Opportunities in Finance

Transcription

1 Opportunities in Finance from Goldmans to Bitcoin Prof. Philip Treleaven Director, UK Centre for Financial Computing & Analytics University College London Gower Street London WC1E 6BT T:

2 Big Data, Big Opportunities:

3 Our Background Fraud Detection Retail mhealth Analytics Algorithmic Trading Systemic Risk Customer Analytics 3

4 Fraud Detection 4 Computer Science PhD students What we did Built the first Insider Dealing Detection system for Front page of the Financial Times What we did next Credit card fraud detection Insurance Fraud detection Telecomms Fraud detection What they did next Started a company called SearchSpace One time had 60% of market Sold the company for $150m 4

5 Konrad Feldman, CEO & co-founder $½ billion 5

6 Collaboration through Student Projects We place students in institutions to build analytics and software PhD Students - Centre for Doctoral Training (CDT) UCL, Imperial, LSE Over 70 PhD students working with institutions on analytics and software. CDT PhD can spend 3 years with their Industry partner. Professional (part-time) PhDs for people working in industry. Masters students UCL CS has 300 Masters students. Most do their Dissertations with companies. Undergraduates UCL CS has 250 undergrads. Encouraged to do projects with outside institutions. Undergrads do internships with banks, consultancies and major tech companies. 6

7 Computational Finance, Business Analytics, Data Science

8 Computational Science: finance, economics, business Computational Science - concerned with constructing mathematical models and quantitative analysis techniques and using computers to analyze and solve scientific problems. Data mining Simulation Modelling Big Data Analytics is the term for a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. Computational Finance is a cross-disciplinary field that applies numerical methods, computational statistics, artificial intelligence techniques and computer simulations to making trading, investment and hedging decisions. Behavioral Finance is the field of finance that proposes psychology-based theories to explain stock market anomalies. Within behavioural finance, it is assumed that the information structure and the characteristics of market participants systematically influence individuals' investment decisions as well as market outcomes. 8

9 Computational Science has two distinct branches: Data Mining knowledge discovery that extracts hidden patterns from huge quantities of data, enabling the forming of hypothesis as a result. Computer Modeling simulation-based analysis that test hypotheses. Simulation is used to attempt to predict the dynamics of systems so that the validity of the underlying assumption can be tested. 9

10 Computational Statistics, Machine Learning, Complexity Computational Statistics Probability Density Estimation covers the methods of constructing an estimate of an unobservable underlying probability density function from observed data Statistical Inference makes inferences concerning some unknown aspect of a population from a random sample. Regression models and analyses a relation between a dependent variable and one or more independent variables. Artificial Intelligence Symbolic (or knowledge-base) AI - is concerned with attempting to explicitly represent human knowledge in a declarative form employing facts and rules. Rule-based systems Fuzzy logic Sub-symbolic (or machine learning) AI - refers to a system capable of the autonomous acquisition and integration of knowledge. Supervised Learning - covers techniques used to learn the relationship between independent attributes and a designated dependent attribute (the label). Unsupervised Learning - covers learning techniques that group instances without a pre- specified dependent attribute. Clustering algorithms are usually unsupervised. Complex Systems complex systems are derive from statistical physics, information theory and non-linear dynamics, and represent organized but unpredictable behaviours of natural systems that are considered fundamentally complex. Agent-based Modelling 10

11 Algorithmic Trading and Flash Crashes

12 Trading volatility

13 Flash Crash May 6, SPX This image cannot currently be displayed :30 AM 9:49 AM 10:08 AM 10:28 AM 10:47 AM 11:07 AM 11:26 AM 11:45 AM 12:05 PM 12:24 PM 12:44 PM 1:03 PM 1:22 PM 1:42 PM 2:01 PM 2:20 PM 2:40 PM 2:59 PM 3:18 PM 3:38 PM 3:57 PM $600 billion in market value of US corporate stocks disappeared

14 Knightmare Knight Capital loose $440m In the mother of all computer glitches, market-making firm Knight Capital Group lost $440 million in 30 minutes One of Knight s trading algorithms reportedly started pushing erratic trades through on nearly 150 different stocks

15 Algorithmic Trading Equities example system

16 Algorithmic/Systematic trading Research Data (Real-time/Historical; market/non-market) Pre-trade Analysis Alpha Model Risk Model Transaction Cost Model Trading Signal Portfolio Construction Model Trade Execution Execution Model Post-trade analysis

17 Algorithmic/Systematic trading Research Data (Real-time/Historical; market/non-market) Implementation Issues Forecast target Pre-trade Analysis Alpha Model Risk Model Transaction Cost Model Time Horizon Bet Structure Investment Universe Trading Signal Trade Execution Post-trade analysis Portfolio Construction Model Execution Model Model Specification Run Frequency Data Availability Regulation Compliance

18 FinTech New (disruptive technology) Finance Financial (FinTech) Innovation is currently transforming our traditional finance industry, with consumers and corporates demanding new innovative solutions for web and mobile platforms.

