Risk Management Basics Andras Bohak| bohak@finance.bme.hu

Agenda Risk Basics How Institutional Investors Use Risk Tools Risk and Return on a Single Equity Manager How an Asset Owner Views the Equity Manager

Risk Basics

Factor Models in One Slide

One Measure of Risk: Standard Deviation Standard normal curve Distribution of possible outcomes, with a mean of zero and standard deviation of one

Standard Deviation of Returns

Risk Relative to a Benchmark Active risk The goal of all active managers is to outperform the benchmark Beating the benchmark requires taking bets by overweighting or underweighting securities Deviating from the benchmark may not result in outperformance Generally the larger the bets, the higher the active risk Bets can be intended or unintended Risk analysis helps ensure that the manager’s intended ideas are implemented without unintended bets negating alpha

Risk Relative to a Benchmark

How Institutional Investors Use Risk Tools

The Investment Process

Why Asset Owners Implement Risk Management Monitor Total Assets Measure the contribution to risk from asset classes, sub asset classes, and managers Analyze Strategic and Tactical Asset Allocations Evaluate plan risk coming from allocation and selection decisions Evaluate Manager Risk and Performance Measure performance against benchmarks, monitor for style drift, and select managers Measure Tail Risk Historical and predictive stress testing, Value at Risk, and Shortfall analysis Perform Risk Budgeting Optimally spend risk, based on traditional asset classes or risk-based buckets

Components Needed to Manage Risk Risk Model Structural Forward Looking Long Horizon Holdings-based Data Holdings Market Data Benchmarks Returns (user-provided) Asset Classes Public Derivatives Private / Illiquid ETFs Mutual Funds Methods Market Values Common Factors Simulations Stress Testing Optimizations Reporting Risk Factors Absolute/Active Space We provide components that can be used to support solutions across the complexity precision spectrum. From holdings-based to index; from market values to VaR simulations. From equities to alternative asset classes. Holdings-based improves modeling precisions. Returns-based model is available for HFs, where no transparency exists. Software Platform

A Typical Asset Management Setup Front Office Middle Office / Aggregators Back Office Typical Roles Portfolio Managers Quant Analysts Risk Managers Asset Allocation Teams Performance Attribution Teams Pension Plan Managers Compliance Performance Reporting Models Types “Analytical” Models Holdings Custom, home-built Valuation Factor (equity) “Risk” Models Hodge-podge Returns Nothing (manager-provided) Factors (growing) Holdings (growing) Portfolio Accounting Trade Order Management Performance Measurement Needs Flexibility and customization Aggregation Structure Automation Predicatibility

Measuring Investment Risk Using Holdings Based Models Sample Factors Interest Rates Credit Spreads Prepayments Leverage Value/Growth Industries Currencies Investment risk is a function of: Risk Position Size Exposure to Factors Factor Volatilities Correlations Between Factors

Measuring Investment Risk Using Returns Based Models Sample Returns Asset A Asset B Manager A Manager B Investment risk is a function of: Risk Historical Return Correlations Between Returns

Using Market and Common Factors to Model Risk Risk analytics are function of pricing models and market or common factors Instruments are mapped to a set of factors Standard instrument pricing models compute exposures to factors Sensitivities & Exposures Stress Testing Simulations (Historical & Monte Carlo) Performance Attribution Factor Risk Market Factors Common Factors * This slide could probably use some arrows, but the point is to show that we have instrument-specific pricing models that are then used to compute exposures to market and/or common factors. Technically in B1, exposures are computed to both market (i.e. durations, stress tests) and common factors (BIM) – but I wouldn’t parse it so fine when discussing this slide with a client. * Make clear when presenting that “sensitivities and exposures” also refers to counterparty risk! Instrument Pricing Models Equities Fixed Income Derivatives Commodities Alternatives

Common Factor Models Identify Sources of Risk Based on the idea that an instrument’s volatility can be explained more precisely by its characteristics than by looking at historical returns Returns do not capture how an asset’s fundamentals have changed over time Current characteristics provide more insight into drivers of risk Risk is broken down into fundamental market factors to understand sources of risk Explain risk using a smaller set of factors that can be easily explained and used to manage the portfolio Intuitive style, industry, interest rate, and spread factors match the investment process To measure instrument risk, measure its exposure to these factors based on market and fundamental data Some amount of risk is “specific”, or idiosyncratic, to that individual security, and not correlated with common factor movements

Equity Manager

Our Equity Manager ~$20M allocation Fundamental manager Twenty names in automotive industry Equally weighted on 1.1.2008 No rebalance rules, no subsequent buys/sells Benchmarked to MSCI World

Our Equity Manager’s Performance Information ratio: -0.11 Beta: 1.60 Portfolio return: -15.3% Benchmark return: -2.5% Active return: -12.8%

Portfolio’s Active Return

Portfolio’s Active Return

Industry Exposures as of August 2012

Our Portfolio: Risk Exposure to Two Industries

MSCI World Benchmark: Broad Industry Exposure

Single Name Risk Concentration in Our Portfolio

US Risk Concentration Across Industries

Large Exposure to Style in Automobiles & Components

Top Ten Names Drive 90% of Risk