT CPU für MINECRAFT :)))) Dies ist Intel-Fanboy und sie werden nicht akzeptieren, die Beweise und Fakten, sie sehen nur den Preis, nicht perfomance. Und Tatsachen ist, Intel gehen down8230 IntelTitanic IcebergAMD 8220ZEN8221 CPUs hmmm8230.interestingly: D billig AMD VS extra unprofitable teuer Intel8230 was wird 2016 sein. Wenn kommt AMD CPUs mit NEW ZEN arhitecture8230 Es wird sehr interessant sein :))) bye, bye Intel. Kommt ZEN CPUs. Zu stark als IRGENDEINER Intel :) aber im 2016. kommt heraus ..check dieses, haben 20 bessere techonology (ähnlich Intels Hyper Threading) aber BESSER. 16 CPUs und viele, viele Threads :)))) genieße dies zu sehen: extremetechextreme198386-amds-next-gen-cpu-leak-14nm-simultan-multithreading-and-ddr4-Unterstützung Laut Fudzilla wird die neue CPU bieten Bis 16 Zen-Kerne, wobei jeder Kern bis zu zwei Gewinde für insgesamt 32 Gewinde stützt. Weve hörte Gerüchte, dass dieser neue Kern Simultane Multithreading verwendet, im Gegensatz zu den Clustered Multi-Threading, dass AMD debütierte in der Bulldozer-Familie und hat die letzten vier Jahre verwendet. Jeder CPU-Kern wird durch 512K L2-Cache, mit 32MB L3-Cache über den gesamten Kern gesichert. Interessanterweise ist der L3-Cache als 8 MB benachbarte Blöcke und nicht als ein einheitliches Design dargestellt. Dies deutet darauf hin, dass Zen erbt seine L3-Struktur von Bulldozer, die einen ähnlichen Ansatz verwendet, obwohl hoffentlich der Cache wurde für eine verbesserte Leistung überholt. Die integrierte GPU soll auch mit doppelter Genauigkeit Gleitkomma bei 12 Einzel-Präzision Geschwindigkeit. Der Kern unterstützt bis zu 16 GB angeschlossenen HBM (High Bandwidth Memory) bei 512 GB und einen Quad DDR4 Controller mit integrierter DDR4-3200-Fähigkeit, PCIe 3.0 und SATA Express Unterstützung. Zu gut um wahr zu sein Das oben dargestellte CPU-Layout macht viel Sinn. AMD hat ein Zen-Modul bestehend aus vier CPU-Kernen, acht Threads, 2 MB L2 und einem zweifelsfrei optionalen L3-Cache definiert. Aber seine die HBM-Schnittstelle, Quad-Kanal-DDR4 und 64 Lanes von PCIe 3.0, die meine Augenbrauen heben. Heres, warum: Gerade jetzt, die höchsten End-Server können Sie von Intel Pack nur 32 PCI-Express Lanes kaufen. Quad-Kanal DDR4 ist sicherlich verfügbar, aber wieder, Intels High-End-Server unterstützen 4x DDR4-2133. Server-Speicherstandards liegen typischerweise hinter den Desktops durch einen fairen Spielraum. Es ist nicht klar, wann ECC DDR4-3200 zur Primetime bereit sein wird. Das ist, bevor wir zu den HBM-Zahlen kommen. Machen Sie keinen Fehler, HBM kommt, und die Integration auf dem Desktop und in Servern wäre ein großer Unterschied machen, aber 16 GB HBM-Speicher ist eine Menge. Darüber hinaus ist der Aufbau einer 512GBs Speicher-Schnittstelle in einem Server-Prozessor auf der Chip-Ebene eine weitere Augenbraue-Wölbung Leistung. Für all das Potenzial von HBM und machen keinen Fehler, es hat eine Menge Potenzial, das ist ein extrem ehrgeiziges Ziel für eine CPU, die in 12 bis 18 Monaten debütieren soll, auch auf dem Server-Raum. Nichts in dieser Folie ist unmöglich, und wenn AMD tatsächlich zog es ausschalten, während Sie die erforderlichen IPC und Stromverbrauch Ziele, würde es einen absolut Mammut-Kern haben. Aber die Zahlen auf dieser Folie sind so ehrgeizig, es sieht so aus, als ob jemand ein Diagramm von allen optimistischsten Prognosen, die über den Computing-Markt im Jahr 2016 gemacht wurden, schlug sie zusammen auf einem Deck, und nannte es gut. Ich bin echt überrascht, wenn AMD einen 16-Core-Chip mit einem massiven integrierten Grafikprozessor und 16 GB HBM-Speicher und 64 Lanes PCI-Express sowie einen neu gestalteten CPU-Kern und einen neuen Quad-Channel-DDR4-Speichercontroller vorstellt Ein TDP, der nicht 200W für einen gesockelten Prozessor knackt. Ich habe vor kurzem mir eine Low-Profile-Desktop-Workstation auf der Grundlage der FX-8320. Ich musste auf der Silizium-Lotterie Glück gehabt haben, weil ich leicht eine stabile FX-8370-Performance (4,3 GHz) übertaktete, ohne den V-Core oder das Ergebnis aufwändige Kühlung zu erweitern, die ich sowieso nicht in einem schlanken Formfaktor mATX HTPC-Gehäuse machen kann. Weiterhin verfügt I8217m über zwei Dual-Display-Komplemente eines DSM-59-Kabels, das mit einem Low-Profile-JATON Video-PX658-DLP-EX GeForce GT 630 2GB 128-Bit DDR3 PCI Express x16 Grafikkarte verbunden ist. It8217s sicher nicht ein Gaming-Rigg, aber es8217s leistungsstark genug für mich, um andere 3D-Rendering-Anwendungen wie Blender oder sogar AutoCAD laufen. I8217m bereits festgelegt, um die Windows-10-Update erhalten, wenn es freigegeben wird. Ich habe derzeit 16 GB DDR3 1600 RAM in diesem Rig. Ich liebe die Kraft, die es für die kleine Abmessungen hat. Wenn ich die CPU unter Volllast unter Verwendung der Tal-Benchmark (unter Verwendung der unigine) getestet, schwebte die CPU temp zwischen 48-53 Grad Celsius. Das ist zwar nicht so schlimm, aber das GT-630 wurde wirklich heiß Der Lager-Kühlkörper und Lüfter, die mit der Grafikkarte kommt funktioniert ok, aber der Mensch war ich erleichtert, wenn der Stress-Test gemacht wurde, da die Temperaturen schien wirklich auf der Grafikkarte zu spitzen. Gibt es andere Low-Profile 2-4 GB DSM-59 Grafikkarten da draußen Sie Jungs bewusst sind, dass laufen Kühler für kleine Form Factoryfootprint-Systeme wie meines, wo Platz ist oft eng und Luftstrom besonders anspruchsvoll Herr Hruska, I8217d schätzen Ihre Gedanken Insbesondere über die Angelegenheit. I8217m liebende ExtremeTech und viel von der Website lernen. Vielen Dank für alles, was Sie alle tun, um dies eine lebendige Online-Community. Lassen Sie mich sehen, was ich für Sie finden kann. Wie heiß, btw, reden wir die meisten GPUs in diesen Tagen tolerieren Temperaturen von 70-80C. Ich sehe viel besser als das, was du hast. DMS-59 ist ein sehr alter Standard. Grats auf dem Overclock. Die meisten FX Kerne steigern ein paar Grade, kein Problem, aber immer über 5GHz ist ziemlich tricky. Nein ist nicht. 5.0Ghz ist nichts, wenn Sie gutes Kühlsystem haben8230 FX CPUs gehen bis zu 8.0-8-3Ghz8230 STABILE. Aber mit sehr, vrey gutes Kühlsystem. Meine 860K ist nicht heiß wie FXs und haben OC bis zu 6.3Ghz8230 Ich habe 5.0Ghz ohne Problem und ist stabil und temp ist sehr niedrig .. Beacuse Ich habe gutes Kühlsystem. 5.0Ghz ist nichts für AMD CPUs8230 für Intel ja8230 wenn Hexe Intel gehen bis zu 5.0Ghz8230 gehen, ist aber nicht stabil und ist sogar mit guten cooling8230 für OC, AMD ist König .. no doubt8230 Wir aren8217t Zählung flüssiger Stickstoff, dude Überhitzung. Ich besitze einen einstufigen Freonkühler, der einen Chip bis zu ungefähr -30C nimmt. Mit diesem Kühler, kann ich eine FX-9590 bis zu einer 5GHz flachen Geschwindigkeit für alle Kerne im Gegensatz zu 4,7GHz 5.0GHz Turbo drücken. Sie gehen höher. I8217ve getestet drei. Nicht alle von ihnen konnten mit einem vollen 5GHz laufen. Delidding könnte Ihnen etwas mehr, aber die Leistungsanforderungen für die FX-9590 Rakete als Spannung steigt, und es kommt ein Punkt, wenn mehr Kühlung einfach isn8217t genug. Wenn der Chip mit 6 GHz auf der Luft laufen könnte, würde AMD eins verkaufen. Die Tatsache, dass der TDP von 125W bei 4,3GHz auf 220W bei 5GHz ansteigt, sollte Ihnen etwas darüber erzählen, wie AMD diese Prozessoren machte und was die Chancen für schnellere Taktgeschwindigkeiten sind. Ja, flüssiger Stickstoff und flüssiges Helium können Taktgeber von 8GHz treffen. Das sagt nichts über das, was normale Anwender erwarten können. Hmmm8230 dann nur Sie auf Welt cant oc diese CPU höher als 5.0Ghz8230 wooow, nur Person auf der Welt. Du bist natürliches Talent für Übertaktung: D Hey Joel, ich habe meine Anlage mit der oben genannten GeForce GTX 750 TI aufgerüstet und bekam die folgenden konsistenten Ergebnisse auf meinem Valley-Benchmark. Drive. googlefiled0B7WJW-ZvDugaW9penlDN1pSN2cviewuspsharing. Vielen Dank für Ihre Hilfe bro. Ich habe die Karte zum Verkauf im Micro Center für nur 130 Dollar. Mit der Post in Rabatt, wird es klopfen aus anderen 20, die ich zurück bekommen. - smiles - Glücklich mal Joel H, hier sind die Endergebnisse meines Rig-Upgrades. Vielen Dank für Ihre Hilfe bro. Docs. googlepresentationd1ScaiwXrzQoYIn0GpjMbtlpuKthYwItH1jkHeMs9MUedituspsharing Ich weiß, es8217s nichts Spektakuläres von heute8217s Standards, sondern gegeben, was wir8217ve diskutiert I8217m ziemlich zufrieden mit den Ergebnissen. Pass auf dich auf, Alter. Haben Sie die GTX 760 oder die 750 Ti Ich dachte, Sie hatten die Ti. Wenn Sie Spiel überhaupt, ich glaube, Sie8217ll viel glücklicher mit diesem Rig im Vergleich zu den anderen. Die alte GeForce würde Ihnen keine Gefallen tun, während die 750 Ti oder 760 1080p Gaming gerade gut schieben können. Ich bekam zuerst die 750 Ti, aber musste es zum Micro Center wegen Überhitzung Probleme hatte es zurückzukehren. Für meine Schwierigkeiten, fanden sie eine 760 für mich, die nur 10 mehr so ​​bekam ich es als Ersatz. Der freigegebene Google Docs-Link, den ich Dir gesendet habe: docs. googlepresentationd1ScaiwXrzQoYIn0GpjMbtlpuKthYwItH1jkHeMs9MUeditslideid. p gibt die Aufschlüsselung, wie es durchgeführt wurde. Hallo Joel. Hier ist eine YouTube-Demo der gleichen Low ProfileSlimline-Karte, die ich glaube, I8217m zu kaufen. Youtubewatchv7gtuAx2ivDY. BTW, meine Monitore sind zwei Dell 178243 Monitore mit 1280x1024 Auflösung in 32bit Farbtiefe. Das gleiche FPS. ) Und AMD kosten 5 mal weniger als Intel dann, warum haben so ultra hohen Preis. Und die gleiche Leistung. 8220perfomance pro dollar8221, AMD immer wins8230 Let8217s sehen, was weiß ich über CPUs Ich weiß, dass die 2012 Bulldozer-Design hat etwa 50 der IPC von Intel8217s Haswell. Ich weiß, dass der primäre Engpass bei Spielen, wie die SLI GTX 970s demonstriert, die GPU ist. Ich weiß, dass AMD8217s CMT-Design gibt ein Maximum von 50 zusätzliche Leistung in der realen Welt, keine, wenn Sie die FPU verwenden. Ich weiß, dass aktuelle Spiele kämpfen, um über 4 Kerne verwenden. Wenn sie es tun, lass es mich wissen. Ich weiß auch, dass du wahrscheinlich nicht so dumm bist wie du vorgibst. Aber was auch immer. AMD hat riesige und großartige Arbeit mit diesem CPu, aber es ist zu viel Energie verbrauchen. Intel8217s Cpu ist wenig besseres aber nicht viel und ich don8217t denke, dass AMD eine weitere 8 Kern CPU 2015 mehr einführen wird, da sie für neue AM4 Einfaßung, neue CPUs und neue grafische Karten im nächsten Jahr vorbereiten. AM3 Sockel ist alt und sie sollten es ersetzen vor 3 Jahren und AMD CPUs wäre viel besser. Beeindruckend. Ich glaube, ich verlor mehrere IQ-Punkte nur versuchen, decypher marx8217s schreckliche Grammatik. Es scheint, Sie mögen andere zu schmälern und oder sogar beleidigen anderen, indem sie sie ein 8220taliban8221. Dieser Thread war tatsächlich im Umlauf bei meinem derzeitigen Arbeitgeber, Intel. Ich kann Ihnen sagen, wie viele von uns im Büro lachten über alle Ihre Ansprüche. Als Prozess-Ingenieur bei Intel, lassen Sie mich Sie etwas fragen8230 Mit dieser hervorragenden Grammatik und all dem Bullshit you8217ve gesprochen haben für die letzten 2 Jahre, was College Sie teilnehmen You8217re schnell beurteilen Sie andere hier, ohne auch nur besser zu wissen. Grow up kleiner Junge. So8230 Was ist die beste Leistung für den Dollar annehmen, dass seine ein Gaming-machineThe Thalesians Bilder von Thalesians Veranstaltungen aus der ganzen Welt in den letzten 6 Jahren Die Thalesians sind ein Think Tank von engagierten Profis mit einem Interesse an quantitativen Finanzen, Wirtschaft, Mathematik, Physik und Informatik, nicht