Investment Banking Technology

1. University of BirminghamSchool of Computer ScienceCommercial Programming PUBLIC Investment Banking Technology Chris Brook Technical Lead, Credit IT - UBS Investment Bank October 13, 2011

2. Table of Contents SECTION 1 Finance 101 - Key Concepts in Credit Trading SECTION 2 Grid Computing SECTION 3 Real-time Business Intelligence SECTION 4 Managing Development SECTION 5 Joining UBS

3. About Me Chris Brook Technical Lead, Structured Credit IT - UBS Investment Bank • Joined UBS June 2011 • Masters graduate in Aerospace Engineering • 6 years experience, specialising in distributed systems and database engineering

4. UBS — Our Services Wealth Management & Swiss Bank Wealth Management Americas Global Asset Management Investment Bank The Investment Bank provides securities and other financial products and research in equities, fixed income, rates, foreign exchange and precious metals. It also provides advisory services and access to the world's capital markets for corporate and institutional clients, governments, financial intermediaries and alternative asset managers and private investors. Wealth Management & Swiss Bank focuses on delivering comprehensive financial services to high net worth and ultra high net worth individuals around the world – except those served by Wealth Management Americas – as well as private and corporate clients in Switzerland. Our Wealth Management business unit provides clients in over 40 countries, including Switzerland, with financial advice, products and tools to fit their individual needs. Our retail & Corporate business unit has a leading position cross its client segments in Switzerland. • Wealth Management Americas provides advice-based relationships through financial advisors who deliver a fully integrated set of products and services specifically designed to address the needs of ultra high net worth, net worth and core affluent individuals and families. • It includes the Wealth Management US Business, as well as the domestic Canadian business and the international business booked in the United State • Global Asset Management is a large-scale asset manager with businesses diversified across regions, capabilities and distribution channels. • It offers investment capabilities and investment styles across all major traditional and alternative asset classes. These include equities, fixed income, currency, hedge fund, real estate and infrastructure investment capabilities that can also be combined in multi-asset strategies. The fund services unit provides legal fund set-up and accounting and reporting for all retail and institutional funds.

5. UBS Investment Bank Three main functions Investment Banking Department – advising companies on their structure, funding, flotation, mergers & acquisitions Equities – distributing, trading, financing and clearing shares and share-linked products Fixed Income, Currencies & Commodities trading in Foreign Exchange, Interest Rates, Emerging Markets and Credit

6. SECTION 1 Finance 101 - Key Concepts in Credit Trading

7. 101: How do Businesses Finance Themselves? Issuing Equity (Shares) A share of the ownership of the company. Price of each share = (Future Earnings + Assets - Liabilities) / Number of Shares Issuing Debt (Bonds) A bond is a debt security that entitles the holder to repayment of the principal sum plus interest. Bonds have a face value (on which the issuer pays interest) a coupon (interest rate paid by issuer) and maturity (date that the principal is due to be re-paid) Bonds pay interest – they have a cash flow Loans pay interest – they have a cash flow Taking a Loan

8. 101: What is the Value of Money? The Time Value of Money Today, the value of £100 is £100 - But in one year it may be more or less. It could go up (earn interest). It could go down (be affected by inflation). I could loan it to someone for one year, at 5% interest… (£105 to repay) • But: • I’d really like the £100 back now… • And, I may not be paid back! - there is a risk attached to this loan Discounted Cash Flow ‘Future value’ =How much my £100 could be worth in one year (e.g. £105) ‘Present value’ = Value today of a £105 debt, re-paid next year (e.g. £100) DCF techniques are used to adjust for the ‘time value’ of money

9. 101: Derivatives, Desks and Books A derivative is fundamentally a contract between two or more parties – a trade. Derivatives Its value is derived from the value and characteristics of another security - the underlying ‘asset’. E.g. an Option - a contract giving the holder the right to buy or sell a quantity of something (the ‘asset’) at a set price, within a certain time period. The buyer pays a fee. Occupied by licensed traders, usually specialising in trading one particular type of investment product / instrument. (e.g. foreign exchange traders, commodities traders, equities traders) Trading Desks A portfolio of financial instruments held by a brokerage or bank. Each book can contain 1000’s of trades. Trading Book

10. 101: The Risks of Trading Market Risk – the risk of loss due to fluctuations in the market The potential for the bank to experience losses due to fluctuations in prices of securities (e.g. the underlying assets). Every day your portfolio value will change depending on the market price of each trade within it. Credit Risk – the risk of loss due to non payment Credit Risk is the risk of loss arising from a client who does not make payments as promised. Such an event is called a default. Particularly in transactions lasting several years (e.g. a loan or mortgage) the lender may need tomake financial provisions against the risk of default. Understanding Credit Risk is an essential component of managing the bank’s balance sheet.

