11th Annual London Business Research Conference - Imperial College, London, UK (July 26, 2016) - Presentation Slides

1. MACROECONOMIC AND
FINANCIAL FACTORS IN
HEDGE FUND RETURNS
L. MICK SWARTZ
11th Annual London Business Research Conference
Imperial College London – July 26, 2016
* Special thanks to my research assistant, Farrokh Emami Langroodi

2. Introduction
• This paper examines 36 hedge fund categories using
various (22) leading, lagging, and coincidental
macroeconomic and financial variables, as explanatory
variables, to explain the hedge fund category returns.

3. Introduction – Cont.
• This paper introduces new macroeconomic variables that
affect hedge fund returns in some hedge fund categories
including the CRB index return, WTI crude oil return, gold
return, U.S. balance of trade, U.S. Dollar/Japan Yen
exchange rate, U.S. Dollar/Euro exchange rate, U.S. 10-
year T-bond, U.S. industrial production, copper return,
U.S. personal consumption expenditure. None of these
variables have been included and examined in the
previous hedge fund literature.

4. Econometric Improvements
• In this study, the generated models are tested and
corrected for time-series assumptions of stationary
variables, autocorrelation, multi-collinearity, conditional
heteroscedasticity, and unconditional heteroscedasticity.
None of the previous major published researches on
hedge funds address any type of heteroscedasticity or
stationarity corrections. The econometric models
presented in this research outperform the standard Fung
& Hsieh seven-factor model in 35 out of 36 hedge fund
categories. Most models presented have four or fewer
explanatory variables as the focus of the research is to
rely on more parsimonious models

5. Previous Models
• Fung & Hsieh (2004) – 7 factor model (standard accepted
Hedge Fund factor model)
• S&P 500, 10 Treasury Note, Size Premium (SML), Moody’s Baa
minus 10 year T-Note (Credit Spread), Bond Option, Commodity
Option, FX Option
• Jurek and Stafford (2015) – Apply 7-9 factor model and
option replication (mentioned Drawdown)
• Agarwal and Naik (2004) – Option Replication

6. Approach for this paper
• Expand the use of Macroeconomic Variables and control
for CAPM and Fama-French CAPM variables
• Test and correction for Stationarity, Autocorrelation, Multi-
Collinearity, Conditional and Unconditional
Heteroskedasticity.
• None of the previous literature addresses these
econometric issues in great detail.
• 22 out of 36 analyzed strategies are not consistent with
Put-writing returns.

7. Model Estimation & Diagnostics
 Model Estimation and Diagnostics
 Hedge fund return models are estimated by Ordinary Least Square
(OLS) technique or one of the ARCH family techniques if needed.
 To generate robust models, each model is tested and corrected for:
• Stationarity (Augmented Dickey-Fuller Unit Root test, corrected by first
differencing),
• Serial-Correlation (Durbin-Watson test, corrected by first order
autoregression term),
• Multi-Collinearity (Variance Inflation Factor test < 10, corrected by
elimination),
• Conditional Heteroskedasticity (tested and corrected by ARCH, GARCH, or
EGARCH modeling).
• Heteroskedasticity (White test, corrected by Newey–West HAC estimation).
 The Akaike information criterion (AIC) and Schwarz information
criterion (SIC) are used for the best model selection, with the SIC
favored, as an indicator of the parsimony model, if there is a
disagreement among these indicators.

8. Data from 2008 not consistent with Put-
Writing Strategies
Hedge Fund Category Jan-08 Feb-08 Mar-08 Apr-08 May-08 Jun-08 Jul-08 Aug-08 Sep-08 Oct-08 Nov-08 Dec-08
Equity Hedge -3.37% 1.39% -2.81% 2.40% 2.39% -1.06% -3.45% -0.90% -8.59% -9.99% -2.49% -1.69%
Equity Market Neutral -2.75 0.79 2.05 1.03 0.23 1.02 -0.03 -1.91 -0.24 0.19 0.69 -2.13
Energy & Basic Materials -2.06 4.01 -0.92 1.69 2.99 1.42 -8.69 -4.17 -16.25 -3.40 -3.93 -3.19
Fundamental Growth -6.45 2.20 -5.34 2.43 1.70 -4.04 -3.39 -4.33 -8.37 -4.28 -1.62 0.62
Fundamental Value -2.14 1.29 -2.30 1.82 2.09 -3.43 -3.71 -0.38 -8.89 -7.77 -2.82 -1.85
Multi-Strategy -5.59 1.79 -2.35 2.86 2.48 -3.94 -0.97 -0.80 -6.48 -6.24 -10.51 2.93
Quantitative Directional -4.00 1.29 0.60 -0.50 1.11 1.19 -0.71 -0.23 -0.56 -1.14 0.27 -0.56
Short Bias 3.87 3.03 0.76 -3.12 -1.23 5.70 -0.15 -0.47 2.56 7.48 4.90 -2.67
Technology & Healthcare -5.52 1.71 -1.37 3.53 3.61 -1.82 0.84 -0.63 -6.27 -1.01 -1.07 -0.23
Event Driven -3.39 1.68 -1.50 1.16 1.47 -3.35 -0.83 -1.00 -7.37 -7.53 -2.74 -0.79
Activist -5.88 0.41 -2.74 2.75 3.39 -2.00 -6.10 -0.44 -11.92 -16.30 -1.36 6.34
Credit Arbitrage 0.02 1.07 -0.85 0.10 0.59 -0.15 -0.39 -0.08 -1.11 -2.05 -2.37 -1.47
Distressed Securities -1.40 -0.01 -0.90 -0.88 -0.12 -0.12 -1.49 -0.12 -3.12 -11.69 -6.15 -9.18
Merger Arbitrage -0.65 0.66 0.23 0.97 1.41 -0.25 0.44 0.56 -2.14 -1.28 1.57 2.21
Multi-Strategy -2.11 -0.91 -1.37 0.85 3.08 -0.40 -1.49 0.97 -14.87 -12.39 0.11 -3.65
Special Situation -4.14 1.86 -1.76 1.32 2.05 -2.90 -1.25 -1.03 -9.42 -10.99 -2.54 -0.01