unbedingt in dieser Reihenfolge. Blog Sehen Sie unser neues Thalesians blog Buch Kaufen Sie unser neues Buch. Trading Thalesians - Was die alte Welt lehren kann uns über den Handel heute (Palgrave Macmillan) durch die Thalesier Mitbegründer, Saeed Amen amp Vorwort von Gründer, Paul Bilokon Gründung Die Gruppe wurde im September 2008 von Paul Bilokon (dann ein quantitativer Analyst Bei Lehman Brothers, der sich auf Devisen spezialisiert hat, und einen Teilzeitforscher im Imperial College) und zwei seiner Freunde und Kollegen: Matthew Dixon (damals quantitativer Analyst bei der Deutschen Bank) und Saeed Amen (damals quantitativer Stratege bei Lehman Brothers) . Die Eröffnung von Level39 im Jahr 2013 durch Bürgermeister Boris Johnson Die Thalesier sind nun auch Mitglied von Level39 - Europas größter Technologie-Beschleuniger für Finanzen, Einzelhandel, Cyber-Security und zukünftige Städte Technologiefirmen Events Research Consulting Veranstaltungen Die Thalesians stammten ursprünglich aus London, Großbritannien . Im Januar 2011 wurde die Organisation wirklich global, wenn Matthew Dixon brachte es in die Vereinigten Staaten, wo er leitet die Thalesians NYC Seminare mit New York Leader Harvey Stein. Attila Agod ist der Budapest Leader für unsere Thalesians Budapest Seminare. Wir sind gerade dabei, unsere Seminare nach Prag auszudehnen und weitere Workshops durchzuführen. Forschung Ende 2013 begannen wir mit der Veröffentlichung breiter Quantisierungsstrategien. Our effort is lead by Saeed Amen, using nearly a decade of his experience both creating and later trading systematic trading models in FX at major investment banks. Visit Research for more. Consulting In 2014, we started offering bespoke quant consulting services in markets, signing up our first client, a major US hedge fund and RavenPack, a major news data vendor. Our services includes the creation of bespoke systematic trading models and other quant analysis of financial markets, such as currency hedging and FX transaction cost analysis (TCA). Visit Consulting for more. Our Philosophy We are named after Thales of Miletus ( ), a pre-Socratic Greek philosopher who lived in ca. 624 BC-ca. 546 BC. Thales was a mathematician and is familiar to many secondary school students for one of his theorems in geometry. But more relevantly to us, he was one of the first users of options: Thales, so the story goes, because of his poverty was taunted with the uselessness of philosophy but from his knowledge of astronomy he had observed while it was still winter that there was going to be a large crop of olives, so he raised a small sum of money and paid round deposits for the whole of the olive-presses in Miletus and Chios, which he hired at a low rent as nobody was running him up and when the season arrived, there was a sudden demand for a number of presses at the same time, and by letting them out on what terms he liked he realised a large sum of money, so proving that it is easy for philosophers to be rich if they choose, but this is not what they care about. Aristotle, Politics, 1259a. The morale of this anecdote is that it is easy for philosophers to be rich if they choose the famous Milesian went ahead and proved it. We, the Thalesians . admire him for that. But we also share many of his values, for example his core belief that a happy man is defined as one , , (who is healthy in body, resourceful in soul and of a readily teachable nature). This wiki was created to serve as a source of information on quantitative finance, to collate references to various related resources, and to serve as a convergence point for the Thalesians . our colleagues and collaborators. It grew out of Paul Bilokons finance wiki, which he started in February, 2007. We believe that secrecy and fidelity are important in the world of finance. But we also acknowledge the power of information sharing in open societies. Let your business logic remain a closely guarded secret. But release everything else into the public domain. What goes around, comes around this will ultimately spare you reinventing the wheel. More of our speakers at Thalesians events over the past 6 years Forthcoming Events Thalesians Seminar (Frankfurt) 8212 Thalesians Frankfurt 1st Open Stage Seminar Registration Instantaneous volatility of logarithmic return in lognormal fractional SABR model is driven by the exponentiation of a correlated fractional Brownian motion. Due to the mixed nature of driving Brownian and fractional Brownian motions, probability density for such models are less known in the literature. We present in this talk a bridge representation for the joint density of the lognormal fractional SABR model in a Fourier space. Evaluating the bridge representation along a properly chosen deterministic path yields an Edgeworth style of expansion of the probability density for the fractional SABR model. A direct generalization of the representation to joint density at multiple times leads to a heuristic derivation of the large deviations principle for the joint density in small time. Approximation of implied volatility is readily obtained by applying the Laplace asymptotic formula to the call or put prices and comparing coefficients. The presentation is based on a joint work with Jiro Akahori and Xiaoming Song. Tai-Ho Wang holds a professorship in mathematics at Baruch College, City University of New York since 2012. His research in quantitative finance includes implied volatility asymptotics in small time, static arbitrage free bounds on basket options, optimal liquidation and execution in market impact models, and recently information dynamics in financial market. IAQF-Thalesians Seminars The IAQF-Thalesians Seminar Series is a joint effort on the part of the IAQF (formerly IAFE) and the Thalesians. The goal of the series is to provide a forum for the exchange of new ideas and results related to the field of quantitative finance. This goal is accomplished by hosting seminars where leading practitioners and academics present new work, and following the seminars with a reception to facilitate further interaction and discussion. The seminar series is limited to IAQF and Thalesians members only. IAQF-Thalesians Seminar (New York) 8212 Dr. Alan Moreira 8212 Volatility Managed Portfolios Wednesday, February 15, 2017: NYU Kimmel Center. Room 914, Kimmel Center, 60 Washington Square South, NY 10012, NY Registration Managed portfolios that take less risk when volatility is high produce large alphas, increase Sharpe ratios, and produce large utility gains for mean-variance investors. We document this for the market, value, momentum, profitability, return on equity, and investment factors, as well as the currency carry trade. Volatility timing increases Sharpe ratios because changes in volatility are not offset by proportional changes in expected returns. Our strategy is contrary to conventional wisdom because it takes relatively less risk in recessions yet still earns high average returns. This rules out typical risk-based explanations and is a challenge to structural models of time-varying expected returns. Alan Moreira is an Assistant Professor of Finance at the Yale University School of Management. Originally from Rio de Janeiro, Brazil, he received his undergraduate degree from the Rio de Janeiro Federal University (UFRJ) and his PhD in Financial Economics from the University of Chicago. Dr. Moreiras research investigates how financial intermediation shapes the real economy and the causes and consequences of fluctuations in uncertainty. His research has been published in the top journals including the Journal of Financial Economics and Journal of Finance. In addition to teaching Risk Management in the MBA program at the Yale School of Management, Dr. Moreira teaches Asset Pricing at the PhD level. In his spare time, he enjoys biking, traveling, and hanging out the family. Alan Moreira, Assistant Professor of Finance, Yale School of Management 1 IAQF-Thalesians Seminars The IAQF-Thalesians Seminar Series is a joint effort on the part of the IAQF (formerly IAFE) and the Thalesians. The goal of the series is to provide a forum for the exchange of new ideas and results related to the field of quantitative finance. This goal is accomplished by hosting seminars where leading practitioners and academics present new work, and following the seminars with a reception to facilitate further interaction and discussion. The seminar series is limited to IAQF and Thalesians members only. Recent Events IAQF-Thalesians Seminar (New York) 8212 Dr. Hongzhong Zhang 8212 Intraday Market Making with Overnight Inventory Costs Thursday, December 14, 2016: NYU Kimmel Center. Room 914, Kimmel Center, 60 Washington Square South, NY 10012, NY Registration The share of market making conducted by high-frequency trading (HFT) firms has been rising steadily. A distinguishing feature of HFTs is that they trade intraday, ending the day flat. To shed light on the economics of HFTs, and in a departure from existing market making theories, we model an HFT that has access to unlimited leverage intraday but must fund any end-of-day inventory at an exogenously determined cost. Even though the inventory costs only occur at the end of the day, they impact intraday price and liquidity dynamics. This gives rise to an intraday endogenous price impact mechanism. As time approaches the end of the trading day, the sensitivity of prices to inventory levels intensifies, making price impact stronger and widening bid-ask spreads. Moreover, imbalance of buy and sell orders may catalyze hikes and drops of prices, even under fixed supply and demand functions. Empirically, we show that these predictions are borne out in the U. S. Treasury market, where bid-ask spreads and price impact tend to rise towards the end of the day. Furthermore, price movements are negatively correlated with changes in inventory levels as measured by the cumulative net trading volume. (Joint work with Tobias Adrian, Agostino Capponi, and Erik Vogt) Hongzhong Zhang is an assistant professor at Columbia University. His research focuses on the broad area of applied probability with applications in engineering, finance and insurance. In particular, some of his current research interests include asymptotics, drawdowns, optimal stopping, and detection of regime changes. IAQF-Thalesians Seminars The IAQF-Thalesians Seminar Series is a joint effort on the part of the IAQF (formerly IAFE) and the Thalesians. The goal of the series is to provide a forum for the exchange of new ideas and results related to the field of quantitative finance. This goal is accomplished by hosting seminars where leading practitioners and academics present new work, and following the seminars with a reception to facilitate further interaction and discussion. The seminar series is limited to IAQF and Thalesians members only. Thalesians Xmas Party (London) 8212 Iain Clark 8212 Implied Distributions from FX Risk-Reversals and Predictions for the Effect of the Brexit Vote and the Trump election We would like to invite you to our Thalesians Christmas seminar in London, where Iain Clark will be presenting This will be followed by our Christmas party at the GampTea Bar in the Marriott Hotel, Canary Wharf, where we will be serving drinks and canapes. The ticket price includes both the talk and the party (first drinks canapes). The canape selection will include some of the following: Aubergine and haloumi wrap Brie and parma ham finger brioche