1

My Life in a Hedge Fund

Marc Potters

Capital Fund Management

2

What is a Hedge Fund?

• Traditional Asset ManagementLong Only – Equity (Stocks)– Bonds

• Alternative Investments– Real Estate– Private Equity– Hedge Funds

• Hedge FundsAt least one of the

following:– Leverage– Short Positions– Derivatives– Profit from Trading

3

Hedge Fund Industry

• Number of Hedge Funds– Total : thousands– Assets > 1 billion$: ~100– Assets > 10 billion$: ~20

• Total Amount in Hedge Funds– 1 – 1.5 trillion$ (1012)

• Worldwide Stock Market Capitalization– ~40 trillion$

• Short Lifetime– Typical lifetime ~ 3y– Survival bias

• Known Quantitative Funds– Simmons’ Medallion– Prediction Company

• Farmer and Packard

– D.E. Shaw– Citadel

4

Types of Hedge Funds

• Long/Short Equity– Stock Picking + Short

• Event Driven– Merger– Distress– Shareholder Activism

• Convertible Bonds• Bond/Yield Arbitrage

e.g. LTCM

• Global Macro

• Others– Complex Derivatives

• Systematic Quantitative– Futures Trading (CTA)– Equity Statistical

Arbitrage– Volatility Arbitragee.g. CFM

5

Short Selling

• Buy Shares: Long Position– Make money if price goes up

• Short Selling: Short Position– Borrow shares from someone else– Sell them on market– Need to buy them back at some future time– Make money if price goes down

6

Futures Market

• Market for Finance Professionals– Contract size = 50-100k $

• Many Asset Classes– Stock Indices– Government Bonds– Short Term Interest Rates– Currencies– Commodities

• Oil Products• Grains + Livestock• Metals

• Symmetric Long/Short• Small Deposit

– 3-5 % of value

• Marked-to-Market Everyday

• Anonymous• No Counterparty Risk

– Exchange between every transaction

• Electronic Almost Everywhere

7

Call Option

• Right to buy an asset at a fixed price X (Strike) at a later time T (Maturity) for a payment upfront C (Premium).

• Premium depends on fluctuations (Volatility)• Similar to insurance policy• Black-Scholes Theory

–Option premium and hedge under continuous-time multiplicative Browninan motion–Unrealistic assumptions–Used as an effective theory to translate market prices in volatility

8

Statistical Trading

• Casino “House”– Odd/Even 19/37=51.3%– Many tables, many

players, many days

• Hedge Fund– Diversify in strategies– Diversify in “space”

• Trade many uncorrelated assets (residuals)

• Avoid global factors– Market mode– Global volatility

– Diversify in time• Short term trading

• Law of Large Numbers– Average ~ N– Fluctuations ~ √N

9

We’ve got computers…

• Short Term Trading Opportunities– ~100 ms

• Monitor Large Number of Assets Simultaneously– 2000 Stocks– 30000 Options

• Implement Sophisticated Pricing Models

• Patient– Can wait hours to save

a few dollars

• Record Everything They Do– Audit– Impact Analysis

• Anonymous• No Emotion• No Stress

10

Ingredients for a Successful Hedge Fund

• Investment Strategy– Profit generating

strategies• Predict future prices

better than chance

– Trade selection• Risk control• Transaction cost

analysis

– Trade ExecutionConstant Innovation

• Other Departments– IT infrastructure– Marketing– Back-Office– Compliance

11

Predictable Random Walk

• How can a random walk be predictable?• Bias (not equal to risk free rate)

– Carry trade: buy currency that pays large interest rate

• Positive Auto-correlation– Trend following

• Negative Auto-correlation– Mean reverting

12

Trend Following

• Strategy– Always Long or Short– Go long if R(t)>R0, go

short if R(t)<-R0, otherwise stay

• Make money on average if random walk is persistent

• Trade statistics is skewed– Winning trades are longer

than loosing trades– Loosing trades are more

frequent• Daily return statistics is

unskewed– gauge transformation

13

Risk Control

• Fat tails– Non-Gaussian statistics

• Leverage Effect– Price drops induce

volatility

• Volatility fluctuations– Long range

autocorrelations– Non-trivial kurtosis– Dynamical leverage

14

Distribution of Stock Returns

15

Risk Control

• Empirical Correlation Matrices– N assets, T time intervals– Q=N/T ~ O(1)– Marcenko-Pastur distribution of eigenvalues– Small eigenvalues are dangerous for Markowitz

• w ~ C-1 r

– Large eigenvalues may be signal• Cut-Off cleaning• M-P dressing of ansatz distribution

16

Empirical Eigenvalue Distribution

17

Applications of Correlation Matrices

• Generalized Pair Trading– Pair trading: compare a stock with a peer– Create a “super-peer” using all correlated stocks

• Uncorrelated Residuals– To get √N diversification need uncorrelated bets

– Invest uncorrelated portfolios with wa=1

• Measure Your Risk– Need reliable matrix “out-of-sample” if you

optimize

18

Transaction Costs

• Broker – Clearer – Exchange fees– Order of 0.1 to 1 bp (10-5 - 10-4)

• Bid-Ask Spread– Order of 1 to 10 bp (10-4 - 10-3)– Can do better with smart execution

• Price Impact– Strongly depends on size– Dominant cost for large funds

• Financing cost– 0.5 to 1% per year per unit of Leverage

19

Trade Execution

• Order Book Dynamics• Short Term Predictive

Models• Price Impact• Market Reaction• Experimental Physics

vs Cosmology

20

Quant Crunch 1998 and 2007

• Aug. 1998• LTCM Strategies

– Emerging Market Yield– European Convergence– Long Term Index Vol– On-the-run Off-the-run

• Trigger: Russian Dept Crisis

• Aug. 2007• Quant Strategies

– High Yield Bonds (credit risk)

– Equity Quantitative– Equity Stat Arb

• Trigger: Sub-Prime Loan Crisis

21

Investment Advices

• Beware of fees!• Don’t buy complicated

products• Diversify

– Large portfolio or indices NOT a few stocks

• Include dividends in your performance analysis

• Investment managers don’t beat the index

• Buy Index Funds or ETFs

• Reasonable long term targets– RFR + 3-5% is very good

• Consider impact of taxes– Retirement accounts,

life insurance etc.

• Don’t invest in Hedge Funds– Unless you know that

• They are smart• They are not crooks

• Beware of fees!