Cross-Sectional PEG Ratios, Market Equity Premium, and Macroeconomic Activity

2018 ◽  
Vol 35 (3) ◽  
pp. 471-500
Author(s):  
Xiaoquan Jiang ◽  
Qiang Kang
Keyword(s):  
Cross Section ◽  
Expected Returns ◽  
Future Market ◽  
Cross Sectional ◽  
Risk Premiums ◽  
Econometric Methods ◽  
Out Of Sample ◽  
Macroeconomic Activity ◽  
Equity Premiums ◽  
Valuation Ratios

This article explores the information content of PEG ratios (price/earnings to growth ratios) for future aggregate returns and economic fundamentals. We first establish an analytic link between PEG ratios and time-varying expected returns of stocks. We then combine the link with empirical asset pricing models to extract market-wide information from cross-sectional PEG ratios. The resultant cross-section estimates of the risk premiums on stock betas serve as proxies for market-wide information. The proxies contain salient information about future market equity premiums and macroeconomic activity both in-sample and out-of-sample. Moreover, the proxies outperform aggregate PEG ratios and the cross-section beta-premium estimate based on conventional valuation ratios and retain incremental power in forecasting future market equity premiums. The results are robust to using various econometric methods for standard error adjustments.

Cross-Section of Expected Returns Based on Equity Duration

2019 ◽  
Vol 27 (3) ◽  
pp. 297-327
Author(s):  
Sungjeh Moon ◽  
Joonhyuk Song
Keyword(s):  
Cross Section ◽  
Risk Premium ◽  
Factor Model ◽  
Explanatory Power ◽  
Significant Risk ◽  
Significant Risk Factor ◽  
Expected Returns ◽  
Expected Return ◽  
Cross Sectional ◽  
Risk Premiums

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.

Tail Risk in the Cross Section of Alternative Risk Premium Strategies

2019 ◽  
Keyword(s):  
Cross Section ◽  
Risk Premium ◽  
Downside Risk ◽  
Empirical Literature ◽  
Direct Result ◽  
Risk Capital ◽  
Cross Sectional ◽  
Risk Premiums ◽  
Out Of Sample ◽  
The Cross

In this article, the authors attempt to get a better understanding of the cross-section of alternative risk premiums using a multi-asset version of the downside risk capital asset pricing model (CAPM). In line with the empirical literature, they find that the cross-section of realized returns is much better explained when using the downside CAPM, rather than relying on the traditional CAPM. However, in contrast to the empirical literature, the authors cannot always recover the required signs in their cross-sectional regressions. In particular, they find that taking on downside risk is not always systematically rewarded. This might be due to the limited availability of time series that essentially overweight the exceptional events of 2008 or a direct result of creating backtests with attractive in-sample features that are impossible to repeat out-of-sample.

The Cross Section of Expected Returns with MIDAS Betas

2011 ◽  
Vol 47 (1) ◽  
pp. 115-135 ◽  
Author(s):  
Mariano González ◽  
Juan Nave ◽  
Gonzalo Rubio
Keyword(s):  
Cross Section ◽  
Risk Premium ◽  
Market Risk ◽  
Ordinary Least Squares ◽  
Mixed Data ◽  
Expected Returns ◽  
Data Sampling ◽  
Cross Sectional ◽  
Market Risk Premium ◽  
The Cross

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.

scholarly journals Accounting Comparability and the Accuracy of Peer-Based Valuation Models

2015 ◽  
Vol 90 (6) ◽  
pp. 2571-2601 ◽  
Author(s):  
Steven Young ◽  
Yachang Zeng
Keyword(s):  
Cross Section ◽  
Foreign Firms ◽  
Future Market ◽  
Entire Cross Section ◽  
Cross Sectional ◽  
Cross Border ◽  
Multiple Method ◽  
Empirical Tests ◽  
Accounting Comparability ◽  
Sample Window

ABSTRACT We examine the link between enhanced accounting comparability and the valuation performance of pricing multiples. Using the warranted multiple method proposed by Bhojraj and Lee (2002), we demonstrate how enhanced accounting comparability leads to better peer-based valuation performance. Empirical tests using firms from 15 European Union (EU) countries over the period 1997–2011 (with comparable peers selected from the entire cross-section of foreign firms) document significant improvement in valuation performance measured as pricing accuracy, the ability of value estimates to explain cross-sectional variation in observed price, and the ability of the pricing multiple to predict future market-to-book multiples. Findings for a series of identification tests suggest that enhanced valuation performance is the consequence of improvements in the degree of cross-border accounting comparability that occurred during the sample window, and that a significant fraction of comparability gain operates through improved peer selection.