Crudits and hummus shot glasses Open face smoked salmon bagel Mini burgers Lamb samosa Spring rolls Prawn potato shells Date and Time 7:30 p. m. on Monday 12th December 2016 Ginger Room, followed by drinks amp canapes at GampTea Bar, Marriott Hotel, Canary Wharf, London, UK, Meetup In May 2016 it was noted, in the audience QampA after a presentation by the speaker, that GBPUSD risk reversals were exhibiting very unusual behaviour - namely, extreme skew in short dated tenors but relatively flat smiles thereafter. This is a most unusual volatility signature and the connection with the upcoming Brexit referendum vote was immediately made. The speaker, as a matter of urgency given the topical nature of the pre-Brexit market, performed an analysis with his co-author on implied distributions for the market expectations for GBPUSD around the referendum date (23 June 2016), with predictions for spot thereafter. The paper was uploaded to SSRN (ssrnabstract2794888 ) on 13 June, in which we identified empirical evidence in the volatility skew for a fall in GBPUSD from 1.4390 to the range 1.10 to 1.30 in the event of a Leave vote - a downward move of 0.14 to 0.34. The analysis, unusually for quant research, received coverage in the FT and the Sunday Telegraph and indeed our predictions were borne out when the referendum result was announced and sterling fell from 1.50 to 1.33 - a downward move of 0.17 - in a matter of hours. Subsequent to this analysis, we applied similar methods to the Mexican peso quoted versus the US dollar (USDMXN) immediately before the 2016 US election and we were able to predict peso devaluation into a range of 20-24 pesos per dollar in the event of a Trump victory, which was borne out by subsequent events. In this talk I will go through our analysis of the information embedded in the volatility skew and the basis for our predictive analysis. Iain J. Clark (MIMA CMath, MInstP CPhys, CStat, FRAS) has over 14 years experience as a front office quant. He has worked as Head of FX and Commodities Quantitative Analysis at Standard Bank, as Head of FX Quantitative Analysis at Unicredit and at Dresdner Kleinwort, and at Lehman Brothers, BNP Paribas and JP Morgan. Iain has a PhD in applied mathematics from Queensland University and a MSc in financial mathematics from Edinburgh and Heriot-Watt Universities. His main research interests are on exotic options, stochastic models for FX and commodities, and numerical methods for option pricing. He is a frequent contributor to industry conferences, training courses and invited speaker at various universities. His first book Foreign Exchange Option Pricing: A Practitioners Guide was published in November 2010 by Wiley Finance and his second book Commodity Option Pricing: A Practitioners Guide is due to appear in early 2014 (also with Wiley Finance). Thalesians Seminar (London) 8212 Vlasios Voudouris 8212 Flexible machine learning for finance Date and Time 7:30 p. m. on Wednesday 23rd November 2016 Ginger Room, Marriott Hotel, Canary Wharf, London, UK. Meetup With rapid changes in computing technology and the big data age, the field of data science is constantly challenged. Data scientists job is to make sense of the vast amounts of data: to extract important patterns and trends, and understand what the data says. The challenges in learning from data have led to a revolution in machine learning techniques. The GAMLSS suite of tools in our attempt to learn from financial data. GAMLSS is now widely used for predictive analytics and risk quantification (e. g. loss given default). Because of the flexibility of GAMLSS models, we can capture the following data characteristics: The heavy-tailed or light-tailed characteristics of the distribution of the data. This means that the probability of rare events (e. g. an outlier value) occurs with higher or lower probability compared with the normal distribution. Furthermore, the probability of occurrence of an outlier value might change as a function of the explanatory values. The skewness of the response variable, which might change as a function of the explanatory variables. The nonlinear or smooth relationship between the target variable and the explanatorypredictor variables. Based on our book Flexible Regression and Smoothing: Using GAMLSS in R, the talk includes a large number of practical examples (e. g. predictions and risk quantification) which reflect the range of problems addressed by GAMLSS models. This also means that the examples provide a practical illustration of the process of using GAMLSS models for machine learning. Vlasios Voudouris is a Data Scientist with expertise in data-driven predictive analytics and risk quantification of financial markets. His primary research focus is on i) semi-parametric machine learning models ii) innovative model selection processes and iii) robust diagnostics for systematic trading and risk quantification. He is the co-author of the book Flexible Regression and Smoothing: Using GAMLSS in R and the associated software in R and Java. GAMLSS (Generalized Additive Models for Location Scale and Shape) is about learning from data using semi-parametric supervised machine learning algorithms. Furthermore, Vlasios developed data-driven agent-based models for stress testing scenarios (with an emphasis on commodity markets). His models and tools are used by a range of organisations. By way of two specific examples: 1) the IMF used GAMLSS for stress testing the U. S. financial System 2) Vlasios and his colleagues demonstrated a suite of GAMLSS models for the Bank of England (BoE). Using GAMLSS, Vlasios developed a systematic trading model for WTI Crude Oil (NYMEX). Vlasios holds a Ph. D. from City, University of London. IAQF-Thalesians Seminar (New York) 8212 Dr. Michael Imerman 8212 Insights from a Data-Driven Analysis of the Volatility Risk Premium Thursday, November 17, 2016: NYU Kimmel Center. Room 914, Kimmel Center, 60 Washington Square South, NY 10012, NY Registration Much of this talk will come from joint work I did with Jianqing Fan at Princeton and Wei Dai now at Dimensional Fund Advisors. We set out to provide a purely data-driven analysis of the volatility risk premium, using tools from high-frequency finance and Big Data analytics. We argue that the volatility risk premium, loosely defined as the difference between realized and implied volatility, can best be understood when viewed as a systematically priced bias. We first use ultra-high-frequency transaction data on SPDRs and a novel approach for estimating integrated volatility on the frequency domain to compute realized volatility. From that we subtract the daily VIX, our measure of implied volatility, to construct a time series of the volatility risk premium. To identify the factors behind the volatility risk premium as a priced bias we decompose it into magnitude and direction. We find compelling evidence that the magnitude of the deviation of the realized volatility from implied volatility represents supply and demand imbalances in the market for hedging tail risk. It is difficult to conclusively accept the hypothesis that the direction or sign of the volatility risk premium reflects expectations about future levels of volatility. However, evidence supports the hypothesis that the sign of the volatility risk premium is indicative of gains or losses on a delta-hedged portfolio consistent with Bakshi and Kapadia (2003). As someone who has come from a background in financial modeling but has developed a penchant for data science and analytics, I will spend some time at the end of my talk on my thoughts about how data science is being embraced (in some ways, and eschewed in others) by the quantitative finance community. Michael B. Imerman is the Theodore A. Lauer Distinguished Professor of Investments and Assistant Professor in the Perella Department of Finance at Lehigh University. Dr. Imermans previous appointments were at Princeton in the ORFE Department and Rutgers Business School from where he received his Ph. D. Before coming to academia, Imerman worked as an analyst at Lehman Brothers supporting the high grade credit and credit derivative trading desks. At Lehigh, Professor Imerman teaches Derivatives and Risk Management both at the undergraduate and graduate levels. His primary research area is in credit risk modeling with applications to banking, risk management, and financial regulation. Most recently he has been actively involved in integrating data science techniques into the evaluation of risk in the securitized mortgage market. IAQF-Thalesians Seminars The IAQF-Thalesians Seminar Series is a joint effort on the part of the IAQF (formerly IAFE) and the Thalesians. The goal of the series is to provide a forum for the exchange of new ideas and results related to the field of quantitative finance. This goal is accomplished by hosting seminars where leading practitioners and academics present new work, and following the seminars with a reception to facilitate further interaction and discussion. The seminar series is limited to IAQF and Thalesians members only. Thalesians Seminar (London) 8212 Prof David Hand 8212 The Improbability Principle: Why Coincidences, Miracles, and Rare Events Happen Every Day Date and Time Registration Sellers of variance swaps earn time-varying risk premia for their exposure to realized variance, the level of variance swap rates, and the slope of the variance swap curve. To measure the variance term premium, we estimate a dynamic term-structure model that prices variance swaps across the US, UK, Europe, and Japan. The model decomposes the variance swap curve into term-structures of risk premia and expected quantities of risk. Empirically, we document a strong factor structure in global variance swap rates and find that variance term premia are negatively correlated with the wealth of the financial intermediary sector. Our results support the hypothesis that financial intermediaries are the marginal investor in the variance swap market. Erik Vogt is a financial economist in the Capital Markets Function of the Federal Reserve Bank of New York. His main research interests are in asset pricing, financial econometrics, volatility and liquidity risk, and high-frequency data across a variety of asset classes, including equities, Treasuries, derivatives, and corporate bonds. His research on market liquidity and broker-dealers has received media coverage in Bloomberg, Reuters, and Yahoo Finance, among others, and was also cited in U. S. Senate testimony before the Subcommittee on Securities, Insurance, and Investment, and the Subcommittee on Economic Policy, Committee on Banking, Housing, and Urban Affairs. Erik actively serves as a referee for several peer-reviewed journals, including the Review of Financial Studies, the Journal of Econometrics, the Journal of Empirical Finance, the Journal of Financial Econometrics, and Quantitative Finance. Erik joined the New York Fed in July 2014 and holds a Ph. D. and M. A. in Economics from Duke University and a B. Sc. in Mathematics and Economics from the London School of Economics. Prior to graduate school, he worked as an Associate Economist at the Federal Reserve Bank of Chicago. IAQF-Thalesians Seminars The IAQF-Thalesians Seminar Series is a joint effort on the part of the IAQF (formerly IAFE) and the Thalesians. The goal of the series is to provide a forum for the exchange of new ideas and results related to the field of quantitative finance. This goal is accomplished