9. Data from 2008 not consistent with Put-
Writing Strategies
Hedge Fund Category Jan-08 Feb-08 Mar-08 Apr-08 May-08 Jun-08 Jul-08 Aug-08 Sep-08 Oct-08 Nov-08 Dec-08
Macro/CTA 3.82% 8.54% -3.00% -0.65% 1.77% 3.25% -5.59% -3.94% -0.85% -1.76% 1.48% 3.26%
Active Trading 0.12 2.11 0.22 3.78 1.28 0.83 2.22 -0.25 -5.14 3.08 1.08 -0.22
Commodity 3.00 9.11 -1.29 -0.42 0.14 2.70 -2.01 -0.57 -0.12 3.33 -0.14 0.56
Commodity-Agriculture 3.14 6.06 -2.11 -0.87 -1.44 5.83 -2.68 -0.88 -4.16 -3.37 -3.68 1.69
Commodity-Metals 7.80 7.97 -7.64 -5.50 1.95 2.04 7.70 -7.11 -2.19 -17.24 8.36 4.68
Commodity-Energy -5.85 10.07 -0.96 4.28 5.80 7.20 -15.03 -1.80 -8.41 -4.98 -1.32 -0.39
Currency -1.65 0.30 1.28 1.28 0.57 0.52 0.84 -2.88 -1.69 0.50 0.68 0.83
Discretionary Thematic 6.31 4.79 -5.75 1.26 2.36 1.27 -3.36 -2.71 -0.42 -9.10 -2.28 3.35
Multi-Strategy -0.09 3.04 -3.62 1.45 -0.21 -0.92 -2.09 0.11 -2.80 1.94 -1.99 2.45
Systematic Diversified 3.20 11.56 -2.13 -2.11 3.26 6.20 -5.13 -1.80 1.61 6.77 4.35 3.12
Relative Value Arbitrage -3.31 -1.40 -3.53 1.55 0.11 -1.55 -2.26 -0.50 -9.37 -14.11 -7.91 -2.76
Convertible Arbitrage -0.43 -1.07 -4.51 -0.83 1.83 -1.77 -1.82 -1.16 -16.55 -34.68 -10.50 -5.75
Energy Infrastructure -4.50 0.01 -4.97 3.59 4.61 0.25 -4.06 -1.05 -12.93 -6.17 -5.51 -3.79
Fixed Income-Asset Backed -1.90 -0.39 -1.34 1.32 1.11 0.64 1.28 1.03 -0.71 -3.34 -0.96 1.44
Fixed Income-Corporate -0.57 0.37 0.00 1.34 0.97 0.02 -0.74 -0.12 -6.84 -12.74 -3.73 -1.66
Fixed Income-Sovereign 1.60 1.39 -6.07 4.40 1.86 -0.85 1.39 0.29 -9.79 -15.94 4.39 0.95
Multi-Strategy -1.89 -0.21 -0.90 -0.55 1.09 0.48 0.37 -0.50 -3.43 -9.25 -1.96 0.37
Real Estate -3.46 0.52 -1.34 0.40 1.07 -3.71 -2.39 0.42 -4.31 -5.39 -0.56 2.46
Volatility -2.98 1.78 0.79 2.10 2.22 1.19 0.87 0.71 -3.80 -1.43 -0.51 1.24
Yield Alternative -2.15 -0.09 -4.95 4.61 4.34 -1.33 -5.51 -0.51 -13.25 -5.10 -5.99 0.95

