Analyszing Hedge Fund Risk

ΛNΛLIZING HΣDGΣ FUND RISKUSING

TRΛNSPΛRΣNCY ΛNΛLYTICS®

PLΛTFORM

40 WALL STREET, 28TH FLOOR NEW YORK, NY 10005‐1304

TEL: (212) 400‐7176FAX: (646) 512‐5819

EMAIL: CONTACT@RISK‐AI.COMWEBSITE: WWW.RISK‐AI.COM

RISK-AI, LLCRISK-AI, LLC

TEL: (212) 400‐7176FAX: (646) 512‐5819

1. Founded in 20082. Risk-AI offers risk management consulting and outsourcing services to Fund of Funds and Family Offices3. Recently released Transparency Analytics platform to our non-consulting clients.

OUR MANAGEMENT TEAMOUR MANAGEMENT TEAM

ALEKSEY MATIYCHENKO, CFA, FRM, CAIA - SENIOR PARTNER & CEO

ALEKSANDR MAZO, MCSE, CCA - PARTNER & COO

TRANSPARENCY ANALYTICS®TRANSPARENCY ANALYTICS®

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1. Risk Analysis and Research platform for investors managing multi fund/multi manager portfolios.2. Offered as Software as a Service (SaaS) platform.3. Includes subscription to major hedge fund database.

THIS WEBINARTHIS WEBINAR

1. This is not a live demo of Transparency Analytics platform.2. Focused on discussing concepts and methodologies.3. Includes screen shots from Transparency Analytics platform.

FOR LIVE DEMO/FREE TRIALFOR LIVE DEMO/FREE TRIAL

Contact Risk-AI at contact@risk-ai.com

THE PROBLEMTHE PROBLEM

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Analyzing hedge funds is akin to solving puzzles…

With missing pieces...

PIECES OF HEDGE FUND RISK ANALYSISPIECES OF HEDGE FUND RISK ANALYSIS

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Quantitative Analysis of Historical Track RecordQuantitative Analysis of Historical Track Record

Position/Exposure/Transparency AnalysisPosition/Exposure/Transparency Analysis

Due DiligenceDue Diligence

WHAT IS A HEDGE FUND?WHAT IS A HEDGE FUND?

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HEDGE FUND – OUR DEFINITIONHEDGE FUND – OUR DEFINITION

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Hedge Fund is an Investor that takes exposure to risk factors , applies leverage, uses skill and with some luck earns a profit.

EQUATION1

HEDGE FUND – OUR DEFINITIONHEDGE FUND – OUR DEFINITION

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Mathematically Hedge Fund is:

HF WiRiskFactorii1

Basic StatisticsTail Risk AnalysisRegime Analysis

Red Flags

Basic StatisticsTail Risk AnalysisRegime Analysis

Red Flags

Style AnalysisPeer AnalysisStyle AnalysisPeer Analysis

Style Analysis

LEVERAGE LUCKSKILL

BASIC STATISTICS

STEPS IN QUANTITATIVE ANALYSISSTEPS IN QUANTITATIVE ANALYSIS

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STLE ANALYSIS

REGIME ANALYSIS

TAIL RISK

RED FLAGS

Summary statistics of the fund’s performance

Analyze exposures to risk factors

Performance in different market regimes

Performance in extreme environments

Inconsistent behavior

PEER ANALYSIS Comparison of the Fund to the peers

Annualized Return

BASIC STATISTICSBASIC STATISTICS

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Standard Deviation

Annualized Std. Dev.

Semi Deviation

Downside Deviation

There are a lot of different statistics that can be calculated based on hedge fund returns. Some of these are shown below:

Sortino Ratio

Sharpe Ratio

Sterling Ratio

Kurtosis

Alpha/Beta

Maximum Drawdown

Up Capture

Active Premium

Down %

VaR Adjusted

Down Capture

Serial Correlation

Information Ratio Omega Jensen Alpha

Not all of these are relevant. Our reports focus only on statistics we find most useful

Calmar Ratio Treynor Ratio ETL

BASIC STATISTICS EXPLANATIONSBASIC STATISTICS EXPLANATIONS

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Statistic Explanation

Annualized Return Average annualized return produced by the fund.