by hosting seminars where leading practitioners and academics present new work, and following the seminars with a reception to facilitate further interaction and discussion. The seminar series is limited to IAQF and Thalesians members only. Thalesians Seminar (London) 8212 Nick Baltas 8212 Multi-Asset Carry Strategies Date and Time 7:30 p. m. on Wednesday 28th September 2016 Ginger Room, Marriott Hotel, Canary Wharf, London, UK. Meetup Carry strategies have been primarily studied and explored within currency markets, where, contrary to the uncovered interest rate parity, borrowing from a low interest rate country and investing in a high interest rate country has historically delivered positive and statistically significant returns. This presentation extends the notion of carry to different asset classes by looking at the futures markets of commodities, equity indices and government bonds. We explore the profitability of cross-sectional and time-series variants of the carry strategy within each asset class but most importantly we investigate the benefits of constructing a multi-asset carry strategy after properly accounting for the covariance structure of the entire universe. Nick Baltas is an Executive Director within the Global Quantitative Research group at UBS. His research interests include systematic multi-asset strategies, portfolio construction, risk analysis and performance evaluation. Nick joined UBS in February 2013 and since then he additionally maintains visiting academic positions at Imperial College Business School and Queen Mary University of London. His research has been awarded with numerous grants and prizes and quoted by the financial press. Prior to his current role, Nick spent two years as Lecturer in Finance at Imperial College Business School, when he was awarded the Star Teacher of the Year award for both years in recognition of his teaching, and almost a year as risk manager in a London-based equity hedge fund. He holds a DEng in electrical and computer engineering from the National Technical University of Athens, an MSc in communications amp signal processing from Imperial College London and a PhD in finance from Imperial College Business School. IAQF-Thalesians Seminar (New York) 8212 Dr. Arun Verma 8212 Statistical arbitrage using news and social sentiment based quant trading strategies Thursday, September 15, 2016: NYU Kimmel Center. Room 914, Kimmel Center, 60 Washington Square South, NY 10012, NY Registration To explore the value embedded in News amp Social Sentiment data, we build three types of equity trading strategies based on sentiment data and show that strategies based on sentiment outperform the corresponding benchmark indexes significantly. Arun Verma joined the Bloomberg Quantitative Research group in 2003. Prior to that, he earned his Ph. D from Cornell University in the computer science amp applied mathematics. At Bloomberg, Dr. Vermas work initially focused on Stochastic Volatility Models for EquityFX Derivatives and Exotics pricing, e. g. Arbitrage free Volatility interpolation, Variance Swaps and VIX FuturesOptions pricing and Cross Currency Volatility Surface construction. More recently, he has enjoyed working at the intersection of such areas as data science, innovative quantitative techniques and interactive visualizations for help reveal embedded signals in financial data, e. g. building quant trading strategies for statistical arbitrage. IAQF-Thalesians Seminars The IAQF-Thalesians Seminar Series is a joint effort on the part of the IAQF (formerly IAFE) and the Thalesians. The goal of the series is to provide a forum for the exchange of new ideas and results related to the field of quantitative finance. This goal is accomplished by hosting seminars where leading practitioners and academics present new work, and following the seminars with a reception to facilitate further interaction and discussion. The seminar series is limited to IAQF and Thalesians members only. Thalesians Seminar (London) 8212 Scott Cogswell 8212 Initial Margin Model and Regulation for Uncleared Derivatives Date and Time 7:30 p. m. on Wednesday 20th July 2016 Meetup Deep Learning has experienced explosive growth over the last few years with applications in diverse areas such as biomedicine, language processing and self-driving cars. The goal of this talk is to give an introduction to Deep Learning from the perspective of learning patterns in sequences, with an emphasis on understanding the core principles behind the algorithms. We will review the latest advances in Recurrent Neural Networks and discuss applications of RNNs to learning patterns in market data. Steve Hutt is a consultant in Deep Learning and Financial Risk, currently working for CME Group. He has previously been head quant for credit at UBS and Morgan Stanley, and before that a mathematician doing stuff in an obscure branch of topology. IAQF-Thalesians Seminar (New York) 8212 Dr. Tobias Adrian 8212 Nonlinearity and Flight-to-Safety in the Risk-Return Tradeoff for Stocks and Bonds Thursday, June 16, 2015: NYU Kimmel Center. Room 905907, Kimmel Center, 60 Washington Square South, NY 10012, NY Registration We document a highly significant, strongly nonlinear dependence of stock and bond returns on past equity-market volatility as measured by the VIX. We propose a new estimator for the shape of the nonlinear forecasting relationship that exploits additional variation in the cross section of returns. The nonlinearities are mirror images for stocks and bonds, revealing flight to safety: Expected returns increase for stocks when volatility increases from moderate to high levels, while they decline for Treasuries. We further demonstrate that these findings are evidence of dynamic asset pricing theories where the time variation of the price of risk is a function of the level of the VIX. Tobias Adrian is a Senior Vice President of the Federal Reserve Bank of New York and the Associate Director of Research and Statistics Group. His research covers asset pricing, financial intermediation, and macroeconomics, with a focus on the aggregate implications of capital market developments. He has contributed to the NY Feds financial stability policy and to its monetary policy briefings. Tobias Adrian holds a Ph. D. from MIT and a MSc from LSE. He has taught at MIT, Princeton University, and NYU. IAQF-Thalesians Seminars The IAQF-Thalesians Seminar Series is a joint effort on the part of the IAQF (formerly IAFE) and the Thalesians. The goal of the series is to provide a forum for the exchange of new ideas and results related to the field of quantitative finance. This goal is accomplished by hosting seminars where leading practitioners and academics present new work, and following the seminars with a reception to facilitate further interaction and discussion. The seminar series is limited to IAQF and Thalesians members only. Thalesians Seminar (Zurich) 8212 Felix Zumstein - Python in Quantitative Finance Date and Time 7:00 p. m. on Thursday, 9 June, 2016 Examining the electronic trading business from a practitioners perspective. This business has undergone many changes in recent years due to the emergence of new hardware and software products, the development of new quantitative and computational techniques, and changes in market structure and regulations. A market maker needs to be agile in order to remain competitive. This synoptic talk briefly considers the various factors that come into a market makers business calculus. Paul A. Bilokon is Director at Deutsche Bank, where he runs the global credit and core quant teams, part of Markets Electronic Trading (MET) group. He is one of the pioneers of electronic trading in credit, including indices, single names, and cash, and has worked in e-trading, derivatives pricing, and quantitative finance at bulge bracket institutions, including Morgan Stanley, Lehman Brothers, Nomura, and Citigroup. His more than a decade-long career spans many asset classes: equities, FX spot and options, rates and credit. Paul was educated at Christ Church, Oxford, and Imperial College. The domain-theoretic framework for continuous-time stochastic processes, developed with Prof. Abbas Edalat, earned him a PhD degree and a prestigious LICS paper. Pauls other academic interests include stochastic filtering and machine learning. He is an expert developer in C, Java, Python, and kdbq, with a special interest in high performance scientific computing. His interests in philosophy and finance led him to formulate the vision for and found Thalesians, a think tank of dedicated professionals working in quant finance, economics, mathematics, physics and computer science, the focal point of a community with over 1,500 members worldwide. He serves as its CEO, and runs it with two of his friends and colleagues, Saeed Amen and Matthew Dixon, as fellow Directors. Dr. Bilokon is a joint winner of the Donald Davis Prize (2005), winner of the British Computing Society Award for the Student Making the Best Use of IT (World Leadership Forums SET award, 2005), Ward Foley Memorial Scholarship (2001), two University of London High Achiever Awards (in mathematics and physics, 1999) a Member of the British Computer Society, Institution of Engineering and Technology, and European Complex Systems Society Associate of the Securities and Investment Institute, and Royal College of Science and a frequent speaker at premier conferences such as Global Derivatives, alphascope, LICS, and Domains. IAQF-Thalesians Seminar (New York) 8212 Dr. Luis Seco 8212 Hedge funds: are negative fees in the horizon An option pricing perspective Thursday, May 12, 2015: NYU Kimmel Center. Room 914, Kimmel Center, 60 Washington Square South, NY 10012, NY Registration The growth of the hedge fund sector is creating a difficult environment for start-ups, which is creating a climate that favors innovative fee structures. In this talk we will review some of them, and will propose a costbenefit analysis using Black-Scholes option pricing which will show that in some situations, the manager will pay the investor. Luis Seco is a Professor of Mathematics at the University of Toronto, where he also directs the Mathematical Finance Program and the RiskLab, a research laboratory that specializes in risk management research. He is the President and CEO of Sigma Analysis amp Management, an asset management firm that provides hedge fund investment products that employ managed account structures to obtain unique transparency, analytics and liquidity services. He holds a PhD in Mathematics from Princeton and was a Bateman Instructor at the California Institute of Technology. IAQF-Thalesians Seminars The IAQF-Thalesians Seminar Series is a joint effort on the part of the IAQF (formerly IAFE) and the Thalesians. The goal of the series is to provide a forum for the exchange of new ideas and results related to the field of quantitative finance. This goal is accomplished by hosting seminars where leading practitioners and academics present new work, and following the seminars with a reception to facilitate further interaction and discussion. The seminar series is limited to IAQF and Thalesians members only. ThalesiansQuant Finance Group Germany (Frankfurt) 8212 Thomas Wiecki 8212 Predicting out-of-sample performance and building multi-strategy portfolios using Random Forests Date and Time 7:30 p. m. on Wednesday 11th May 2016 PPI AG Office, Wilhelm-Leuschner-Strae 79, Frankfurt Am Main Meetup FREE