scholarly journals Firm-specific News and Anomalies

2020 ◽  
Author(s):  
Hoang Van Hai ◽  
Phan Kim Tuan ◽  
Le The Phiet
Keyword(s):  
Factor Model ◽  
Idiosyncratic Volatility ◽  
Fresh Sample ◽  
Cross Sectional ◽  
Out Of Sample ◽  
Market Beta ◽  
Limited Arbitrage ◽  
Sample Test ◽  
Fama And French ◽  
Macro Finance

This study investigates the relation between idiosyncratic volatility and future returns around the firm-specific news announcements in the Korean stock market from July 1995 to June 2018. The excess returns of decile portfolios that are formed by sorting the stocks based on news and non-news idiosyncratic volatility measures. The Fama and French three-factor model is also examined to see whether systematic risk affects news and non-news idiosyncratic volatility profits. The pricing of our news and non-news idiosyncratic volatility are confirmed in the cross-sectional regression using the Fama and MacBeth method. Market beta, size, book to market, momentum, liquidity, and maximum return are controlled to determine robustness. Our empirical evidence suggests that the pricing of the non-news idiosyncratic volatility is more strongly negative compared to the news idiosyncratic volatility, which is contrary to the limited arbitrage explanation for the negative price of the idiosyncratic volatility. We find that the non-news idiosyncratic volatility has a robust negative relation to returns in non-January months. Macro-finance factors drive the conditioned on the missing risk factor hypothesis, the pricing of idiosyncratic volatility. This study contributes to a better understanding of the role of the conditional idiosyncratic volatility in asset pricing. As the Korean stocks provide a fresh sample, our non-U.S. investigation delivers a useful out-of-sample test on the pervasiveness of the non-news volatility effect across the emerging markets.

scholarly journals Is idiosyncratic risk ignored in asset pricing: Sri Lankan evidence?

2019 ◽  
Vol 5 (1) ◽  
Author(s):  
Moinak Maiti
Keyword(s):  
Factor Model ◽  
Stock Exchange ◽  
Investment Decision ◽  
Idiosyncratic Risk ◽  
Idiosyncratic Volatility ◽  
Sri Lankan ◽  
Cross Sectional ◽  
Volatility Risk ◽  
And Performance ◽  
Three Factor

AbstractThe present study focused on one of the important South Asian nations—Sri Lanka—to examine the role of idiosyncratic volatility in asset prices. A four-factor model with idiosyncratic volatility was designed for capturing the market, size, value and idiosyncratic risk yields better than Fama and French’s (J Financ Econ 33:3–56, 1993) three-factor model and performance of the model. Fama–MacBeth’s cross-sectional regression, residual graphs and GRS test all confirm the superiority of four-factor model over 2 three-factor models. For all MC- and IVOL-based portfolios, idiosyncratic volatility is negatively related to the expected returns and positively related for all PB-based portfolios. Finally, study findings confirm that there is a high importance for idiosyncratic volatility risk factor while considering investment decision in Colombo stock exchange. Hence, investor should compensate for holding such risk factors in the portfolio.

Dynamic Factors and Asset Pricing

2010 ◽  
Vol 45 (3) ◽  
pp. 707-737 ◽  
Author(s):  
Zhongzhi (Lawrence) He ◽  
Sahn-Wook Huh ◽  
Bong-Soo Lee
Keyword(s):  
Asset Pricing ◽  
Factor Model ◽  
Dynamic Factor ◽  
Pricing Model ◽  
Portfolio Returns ◽  
Dynamic Factors ◽  
Ex Ante ◽  
Out Of Sample ◽  
Competing Models ◽  
Fama And French

AbstractThis study develops an econometric model that incorporates features of price dynamics across assets as well as through time. With the dynamic factors extracted via the Kalman filter, we formulate an asset pricing model, termed the dynamic factor pricing model (DFPM). We then conduct asset pricing tests in the in-sample and out-of-sample contexts. Our analyses show that the ex ante factors are a key component in asset pricing and forecasting. By using the ex ante factors, the DFPM improves upon the explanatory and predictive power of other competing models, including unconditional and conditional versions of the Fama and French (1993) 3-factor model. In particular, the DFPM can explain and better forecast the momentum portfolio returns, which are mostly missed by alternative models.

scholarly journals MULTIFACTOR ASSET PRICING ANALYSIS OF THE BALTIC STOCK MARKET

Ekonomika ◽  
2010 ◽  
Vol 89 (4) ◽  
pp. 85-95 ◽  
Author(s):  
Raimonds Lieksnis
Keyword(s):  
Asset Pricing ◽  
Stock Market ◽  
Factor Model ◽  
Stock Market Index ◽  
Cross Sectional ◽  
Economic Significance ◽  
Market Index ◽  
Fama And French ◽  
The Baltic ◽  
Three Factor