Annualized Volatility Annualized volatility of fund.

SkewSkew is measure of asymmetry in of the fund’s return distribution. Positive skew implies that returns above the mean are more likely than returns below the mean and vice versa. Normal distribution has a skew of 0.

Kurtosis Measures peakedness or fat tails of return distribution. High value of kurtosis suggests that the volatility of returns is driven by extreme / tail events. Normal distribution has a kurtosis of 3.0.

Serial CorrelationMeasures correlation between returns in successive months of the fund. High value of serial correlation may be indicative of return smoothing of investment in illiquid securities. In addition, Fixed income strategies often have higher value of serial correlation due to repetitive nature of coupon income,

Max Drawdown Measures the highest loss suffered by the fund from peak to trough.

Value At RiskMeasures the minimum loss that is likely to be suffered by the fund 95% of the time due to normal market fluctuations. Does not measure tail risk. Calculated using assumption of normal return distribution.

Value At Risk Adjusted VaR adjusted to incorporate Skew and Kurtosis of the return distribution. The adjustment is done using Cornish-Fisher formula.

ETL Measures losses likely to be suffered by the fund when such losses exceed VaR.

Sharpe Ratio Skill ratio that measures fund’s excess return per unit of risk (volatility)

BASIC STATISTICS in Transparency AnalyticsBASIC STATISTICS in Transparency Analytics

1. Summary of Basic Statistics2. Return Distribution3. Historical returns4. Drawdown Analysis5. Rolling Volatility Analysis

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WHY LIMIT OURSELVES?WHY LIMIT OURSELVES?

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Basic statistics provide a quick view into the fund, but do not explain fund performance and can be misleading. For example:

Downside / Upside deviation / Sortino Ratio.

Hedge fund analysts often say things such as “this fund is volatile, but the volatility is all on the up side”. They quote statistics such as Downside / Upside deviation and Sortino Ratio.

Why is it wrong ?

A fund that has not encountered any losses will have an infinitely high Sortino Ratio and downside volatility of 0. If the same fund experiences a significant increase in rolling volatility, an investor should be concerned with increased potential for losses.

What goes up…

DOWNSIDE VOLATILITY EXAMPLEDOWNSIDE VOLATILITY EXAMPLE

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This Fund is fictitious, but this example is not far fetched…

-60.00%

-50.00%

-40.00%

-30.00%

-20.00%

-10.00%

10.00%

20.00%

Monthly Return

DOWNSIDE VOLATILITY IS BASICALLY 0.0%

EXAMPLEEXAMPLE

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This Fund is fictitious, but this example is not far fetched…

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

70.00%

80.00%

Rolling 12 Month Volatility and Down VolatilutyAnnualized Volatilty Annualized Downside Volatility

Increase in Symmetrical Volatility would have pointed out change in

Risk Profile long before the drawdown…

Increase in Symmetrical Volatility would have pointed out change in

Risk Profile long before the drawdown…

ROLLING CHARTS

ANALYZING ROLLING VOLATILITYANALYZING ROLLING VOLATILITY

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Rolling charts are helpful in examining changes in the fund’s risk profile but suffer from slow changes

ANALYZING ROLLING VOLATILITYANALYZING ROLLING VOLATILITY

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CUMULATIVE SQUARED RETURN

CHARTAllows us to capture such changes quickly

PEER ANALYSISPEER ANALYSIS

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Peer Analysis helps fund’s returns into the context of strategy or similar funds.