event, kindly hosted by PPI Thanks for Jochen Papenbrock and Adrian Zymolka for organising and for PPI for hosting. The question of how predictive a backtest is of out-of-sample performance is at the heart of algorithmic trading. Using a unique dataset of 888 algorithmic trading strategies developed and backtested on the Quantopian platform with at least 6 months of out-of-sample performance, we study the prevalence and impact of backtest overfitting. Specifically, we find that commonly reported backtest evaluation metrics like the Sharpe ratio offer little value in predicting out of sample performance (R lt 0.025). However, we show that by training a Random Forest regressor on a variety of features that describe backtest behavior, out-of-sample performance can be predicted at a much higher accuracy (R 0.17) on hold-out data compared to using linear, univariate features. We then show that we can construct a multi-strategy portfolio based on predictions by the Random Forest which performed significantly better out-of-sample than other alternatives. Thomas Wiecki is the Data Science Lead at Quantopian focusing Bayesian models to evaluate trading algorithms. Previously, he was a Quantitative Researcher at Quantopian developing an open-source trading simulator as well as optimization methods for trading algorithms. Thomas holds a PhD from Brown University. Global Derivatives (Budapest - External Event) 8212 Speakers including Carr amp Hull 8212 Trading and risk management Thalesians Workshop Date and Time 9th - 13th May, 2016 Hotel Intercontinental, Budapest, Hungary To sign up You can register for this event and pay online at the Global Derivatives Europe website: icbi-derivativesFKN2466TH - Members of the Thalesians receive a 15 discount (click on the link to activate) The Worlds Largest Quant Finance Conference Join 500 Quants amp Traders From Around The World Over 130 Sessions Covering 5 Full Days Of Content 120 Expert Speakers Buy-Side Summit: Quantitative Investment amp Portfolio Strategies Fintech amp Disruptive Innovation Summit Unmissable speakers for 2016 Peter Carr, Global Head of Market Modelling, Morgan Stanley John Hull, Professor Of Derivatives amp Risk Management, University of Toronto Zoltan Eisler, Co-Head of Execution, Capital Fund Management Fabrizio Anfuso, Head of Collateralized Exposure Modelling, Credit Suisse Thalesians Workshop on ElectronicSystematic Trading at Global Derivatives The Thalesians will be running a workshop at Global Derivatives, which will be led by Saeed Amen and Paul Bilokon, who have a combined experience of two decades in this field. Topics to be discussed include market microstructure and an interactive Python session on systematic trading strategies. Introduction to algorithmic trading and market microstructure models Foundations of linear filtering with applications Foundations of nonlinear filtering with applications How can we define beta in FX and how can we make it smarter Trading with Big Data: Creating systematic trading strategies in FX and fixed income, using new forms of data, with a focus on central bank communications, alpha capture amp news analytics Trading Strategy Focus: How to build a CTAtrend following fund Python amp PyThalesians: Going from systematic trading ideas to backtesting in Python (with tutorial) Author Talk: Trading Thalesians What the ancient world can teach us about trading today (Palgrave Macmillan) External: Emerging Quant Managers (Chicago) 8212 Euan Sinclair 8212 Systematic Vol Trading Date and Time 3:30 p. m. on Friday 6th May 2016 In this talk, we investigate whether we can improve the risk adjusted returns of a traditional, directional (CTA style) trend following strategy by employing systematic option trading strategies. We shall be looking at several markets including FX and equities. Jacob Bartram has extensive experience in trading at both banks and hedge funds. His background includes FX option and volatility trading, along with trading system design and development. He has presented at numerous industry conferences, including Global Derivatives and TradeTech FX. IAQF-Thalesians Seminar (New York) 8212 Dr. Lawrence R. Glosten 8212 Strategic Foundation for the Tail Expectation in Limit Order Book Markets Thursday, April 14, 2015: NYU Kimmel Center. Room 914, Kimmel Center, 60 Washington Square South, NY 10012, NY Registration We analyze the strategic interactions of liquidity suppliers quoting on a limit order book. In an environment with noise traders and informed traders trading on news we show that there is an equilibrium that feature quoters using mixed strategies each offering the same quantity of shares at random prices (and, of course, random bid prices). These random prices with the associated quantities form the market quotes and the depth of book, or price schedule. There are equilibria with a smaller number of quoters quoting a larger number of shares and equilibria with a larger number of quoters quoting a smaller number of shares. Considering a sequence of equilibria with the number of quoters getting large, we establish that the stochastic equilibrium price schedule converges to the zero profit deterministic competitive price schedule. An offer (or bid) is characterized as the expectation of the future value conditional on the offer being picked off by a larger buy (or sell) order. Lawrence R. Glosten is the S. Sloan Colt Professor of Banking and International Finance at Columbia Business School. He is also co-director (with Merritt Fox and Ed Greene) of the Program in the Law and Economics of Capital Markets at Columbia Law School and Columbia Business School and is an adjunct faculty member at the Law School. He has been at Columbia since 1989, before which he taught at the Kellogg Graduate School of Management at Northwestern University, and has held visiting appointments at the University of Chicago and the University of Minnesota. He has published articles on the microstructure and industrial organization of securities markets the relationship between venture capitalists and entrepreneurs evaluating the performance of portfolio managers asset pricing and more recently exploration of the law and economics of capital market regulation. His work on electronic exchanges in the Journal of Finance won a Smith Breeden Distinguished Paper Prize. He has served as an editor of the Review of Financial Studies, associate editor of the Journal of Finance and serves on several other editorial boards. He has been a consultant for the New York Stock Exchange, Justice Department, and SEC and has served on the NASDAQ Economic Advisory Board. He received his AB from Occidental College (1973) and his Ph. D. in managerial economics from Northwestern University (1980). IAQF-Thalesians Seminars The IAQF-Thalesians Seminar Series is a joint effort on the part of the IAQF (formerly IAFE) and the Thalesians. The goal of the series is to provide a forum for the exchange of new ideas and results related to the field of quantitative finance. This goal is accomplished by hosting seminars where leading practitioners and academics present new work, and following the seminars with a reception to facilitate further interaction and discussion. The seminar series is limited to IAQF and Thalesians members only. Thalesians Seminar (London) 8212 Robin Hanson 8212 Economics when robots rule the Earth (Book) Date and Time 7:30 p. m. on Monday, 21 March, 2016 Level39, One Canada Square, Canary Wharf, London, E14, UK Meetup FREE event - kindly sponsored by the Level39 - fintech accelerator - level39.co Full title: The Age of Em: Work, Love and Life when Robots Rule the Earth (Amazon pre-order book here ) Robots may one day rule the world, but what is a robot-ruled Earth like Many think the first truly smart robots will be brain emulations or ems. Scan a human brain, then run a model with the same connections on a fast computer, and you have a robot brain, but recognizably human. Train an em to do some job and copy it a million times: an army of workers is at your disposal. When they can be made cheaply, within perhaps a century, ems will displace humans in most jobs. In this new economic era, the world economy may double in size every few weeks. Some say we cant know the future, especially following such a disruptive new technology, but Professor Robin Hanson sets out to prove them wrong. Applying decades of expertise in physics, computer science, and economics, he uses standard theories to paint a detailed picture of a world dominated by ems. While human lives dont change greatly in the em era, em lives are as different from ours as our lives are from those of our farmer and forager ancestors. Ems make us question common assumptions of moral progress, because they reject many of the values we hold dear. Read about em mind speeds, body sizes, job training and career paths, energy use and cooling infrastructure, virtual reality, aging and retirement, death and immortality, security, wealth inequality, religion, teleportation, identity, cities, politics, law, war, status, friendship and love. This book shows you just how strange your descendants may be, though ems are no stranger than we would appear to our ancestors. To most ems, it seems good to be an em. Robin Dale Hanson is an associate professor of economics at George Mason University and a research associate at the Future of Humanity Institute of Oxford University. He is known as an expert on idea futures and markets, and he was involved in the creation of the Foresight Exchange and DARPAs FutureMAP project. He invented market scoring rules like LMSR (Logarithmic Market Scoring Rule)used by prediction markets such as Consensus Point (where Hanson is Chief Scientist), and has conducted research on signaling. MathFinance 2016 (Frankfurt - External Event) 8212 Speakers including Wystup amp Dupire 8212 Quant event Date and Time 21-22st March 2016 Frankfurt School of Finance amp Management To sign up You can find out more about this event and register and pay online at the MathFinance website: mathfinanceconference. html In the past 16 years the MathFinance Conference became to one of the top quant events tailored to the European Finance Community. The conference is intended for practitioners in the areas of trading, quantitative or derivative research, risk and asset management, insurance as well as for academics studying or researching in the field of financial mathematics or finance in general. The Conference talks are given by both industry experts and top academics. A wide range of subjects is covered, from state-of-the-art approaches to key issues faced in industry and academia to IT implementation and pricing software. There will be enough time for questions and discussions after each talk and additional breaks provide you the opportunity to build networks within the quantitative finance community. Many speakers who have also spoken at the Thalesians will be speaking, including Uwe Wystup and Attilio Meucci. Many other well known figures such as Bruno Dupire will also be addressing the conference. IAQF-Thalesians Seminar (New York) 8212 Dr. Alexander Lipton 8212 Modern Monetary Circuit Theory Tuesday, March 15, 2015: NYU Kimmel Center. Room 914, Kimmel Center, 60 Washington Square South, NY 10012, NY Registration A modern version of Monetary Circuit Theory with a particular emphasis on stochastic underpinning mechanisms is developed. It is explained how money is created by the banking system as a whole and