This study investigates whether the Fama–French three-factor asset pricing model is applicable for explaining cross-sectional returns of stocks listed in the Baltic stock exchanges. Findings confirm the validity and economic significance of the three-factor model for the Baltic stock market: only investors who chose to invest in value stocks during the reference period achieved positive returns by matching or beating the returns of the stock market index. The monthly returns of 8 Latvian, 13 Estonian and 27 Lithuanian company stocks are analyzed for the time period from June 2002 till February 2010 by the methodology presented in Davis, Fama, and French (2000). Cross-sectional multivariate regression is calculated with stock portfolios representing the book-to-market and capitalization of companies as independent variables along with the stock market index. The study concludes that these three factors in the three-factor model are statistically significant, but, in line with earlier studies, regression intercepts are significantly different from zero and the model is not statistically confirmed.p>

Bayesian Analysis of Stochastic Betas

2005 ◽  
Vol 40 (4) ◽  
pp. 747-778 ◽  
Author(s):  
Gergana Jostova ◽  
Alexander Philipov
Keyword(s):  
Asset Pricing ◽  
Stock Returns ◽  
Idiosyncratic Volatility ◽  
Firm Level ◽  
Conditional Capm ◽  
Asset Pricing Anomalies ◽  
Proposed Model ◽  
Out Of Sample ◽  
Market Beta ◽  
Rolling Regression

AbstractWe propose a mean-reverting stochastic process for the market beta. In a simulation study, the proposed model generates significantly more precise beta estimates than GARCH betas, betas conditioned on aggregate or firm-level variables, and rolling regression betas, even when the true betas are generated based on these competing specifications. Our model significantly improves out-of-sample hedging effectiveness. In asset pricing tests, our model provides substantially stronger support for the conditional CAPM relative to competing beta models and helps resolve asset pricing anomalies such as the size, book-to-market, and idiosyncratic volatility effects in the cross section of stock returns.

scholarly journals Financial Distress premium in Pakistan’s Banking Stocks

2020 ◽  
Vol 13 (4) ◽  
pp. 127-146
Author(s):  
Fahim Ullah Khan ◽  
Ahmad Fraz ◽  
Asif Ali
Keyword(s):  
Stock Returns ◽  
Financial Distress ◽  
Banking Sector ◽  
Factor Model ◽  
Covariance Structure ◽  
Additional Risk Factor ◽  
Cross Sectional ◽  
Portfolio Returns ◽  
Fama And French ◽  
Model Approach

This paper examines the role of financial distress premium in explaining the stock returns of banking sector in Pakistan using the sample of twenty listed banks for the period of 2008 to 2018. The study has used two methodologies. Firstly, multifactor model approach of Fama and French (1992) is used to test the financial distress premium (additional risk factor) where portfolio returns are regressed with factor premiums in time series framework. Fama and French (1993) argue that the relationship between the stock return and the selected characteristics occur for that reason these characteristics are proxies for non-diversifiable factor risk. So, the characteristic based model approach of Huang (2009) is used in cross-sectional regression framework where stock returns are regressed with the characteristics. The results indicate that the proposed four factor model is applicable in the banking sector of Pakistan where financial distress premium is priced by the market. The characteristic based model shows insignificant impact of distress proxy of Altman Z score on the banking returns. It suggests that the cross-sectional returns are explained on the covariance structure of returns not the characteristics in the Pakistani banking stocks. The findings of the study suggests that the financial distress is important and consider while forming their portfolios.

scholarly journals Empirical test of Fama French three factor model and illiquidity premium in Indonesia

2015 ◽  
Vol 12 (2) ◽  
pp. 362-373 ◽  
Author(s):  
Citra Amanda ◽  
Zaäfri Ananto Husodo
Keyword(s):  
Time Series Data ◽  
Factor Model ◽  
Empirical Test ◽  
Series Data ◽  
Subprime Mortgage ◽  
Mortgage Crisis ◽  
Market Beta ◽  
Fama And French ◽  
Stock Portfolio ◽  
Three Factor

This study, using more than 10 years of monthly time-series data and controlling for the non-crisis as well as crisis period, investigates the existence of Fama-French three factors and liquidity to the excess return of stock portfolio in Indonesia. The results show that market beta is consistently positive and significant in each portfolios, when sorted by size-illiquidity and book-to-market (BM)-illiquidity. SMB could explain ILLIQ and vice versa, and in general the hypothesis in this research are accepted, also there are consistency in SMB when sorted by size-illiquidity and also BM-illiquidity which are two out of six are not significant. Subprime mortgage crisis statistically has no effect in all portfolios. The results supported Fama and French (1992, 1993) and the results of Lam and Tam (2011).