11. 101: Securitised Products: What is a CDO? Collateralised Debt Obligation Assets Losses Liabilities AAA-rated Bonds Last Loss 5th Loss 4th Loss 3rd Loss 2nd Loss 1st Loss Diversified Portfolio of CreditsgenerateCash flows AA-rated Bonds A-rated Bonds Credit exposure BBB-rated Bonds BB-rated Bonds ‘Equity’ Bonds

12. From Sub Prime to Credit Crunch • Mortgages and loans produce a cash flow • Subprime: making loans to people who may have difficulty repaying • The Subprime mortgage crisis arose from 'bundling' American subprime and American regular mortgages into Asset-backed securities (ABS/MBS) and selling these bundles onward • Real Estate prices peaked in the US in 2006, and then started to fall • Leading to a rise in subprime mortgage defaults during 2007 • Leading to an increase in losses reported within ABS/MBS • During 2008 finance institutions wrote off $750 billion in associated losses • ….which led to Banks experiencing reduced access to funds (and no money to lend)

13. CDX Credit Default Swap Index 2007 to Feb 2011 HBOSRBS Lehmans Merrill Icelandin trouble AIGWAMU Citigroup AIG loss Greece in Trouble Bear StearnsNorthern Rock Spain onwatch US Stimulus Package SubprimeCrisis GM&Chrysler bankrupt Ireland in trouble US eases money

14. 101: Managing Risk Risk Management • Market Risk (VaR, Stress) – probable loss on portfolio given changes in the market • Credit Risk (PFE, CVA) – probable loss on portfolio given default of counterparty • Profit and Loss explain (P&L) – daily change to the value of our trading positions • Sensitivities – of prices due to potential changes in underlying parameters on which their value is dependent • Collateral – how can we ‘net’ this / optimise our use of collateral? Front Office (The Traders) • Position keeping, sensitivities • FX book management • Real time P&L – present value of our trading positions • Continuous hedging – protect trading positions against potential shifts in the market

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16. 101: Monte Carlo Simulations Monte Carlo Simulation Monte Carlo Simulation Value Distributionof final values Time For illustrative purposes only. • Monte Carlo is a powerful simulation method for estimating the future performance of a portfolio. • Relies on repeated random sampling to compute results. • Simulate sources of uncertainty affecting value, and then determine average value over the range of resultant outcomes. Monte Carlo simulation allows us to evaluate a wide range of market conditions and investment scenarios.

17. 101: Monte Carlo Simulations – Computing challenges Monte Carlo simulations are useful because… • They are generic – you can model any cash flow • They provide a Probability Distribution However, they are computationally expensive… • You can try and optimise your model • You can pre-generate random numbers as input • You can optimise your software to enable it to run faster • And, you can run them on the Grid

18. 101: Calculating the price and risk of every trade in a portfolio AAA-rated Notes AAA-rated Notes AAA-rated Notes AAA-rated Notes AAA-rated Notes AAA-rated Notes AAA-rated Notes AAA-rated Notes AAA-rated Notes AAA-rated Notes AA-rated Notes AA-rated Notes AA-rated Notes AA-rated Notes AA-rated Notes AA-rated Notes AA-rated Notes AA-rated Notes AA-rated Notes AA-rated Notes A-rated Notes A-rated Notes A-rated Notes A-rated Notes A-rated Notes A-rated Notes A-rated Notes A-rated Notes A-rated Notes A-rated Notes BBB-rated Notes BBB-rated Notes BBB-rated Notes BBB-rated Notes BBB-rated Notes BBB-rated Notes BBB-rated Notes BBB-rated Notes BBB-rated Notes BBB-rated Notes BB-rated Notes BB-rated Notes BB-rated Notes BB-rated Notes BB-rated Notes BB-rated Notes BB-rated Notes BB-rated Notes BB-rated Notes BB-rated Notes CDO equity CDO equity CDO equity CDO equity CDO equity CDO equity CDO equity CDO equity CDO equity CDO equity Thousands of trades If then goto Lorem ipsum, lorem ipsum 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19. SECTION 2 Grid Computing