Strategic Informed Trades, Diversification, and Expected Returns

2015 ◽  
Vol 90 (5) ◽  
pp. 1811-1837 ◽  
Author(s):  
Judson Caskey ◽  
John S. Hughes ◽  
Jun Liu
Keyword(s):  
Private Information ◽  
Expected Returns ◽  
Cross Sectional ◽  
Risk Premiums ◽  
Factor Loadings ◽  
Large Economy ◽  
Strategic Trade ◽  
Concomitant Decrease ◽  
Informed Traders ◽  
The Impact

ABSTRACT We examine how strategic trade affects expected returns in a large economy. In our model, both a monopolist (strategic) informed trader and uninformed traders consider the impact of their demands on prices. In contrast to settings with price-taking traders, private information never eliminates a priced risk, and can lead to higher risk premiums. Also unlike settings with price-taking informed traders, risk premiums decrease in response to an increase in liquidity-motivated trades in diversified portfolios. These differing effects arise because a privately informed strategic trader conceals her trades by taking small positions relative to the magnitude of noise trades. Although prices partially reveal her information and reduce uncertainty, a concomitant decrease in her risk absorption dominates and leads to higher risk premiums. Similar to settings with price-taking traders, private information affects expected returns only via factor loadings and risk premiums on existing payoff risks—it introduces no new priced risks, and factor loadings (betas) explain all cross-sectional differences in expected returns.

Idiosyncratic Volatility and the Cross Section of Expected Returns

2008 ◽  
Vol 43 (1) ◽  
pp. 29-58 ◽  
Author(s):  
Turan G. Bali ◽  
Nusret Cakici
Keyword(s):  
Stock Returns ◽  
Cross Section ◽  
Idiosyncratic Volatility ◽  
Expected Returns ◽  
Cross Sectional ◽  
Monthly Data ◽  
Portfolio Returns ◽  
Expected Stock Returns ◽  
The Cross ◽  
Data Frequency

AbstractThis paper examines the cross-sectional relation between idiosyncratic volatility and expected stock returns. The results indicate that i) the data frequency used to estimate idiosyncratic volatility, ii) the weighting scheme used to compute average portfolio returns, iii) the breakpoints utilized to sort stocks into quintile portfolios, and iv) using a screen for size, price, and liquidity play critical roles in determining the existence and significance of a relation between idiosyncratic risk and the cross section of expected returns. Portfoliolevel analyses based on two different measures of idiosyncratic volatility (estimated using daily and monthly data), three weighting schemes (value-weighted, equal-weighted, inverse volatility-weighted), three breakpoints (CRSP, NYSE, equal market share), and two different samples (NYSE/AMEX/NASDAQ and NYSE) indicate that no robustly significant relation exists between idiosyncratic volatility and expected returns.

Factors That Fit the Time Series and Cross-Section of Stock Returns

2020 ◽  
Vol 33 (5) ◽  
pp. 2274-2325 ◽  
Author(s):  
Martin Lettau ◽  
Markus Pelger
Keyword(s):  
Time Series ◽  
Stock Returns ◽  
Cross Section ◽  
Principal Component ◽  
Expected Returns ◽  
Portfolio Returns ◽  
Pricing Errors ◽  
Out Of Sample ◽  
Pricing Error ◽  
Sharpe Ratios

