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Reaching for Yield
Yichuan Wang
Michigan Interactive InvestmentsUniversity of Michigan
April 7, 2013
Outline
IntroductionReaching for YieldCAPM
Empirical Data and ResultsJournal ArticlesRegression Data
ConclusionsStrategyFuture Work
References
Outline
IntroductionReaching for YieldCAPM
Empirical Data and ResultsJournal ArticlesRegression Data
ConclusionsStrategyFuture Work
References
Reaching for YieldI When rates of return are low, people go into riskier assetsI Imagine you are a pension manager
I You need to get 3% yield, but Interest rates are very low
Figure: Bond Yields
Choice of AssetsI One potential solution: risker stocks – better to go for broke
than to get fired
0.0
0.1
0.2
0.3
0.4
−5 0Return
Figure: Return Distributions
Tangent – CAPM
I Basic idea: risk compensated by returnI Risk: Market BetaI Return: Alpha
I Standard CAPM:ri ∼ αi + βi rm
I Beta (βi ) – measure of volatility, used to indicate risk, but notperfect
I Example: Deep out of the money putsI But is sufficient for a short term measure of ’reaching for yield’
Example With McDonalds
−0.050
−0.025
0.000
0.025
0.050
−0.050 −0.025 0.000 0.025 0.050SPY
MC
D
2007
2008
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2011
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2013Year
Figure: MCD vs. SPY Daily Returns
Example with McDonalds
−0.0050
−0.0025
0.0000
0.0025
0.0050
−0.0050 −0.0025 0.0000 0.0025 0.0050SPY
MC
D
2007
2008
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2010
2011
2012
2013Year
Figure: Return Scatterplot – Alpha is the Y-Intercept
Outline
IntroductionReaching for YieldCAPM
Empirical Data and ResultsJournal ArticlesRegression Data
ConclusionsStrategyFuture Work
References
Insurance Portfolios
I Prevalent in corporate bond market - Abstract from Beckerand Ivashina [2013]
...insurance portfolios are systematically biased towardhigher yield, higher CDS bonds. Reaching-for-yield ... isalso more pronounced for firms with poor corporategovernance and for which regulatory capital requirementis more binding. A comparison of the ex-post performanceof bonds acquired by insurance companies shows nooutperformance, but higher systematic risk and volatility.
I Matches theory:
1. Poor corporate governance and binding capital makes ’goingfor broke’ more attractive
2. Negative sum game – higher risk and volatility
Stock Prices and Portfolio StrategyI Suggests high beta stocks will earn lower risk-adjusted returns
when credit is easyI Risk-adjusted is important – helps filter out the noise from
market returnsI Easy credit allows firms to lever up to pursue these high risk
strategies
I Betting against beta factor Frazzini and Pedersen [2010]
We test the model’s predictions within U.S. equities,across 20 global equity markets, for Treasury bonds,corporate bonds, and futures. Consistent with the model,we find in each asset class that a betting-against-beta(BAB) factor which is long a leveraged portfolio oflow-beta assets and short a portfolio of high-beta assetsproduces significant risk-adjusted returns. When fundingconstraints tighten, betas are compressed towards one,and the return of the BAB factor is low.
Portfolio Performance
Figure: Monthly Alpha (Percent) for Portfolios Sorted into Beta Deciles
Dependence on Funding Conditions
Figure: Frazzini and Pedersen [2010] BAB Regressions
Stock Price Regressions
I We can see effects of ’Betting against Beta’ in a simpleregression!
I Take price history of almost all stocks traded on US exchangesfrom available price data from 2007 – Present
I Comprise ∼100% of total market capitalization
I Weight regressions by market capitalization, use robustregression (Huber M-Estimator)
I Specification:
1. Standard CAPM:ri ∼ αi + βi rm
2. Betting Against Beta (b):
αi ∼ a + b |βi |
Data Source
I ’Yahoo Finance’, interfaced through open source R:I Quantmod, TTR, ggplot2
Figure: Console Output of Code
Yearly Results
−0.20
−0.15
−0.10
−0.05
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2007 2008 2009 2010 2011 2012
Bet
a C
oeffi
cien
t
Reaching for Yield?
Figure: Coefficient (b) for 2007 – 2012
Sorted by Market Capitalization
−0.3
−0.2
−0.1
0.0
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2007 2008 2009 2010 2011 2012
Bet
a C
oeffi
cien
t
0.010
0.015
0.020
0.025
0.030BetaSE
Market Cap
Small
Medium
Large
Reaching for Yield?
Figure: Divided by Market Capitalization
Outline
IntroductionReaching for YieldCAPM
Empirical Data and ResultsJournal ArticlesRegression Data
ConclusionsStrategyFuture Work
References
Portfolio Strategy
I Should try to avoid highly volatile stocks – everybody islooking for the explosive investment
I Mentioned in BBBY PitchI Pitch more than stocks – look for an optimal portfolio, not
just a good stock
I Betting against beta should be persistentI Institutional biases
I Caveat:I Regression data is low R2, but Frazzini and Pedersen [2010]
has more portfolio based evidence
Refinements
I More controlsI Becker and Ivashina [2013] – control for Fama-French, more
robust estimation
I Longer history of pricesI Can compare slopes with wider range of credit conditions
I Other asset classesI Could have implications for the corporate debt market
Research Areas
I Relationship between business cycle and ’reaching for yield’I Becker and Ivashina [2013] – when growth is highI Frazzini and Pedersen [2010] – when growth (and thus interest
rates) are low
I Monetary Policy:I Potential new channel in which nominal shocks have real
effectsI Need better tools for macroprudential regulation if we want
extended periods of low interest rates – Stein [2011]
Outline
IntroductionReaching for YieldCAPM
Empirical Data and ResultsJournal ArticlesRegression Data
ConclusionsStrategyFuture Work
References
Bibliography
Bo Becker and Victoria Ivashina. Reaching for yield in the bondmarket. Working Paper 18909, National Bureau of EconomicResearch, March 2013. URLhttp://www.nber.org/papers/w18909.
Andrea Frazzini and Lasse H. Pedersen. Betting against beta.Working Paper 16601, National Bureau of Economic Research,December 2010. URL http://www.nber.org/papers/w16601.
Jeremy C. Stein. Monetary policy as financial-stability regulation.Working Paper 16883, National Bureau of Economic Research,March 2011. URL http://www.nber.org/papers/w16883.
