THE 2ND BIG DATA IN QUANTITATIVE FINANCE CONFERENCE

Transcription

1 THE MARYLEBONE HOTEL, LONDON 10TH / 11TH / 12TH JUNE 2015 THE 2ND BIG DATA IN QUANTITATIVE FINANCE CONFERENCE This conference will showcase some of the latest progress made in financial data: This conference offers an intuitive insight into the latest practical aspects Deutsche Börse: Big Data Enabling Technologies A Financial Market Perspective of The CVA desk: Reviewing the impact of regulatory changes & capital Bloomberg will explore Newscasting - Forecasting Global Macro Economic Data from News and Events UBS discuss High-Frequency Beta Estimation in Practice charges, XVA management, pricing adjustments & desk organization ABN AMRO Analyze Large Volume Transactions on Capital Markets and Natixis the will latest present pricing, Anomaly Detection trading Sensitivity & modelling Computation techniques by Machine Learning as well Techniques as a more Global Valuation Limited present on the latest develoements on Capital Simulations for OTC books RavenPack open the conference with Tales from the Front Line; The Quant Market for Big Data The Python Quants look at How Open Source Revolutionizes Financial Analytics HEAR FROM LEADING INDUSTRY EXPERTS INCLUDING: Maurizio Luisi: Senior Quantitative Strategist, Bloomberg LP Dragos Crintea: Innovation Office, Deutsche Börse Tobias Preis: Associate Professor of Behavioural Science and Finance, Warwick Business School, University of Warwick David Jessop: Managing Director Global Head of Equities Quantitative Research, UBS Jose Luu: Head of Scientific Computing, Natixis Yves J. Hilpisch: The Python Quants Igor Stojkovic: Business Advisor Big Data Scientist, ABN Amro Hugh Taggart: Director of Business Development, RavenPack Claudio Albanese: CEO: Global Valuation Limited Saeed Amen: Managing Director & Co-founder: THE THALESIANS Bas van Schriek: Risk Manager: ABN Amro EARLY BIRD DISCOUNTS: 20% BEFORE 17TH APRIL 10% BEFORE 15TH MAY RECEIVE A 100 DISCOUNT WHEN YOU REGISTER TO THE MAIN CONFERENCE + WORKSHOP GOLD SPONSORS SILVER SPONSOR

2 OVERVIEW WEDNESDAY 10TH JUNE PRE-CONFERENCE WORKSHOP DAY: EXPLORING IDEAS IN SYSTEMATIC TRADING by Saeed Amen by Saeed Amen: Managing Director & Co-founder: THE THALESIANS THURSDAY 11TH JUNE MAIN CONFERENCE DAY 1: EFFECTIVE TRADING STRATEGIES & MODELLING TECHNIQUES IN BIG DATA FRIDAY 12TH JUNE MAIN CONFERENCE DAY 2: LATEST TECHNOLOGIES, PROGRAMMING LANGUAGES AND RECENT DEVELOPMENTS IN BIG DATA IMPORTANT NOTES: Main Conference presentation files on USB memory sticks will be provided on arrival. The Main Conference files will also be made available for download via a password protected website before the event. Please print out each presentation if you wish to have hard copies before the conference and bring them with you. Also, Wi-Fi access will be available at the hotel venue to view presentations on laptops, ipads etc. CONFERENCE BOOKINGS: DISCOUNT STRUCTURE: Early Bird Discount: 20% Before 17th April Early Bird Discount: 10% Before 15th May Main Conference + Workshop ( 100 Discount) Receive an extra 5% discount when booking 3 or more delegates 70% Academic Discount (FULL-TIME Students Only) VENUE DETAILS The Marylebone Hotel is only 500 metres from the shops of Oxford Street including Selfridges, John Lewis and the designer boutiques of Bond Street. It offers complimentary access to a state-of-the-art gym, 18-metre swimming pool and fitness classes, as well as free Wi-Fi. 108 Bar & Restaurant and the new Pantry at 108 serve modern cuisine made with fresh produce from local suppliers, and provides 24-hour room service. The Marylebone Hotel is less than a mile (1.5 km) from Oxford Circus, Soho, and Hyde Park. The Marylebone Hotel 47 Welbeck Street London W1G 8DN Tel: +44 (0)

3 PRE-CONFERENCE WORKSHOP DAY WEDNESDAY 10 TH JUNE EXPLORING IDEAS IN SYSTEMATIC TRADING BY SAEED AMEN: MANAGING DIRECTOR & CO-FOUNDER: THE THALESIANS DAY SCHEDULE: 09:00 17:30 / BREAK: 10:30 10:45 / LUNCH: 12:30 13:30 / BREAK: 15:15 15:30 In this workshop, we shall explore themes in systematic trading and Big Data. The day will consist mostly of presentations, and also some demonstrations, as well as a debate with audience participation. MORNING SESSIONS: Introduction: How can we define beta in FX and how can we make it smarter? Exploring Volatility: Systematic trading strategies for FX options Extended Session: Big Data and using it to trade macro asset classes (with multiple case studies) Social Media: How to use Twitter to follow financial markets AFTERNOON SESSIONS: Inside the Box: Going from systematic trading ideas to backtesting in Python Emerging Markets Focus: Trading EMFX from a systematic angle Free debate: discretionary or systematic trading, what is best?