Peer groups can be selected by:

1. Correlation Analysis

2. Cluster Analysis

3. Qualitative Classification

In Transparency Analytics we have two ways to set up Peer Groups:

1. Using most correlated peers approach

2. Manual Qualitative Classification (through a concept of universe)

PEER ANALYSIS – Snapshot ComparisonPEER ANALYSIS – Snapshot Comparison

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Snapshot analysis allows us to quickly compare performance, correlation and risk statistics over different overlapping periods.

PEER ANALYSIS – Compare Entire Return Distribution of All FundsPEER ANALYSIS – Compare Entire Return Distribution of All Funds

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Box Plots allow us to compare full return distribution of all peer funds

PEER ANALYSIS – Correlation & Leverage AnalysisPEER ANALYSIS – Correlation & Leverage Analysis

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This chart allows to analyze correlation (size of the circle) to peers and relative leverage (color) of the fund.

Compare Annualized Return (Y-axis) Annualized Volatility (X-axis) and relative leverage (size of circle) of most correlated peers.

EQUATION 2

STYLE ANALYSISSTYLE ANALYSIS

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Style Analysis helps explain the risk factors that influence the fund’s performance.

Style Analysis can be either Uni-Variate (e.g. CAPM), or Multi-Variate (e.g. APT). We prefer the Multi-Variate style. Analysis can be performed on either raw returns or excess returns.

E(Rfund ) iXii1

STATIC & ROLLING ANALYSISSTATIC & ROLLING ANALYSIS

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It’s important to analyze overall exposure to risk factors as well as estimate changes in these exposures

PICKING RISK FACTORSPICKING RISK FACTORS

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Standard Risk Factors (Equity , Credit, Interest Rates, Volatility, Commodities, FX)

Economic Factors (Money supply, Merger Activity, etc.)

Hedge Fund Strategy Factors

Synthetic Factors (e.g. HML, SMB, PCA)

STEPWISE REGRESSIONSTEPWISE REGRESSION

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Stepwise Regression Analysis can be used to identify a subset of factors from a large pool of risk factors.

Analysts must be careful in setting the size of the pool. Choosing a pool that is too large is akin to throwing spaghetti at the wall. Something will always stick.

Statistical significance does not imply economic significance.

There is a positive correlation between performance of S&P 500 Index and snow falls in January (33%)

STEPWISE REGRESSION IN TRANSPARENCY ANALYTICSSTEPWISE REGRESSION IN TRANSPARENCY ANALYTICS

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EQUATION 3

FACTOR RISK ATTRIBUTIONFACTOR RISK ATTRIBUTION

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HF can be viewed as Portfolio of Risk Factors + Idiosyncratic Exposure. Therefore…

VolHF wt w

Where is a covariance of risk factors, w is fund’s exposure to risk factors (beta) and is idiosyncratic exposure

FACTOR RISK ATTRIBUTIONFACTOR RISK ATTRIBUTION

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We can, therefore, calculate each factor’s contribution to the fund’s return.

EQUATION 4-A – MULTIPLE FACTOS

NON-LINEAR SENSITIVITY ANALYSIS - CONVEXITYNON-LINEAR SENSITIVITY ANALYSIS - CONVEXITY

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Style Analysis relies on linear regression.

We can, however, incorporate non linear factors into the analysis. One expansion of the model is to add factors that correspond to squared returns of our standard linear risk factors.

E(Rfund ) iXii1

E(Rfund ) X X 2

EQUATION 4-B – SINGLE FACTOR

INTERPRETATION?INTERPRETATION?

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Original Model Use - Market timing of Mutual Funds (Treynor-Mazuy model)

Hedge Funds trade in non-linear strategies so we cannot use the model to interpret as market timing.

Useful for:- Fund selection- Stress Test Analysis

REGIME ANALYSISREGIME ANALYSIS

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Market Regime Analysis provides information about the fund performance in various market environments.

Regime models can be useful in Monte Carlo simulations, stress tests and other analysis.