by individual banks. The role of central banks as system stabilizers and liquidity providers is elucidated. Both the Chicago Plan and the Free Banking Proposal are discussed. It is shown how in the process of money creation, banks become naturally interconnected. A novel Extended Structural Default Model describing the stability of the Interconnected Banking Network is proposed. The purpose of bank capital and liquidity is explained. A multi-period constrained optimization problem for a banks balance sheet is formulated and solved in a simple case. Both theoretical and practical aspects are covered. Alexander Lipton is a Managing Director, Quantitative Solutions Executive at Bank of America, Visiting Professor of Quantitative Finance at University of Oxford and Advisory Board member at the Oxford-Man Institute. Prior to his current role, he was a Managing Director, Co-head of the Global Quantitative Group at Bank of America Merrill Lynch and a Visiting Professor of Mathematics at Imperial College London. Earlier, he was a Managing Director and Head of Capital Structure Quantitative Research at Citadel Investment Group in Chicago he has also worked for Credit Suisse, Deutsche Bank and Bankers Trust. Before switching to finance, Alex was a Full Professor of Mathematics at the University of Illinois and a Consultant at Los Alamos National Laboratory. He received his undergraduate and graduate degrees in pure mathematics from Moscow State University. Liptons interests encompass all aspects of financial engineering, including large-scale bank balance sheet modeling and optimization, enterprise-wide holistic risk management and stress testing, CCPs, electronic trading, trading strategies, payment systems, theory of monetary circuit, as well as hydrodynamics, magnetohydrodynamics, and astrophysics. Lipton authored two books, and edited five books, including, most recently, Risk Quant of the Year Award, Risk Books, London, 2014, and The Oxford Handbook of Credit Derivatives, Oxford University Press, Oxford, 2011 (with Andrew Rennie). He published more than a hundred scientific papers on a variety of topics in applied mathematics and financial engineering. IAQF-Thalesians Seminars The IAQF-Thalesians Seminar Series is a joint effort on the part of the IAQF (formerly IAFE) and the Thalesians. The goal of the series is to provide a forum for the exchange of new ideas and results related to the field of quantitative finance. This goal is accomplished by hosting seminars where leading practitioners and academics present new work, and following the seminars with a reception to facilitate further interaction and discussion. The seminar series is limited to IAQF and Thalesians members only. Thalesians Seminar (London) 8212 Prof Jessica James 8212 FX Option Trading (Book) Date and Time 7:30 p. m. on Monday, 29 February, 2016 Ginger Room, Marriott Hotel, Canary Wharf, London, UK. Meetup Full title: FX Option Performance - An Analysis of the Value Delivered by FX Options Since the Start of the Market (The Wiley Finance Series) (Amazon book order here ) Get the little known yet crucial facts about FX options Daily turnover in FX options is an estimated U. S. 207 billion, but many fundamental facts about this huge and liquid market are generally unknown. FX Option Performance provides the information practitioners need to be more effective in the market, with detailed, specific guidance. This book is a unique and practical guide to option trading, with the courage to report how much these contracts have really made or lost. Breaking free from the typical focus on theories and generalities, this book gets specific travelling back in history to show exactly how options performed in different markets and thereby helping investors and hedgers alike make more informed decisions. Not overly technical, the rigorous approach remains accessible to anyone with an interest in the area, showing investors where to look for value and helping corporations hedge their FX exposures. FX Option Performance begins with a quick and practical introduction to the FX option market, then provides specific advice toward structures, performance, rate fluctuation, and trading strategies. Examine the historical payoffs to the most popular and liquidly traded options Learn which options are overvalued and which are undervalued Discover surprising, generally unpublished facts about emerging markets Examine systemic option trading strategies to find what works and what doesnt On average, do options result in profit, loss, or breaking even How can corporations more costeffectively hedge their exposure to emerging markets Are cheap outofthemoney options worth it Professor Jessica James is Senior Quantitative Researcher at Commerzbank in London. She joined Commerzbank from Citigroup where she held a number of FX roles, latterly as Global Head of the Quantitative Investor Solutions Group. Prior to this she was the Head of Risk Advisory and Currency Overlay for Bank One. Before her career in finance, James lectured in physics at Trinity College, Oxford. Her significant publications include the Handbook of Foreign Exchange (Wiley), Interest Rate Modelling (Wiley), and Currency Management (Risk books). Her new book FX Option Performance was published in May 2015. She has been closely associated with the development of currency as an asset class, being one of the first to create overlay and currency alpha products. Jessica is a Managing Editor for the Journal of Quantitative Finance, and is a Visiting Professor both at UCL and at Cass Business School. Apart from her financial appointments, she is a Fellow of the Institute of Physics and has been a member of their governing body and of their Industry and Business Board. IAQF-Thalesians Seminar (New York) 8212 Dr. Harry Mamaysky 8212 Does Unusual News Forecast Market Stress Meetup How to build a CTA - Creating a trend following fund (Saeed Amen) - In this talk we explain how to create trend following strategies which CTA-style funds typically follow. We shall also give a step by step demo of implementing an FX trend following strategy in PyThalesians - open source Python library for analysing markets - githubthalesianspythalesians Pair trading strategies (Delaney Granizo-Mackenzie) - Pairs trading is a form of mean reversion that has a distinct advantage in always being hedged against market movements. It is generally a high alpha strategy when backed up by some rigorous statistics. Delaney Granizo-Mackenzie will review some general principles for pairs trading, and then dive into the statistics behind the strategy during this talk. What is cointegration How to test for cointegration What is pairs trading How to find cointegrated pairs How to generate a tradeable signal This talk is part of The Quantopian Lecture Series. All lecture materials can be found at: quantopianlectures. Saeed Amen is a co-founder of the Thalesians. Over the past decade, Saeed Amen has developed systematic trading strategies at major investment banks including Lehman Brothers and Nomura. Independently, he is also a systematic FX trader, running a proprietary trading book trading liquid G10 FX, which has had a Sharpe ratio over 1.5 since 2013. He is also the author of Trading Thalesians: What the ancient world can teach us about trading today (Palgrave Macmillan). He is also the founder of Cuemacro. Delaney Granizo-Mackenzie is an engineer at Quantopian who focuses on how Quantopian can be used as a teaching tool. After studying computer science at Princeton, Delaney joined Quantopian in 2014. Since then he has led successful course integrations at MIT Sloan and Stanford, and is working with over 20 courses for this fall. Delaney is using his experience and feedback from professors to build a quantitative finance curriculum focusing on best statistical practices to be offered for free. Delaneys background includes 7 years of academic research at a bioinformatics lab, and a strong focus on statistics and machine learning. Thalesians Sance (Budapest) 8212 Robin Hanson amp Panel 8212 Economics when robots rule the Earth A very special thanks to Attila Agod for organising this talk Our goal is to create a social convergence point for the quantitative financial professionals in Hungary with quarterly events Date and Time 7:00 p. m. on Fri 29th January, 2016 7:00 p. m. - Welcome drinks, 8:00 p. m. - Robin Hanson presentation 9:00 p. m. - Discussion panel 12.00 a. m. - Next pub Palack Borbr, Szent Gellrt sqr 3, Budapest Meetup At the 8th Thalesians Sance, Robin Hanson will present us a thought experiment about the life and economics of our society after the singularity. Robin is the author of the Age of Em - Work, Love and Life when Robots Rule the Earth (ageofem ). Members of the panel: - Attila Agod - Mark Horvath (Causality) - Saeed Amen (The Thalesians) Robin Dale Hanson is an associate professor of economics at George Mason University and a research associate at the Future of Humanity Institute of Oxford University. He is known as an expert on idea futures and markets, and he was involved in the creation of the Foresight Exchange and DARPAs FutureMAP project. He invented market scoring rules like LMSR (Logarithmic Market Scoring Rule)used by prediction markets such as Consensus Point (where Hanson is Chief Scientist), and has conducted research on signaling. Thalesians Seminar (London) 8212 Nick Firoozye 8212 Managing Uncertainty, Mitigating Risk (Book) Date and Time 7:30 p. m. on Wednesday, 20 January, 2016 Ginger Room, Marriott Hotel, Canary Wharf, London, UK. Meetup Financial risk management started in a period when academic finance was wedded to probability. Risk and its transferability was the focus and uncertainty was sidelined. After the recent financial crisis, uncertainty and its consequences have become a major concern for many prominent academics, yet practitioners are constrained by probability-based tools and regulatory mandates. Managing Uncertainty, Mitigating Risk offers a liberated perspective on uncertainty in banking and finance. The book stresses that uncertainty must be confronted by using a broader range of inputs, employing methods outside conventional probability. More often than not, systemic risks are not completely unforeseeable and a range of likely risk scenarios can be fleshed out, quantified and largely mitigated. We can accomplish this only if we widen our knowledgebase to include qualitative data and judgment. Probability and historical data alone cannot sufficiently model game-changing and catastrophic one-off situations such as Eurozone exit and breakup, US debt ceiling, and Brexit. This book presents a robust foundation and a novel and practical method for incorporating uncertainty into existing risk frameworks. It takes the reader beyond the realms of probability in modern finance, into imprecise probability the mathematics of uncertainty. We introduce uncertain value-at-risk (UVaR), a measure which takes the VaR engine and enhances it using credal nets, an imprecise extension of Bayesian nets. Unlike the unjustified precision of probability-based models, UVaR helps to assesses uncertainty by incorporating expert insight through priors, with more extensive datasets. By combining a solid quantitative method with an implementation framework and cases, this book allows the reader to not only understand the solution for managing uncertain one-offs, but also to see the end-product. This is a starting point for risk practitioners