4 MAIN CONFERENCE, DAY 1: THURSDAY 11 TH JUNE EFFECTIVE TRADING STRATEGIES & MODELLING TECHNIQUES IN BIG DATA 08:20 09:00 REGISTRATION 09:00 10:00 TALES FROM THE FRONT LINE; THE QUANT MARKET FOR BIG DATA by Hugh Taggart: Director of Business Development, RavenPack Abstract: Big Data is a catchy phrase to throw around in finance, but in many cases it s still a nice to have. Part of the issue is its scope is boundless. So what big data sets are practioners actually using or trying to use and what are the key features of data sets that are seeing some traction? And how can we make Big Data available to more of the financial community? 10:00 11:00 ANALYSING LARGE VOLUME TRANSACTIONS ON CAPITAL MARKETS by Igor Stojkovic: Business Advisor Big Data Scientist, ABN Amro During the last three decades proprietary market makers, hedge funds and investment banks have been investing ferocious amounts of time and effort in absorbing newest results from machine learning and other disciplines in order to boost their revenues. On the other hand regulators and clearing houses and their members seem not to have been following these developments in their risk management practices. A specific operational risk topic of interest for clearing members is a situation where client s high frequency trading machine starts malfunctioning. Such a sequence of events may not necessarily lead to bankruptcy of the clearing member itself due to frequent risk limits checks, but could bankrupt or seriously damage their client. In this talk we shall discuss a method for finding anomalous trading patterns of clients, before the risk limits are breached and damage is done. Patterns are interpreted as random functions and specific methodology is applied to find regions of typical and atypical trading patterns in appropriate spaces of functions. 11:00 11:30 BREAK 11:30 12:45 CAPITAL SIMULATIONS FOR OTC BOOKS by Claudio Albanese: CEO, Global Valuation Limited Holistic credit-market simulations of OTC books Nested simulations Algebraic versus Monte Carlo logic Parallelisation strategies on MIMD, SIMD and fusion chips Memory/cache hierarchies 12:45 13:45 LUNCH

5 MAIN CONFERENCE, DAY 1: THURSDAY 11 TH JUNE EFFECTIVE TRADING STRATEGIES & MODELLING TECHNIQUES IN BIG DATA 13:45 14:45 HIGH-FREQUENCY BETA ESTIMATION IN PRACTICE by David Jessop: Managing Director Global Head of Equities Quantitative Research, UBS Using high frequency data in a realised volatility calculation is seen as an efficient approach to estimating and forecasting short term volatility. We investigate an extension to this work in estimating high frequency betas. There are many problems in this area, including coping with asynchronicity, with missing data, with markets being open at different times. We will start by discussing the problems of actually implementing this work for a sensible universe in a sensible time (comparing implementation strategies in R and Julia), and also showing where these higher frequency betas add value. 14:45 15:45 FX VOLATILITY OVER EVENTS & USING BIG DATA TO TRADE MACRO by Saeed Amen: Managing Director & Co-founder: THE THALESIANS We examine the impact of major scheduled events such as FOMC and ECB meetings on FX implied volatility for the most liquid currency pairs. We discuss the behaviour of the volatility risk premium. Later we examine how big data, in the context of news analytics data, can be used to create sentiment based indicators. We shall use these indicators to systematically trade macro based asset classes (bond futures and FX). 15:45 16:00 BREAK 16:00 17:00 NEWSCASTING - FORECASTING GLOBAL MACRO ECONOMIC DATA FROM NEWS AND EVENTS by Maurizio Luisi: Senior Quantitative Strategist, Bloomberg LP We propose a powerful filtering technique to extract daily factors from economic news and events released at different times and frequencies. Our approach can effectively handle a large number of different announcements that are relevant for tracking current economic conditions. This technique takes advantage of a large cross-section of real-time economic releases combined with metadata derived using machine-learning news analytics engines. This approach can effectively handle an extremely large number of different announcements that would be difficult to lever using standard filtering techniques previously utilised in the nowcasting literature. We examined the practical uses of our linear and nonlinear projection components to extract real-time measures of inflation, output, employment, and macroeconomic sentiment, as well as corresponding measures of disagreement about these indices. We find that the factors extracted by our nonlinear auto-associative mapping provide more timely and accurate forecasts of future changes in economic conditions than other real-time forecasting approaches.

