What is the Shape of the Risk-Return Relation? PDF Download
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Author: Alberto G. P. Rossi
Publisher:
ISBN:
Category :
Languages : en
Pages : 58
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Book Description
Using a flexible econometric approach that avoids imposing restrictive modeling assumptions, we find evidence of a non-monotonic relation between conditional volatility and expected stock market returns: At low-to-medium levels of conditional volatility there is a positive trade-off between risk and expected returns, but this relationship gets inverted at high levels of volatility as observed during the recent financial crisis. We propose a new measure of risk based on the conditional covariance between daily observations of a broad economic activity index and stock returns. Using this covariance measure, we find clear evidence of a monotonically increasing risk-return trade-off. Our finding of a non-monotonic mean-volatility relation helps explain the absence of a consensus in the empirical literature on the sign of the risk-return trade-off. At the same time, our finding that the expected return is a monotonically rising function of the conditional covariance measure also suggests that a positive risk-return relation can be established once a better measure of risk is used.
Author: Alberto G. P. Rossi
Publisher:
ISBN:
Category :
Languages : en
Pages : 58
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Book Description
Using a flexible econometric approach that avoids imposing restrictive modeling assumptions, we find evidence of a non-monotonic relation between conditional volatility and expected stock market returns: At low-to-medium levels of conditional volatility there is a positive trade-off between risk and expected returns, but this relationship gets inverted at high levels of volatility as observed during the recent financial crisis. We propose a new measure of risk based on the conditional covariance between daily observations of a broad economic activity index and stock returns. Using this covariance measure, we find clear evidence of a monotonically increasing risk-return trade-off. Our finding of a non-monotonic mean-volatility relation helps explain the absence of a consensus in the empirical literature on the sign of the risk-return trade-off. At the same time, our finding that the expected return is a monotonically rising function of the conditional covariance measure also suggests that a positive risk-return relation can be established once a better measure of risk is used.
Author: Napon Hongsakulvasu
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
In this paper, I propose a new semi-parametric GARCH-in-Mean model. Since many empirical papers have the mix results on the risk-return relation, the cause of problem may come from the misspecification of conditional mean equation or conditional variance equation or both of them. My model uses non-parametric estimation in conditional mean equation and semi-parametric estimation in conditional variance equation which allows the non-linear risk return relation in conditional mean equation and allows the non-linear relation between the volatility and the cumulative sum of exponentially weighted past returns. Three parameters on my model are GARCH parameter, the leverage effect parameter and leptokurtic parameter. I also extend my model to include four exogenous variables, dividend yield, term spread, default spread and momentum into conditional mean equation by using additive model which allows each variable to have non-linear relation with the return. An empirical study on S&P 500 suggests that risk has a small affect on market return. However, when four exogenous variables are added to the model, my model shows that the risk-return relation has a positive hump shape. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/155545
Author: Hui Guo
Publisher:
ISBN:
Category : Investments
Languages : en
Pages : 40
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Book Description
There is an ongoing debate in the literature about the apparent weak or negative relation between risk (conditional variance) and return (expected returns) in the aggregate stock market. We develop and estimate an empirical model based on the ICAPM to investigate this relation. Our primary innovation is to model and identify empirically the two components of expected returns--the risk component and the component due to the desire to hedge changes in investment opportunities. We also explicitly model the effect of shocks to expected returns on ex post returns and use implied volatility from traded options to increase estimation efficiency. As a result, the coefficient of relative risk aversion is estimated more precisely, and we find it to be positive and reasonable in magnitude. Although volatility risk is priced, as theory dictates, it contributes only a small amount to the time-variation in expected returns. Expected returns are driven primarily by the desire to hedge changes in investment opportunities. It is the omission of this hedge component that is responsible for the contradictory and counter-intuitive results in the existing literature
Author: Scott Cederburg
Publisher:
ISBN:
Category :
Languages : en
Pages : 78
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Book Description
The ICAPM implies that the market's conditional expected return is proportional to its conditional variance and that the reward-to-risk ratio equals the representative investor's coefficient of relative risk aversion. Prior studies examine this relation using the stock market to proxy for aggregate wealth and find mixed results. We show, however, that stock-based tests suffer from low power and lead to biased estimates of the risk-return tradeoff when stocks are an imperfect market proxy. Tests designed to mitigate this bias by incorporating a more comprehensive measure of aggregate wealth produce large, positive estimates of the risk-aversion coefficient around seven to nine.
Author: Frank H. Knight
Publisher: Cosimo, Inc.