to go beyond regulatory-initiated tools in order to employ their own approaches towards recognizing and managing uncertainty. Nick Firoozye is a Managing Director at Nomura International and heads a global team in cross-product derivatives research. He has many years of experience in a variety of research and trading roles in both buy-side and sell-side firms including Goldman Sachs, Deutsche Bank, Citadel, Sanford Bernstein and Lehman Brothers. Known for his work in Quantitative Strategy, Nicks area of expertise ranges from asset allocation models and macro-financial forecasting to systematic and RV trading. Previously, he was Head of European Rates Strategy, and covered the Eurozone crisis, rescue packages and possible break-up, working closely with the risk management and legal teams. Dr Firoozye was an Assistant Professor at the University of Illinois, and holds a PhD in Applied Mathematics from Courant Institute, New York University. He speaks and writes frequently on financial markets and economics issues. His team was recently awarded Global Capitals Derivatives Research House of 2015, and he was co-author of one of five papers shortlisted for the 2012 Wolfson Economics Prize on the breakup of the Eurozone. IAQF-Thalesians Seminar (New York) 8212 Dr. Nick Costanzino 8212 Pricing and Hedging Recovery Risk with Structural and Reduced Form Models Tuesday, January 12, 2015: NYU Kimmel Center. Room 914, Kimmel Center, 60 Washington Square South, NY 10012, NY Registration The fixed-income literature attempts to explain credit spreads though a decomposition into different risk premia. The most commonly analyzed risk premia are default and liquidity risk. Recovery risk has not received much attention most likely because of the pervasive practice of assuming constant recovery in most credit models. However, assuming a constant recovery has two major effects. The first is we have inconsistent pricing (if recovery is a known constant, what is the price of a recovery swap) and the second is over - or underpricing the default risk portion of the credit spread. In this talk I will present recent work on isolating the recovery risk premium in corporate bond and CDS spreads using both structural and hazard rate models. This allows us to isolate the recovery risk premium from the default risk premium, as well as provide a consistent pricing framework for all recovery linked products including bonds, CDS and recovery swaps. Finally, we discuss some trading opportunities that can be exploited using framework. Nick Costanzino received his PhD in Applied Mathematics in 2006 from Brown University in Providence R. I. His thesis combined tools from pseudodifferential operators and dynamical systems to prove multidimensional stability of certain nonlinear wave structures in fluids. He later moved to the Penn State University Math Department as a Chowla Assistant Professor where he was introduced to quantitative finance and helped developed their Mathematical Finance program. After a brief tenure at Wilfrid Laurier University in Canada he then moved to the finance industry working in various credit roles including risk manager for the CDS and corporate bond trading desk at Scotiabank. He is interested in all areas of quantitative finance, but particularly those which lead to improvements in understanding the credit and equity markets. Nick is currently in the Investment Analytics group at AIG in New York and is a member of RiskLab at the University of Toronto. IAQF-Thalesians Seminars The IAQF-Thalesians Seminar Series is a joint effort on the part of the IAQF (formerly IAFE) and the Thalesians. The goal of the series is to provide a forum for the exchange of new ideas and results related to the field of quantitative finance. This goal is accomplished by hosting seminars where leading practitioners and academics present new work, and following the seminars with a reception to facilitate further interaction and discussion. The seminar series is limited to IAQF and Thalesians members only. External (London) 8212 International Conference on Computational Finance (ICCF2015) University of Greenwich Date and Time Registration We present a liquidity factor IML, the return on illiquid-minus-liquid stock portfolios. The IML, adjusted for the common risk factors, measures the illiquidity premium whose annual alpha is about 4 over the period 1950-2012. I then test whether the systematic risk () of IML is priced in a multi-factor CAPM. The model allows for a conditional of IML that rises with observable funding illiquidity and adverse market conditions. The conditional IML is positively and significantly priced, and remains so after controlling for the beta of illiquidity shocks. Yakov Amihud is Ira Rennert Professor of Entrepreneurial Finance at the Stern School of Business, New York University. He is the coauthor of Market Liquidity: Asset Pricing, Risk and Crises (Cambridge University Press, 2013). His research focuses on the effects of asset liquidity on value and expected return, and on the design and evaluation of securities markets trading methods. On these topics, Amihud has done consulting work for the NYSE, AMEX, CBOE, CBOT, and other securities markets. He has published more than seventy research articles in professional journals and in books, and edited and co-edited five books on topics such as LBOs, bank MampAs, international finance, and securities market design. His research also includes the evaluation of corporate financial policies, mergers and acquisitions, initial public offerings, objectives of corporate managers, dividend policy, and law and finance. IAQF-Thalesians Seminars The IAQF-Thalesians Seminar Series is a joint effort on the part of the IAQF (formerly IAFE) and the Thalesians. The goal of the series is to provide a forum for the exchange of new ideas and results related to the field of quantitative finance. This goal is accomplished by hosting seminars where leading practitioners and academics present new work, and following the seminars with a reception to facilitate further interaction and discussion. The seminar series is limited to IAQF and Thalesians members only. Thalesians SeminarXmas Dinner (London) 8212 Matthew Dixon 8212 Machine Learning in Trading: Implementing Deep Neural Networks for Financial Market Prediction on the Intel Xeon Phi Date and Time 6.30p. m. on Monday, 14 December, 2015 La Tasca, West India Quay, Canary Wharf, London E14 4AE Meetup Talk amp Dinner We invite you to our 2015 Thalesians LDN Xmas seminar amp dinner by Matthew Dixon on Implementing Deep Neural Networks for Financial Market Prediction on the Intel Xeon Phi followed by dinner at La Tasca in Canary Wharf. The presentation begins at 6.30pm, followed by dinner at 7.30pm (menu below). On Arrival - A Glass of Sangra Tradicional To Start - Tabla Espanola (to share) - Traditional Spanish cured meats with mixed olives, Manchego cheese, bread and oil. Christmas Albndigas (Madrid) - Turkey amp pork meatballs, in a rich, sherry and cranberry sauce. Pulpo Gratin Y Queso GF (Galicia) - A medley of potatoes and octopus baked in a creamy lobster sauce and gratinated with Manchego cheese. Pollo Marbella GF (Malaga) - Chicken breast, cooked with chorizo in a white wine amp cream sauce. La Tasca House Green Salad GF V (Navarra) Patatas Bravas con Alioli (Espaa) - Fried potato, with spicy tomato sauce and roasted garlic mayonnaise. Paella de Carne GF (Valencia) - With chicken breast and chorizo. Paella Verduras GF V (Valencia) - With seasonal vegetables. To Finish - Churros - Doughnut twists, served with fresh strawberries and marshmallows, plus a rich chocolate sauce Deep neural networks (DNN) have demonstrated their power in areas such as vision (think Google image search) and speech recognition (think Siri). Some financial firms are beginning to apply these techniques to market data and other information important for trading and investing. But training DNNs (that is, setting them to work to develop models) is extremely compute intensive. In this talk, Matthew will describe a DNN model for predicting price movements from time series data, then explain techniques that enable this model to exploit the parallel computing capacity of the Intel Xeon Phi processor in conjunction with multi-core CPUs. Matthew Dixon is a Managing Director and Head of Americas at Thalesians Ltd. He is also an Assistant Professor of Finance in the Stuart Business School at the Illinois Institute of Technology. His research focuses on the application of advanced computational techniques to financial modeling and data analysis especially where high performance and scalability are critical for practical application. Matthews research is currently funded by Intel Corporation. He has contributed to the R package repository and published around twenty peer-reviewed technical articles. He has taught financial econometrics, derivatives, machine learning and text mining at the University of San Francisco and held visiting appointments in CSMath at Stanford University and UC Davis. Prior to joining academia, he has held industry appointments as a quant at banks such as Lehman Brothers, the Bank for International Settlements and Barclays Capital. He chairs the workshop on computational finance at the annual SuperComputing conference and serves on the program committee of HPC and on the editorial board of the Journal of Financial Innovation. Matthew holds a MEng in Civil Engineering from Imperial College London, a MSc in Parallel and Scientific Computation (with distinction) from the University of Reading, and a PhD in Applied Math from Imperial College London. He became a chartered financial risk manager in 2014. Thalesians Panel (London) 8212 CudmoreBurroughs amp more 8212 Global macro panel Registration The structural default model of Lipton and Sepp, 2009 is generalized for a set of banks with mutual interbank liabilities whose assets are driven by correlated Levy processes with idiosyncratic and common components. The multi-dimensional problem is made tractable via a novel computational method, which generalizes the one-dimensional fractional partial differential equation method of Itkin, 2014 to the two - and three-dimensional cases. This method is unconditionally stable and of the second order of approximation in space and time in addition, for many popular Levy models it has linear complexity in each dimension. Marginal and joint survival probabilities for two and three banks with mutual liabilities are computed. The effects of mutual liabilities are discussed, and numerical examples are given to illustrate these effects. Dr. Andrey Itkin is an Adjunct Professor at NYU, Department of Risk and Financial Engineering and Director, Senior Research Associate at Bank of America. He received his PhD in physics of liquids, gases and plasma, and degree of Doctor of Science in computational molecular physics. During his academic carrier he published few books and multiple papers on chemical and theoretical physics and astrophysics, and later on computational and mathematical finance. Andrey occupied various research and managerial positions in financial industry and also is a member of multiple professional associations in finance and physics. IAQF-Thalesians Seminars The IAQF-Thalesians Seminar Series is a joint effort on the part of the IAQF (formerly IAFE) and the Thalesians. The goal of the series is to provide a forum for the exchange of new ideas and results related to the field