Abstract We propose a new method for estimating latent asset pricing factors that fit the time series and cross-section of expected returns. Our estimator generalizes principal component analysis (PCA) by including a penalty on the pricing error in expected returns. Our approach finds weak factors with high Sharpe ratios that PCA cannot detect. We discover five factors with economic meaning that explain well the cross-section and time series of characteristic-sorted portfolio returns. The out-of-sample maximum Sharpe ratio of our factors is twice as large as with PCA with substantially smaller pricing errors. Our factors imply that a significant amount of characteristic information is redundant. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

International diversification benefits: an investigation from the perspective of Chinese investors

2013 ◽  
Vol 3 (3) ◽  
pp. 225-249 ◽  
Author(s):  
Chonghui Jiang ◽  
Yongkai Ma ◽  
Yunbi An
Keyword(s):  
Optimization Procedure ◽  
Optimal Strategies ◽  
International Diversification ◽  
Expected Returns ◽  
Domestic Investment ◽  
Foreign Markets ◽  
Content Type ◽  
Econometric Methods ◽  
Out Of Sample ◽  
Set Up

PurposeThe main purpose of this paper is to investigate whether Chinese investors can benefit from international diversification and where these benefits are to be found.Design/methodology/approachThis paper applies an expanding optimization procedure, which is different from the econometric methods or Monte Carlo simulations adopted in many empirical investigations in the literature. The authors' analysis is based on various realized portfolios that are set up at different dates in the sample period.FindingsBased on a stream of realized portfolios, the authors show that Chinese investors can gain substantially in terms of risk reduction as they venture into foreign markets, regardless of the region into which they choose to diversify and whether in‐sample or out‐of‐sample performance is evaluated. However, the optimal strategies under consideration cannot achieve higher out‐of‐sample expected returns and risk‐adjusted returns than does the domestic investment.Originality/valueIn contrast with those in the literature, the authors' analysis is based on the out‐of‐sample performance of a series of realized optimal portfolios. Their method can address time‐varying correlations that are ignored in most previous research. In addition, this method not only allows them to analyze sizes of diversification benefits but also enables them to examine the major characteristics of international portfolios to gauge the effectiveness of different diversification strategies.

Anchoring Credit Default Swap Spreads to Firm Fundamentals

2016 ◽  
Vol 51 (5) ◽  
pp. 1521-1543 ◽  
Author(s):  
Jennie Bai ◽  
Liuren Wu
Keyword(s):  
Explanatory Power ◽  
Credit Default Swap ◽  
Future Market ◽  
Cross Sectional ◽  
Credit Default ◽  
Out Of Sample ◽  
Shrinkage Method ◽  
Distance To Default ◽  
Bayesian Shrinkage ◽  
Default Swap

In this article, we examine the extent to which firm fundamentals can explain the cross-sectional variation in credit default swap (CDS) spreads. We construct a fundamental CDS valuation by combining the Merton distance-to-default measure with a long list of firm fundamentals via a Bayesian shrinkage method. Regressing CDS quotes against the fundamental valuation cross-sectionally generates an averageR2of 77%. The explanatory power is stable over time and robust in out-of-sample tests. Deviations between market quotes and the valuation predict future market movements. The results highlight the important role played by firm fundamentals in differentiating the credit spreads of different firms.

Competition, Markups, and Predictable Returns

2020 ◽  
Vol 33 (12) ◽  
pp. 5906-5939 ◽  
Author(s):  
Alexandre Corhay ◽  
Howard Kung ◽  
Lukas Schmid
Keyword(s):  
Time Series ◽  
Cross Section ◽  
Industry Concentration ◽  
Expected Returns ◽  
Oligopolistic Competition ◽  
Risk Premiums ◽  
Macroeconomic Volatility ◽  
Aggregate Risk ◽  
Secular Increase ◽  
Over Time

Abstract This paper jointly examines the link between competition and expected returns in the time series and in the cross-section. To this end, we build a general equilibrium model where markups vary because of firm entry with oligopolistic competition. When concentration is high, markups are more sensitive to entry risk. We find that higher markups are associated with higher expected returns over time and across industries, in line with the data. The model can also quantitatively account for the persistent rise in aggregate risk premiums and macroeconomic volatility associated with the secular increase trend industry concentration since the mid-1980s.

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