ISBN: 1602060053
Category : Business & Economics
Languages : en
Pages : 401
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Book Description
A timeless classic of economic theory that remains fascinating and pertinent today, this is Frank Knight's famous explanation of why perfect competition cannot eliminate profits, the important differences between "risk" and "uncertainty," and the vital role of the entrepreneur in profitmaking. Based on Knight's PhD dissertation, this 1921 work, balancing theory with fact to come to stunning insights, is a distinct pleasure to read. FRANK H. KNIGHT (1885-1972) is considered by some the greatest American scholar of economics of the 20th century. An economics professor at the University of Chicago from 1927 until 1955, he was one of the founders of the Chicago school of economics, which influenced Milton Friedman and George Stigler.
Author: Sydney C. Ludvigson
Publisher:
ISBN:
Category : Rate of return
Languages : en
Pages : 26
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Book Description
"A key criticism of the existing empirical literature on the risk-return relation relates to the relatively small amount of conditioning information used to model the conditional mean and conditional volatility of excess stock market returns. To the extent that financial market participants have information not reflected in the chosen conditioning variables, measures of conditional mean and conditional volatility--and ultimately the risk-return relation itself--will be misspecified and possibly highly misleading. We consider one remedy to these problems using the methodology of dynamic factor analysis for large datasets, whereby a large amount of economic information can be summarized by a few estimated factors. We find that three new factors, a "volatility, " "risk premium, " and "real" factor, contain important information about one-quarter ahead excess returns and volatility that is not contained in commonly used predictor variables. Moreover, the factor-augmented specifications we examine predict an unusual 16-20 percent of the one-quarter ahead variation in excess stock market returns, and exhibit remarkably stable and strongly statistically significant out-of-sample forecasting power. Finally, in contrast to several pre-existing studies that rely on a small number of conditioning variables, we find a positive conditional correlation between risk and return that is strongly statistically significant, whereas the unconditional correlation is weakly negative and statistically insignificant"--National Bureau of Economic Research web site.
Author: Richard A. Brealey
Publisher: MIT Press (MA)
ISBN:
Category : Investment analysis
Languages : en
Pages : 168
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Book Description
Author: Minxian Yang
Publisher:
ISBN:
Category :
Languages : en
Pages : 31
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Book Description
The risk return relationship is analysed in bivariate models for return and realised variance (RV) series. Based on daily time series from 21 international market indices for more than 13 years (January 2000 to February 2013), the empirical findings support the arguments of risk return tradeoff, volatility feedback and statistical balance. It is reasoned that the empirical risk return relationship is primarily shaped by two important data features: the negative contemporaneous correlation between the return and RV, and the difference in the autocorrelation structures of the return and RV.
Author: C. N. V. Krishnan
Publisher:
ISBN:
Category :
Languages : en
Pages : 34
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Book Description
We analyze the stock market risk-return relation over the period from 1927 to 2005. We empirically implement the Intertemporal Capital Asset Pricing Model (ICAPM) using a cross-section of stock and bond portfolios, and allow for the market price of risk to be time-varying. We show that including bond portfolios in the estimation not only significantly changes the time-series estimates of the market price of risk, but also makes the correlation between conditional stock-market variance and the variance component of expected market return positive.
Author: Suzanne G.M. Fifield
Publisher:
ISBN:
Category :
Languages : en
Pages : 46
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Book Description
Traditional finance theory posits that the relationship between the risk and return of stocks is positive. Furthermore, investment practice is often based on the central contention of the Capital Asset Pricing Model (CAPM) that high (low) beta stocks earn higher (lower) returns. However, this fundamental return and risk relationship is questioned by a several researchers who assert that the relationship is, in fact, negative. Consequently, a growing body of research examines the nature of the stock return-risk relationship using both market- and firm-level data. The results of this research are mixed. The purpose of this paper is to shed further light on this relationship by (i) examining both market- and firm-level price data; (ii) employing a battery of tests, including individual market, panel and quantile regressions; and (iii) analysing the nature of the relationship during periods of high and low volatility and in bull and bear markets. The results indicate that there is no single robust relationship between risk and return. Of note, our results suggest a positive relationship when returns are high and during bear markets. Furthermore, the finding of a positive relationship is stronger (i) at the market-level than the firm-level; and (ii) over long time periods. However, the analysis indicates that a negative relationship exists at low return levels, during bull markets and, more so, at the individual firm level. Overall, the results suggest that the risk-return relationship is switching in nature and is primarily driven by changing risk preferences. Notably, a positive relationship exists when macroeconomic risk plays a larger role.