of quantitative finance. This goal is accomplished by hosting seminars where leading practitioners and academics present new work, and following the seminars with a reception to facilitate further interaction and discussion. The seminar series is limited to IAQF and Thalesians members only. Thalesians Seminar (London) 8212 Robert Carver 8212 Lessons from Systematic Trading Date and Time 7:30 p. m. on Wednesday, 21 October, 2015 Ginger Room, Marriott Hotel, Canary Wharf, London, UK. Meetup Its my belief that successful systematic trading is not about finding some deep hidden source of alpha, but about avoiding stupid mistakes. In this talk I share some of the mistakes Ive made, and seen others make, whilst designing and managing systematic trading systems for both a multi billion hedge fund and a retail trading account. This is a wide ranging talk which provocatively questions many commonly held beliefs about the business of managing money systematically. Robert Carver is an independent systematic trader, and writer. He trades his own capital with a fully automated system of 40 futures markets, using a proprietary system written in python. Robert is the author of Systematic Trading, a forthcoming book to be published by Harriman House in October 2015. He regularly blogs on the subject of trading, finance and investment. Robert, who has bachelors and masters degrees in Economics, began his city career trading exotic derivative products for Barclays Capital. He then worked as a portfolio manager for AHL. one of the worlds largest systematic hedge funds before, during and after the global financial meltdown of 2008. Robert was responsible for the creation of AHLs fundamental cross asset global macro strategy, and then managed the funds multi billion dollar fixed income portfolio. He retired from the industry in 2013. IAQF-Thalesians Seminar (New York) 8212 Dr. Dan Pirjol 8212 Can one price Eurodollar futures in the Black-Derman-Toy model Wednesday, October 14, 2015: NYU Kimmel Center. Room 914, Kimmel Center, 60 Washington Square South, NY 10012, NY Registration Interest rates models with log-normally distributed rates in continuous time are known to display singular behavior. For example, Eurodollar futures prices are infinite in the Dothan and Black-Karasinski models, as shown in 1998 by Hogan and Weintraub. These singularities are usually assumed to disappear when the models are simulated in discrete time. Using a precise simulation of the BDT model, we demonstrate that this is true only for sufficiently low volatilities. Eurodollar futures prices explode for volatilities above a critical value. The explosion is due to contributions from a region in state space which corresponds to very large interest rates and is truncated off in usual simulation methods such as trees and finite difference methods. In the limit of a very small simulation time step the explosion appears for any volatility, and reproduces the Hogan-Weintraub singularity of the continuous time model. Dan Pirjol works in the Model Risk Group at JP Morgan, covering valuation models in commodities. Previously he was with Markit and Merrill Lynch in various roles in modeling and model risk, after doing research in theoretical high energy physics. He is interested in applications of methods from mathematical physics and probability to problems in mathematical finance. IAQF-Thalesians Seminars The IAQF-Thalesians Seminar Series is a joint effort on the part of the IAQF (formerly IAFE) and the Thalesians. The goal of the series is to provide a forum for the exchange of new ideas and results related to the field of quantitative finance. This goal is accomplished by hosting seminars where leading practitioners and academics present new work, and following the seminars with a reception to facilitate further interaction and discussion. The seminar series is limited to IAQF and Thalesians members only. Thalesians Sance (Budapest) 8212 Taylor Spears amp Panel 8212 The Sociology of CVA A very special thanks to Attila Agod for organising this talk Our goal is to create a social convergence point for the quantitative financial professionals in Hungary with quarterly events Date and Time 7:00 p. m. on Fri 9th October, 2015 7:00 p. m. - Welcome drinks, 8:00 p. m. - Taylor Spears presentation 9:00 p. m. - Discussion panel 12.00 a. m. - Next pub Palack Borbr, Szent Gellrt sqr 3, Budapest Meetup At the 7th Thalesians Sance Taylor Spears from the Sociology Department of The University Edinburgh will introduce the evolution of Credit Valuation Adjustment (CVA) from a sociologists point of view. After Taylors talk a panel of practitioners will challenge his ideas. Members of the panel: - Andras Bohak (MSCI, Counterparty credit researcher) - Daniel Homolya (Mol Group, Financial risk management team lead) - Balazs Palosi-Nemeth (ING, Architect) - Gabor Salamon (Morgan Stanley, CVA team lead) Dr Taylor Spears is a research fellow in the Sociology of Financial Modelling at the School of Social and Political Science in the University of Edinburgh. Thalesians Seminar (New York) 8212 Creating trend following fund: How to build a CTA interactive Python PyThalesians demo Date and Time 6:00 p. m. on Thursday, 1 October, 2015 Shark Tank, Grind Broadway, 22nd Floor, 1412 Broadway, New York, NY Meetup In this talk, we shall be discussing CTAs and giving some background about the industry. We shall give a brief overview of the types of strategies CTAs use to trade markets, creating a generic proxy for a typical CTA fund. We shall also be discussing how CTA strategies can be used to improve the risk adjusted returns of long only equity and bond investors. Later, there will also be an interactive Python demo showing how to use the PyThalesians Python code library (partially open sourced on GitHub ). Amongst other things we shall investigate the properties of intraday FX volatility, where well be accessing live market data via Bloomberg and also creating customised plots using Matplotlib. Selected Bios Saeed Amen is a co-founder of the Thalesians. Over the past decade, Saeed Amen has developed systematic trading strategies at major investment banks including Lehman Brothers and Nomura. Independently, he is also a systematic FX trader, running a proprietary trading book trading liquid G10 FX, which has had a Sharpe ratio over 1.5 since 2013. He is also the author of Trading Thalesians: What the ancient world can teach us about trading today (Palgrave Macmillan). He is also the founder of Cuemacro. Thalesians Seminar (London) 8212 Stephen Pulman 8212 Multi-Dimensional Sentiment Analysis Date and Time 7:30 p. m. on Wednesday, 23 September, 2015 Ginger Room, Marriott Hotel, Canary Wharf, London, UK. Meetup All sentiment analysis systems can deliver positive negativeneutral classifications. But there are many other useful signals in text: emotion, intent, speculation, risk, etc. This talk will present a survey of the state of the art in recognising these other dimensions of sentiment in text and describe some practical applications in finance and elsewhere. Stephen Pulman is Professor of Computational Linguistics at the Department of Computer Science, Oxford University. He is a Professorial Fellow of Somerville College, Oxford, and a Fellow of the British Academy. He has also held visiting professorships at the Institut fr Maschinelle Sprachverarbeitung, University of Stuttgart and at Copenhagen Business School. He is a co-founder of TheySay Ltd. Previous positions include Professor of General Linguistics at Oxford University, Assistant Professor (Reader) at the University of Cambridge Computer Laboratory, and Director of SRI Internationals Cambridge. IAQF-Thalesians Seminar (New York) 8212 Dr. Agostino Capponi 8212 Arbitrage-Free Pricing of XVA Monday, September 21, 2015: NYU Kimmel Center. Room 914, Kimmel Center, 60 Washington Square South, NY 10012, NY Registration The recent financial crisis has highlighted the importance to account for counterparty risk and funding costs in the valuation of over-the-counter portfolios of derivatives. When managing their portfolios, traders face costs for maintaining the hedge of the position, posting collateral resources, and servicing their collateral requests. Due to the interdependencies between these operations, such costs cannot be separated and attributed to different business units (CVA, DVA and FVA desks). In this talk, we introduce a unified framework for computing the total costs, referred to as XVA, of an European style derivative transaction traded between two risky counterparties. We use no-arbitrage arguments to derive the nonlinear backward stochastic differential equations (BSDEs) associated with the portfolios which replicate long and short positions in the claim. This leads to defining buyers and sellers XVAs which in turn identify a no-arbitrage band. When borrowing and lending rates coincide, our framework recovers a generalized version of Piterbargs model. In this case, we provide a fully explicit expression for the uniquely determined price of XVA. When they differ, we derive the semi-linear partial differential equations (PDEs) associated with the non-linear BSDEs and show that they admit a unique classical solution. We use these solutions to conduct a numerical analysis showing high sensitivity of the no-arbitrage band and replicating strategies to funding spreads and collateral levels. Agostino Capponi is an assistant professor in the IEOR Department at Columbia University, where he is also a member of the Institute for Data Science and Engineering. Agostino received his Master and Ph. D. Degree in Computer Science and Applied and Computational Mathematics from the California Institute of Technology, respectively in 2006 and 2009. His main research interests are in the area of networks, with a special focus on systemic risk, contagion, and control. In the context of financial networks, the outcome of his research contributes to a better understanding of risk management practices, and to assess the impact of regulatory policies aimed at controlling financial markets. He has been awarded a grant from the Institute for New Economic Thinking for his research on dynamic contagion mechanisms. His work on systemic risk dynamics under central clearing done in collaboration with the Department of Treasury has obtained press coverage from major organizations such as Bloomberg and Reuters. His research has been published in top-tier journals of Financial Mathematics, Operations Research, and Engineering. His work has also been published in leading practitioner journals and invited book chapters. Agostino holds a world patent for a target tracking methodology in military networks. IAQF-Thalesians Seminars The IAQF-Thalesians Seminar Series is a joint effort on the part of the IAQF (formerly IAFE) and the Thalesians. The goal of the series is to provide a forum for the exchange of new ideas and results related to the field of quantitative finance. This goal is accomplished by hosting seminars where leading practitioners and academics present new work, and following the seminars with a reception to facilitate further interaction and discussion. The seminar series is limited to IAQF and Thalesians members only. Thalesians Seminar (San Francisco) 8212 Steven Pav - Portfolio Inference and Portfolio Overfit Date and Time amp Schedule 6:00 p. m. on Thursday, 10 September, 2015 6pm: Reception in Julias Lounge 7pm: Talk in the Members Lounge 8pm: Networking