Dr. Lisa Kramer

Winter Blues and Time-Variation in the Price of Risk

Published by Journal of Empirical Finance

2005 Previous research has documented robust links between seasonal variation in length of day, seasonal depression (known as seasonal affective disorder, or SAD), risk aversion, and stock market returns. The influence of SAD on market returns, known as the SAD effect, is large. We study the SAD effect in the context of an equilibrium asset pricing model to determine whether the seasonality can be explained using a conditional version of the CAPM that allows the price of risk to vary over time. Using daily and monthly data for the US, Sweden, New Zealand, the UK, Japan, and Australia, we find that a conditional CAPM that allows the price of risk to vary in relation to seasonal variation in the length of day fully captures the SAD effect. This is consistent with the notion that the SAD effect arises due to the heightened risk aversion that comes with seasonal depression, reflected by a changing risk premium.

URL: http://www.sciencedirect.com/science/article/pii/S0927539804000830

Winter Blues: A SAD Stock Market Cycle

Published by American Economic Review

2003

URL: http://www.jstor.org/stable/3132178?seq=1#page_scan_tab_contents

This is Your Portfolio on Winter: Seasonal Affective Disorder and Risk Aversion in Financial Decision Making

Published by Social Psychological and Personality Science

2012 This study found that people who suffer from seasonal affective disorder (SAD) displayed financial risk aversion that varied across the seasons as a function of seasonally changing affect. The SAD-sufferers had significantly stronger preferences for safe choices during the winter than non-SAD-sufferers, and they did not differ from non-SAD-sufferers during the summer. The effect of SAD on risk aversion in the winter was mediated by depression.

URL: http://spp.sagepub.com/content/3/2/193.short

Seasonal Asset Allocation: Evidence from Mutual Fund Flows

Published by Journal of Financial and Quantitative Analysis

Forthcoming We analyze the flow of money between mutual fund categories, finding strong evidence of seasonality in investor risk aversion. Aggregate investor flow data reveal investor preference for safe mutual funds in autumn and risky funds in spring. During September alone, outflows from equity funds average $13 billion, controlling for previously documented flow determinants (e.g., capital-gain overhang). This movement of large amounts of money between fund categories is correlated with seasonality in investor risk aversion, consistent with investors preferring safer (riskier) investments in autumn (spring). We find consistent evidence in Canada, and in Australia where seasons are offset by six months.

URL: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1907904

Seasonal Variation in Treasury Returns

Published by Critical Finance Review

2015 We document a novel and striking annual cycle in the U.S. Treasury market, with a variation in mean monthly returns of over 80 basis points from peak to trough. We show that this seasonal Treasury return pattern does not arise due to macroeconomic seasonalities, seasonal variation in risk, the weather, cross-hedging between equity and Treasury markets, conventional measures of investor sentiment, seasonalities in the Treasury market auction schedule, seasonalities in the Treasury debt supply, seasonalities in the FOMC cycle, or peculiarities of the sample period considered. Rather, the seasonal pattern in Treasury returns is significantly correlated with a proxy for variation in investor risk aversion across the seasons, and a model based on that proxy is able to explain more than sixty percent of the average seasonal variation in monthly Treasury returns. The White (2000) reality test confirms that the correlation between returns and the proxy for seasonal variation in investor risk aversion cannot be easily dismissed as the simple result of data snooping.

URL: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1076644

Seasonally Varying Preferences: Theoretical Foundations for an Empirical Regularity

Published by Review of Asset Pricing Studies

2014 We investigate an asset pricing model with preferences cycling between high risk aversion and low EIS in fall/winter and the reverse in spring/summer. Calibrating to consumption data and allowing plausible preference parameter values, we produce returns that match observed equity and Treasury returns across the seasons: risky returns are higher and risk-free returns are lower or stable in fall/winter, and they reverse in spring/summer. Further, risky returns vary more than risk-free returns. A novel finding is that both EIS and risk aversion must vary seasonally to match observed returns. Further, the degree of necessary seasonal change in EIS is small.

URL: http://raps.oxfordjournals.org/content/4/1/39.short

Losing Sleep at the Market: The Daylight Saving Anomaly

Published by American Economic Review

2000

URL: http://www.jstor.org/stable/117321

Losing Sleep at the Market: The Daylight Saving Anomaly: Reply

Published by American Economic Review

2002

URL: http://www.jstor.org/stable/3083314

Estimating the Equity Premium

Published by Journal of Financial and Quantitative Analysis

2010 Existing empirical research investigating the size of the equity premium has largely consisted of a series of innovations around a common theme: producing a better estimate of the equity premium by using better data or a better estimation technique. The equity premium estimate that emerges from most of this work matches one moment of the data alone: the mean difference between an estimate of the return to holding equity and a risk-free rate. We instead match multiple moments of U.S. market data, exploiting the joint distribution of the dividend yield, return volatility, and realized excess returns, and find that the equity premium lies within 50 basis points of 3.5%, a range much narrower than was achieved in previous studies. Additionally, statistical tests based on the joint distribution of these moments reveal that only those models of the conditional equity premium that embed time variation, breaks, and/or trends are supported by the data. In order to develop the joint distribution of the dividend yield, return volatility, and excess returns, we need a model of price and return fundamentals. We document that even recently developed analytically tractable models that permit autocorrelated dividend growth rates and discount rates impose restrictions that are rejected by the data. We therefore turn to a wider range of models, requiring numerical solution methods and parameter estimation by the simulated method of moments.

URL: http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=7916829&fileId=S0022109010000347