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20 Disruptive Technologies A disruptive technology is an innovation that helps create a new market and value network, and eventually goes on to disrupt an existing market and value network (over a few years or decades), displacing an earlier technology. Peer-2-Peer payments (PayPal) Online (payday) loans (Wonga) Reloadable prepaid card market (Netspend) Microfinance (Kiva) Crowdsourced funding (Kickstarter) Location based APPs Contactless & Mobile Payments (Square) Digital currencies (bitcoin) Social Investing (etoro)?

21 Sectors Traditional Alternative/Shadow Financial Taxonomy ServicesTraditional Services Payment Services Bartering Jam Jar Banking products Tech-driven Services Web-based payments Near Field Communication Example Companies Paypal Google Wallet Square M PESA Dwolla Card Case GlobalWebPay, Remit2India Lending Investing Foreign Currency Exchanges Personal Loans Signature loan Student Loans Trade Finance SME Finance Bank loan Seed Capital Payday Loans Microfinance Social Impact Bonds Microfinance Angel Investment Renewable Debentures High yield Revenue participation Peer-to-peer Trade finance Peer-to-peer lending Crowdfunding Social Bonds P2P Microfinance Green bonds Bureau de Changes Parallel Currencies Markets Cloud Solutions Online Platforms P2P FX Hedging Zopa Green note Market Invoice Funding Circle Seeders SecondMarket Funding Circle Abundance Numbers4Good Currency Cloud Currencies National currencies Digital Currencies Community Currency LETS Bitcoin,Line coins Bristol Pound Insurance P2P Insurance Friendsurance Pensions Reinsurance Stock Exchanges OTC, ECNs Alterative SME Stock Markets Social Exchanges Carbon Credit Exchanges GXG Markets Social Stock Exchange? Betting Betting Shops Numbers Racket Gambling APPs Goalsetting Gamification SmartyPig

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23 Crowdsourced Funding Crowdsourced is the process of getting work or funding, usually online, from a crowd of people. Crowdfunding (alternately crowd financing, equity crowdfunding, crowd equity, crowd-sourced fundraising) is the collective effort of individuals who network and pool their money, usually via the Internet, to support efforts initiated by other people or organizations. Crowdfunding is the application of this concept to the collection of funds through small contributions from many parties in order to finance a particular project or venture.

24 Bitcoin compared to Dollar Bitcoin serial number like a unique prime number. You buy from issuers using dollars. Bitcoin wallet wallet has an address (cf. IP address) and each bitcoin has an identifier (cf. dollar serial number). However, every wallets (cf. Central bank) records every bitcoin in circulation and every transactions. Bitcoin wallet address - 1JArS6jzE3AJ9sZ3aFij1BmTcpFGgN86hA Bitcoin payment bitcoins ed to unique wallet address. However all other wallets record the transaction. Bitcoin printing/mining like finding a block of new prime numbers using advanced computation.

25 ehealthcare - esport: Software, Devices and Analytics

26 Healthcare Expertise 3D body scanning for anthropometrics ehealthcare devices Medical devices (body temperature, blood pressure, blood oximetry, blood glucose, spirometry (lung function), electrocardiogram - ECG (heart function)) + mobile devices Data fusion infrastructure web database, interfaces, etc. Analytics computational statistics & machine learning iphone Apps etc.

27 Consumer/Patient-centric ehealthcare

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29 Sports Analytics Professional Football Nutrition Coaching Observations Gym Equipment Physiology Sports Analytics Data Analytics: Injury Performance Talent GPS Data Video Recording 29

30 Social Media Analytics

31 UCL Social Media Platform (SocialSTORM) 31 31

32 Financial Computing & Business Analytics 70 PhD Students who we place in companies Computational Finance Work with DB, BAML, BNP Paribas, Barclays, Citi, HSBC, BOE Algorithmic Trading Risk Management etc. Computational Retail Customer Analytics Loyalty cards Fashion/Clothing Computational Healthcare ehealthcare Boots, BUPA 3D Healthcare Computational Sport Injury Performance Talent Identification Big Data Data Mining Simulation Modelling Computational Statistics Machine Learning Complexity Finance Retail ehealth Sport $½b 32