20. Sequential Computing • Excel typically calculates cells sequentially, based on dependencies. • Multi-threaded Excel can calculate in parallel, but is limited by CPU cores. • The 50 cells in this example take 10 seconds each to calculate. • 50 x 10 = 500 sec CPU time • A dual-core machine would take over 4 minutes to calculate this simple example …Can we continue buying faster workstations?

21. Parallel Computing on the Grid Distributed, parallel computation – break long running calculations into many pieces and run in parallel across many computers • Excel Add-in communicates with the Grid. • Grid Software divides calculation into 50 separate units of work. 5 second overhead in setting this up. • The work units are allocated to engines and computed simultaneously. • As engines complete, they notify the Grid Controller of the result. • Controller aggregates results and returns to Excel. Further 5 second overhead. • 4 min calculation reduced to ~20 sec.

22. UBS Investment Bank IT: Key Facts & Figures > 24,000 Grid Engines (dedicated cores) > 6,000 servers – grows 5% per year > 2.4 Petabytes of storage – grows 12% per year > 31,000 system changes in 2009 - grows 10% per year >1.7 MW power consumption = 1700 Kettles! October 2010

23. Current & future challenges for the Grid – feeding it! Networks are not increasing in performance at the same rate as CPUs Huge volumes of input and output data Ensuring coherent data Sequential or parallel calculations? Sudden need for extra capacity – e.g. the ‘Flash Crash’ of May 2010? CPU Scavenging? (use spare desktop capacity)

24. Essay Question Optimising workload to run on a grid is non-trivial… Example: Daily Trade Valuation • 108,000 trades need to be valued in London each day • There are 20 different trade types: some are fast to price, some are slow • 99% of trades fall into just 3 types (the simple or ‘vanilla’ trades) • However, the remaining 1% of trades account for 30% of the net calculation time! • Calculation time for a single trade is due to two things: • The amount of network I/O required to move the input data to the calc node • The amount of CPU time taken to calculate the result • We can bundle trades together, where they share common input data • This reduces network I/O time and contention, but will increase CPU time / decrease parallelism • The trade population changes daily, and new trade types can be created. Question • Present some techniques which could be used to optimise the grouping of trades into work units, to reduce the overall end-to-end processing time. • Options could include using a feedback loop, based on instrumentation of the previous run. • What about machine learning?

25. SECTION 3 Real-time Business Intelligence

26. The challenge of Timeliness AND Complexity • Decision making happens under pressure • Data ischanging dynamically • Large amounts of data have to be analysed / correlated • You need to visualise data in a way that supports decision making • This all needs to happen quickly

27. Introducing OLAP (online analytical processing) • OLAP gives the capability to query and analyse data using dimensions. • OLAP Cubes extend the two-dimensional array of a spreadsheet into n-dimensions. • A cube’s metadata structure is created from a star schema or snowflake schema, by joining several tables in a relational database. • OLAP tools are sold by database and analytic software vendors, and are widely used in business to analyse historical data, e.g. for root cause analysis. • Data is imported into the cube, and processed into complex proprietary data structures, optimised for querying of results. Data compression, bitmap indexes, and pre-aggregation are used to achieve fast query performance. OLAP performance depends on pre-processing of the data. It can be too slow to collect and analyse the input data to enable the business to make decisions on ‘live’ information (e.g. market prices)

28. Complex Event Processing (CEP) Decision-making based on analysing streams of information in real-time. • Uses a ‘SQL-like’ language to query an Event Stream. • An Event Stream could be live market prices / exchange trades. • Detect patterns among multiple streams of event data. • Execute calculations on multiple streams of event data – e.g. calculate averages. • Information complexity is low but decision timeliness is fast. The combination of CEP and OLAP provides a Real-Time Business Intelligence platform that enables us to analyse the latest information and react immediately.