10. List of Macroeconomic Variables
(Independent Variables)
• Standard & Poor’s 500 index (S&P 500) monthly total
return, Commodity Research Bureau (CRB) index
monthly total return, high grade Copper (CU) monthly
return, Gold Bullion (XAU) monthly return, West Texas
Intermediate (WTI) crude oil monthly return, U.S. Dollar
Trade Weighted Index (DXY) monthly return, US Dollar
(USD) per Euros (USD/EUR) rate, USD per 100
Japanese Yen (USD/JPY) rate, U.S. government 10-year
Treasury bond (T-bond) total return, U.S. Treasury bill (T-
bill) total return, U.S. Industrial Production Index
(INDPRO) rate of change, U.S. Personal Consumption
Expenditures (PCE) rate of change, U.S. Real PCE rate of
change, and U.S. Consumer Price Index (CPI) rate of
change.

11. Other Macroeconomic Variables
• The three-month and 12-month London Interbank Offered
Rate (LIBOR) rates based on U.S. Dollar, U.S.
government 10-year T-bond yield, and U.S. government
three-month T-bill yield are collected from Federal
Reserve Bank of St. Louis (FRED) database. U.S. Total
Balance of International Trade (BOT) rate of change data
is collected from U.S. Census Bureau, Foreign Trade
Division. U.S. monthly Unemployment rate (UNRATE)
data is collected from U.S. Bureau of Labor Statistics
(BLS).

12. Empirical Results
Global Macro
• The simpler models, for every category, outperform the Fung
and Hsieh (2004) seven-factor models considering the AIC,
SIC, and adjusted R-squared as the performance criteria.
• The first hedge fund group studied in this article is the Macro
group which comprises of ten hedge fund categories. Some of
the main realized points regarding this group are that the
economic variables such as the CRB index return and Gold
index return (XAU) the dominant significant factors in majority
of estimated models.
• U.S. Unemployment Rate (UNRATE) and USD/JPY exchange
rate and the S&P 500 return is also a dominant factor,
especially in non-commodity-related hedge fund categories.

13. Global Macro
Regression Results

14. Global Macro
Regression Results (Cont.)

15. Empirical Results
Equity Hedge (Long/Short)
• The second hedge fund group studied in this article is the
Equity Hedge group which comprises of nine hedge fund
categories. The main realized points about this group are
that S&P 500 return, CRB index return, SML (size
premium), and the U.S. Unemployment Rate (UNRATE)
are the significant factors, dominating most of the
estimated models
• This set of hedge funds seems to be more correlated to
the financial market factors, however, only two categories
in this group (i.e. Multi-Strategy index and Technology &
Healthcare index) find both SML (size premium) and HML
(value premium) significant in their corresponding
estimated Fama-French models.

16. Equity Hedge
Regression Results

17. Equity Hedge
Regression Results (Cont.)

18. Empirical Results
Relative Value
• The third hedge fund group studied in this article is the
Relative Value group which comprises of ten hedge fund
categories. Some of the main realized points regarding
this group are that the economic variables such as Credit
Spread (CRSPRD), USD/JPY exchange rate, and WTI
crude oil return are the dominant significant variables in
most of the categories. It worth to note that the Credit
Spread is a significant factor in seven out of ten
categories including Energy Infrastructure category and
all the Fixed-Income related ones. S&P 500 return is also
a dominant factor in explaining the hedge fund returns

19. Relative Value
Regression Results

20. Relative Value
Regression Results (Cont.)

21. Empirical Results
Event Driven
• The fourth hedge fund group studied in this article is the Event
Driven group which comprises of seven hedge fund categories.
Some of the main realized points regarding this group are that
the S&P 500 index return, the Credit Spread (CRSPRD), WTI
crude oil return, and the U.S. Unemployment Rate (UNRATE)
are the dominant significant variables throughout the estimated
models. It worth to note that in this group, Distressed Securities
hedge fund category has Copper index return (CU), Credit
Spread (CRSPRD), USD/JPY rate, Personal Consumption
Expenditure (PCE), and S&P 500 index return as significant
variables among which only Credit Spread is the only
negatively correlated factor to the hedge fund return and the
other factors, due to their positive correlation, increase the
hedge fund returns when the economy is improving.

22. Event Driven
Regression Results

23. Event Driven
Regression Results (Cont.)

24. Conclusion
• The models presented in this paper outperform the Fung
and Hsieh 7-factor models in 31 out of 36 categories
(using SIC, AIC, R2 and adjusted R2) or over 86% of the
time. If SIC and AIC are the only criteria used to select the
models for each category, then all 36 models outperform
the Fung and Hsieh 7-factor model. In addition, this
paper examines many individual hedge fund categories
that have never been presented in the previous hedge
fund literature. The obtained models are controlled for
CAPM and Fama-French variables and are usually
consist of four or fewer significant variables with only a
few of them having five significant variables

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