Evidence on aggregate volatility risk premium for the French stock market

2019 ◽  
Vol 46 (1) ◽  
pp. 72-91
Author(s):  
Amal Zaghouani Chakroun ◽  
Dorra Mezzez Hmaied
Keyword(s):  
Risk Factor ◽  
Stock Market ◽  
Risk Premium ◽  
Factor Model ◽  
Excess Returns ◽  
Time Series Regression ◽  
Volatility Risk ◽  
Content Type ◽  
Volatility Risk Premium ◽  
Fama And French

Purpose The purpose of this paper is to examine alternative six- and seven-factor equity pricing models directed at capturing a new factor, aggregate volatility, in addition to market, size, book to market, profitability, investment premiums of the Fama and French (2015) and Fama and French’s (2018) aggregate volatility augmented model. Design/methodology/approach The models are tested using a time series regression and Fama and Macbeth’s (1973) methodology. Findings The authors show that both six- and seven-factor models best explain average excess returns on the French stock market. In fact, the authors outperform Fama and French’s (2018) model. The authors use sensitivity of aggregate volatility of a stock VCAC as a proxy to construct the aggregate volatility risk factor. The spanning tests suggest that Fama and French’s (1993, 2015, 2018) and Carhart’s (1997) models do not explain the aggregate volatility risk factor FVCAC. The results show that the FVCAC factor earns significant αs across the different multifactor models and even after controlling for the exposure to all the other in Fama and French’s (2018) model. The asset pricing tests show that it is systematically priced. In fact, the authors find a significant and negative (positive) relation between the aggregate volatility risk factor and the excess returns in the French stock market when it is rising (falling), in addition, periods with downward market movements tend to coincide with high volatility. Originality/value The authors contribute to the related literature in several ways. First, the authors test two new empirical six- and seven-factor model and the authors compare them to Fama and French’s (2018) model. Second, the authors give new evidence about the VCAC, using it for the first time to the authors’ knowledge, to construct a volatility risk premium.

scholarly journals Exploring the Initial Impact of COVID-19 Sentiment on US Stock Market Using Big Data

2020 ◽  
Vol 12 (16) ◽  
pp. 6648
Author(s):  
Hee Soo Lee
Keyword(s):  
Big Data ◽  
Stock Market ◽  
Factor Model ◽  
Time Lag ◽  
Google Trends ◽  
Investment Planning ◽  
Excess Returns ◽  
Time Series Regression ◽  
Strategic Investment ◽  
Daily News

This study explores the initial impact of COVID-19 sentiment on US stock market using big data. Using the Daily News Sentiment Index (DNSI) and Google Trends data on coronavirus-related searches, this study investigates the correlation between COVID-19 sentiment and 11 select sector indices of the Unites States (US) stock market over the period from 21st of January 2020 to 20th of May 2020. While extensive research on sentiment analysis for predicting stock market movement use tweeter data, not much has used DNSI or Google Trends data. In addition, this study examines whether changes in DNSI predict US industry returns differently by estimating the time series regression model with excess returns of industry as the dependent variable. The excess returns are obtained from the Fama-French three factor model. The results of this study offer a comprehensive view of the initial impact of COVID-19 sentiment on the US stock market by industry and furthermore suggests the strategic investment planning considering the time lag perspectives by visualizing changes in the correlation level by time lag differences.

Determinants of the Index Straddle Returns

2013 ◽  
Vol 21 (4) ◽  
pp. 411-434
Author(s):  
Byung Jin Kang
Keyword(s):  
Risk Premium ◽  
Trading Strategies ◽  
Excess Returns ◽  
Index Options ◽  
Volatility Risk ◽  
Volatility Risk Premium ◽  
Theoretical View

This paper investigates ATM zero-beta straddle (i.e., ZBS) returns, one of the most widely used volatility trading strategies, and then examines the determinants of them. First, from a point of theoretical view, we find that the determinants of the ZBS returns without rebalancing are different from those with rebalancing. This means that most previous studies overlooking the return characteristics by difference of rebalancing frequency could result in misleading implications. Next, from a point of empirical view, we find that the negative excess returns are also obtained by taking a long position in ZBS on the KOSPI 200 index options, as in most other markets. Even though these negative excess returns are not strongly significant, but they are found to be closely related to the volatility risk premium.

What explains the investment anomaly in the Chinese stock market?