BUILDING REGIME MODELSBUILDING REGIME MODELS

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STATISTICAL ANALYSIS1.Collect Risk Factor Time Series2.Group time series points based cluster analysis3.Examine groups and assign meaning (e.g. Flight to Quality, Treading Water, Bull Market)4.Classify every new point using Bayesian Analysis

DETERMINISTIC QUANTITATIVE RULE (E.G. LEVEL OF VIX).

DETERMINISTIC QUALITATIVE RULE (E.G. RECESSION, GROWTH)

EXAMPLE: MODEL BASED ON THREE REGIMESEXAMPLE: MODEL BASED ON THREE REGIMES

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FACTOR RETURNS

EXAMPLE: MODEL BASED ON THREE REGIMES - CORRELATIONSEXAMPLE: MODEL BASED ON THREE REGIMES - CORRELATIONS

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CORRELATIONS

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CORRELATIONS

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CORRELATIONS

MONTE CARLO ANALYSIS BASED ON REGIME SWITCHING MODELMONTE CARLO ANALYSIS BASED ON REGIME SWITCHING MODEL

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I. Identify regime model based on behavior of various risk factors (e.g. Treading Water, Flight to Quality, Bull Market).

II. Identify Expected Return model for the fund using specified risk factorsIII. Identify transition probability matrix IV. Identify average returns and covariance matrixes of the risk factors in

various regimes.V. Simulate regimes using starting regime and transition matrix.VI. Draw risk factor returns from multi variate distribution for each regimeVII.Calculate Expected Return for the fund based on expected return model.

REGIME MODEL - SIMULATIONREGIME MODEL - SIMULATION

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REGIME MODEL - SIMULATIONREGIME MODEL - SIMULATION

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TAIL RISK ANALYSISTAIL RISK ANALYSIS

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Stress Tests – Stress Tests are useful in estimating fund performance during either historical or theoretical scenarios.In absence of position data stress tests can be performed using Expected Return model calculated through either Uni-Variate or multi-variate regression.

We recommend adding the convexity calculation into the formula. Convexity calculation (described above)

In practice convexity analysis can be used with either Uni-Variate models or Multi-Variate models with limited number of variables.

E(Rfund ) iXistressi1

iX2istress

E(Rfund ) iXistressi1

EQUATION 5

EQUATION 6

TAIL RISK ANALYSIS IN Transparency AnalyticsTAIL RISK ANALYSIS IN Transparency Analytics

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RED FLAG IDENTIFICATIONRED FLAG IDENTIFICATION

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Red flag identification is a tool that allows investors to quickly identify unusual patterns in the fund’s risk profile. We currently have six red flags calculated in TA.

FLAG DESCIPTION

High Serial Correlation High serial correlation maybe sign of return smoothing or illiquidity

High Beta to Strategy High beta to strategy Abs(Beta) > 3 is indicative of excessive leverage

Low Correlation to Strategy May be sign of misclassification

Volatility is too low Volatility that is too low (<2% on annualized basis) may be sign of fraud.

Abnormal Monthly Return (Historical) Return outside of historical s standard deviation range

Abnormal Monthly Return (strategy) Return that is either too low or too high compared to the peer group.

SAMPLE RED FLAG REPORT SAMPLE RED FLAG REPORT

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PUTTING IT ALL TOGETHER – FUND RISK DASHBOARDPUTTING IT ALL TOGETHER – FUND RISK DASHBOARD

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FINAL THOUGHTFINAL THOUGHT

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ALL MODELS ARE WRONG BUT SOME ARE USEFUL – George E. P. Box

CONTACT INFORMATIONCONTACT INFORMATION

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Σ Online: http://www.TransparencyAnalytics.com

http://www.Risk-AI.com

Σ Email: contact@risk-ai.comΣ Phone: (212) 400-7176

Σ Address:

Risk-AI, LLC

40 Wall Street, 28th Floor

New York, NY 10005

Analyszing Hedge Fund Risk

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Transcript of Analyszing Hedge Fund Risk

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