29. Performance Metrics Our Cube has • 1 trillion data points • 20 dimensions, 39 levels • 5-dayshistory held in memory • 5-days – 250 GB loaded into cube (50 GB x 5 days) • 1-yearhistory available on disk • 1 year – 13 TB data is compressed into 1.5 TBand loaded into cubes • A new day’s data must be accessible within 10 minutes This translates into • Processing concurrent Updates: 200,000 updates/sec – one every 5ms • Processing concurrent Queries: 266 queries/sec

30. SECTION 4 Managing Development

31. UBS IT: Our Geographic Footprint EMEA801 Switzerland5601 UBS has 65,000 staff: 17,000 in IT (and 5,500 in the Investment Bank) UK2829 Americas3660 Russia .APAC4341 Japan Hong Kong Brazil Australia

32. How to Manage an Enterprise Development Team?

33. Iterative / Lean Development Iterative cycle (e.g. Scrum) • Split work into small, tangible deliverables • Split time into short fixed-length cycles • Limit work per iteration • Communicate: daily stand-ups (10 mins) • Continually improve: reviews after each iteration • Tailor methodology to the team ‘Lean’ principles (e.g. KanBan) • Define workflow stages: To-Do, In-Progress, Complete • Limit tasks per workflow stage • Constrain ‘Technical Debt’

34. Task Board @ UBS

35. Essential Practices for Sustainable Development Modular Design Compose the system from modular services.Strive to make the software maintainable, above all else. Source Control Single sharedcode repository (global). Automated Builds Re-build after every check-in… never break the build!Repeatable process. Auditable. Unit Tests (TDD) Write tests first (delivers better designs). Learn IoC and a Mocking framework.Run the tests on the build. Aim for high test coverage (>70%). Create scripts to install your most recent build, to any environment. ‘One-Click’ Deploy Deploy your code automatically, and then run end-to-end tests. Continuous Integration Design Patterns Learn the useful OO design patterns, and use them.

36. Essential Practices for Sustainable Development

37. UBS Investment Bank IT: Award-winning Technology Best FX Post-Trade ServiceProfit & Loss 2010 Best All Round Solutions for Prime Broking Asiamoney 2006-2009 Best All Round Solutions for Prime Broking Thomson Reuters Extel 2001-2010Best Firm for Portfolio Trading Execution Thomson Reuters Extel 2008-2010 Best product innovation for Prime Broking Asiamoney 2009 Best Post Trade Services Global FX Week 2009 No.1 Internal Crossing The Trade 2010 Best Fixed Income Research and StrategyTechnical Analyst Magazine 2009 No.1 for Currency Forwards, Swaps and Vanilla Options Risk 2009 UBS Delta: Most Innovative Actuarial Software Life & Pension Risk 2010 UBS Delta: Best Technology Vendor for Risk ManagementCredit Awards 2009Technology Innovation AwardCredit Magazine 2009, 2010Best Proprietary TechnologyBuy-Side Technology 2007 No.1 for Algorithmic TradingThomson Reuters Extel 2010 No.1 First for Overall Post-Trade ServicesZ/Yen McLagan 2009 No.1 for Post Trade Performance in FX McLagan/Z-Yen 2010 No.1 for Post Trade Services – North AmericaZ/Yen McLagan 2009Best in AlgorithmsAsianInvestor 2010

38. SECTION 5 Joining UBS

39. Graduate Training Program (GTP) – Your future at UBS GTP Discovery Role-based Training GTP Fundamentals GTP intro to UBS & Financial Services Technical training based on individual learning needs GT Strategy, Business Model & Operating Principles Building the network 24 months Getting on board Joining the team Into the future Permanent Placement Rotation • The UBS GTP program will equip you with the skills, knowledge and experience to achieve long-term personal and professional goals and challenge you to achieve your potential. • You'll learn the business while developing your technical skills to deliver real world solutions. • By the end of the two year program you’ll be an integral part of the UBS Group Technology team.

40. Ready for take off? Without our systems and infrastructure, we wouldn’t be in business … Apply today at www.ubs.com / graduates