2017 ◽  
Vol 8 (4) ◽  
pp. 495-520 ◽  
Author(s):  
Jieting Chen
Keyword(s):  
Risk Factor ◽  
Stock Market ◽  
Risk Premium ◽  
Regime Switching ◽  
Expected Returns ◽  
Chinese Stock Market ◽  
Content Type ◽  
Switching Model ◽  
Market Regimes ◽  
Markov Regime Switching Model

Purpose This paper aims to examine the Chinese investment anomaly and dissect it from a perspective of rational expectation framework. Design/methodology/approach Characteristic-based sorting and Fama–MacBeth two-stage cross-sectional regression are adopted to test the relationship between corporate investment and expected returns in both portfolio and individual stock levels. Under the framework of pricing kernels, an investment-based common risk factor is constructed to test the role of risk played in the negative investment-return relationship. Moreover, a Markov regime switching model is adopted to investigate the time-varying risk premium across market regimes. Findings Empirical results provide ample evidence showing that there is a negative relationship between investment and expected returns in the Chinese stock market. The new investment-based risk factor is found to capture the return differences across characteristic-based portfolios. In addition, risk premium of the new risk factor is not only statistically positive throughout the sample period, but also has an asymmetry that is higher during market downturn but lower under bull market. Research limitations/implications This paper merely tests the hypotheses derived from rational school. Practical implications Investment strategies based on characteristic-sorted portfolios should be adjusted to different market regimes. Originality/value First, this paper provides comprehensive empirical results by adopting different methodologies for investigating the investment anomaly in China. Second, an investment-based factor is constructed specifically for the Chinese stock market for the first time. Finally, this is the first paper to investigate the asymmetric risk premium across the Chinese bear and bull regimes by using a multivariate Markov regime switching model.

Is there persistence among non-professionals? Evidence from the Chicago Mercantile Exchange Group Trading Challenges

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Omid Sabbaghi ◽  
Min Xu
Keyword(s):  
Financial Markets ◽  
Factor Model ◽  
Five Factor Model ◽  
Statistical Significance ◽  
Performance Persistence ◽  
Excess Returns ◽  
Data Set ◽  
Content Type ◽  
Chicago Mercantile Exchange ◽  
Fama And French

PurposeThe study systematically investigates persistence in performance for simulated trading among non-professional traders in the futures market.Design/methodology/approachIn this study, the authors employ a novel data set from the Chicago Mercantile Exchange (CME) Group's Trading Challenges for years 2014 through 2018 and expand upon the empirical methodology of Malkiel (1995) through improved interval estimations in testing for persistence in performance. The authors implement Fama-MacBeth style regressions to understand the degree of persistence in performance and the extent to which non-professionals extrapolate from prior returns. They adjust returns for risk through the Fama and French (2015) five-factor model in understanding whether the sample of non-professionals is able to produce excess returns after expenses and whether there is evidence of excess gross to cover expenses.FindingsThe empirical analysis suggests strong evidence for performance persistence among non-professionals participating in the Preliminary Rounds. In the Championship Rounds, the authors find that the persistence effect becomes stronger in economic and statistical significance after accounting for expenses. The results suggest that competition and transaction costs help to distinguish between winners and losers. When conducting Fama-MacBeth style regressions, the authors present evidence that strongly supports the persistence effect and over-extrapolation. While the results of the multi-factor model analysis suggest that, after adjusting for risk, most teams are experiencing negative excess returns prior to expenses, the authors also uncover evidence of teams earning returns sufficient to cover their expenses.Originality/valueThe authors bridge the gap between the literature on performance persistence and the emerging literature on non-professionals in the financial markets. Data from the CME Group’s Trading Challenge provide a rich source in studying the beliefs of non-professionals, and this study is helpful for understanding how beliefs, operationalized in simulated trades, perform over short time horizons, thereby providing insights into the behavioral dynamics of the financial markets. The results provide new empirical evidence for performance persistence among non-professionals.

scholarly journals Stock Return Variations: The Validity of Systemic Risk, Size and Valuation as Explanatory Variables in the Lebanese Stock Market

2021 ◽  
Vol 12 (3) ◽  
pp. 135
Author(s):  
Jamil Chaya ◽  
Jamil A. Hammoud ◽  
Wael A. Saleh
Keyword(s):  
Stock Market ◽  
Risk Premium ◽  
Systemic Risk ◽  
Stock Return ◽  
Factor Model ◽  
Expected Returns ◽  
Investment Strategies ◽  
Explanatory Variables ◽  
Fama And French ◽  
High Level

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.

Dividend Risk Premia

2019 ◽  
Vol 55 (4) ◽  
pp. 1199-1242
Author(s):  
Georg Cejnek ◽  
Otto Randl
Keyword(s):  
United States ◽  
Risk Factor ◽  
United Kingdom ◽  
Time Variation ◽  
Factor Model ◽  
International Markets ◽  
Risk Premia ◽  
Excess Returns ◽  
Stock Indices ◽  
Bond Risk

This article studies time variation in the expected excess returns of traded claims on dividends, bonds, and stock indices for international markets. We introduce a novel dividend risk factor that complements the bond risk factor of Cochrane and Piazzesi (2005). By aggregating over 4 regions (United States, United Kingdom, Eurozone, and Japan), we create global dividend and bond factors. Our global 2-factor model captures the excess returns of most Morgan Stanley Capital International (MSCI) country indices, as well as a variety of other test assets. Our findings highlight the value of the information contained in dividend and bond forward curves and suggest substantial comovement in international risk premia.

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