The enhanced risk premium factor model and expected returns

2013 ◽  
Vol 2 (3) ◽  
pp. 3-21
Author(s):  
Javier Estrada
2019 ◽  
Vol 27 (3) ◽  
pp. 297-327
Author(s):  
Sungjeh Moon ◽  
Joonhyuk Song

We analyze the cross-sectional expected return of KOSPI stocks using equity duration. From 1991 to 2018, we calculate equity durations for the KOSPI listed stocks (including de-listed stocks) and find that the shorter the equity duration, the higher the risk premium. Using the 4-factor model with equity duration added to the benchmark 3-factor model, the explanatory power of the 4-factor model is superior to that of the existing benchmark model in accounting for risk premiums. This is an unusual finding that is not readily explainable by the traditional CAPM or the Fama-French 3-factor model. This can be interpreted that the equity duration is a separate and significant risk factor dissociated from the HML of the 3-factor model.


2021 ◽  
Vol 12 (3) ◽  
pp. 135
Author(s):  
Jamil Chaya ◽  
Jamil A. Hammoud ◽  
Wael A. Saleh

Understanding stock return variations and accounting for their drivers help academics and practitioners estimate expected returns and gauge risk exposures, thereby optimizing investment strategies. This paper seeks to study the effect of systemic risk, size and valuation on stock return, in the Lebanese stock market. The research design and methodology are the Fama French Factor Model (FFFM) as developed by Fama and French in their seminal work of 1993. The research demonstrates validity of the three variables in question, and that is consistent with results obtained for global equity markets. However, the results exhibit a negative market risk premium with respect to US T-bills, and a high level of factor inter-correlation for the period in question.


2021 ◽  
pp. 014616722199853
Author(s):  
Judith Gerten ◽  
Michael K. Zürn ◽  
Sascha Topolinski

For financial decision-making, people trade off the expected value (return) and the variance (risk) of an option, preferring higher returns to lower ones and lower risks to higher ones. To make decision-makers indifferent between a risky and risk-free option, the expected value of the risky option must exceed the value of the risk-free option by a certain amount—the risk premium. Previous psychological research suggests that similar to risk aversion, people dislike inconsistency in an interaction partner’s behavior. In eight experiments (total N = 2,412) we pitted this inconsistency aversion against the expected returns from interacting with an inconsistent partner. We identified the additional expected return of interacting with an inconsistent partner that must be granted to make decision-makers prefer a more profitable, but inconsistent partner to a consistent, but less profitable one. We locate this inconsistency premium at around 31% of the expected value of the risk-free option.


2011 ◽  
Vol 47 (1) ◽  
pp. 115-135 ◽  
Author(s):  
Mariano González ◽  
Juan Nave ◽  
Gonzalo Rubio

AbstractThis paper explores the cross-sectional variation of expected returns for a large cross section of industry and size/book-to-market portfolios. We employ mixed data sampling (MIDAS) to estimate a portfolio’s conditional beta with the market and with alternative risk factors and innovations to well-known macroeconomic variables. The market risk premium is positive and significant, and the result is robust to alternative asset pricing specifications and model misspecification. However, the traditional 2-pass ordinary least squares (OLS) cross-sectional regressions produce an estimate of the market risk premium that is negative, and significantly different from 0. Using alternative procedures, we compare both beta estimators. We conclude that beta estimates under MIDAS present lower mean absolute forecasting errors and generate better out-of-sample performance of the optimized portfolios relative to OLS betas.


Author(s):  
Alessandro Beber ◽  
Joost Driessen ◽  
Anthony Neuberger ◽  
Patrick Tuijp

We develop an asset pricing model with stochastic transaction costs and investors with heterogeneous horizons. Depending on their horizon, investors hold different sets of assets in equilibrium. This generates segmentation and spillover effects for expected returns, where the liquidity (risk) premium of illiquid assets is determined by investor horizons and the correlation between liquid and illiquid asset returns. We estimate our model for the cross-section of U.S. stock returns and find that it generates a good fit, mainly due to a combination of a substantial expected liquidity premium and segmentation effects, while the liquidity risk premium is small.