6 MAIN CONFERENCE, DAY 1: THURSDAY 11 TH JUNE EFFECTIVE TRADING STRATEGIES & MODELLING TECHNIQUES IN BIG DATA 17:10 18:00 EFFECTIVE TRADING STRATEGIES & MODELLING TECHNIQUES IN BIG DATA PANEL Our expert panel will discuss the latest effective trading Strategies, algorithms & modelling techniques in big data. How to define Big Data? What are the challenges when working with Big Data? What are the benefits of structured data versus unstructured? What forms of Big Data are the most popular? Are there Big Data sources that are underutilised? Has Big Data moved from the research to trading phase yet? What are the computational advantages of using GPUs vs multicore? CHAIR: Saeed Amen: Managing Director & Co-founder: THE THALESIANS PANEL Claudio Albanese: CEO, Global Valuation Limited Maurizio Luisi: Senior Quantitative Strategist, Bloomberg LP Igor Stojkovic: Business Advisor Big Data Scientist, ABN Amro

7 MAIN CONFERENCE, DAY 2: FRIDAY 12 TH JUNE LATEST TECHNOLOGIES, PROGRAMMING LANGUAGES AND RECENT DEVELOPMENTS IN BIG DATA 09:00 10:30 MEASURING AND PREDICTING HUMAN BEHAVIOUR USING ONLINE DATA by Tobias Preis: Associate Professor of Behavioural Science and Finance, Warwick Business School, University of Warwick In this talk, I will outline some recent highlights of our research, addressing two questions. Firstly, can big data resources provide insights into crises in financial markets? By analysing Google query volumes for search terms related to finance and views of Wikipedia articles, we find patterns which may be interpreted as early warning signs of stock market moves. Secondly, can we provide insight into international differences in economic wellbeing by comparing patterns of interaction with the Internet? To answer this question, we introduce a future-orientation index to quantify the degree to which Internet users seek more information about years in the future than years in the past. We analyse Google logs and find a striking correlation between the country s GDP and the predisposition of its inhabitants to look forward. Our results illustrate the potential that combining extensive behavioural data sets offers for a better understanding of large scale human economic behaviour. Preis, T., Moat, H. S., Stanley, H. E. & Bishop, S. R. Quantifying the Advantage of Looking Forward. Sci. Rep. 2, 350 (2012). Preis, T., Moat, H. S. & Stanley, H. E. Quantifying trading behavior in financial markets using Google Trends. Sci. Rep. 3, 1684 (2013). Moat, H. S., Curme, C., Avakian, A., Kenett, D. Y., Stanley, H. E. & Preis, T. Quantifying Wikipedia usage patterns before stock market moves. Sci. Rep. 3, 1801 (2013). Curme, C., Preis, T., Stanley, H. E., Moat, H. S. Quantifying the semantics of search behavior before stock market moves. PNAS 111, (2014). 10:30 10:50 BREAK 10:50 11:50 ANOMALY DETECTION IN SENSITIVITY COMPUTATION BY MACHINE LEARNING TECHNIQUES by Jose Luu: Head of Scientific Computing, Natixis 4 million computations per day (night) Some of them suspicious Idea: use machine learning algorithms for detection Algorithm selection Detection results for delta, gamma, rho

8 MAIN CONFERENCE, DAY 2: FRIDAY 12 TH JUNE LATEST TECHNOLOGIES, PROGRAMMING LANGUAGES AND RECENT DEVELOPMENTS IN BIG DATA 11:50 12:50 BIG DATA ENABLING TECHNOLOGIES A FINANCIAL MARKET PERSPECTIVE by Dragos Crintea: Innovation Office, Deutsche Börse There is nothing more exciting right now than living in the big data revolution. We all heard of the booming ecosystem, the data deluge, success stories and failures, the incumbents taking a stake in this new technology space. All this and more happened over just a 5 year period at a unprecedented pace. This talk is aimed to present you with a feet view of what s available today. You might then ask yourself what are the key technologies that would enable you to get your data-driven project quickly of the ground. Drawn from a wider industry perspective, the second part of the talk will give you a potential answer to this question, and what made all this possible. 12:50 13:50 LUNCH 13:50 15:20 HOW OPEN SOURCE REVOLUTIONIZES FINANCIAL ANALYTICS by Yves J. Hilpisch: The Python Quants ABSTRACT: This talk is about technologies and recent developments in the Open Source space that are about to re-define and revolutionize financial analytics (e.g. data processing, quantitative research, derivatives & risk analytics, algorithmic trading). With a focus on Python, the talk illustrates how Open Source technologies can reduce costs and improve efficiency in financial analytics at the same time. Many of the leading players in investment banking (e.g. BoAML, JPMorgen) and in the hedge fund industry (e.g. AQR Capital Management, Two Sigma Investments) are already making heavy use of these technologies. 15:20 15:40 BREAK 15:40 16:30 AN ALGORITHM FOR PREDICTION MODELS BASED ON SUPERVISED DATA by Bas van Schriek: Risk Manager, ABN AMRO, CISO, Information Security Risk Management Gini coefficient Bucket algorithm Logistic regression

9 MAIN CONFERENCE, DAY 2: FRIDAY 12 TH JUNE LATEST TECHNOLOGIES, PROGRAMMING LANGUAGES AND RECENT DEVELOPMENTS IN BIG DATA 16:30 17:20 LATEST TECHNOLOGIES, PROGRAMMING LANGUAGES AND RECENT DEVELOPMENTS IN BIG DATA PANEL Our expert panel will discuss the best programming languages to use when dealing with large volumes of data and alternative approaches to managing big data in financial institutions. Opportunities and challenges of big data: How to ask the right questions? How to find the right data sets? How to identify the right methods and models? CHAIR: Tobias Preis: Associate Professor of Behavioural Science and Finance, Warwick Business School, University of Warwick PANEL Dragos Crintea: Innovation Office, Deutsche Börse Yves J. Hilpisch: The Python Quants Jose Luu: Head of Scientific Computing, Natixis

10 CONFERENCE SPONSORS GOLD SPONSOR: Global Valuation Ltd. (GVL) is a software firm based in London. GVL s two products are Esther, a software-hardware solution for the simulation of large OTC portfolios and megamodels for CVA-FVA-DVA, and Athena, a data service for calibrated models in collaboration with ICAP. GVL also partners with TriOptima in the delivery of tricalculate, a hosted risk analytics service for OTC portfolios. GOLD SPONSOR: The Python Quants Group ( focuses on the use of Python and Open Source software for Quantitative Finance and Data Science. The group provides browser-based, scalable solutions for financial analytics ( and data science ( It also develops and maintains the Python-based Open Source library DX Analytics ( In addition, the group offers consulting, development and training services. Dr. Yves J. Hilpisch ( the group s founder, is author of Python for Finance (O Reilly) and Derivatives Analytics with Python (Wiley Finance). He organizes Meetup groups and conferences in Frankfurt, Berlin, London and New York. SILVER SPONSOR: Automated Trader is the first global magazine dedicated to automated and algorithmic trading, and offers in-depth business and technical coverage through comprehensive news, features, in-depth articles on best practice/techniques and detailed user case studies. In addition to thousands of CTAs, hedge funds, proprietary trading operations and conventional asset managers globally, Automated Trader is also read by all major sellside participants in automated and algorithmic trading.

11 THE 2ND BIG DATA IN QUANTITATIVE FINANCE CONFERENCE THE MARYLEBONE HOTEL, LONDON 10TH / 11TH / 12TH JUNE 2015 CONFERENCE FEE STRUCTURE Early Bird Discount: 20% Before 17th April Early Bird Discount: 10% Before 15th May Regular Event Fee Conference + Workshop ( 100 Discount): UK VAT UK VAT UK VAT Conference Only: UK VAT UK VAT UK VAT Workshop Only (No Discount): UK VAT UK VAT UK VAT Special Discount Code: 70% Academic Discount / FULL-TIME Students Only DELEGATE DETAILS COMPANY: NAME: JOB TITLE/POSITION: NAME: JOB TITLE/POSITION: NAME: JOB TITLE/POSITION: DEPARTMENT: ADDRESS: TO REGISTER, PLEASE THE COMPLETED BOOKING FORM TO: sales@wbstraining.com OR VIA FAX TO: +44 (0) FLIGHT DETAILS: All delegates flying into London on the morning of the event are reminded that they should arrive 30 minutes before the workshop starts for registration. The hotels West End location is approximately 1 hour from all 3 main London airports, Heathrow, Gatwick and City. Returning flights should equally allow for the events finishing time. SPONSORSHIP: World Business Strategies Ltd, offer sponsorship opportunities for all events, headers and the web site. Contact sponsorship via telephone on: +44 (0) DISCLAIMER: World Business Strategies command the rights to cancel or alter any part of this programme. CANCELLATION: COUNTRY: TELEPHONE: DATE: SIGNATURE: By completing of this form the client hereby enters into a agreement stating that if a cancellation is made by fax or writing within two weeks of the event date no refund shall be given. However in certain circumstances a credit note maybe issued for future events. Prior to the two week deadline, cancellations are subject to a fee of 25% of the overall course cost. DISCOUNT STRUCTURE: The discount is available on any day permutation, and can be combined across delegates within the same company (only at the time of booking and not retrospectively). REGISTRATION: Tel: +44 (0) / Fax: +44 (0) CONTACT: / sales@wbstraining.com