2019 ◽  
Vol 22 (02) ◽  
pp. 1950012
Author(s):  
Thomas Gramespacher ◽  
Armin Bänziger

In two-pass regression-tests of asset-pricing models, cross-sectional correlations in the errors of the first-pass time-series regression lead to correlated measurement errors in the betas used as explanatory variables in the second-pass cross-sectional regression. The slope estimator of the second-pass regression is an estimate for the factor risk-premium and its significance is decisive for the validity of the pricing model. While it is well known that the slope estimator is downward biased in presence of uncorrelated measurement errors, we show in this paper that the correlations seen in empirical return data substantially suppress this bias. For the case of a single-factor model, we calculate the bias of the OLS slope estimator in the presence of correlated measurement errors with a first-order Taylor-approximation in the size of the errors. We show that the bias increases with the size of the errors, but decreases the more the errors are correlated. We illustrate and validate our result using a simulation approach based on empirical data commonly used in asset-pricing tests.


2012 ◽  
Vol 02 (02) ◽  
pp. 1250006 ◽  
Author(s):  
Frank de Jong ◽  
Joost Driessen

This paper explores the role of liquidity risk in the pricing of corporate bonds. We show that corporate bond returns have significant exposures to fluctuations in treasury bond liquidity and equity market liquidity. Further, this liquidity risk is a priced factor for the expected returns on corporate bonds, and the associated liquidity risk premia help to explain the credit spread puzzle. In terms of expected returns, the total estimated liquidity risk premium is around 0.6% per annum for US long-maturity investment grade bonds. For speculative grade bonds, which have higher exposures to the liquidity factors, the liquidity risk premium is around 1.5% per annum. We find very similar evidence for the liquidity risk exposure of corporate bonds for a sample of European corporate bond prices.


2020 ◽  
Vol 83 ◽  
pp. 01031
Author(s):  
Miroslav Kmeťko ◽  
Eduard Hyránek

One of the best-known Capital Asset Pricing Model (CAP/M) provides us with a methodology for measuring the relationship between the risk premium and the impact of leverage on expected returns. However, this model is not used only to value the cost of capital but also to evaluate the performance of managed portfolios. We will test how the expected return changes in percent by changing the debt-equity ratio and the tax rate based on following assumptions: market return 7%, risk-free rate of return 1% and beta 1.2. These assumptions will be constant and we will change the debt-equity ratio and tax rate. Based on these results, it is clear that the change in profitability varies, in relation to the change of the DE ratio by one tenth. As for changes I n tax rates, changes in expected profitability are not entirely in direct proportion to these changes.


2019 ◽  
Vol IV (I) ◽  
pp. 30-38
Author(s):  
Maria Sultana ◽  
Muhammad Imran ◽  
Muhammad Amjad Saleem

The fundamental structure of the present theory of asset pricing underscored clarifying the path as to how the systematic risk is estimated and how investors are adapted to behavior for such risk. The mixed expense of debt and equity that an association should procure to raise funds for its assignments impacts its stock returns through investment choices and is an additional significant segment of business valuation work on the grounds that for putting resources into more risky resources, investors request better yields or higher returns, for legitimizing better yields this risk premium emerging from such risks is included in the returns. Hence, in clarifying portfolio returns, the three-factor model is increased with WACC to analyze its logical force that if WACC is estimated by the market or not through multivariate regressions. Two principle results are deduced by the examination; first; the findings attest to the presence of market premium, size impact, value impact, WACC premium in the equity market of Pakistan. Second, however generally exciting with exceptional interest, when contrasted with FF unique 3-factor model, the models which join WACC outperformed, which also affirmed from Adj.R2 results.


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