scholarly journals POST-MERGER RETURNS IN FRONTIER MARKETS, OR HOW WE LEARNED TO STOP WORRYING AND LOVE THE ACQUIRERS

2018 ◽  
Vol 19 (1) ◽  
pp. 96-109 ◽  
Author(s):  
Adam ZAREMBA ◽  
Adam SZYSZKA ◽  
Michał PŁOTNICKI ◽  
Przemysław GROBELNY
Keyword(s):  
Time Series ◽  
Mergers And Acquisitions ◽  
Portfolio Construction ◽  
Calendar Time ◽  
Cross Sectional ◽  
Developed Markets ◽  
Long Run ◽  
Out Of Sample ◽  
Sample Test ◽  
Portfolio Approach

This study presents the results from a comprehensive out-of-sample test of long-run returns following mergers and acquisitions (M&As). Using a unique sample from 23 frontier markets of almost 800 transactions conducted during the years 1992 to 2016, we implement both cross-sectional tests and time-series examinations based on a calendar-time portfolio approach. Contrary to evidence from developed markets, the M&As in these frontier markets do not lead to abnormal underperformance of acquirers, regardless of whether they paid for the acquisition with cash or stock. The results are robust to many considerations, including subsample and subperiod analysis, alternative formation periods, different portfolio construction approaches.

scholarly journals Best of the Best: A Comparison of Factor Models

2018 ◽  
Vol 54 (4) ◽  
pp. 1713-1758 ◽  
Author(s):  
Shamim Ahmed ◽  
Ziwen Bu ◽  
Daniel Tsvetanov
Keyword(s):  
Time Series ◽  
Model Comparison ◽  
Factor Model ◽  
Factor Models ◽  
Multiple Model ◽  
Third Place ◽  
Cross Sectional ◽  
Horse Race ◽  
Fama And French

We compare major factor models and find that the Stambaugh and Yuan (2016) 4-factor model is the overall winner in the time-series domain. The Hou, Xue, and Zhang (2015) q-factor model takes second place and the Fama and French (2015) 5-factor model and the Barillas and Shanken (2018) 6-factor model jointly take third place. The pairwise cross-sectional R2 and the multiple model comparison tests show that the Hou et al. (2015) q-factor model, the Fama and French (2015) 5-factor and 4-factor models, and the Barillas and Shanken (2018) 6-factor model take equal first place in the horse race.

The Influence of Internal and External Factors to the Indian Stock Market

2016 ◽  
Vol 3 (2) ◽  
pp. 52-59
Author(s):  
Ved Prakash Bansal
Keyword(s):  
Factor Model ◽  
Time Frame ◽  
Annual Data ◽  
Cross Sectional ◽  
Monthly Data ◽  
Average Return ◽  
Fama And French ◽  
Internal And External Factors ◽  
Indian Stock Market ◽  
Cross Sectional Average

This paper has been undertaken with the aim of testing the applicability of Fama and French three factor model (1993) in explaining cross-sectional average return for Stocks in Indian equity market for the time frame of 5 years from 2011-2016.The sample includes firms that traded on NIFTY 50 index from 2011-2016. Monthly data has been used to assess the performance of various stocks which have been categorized into big and small portfolios. Monthly data gives a better picture as compared to annual data when the time horizon for study is short.

scholarly journals Asset Pricing Behaviour with Dual-Beta in Case of Pakistani Stock Market

2011 ◽  
Vol 50 (2) ◽  
pp. 95-118 ◽  
Author(s):  
Attiya Y. Javid ◽  
Eatzaz Ahmad
Keyword(s):  
Factor Model ◽  
Stock Exchange ◽  
Jel Classification ◽  
Conditional Capm ◽  
Egarch Model ◽  
Market Beta ◽  
Fama And French ◽  
News Asymmetry ◽  
The Relationship ◽  
Three Factor

This study investigates the dynamics of beta by the asymmetric response of beta to bullish and bearish market environment on 50 stocks traded in Karachi Stock Exchange during 1993-2007. The results show that the betas increase (decrease) when the market is bullish (bearish). The results however suggest that investors receive a positive premium for accepting down-side risk, while a negative premium is associated with up-market beta. The results suggest that the conditional Fama and French three factor model has performed better than the conditional CAPM when news asymmetry was taken into account compared with the unconditional Fama and French three factor model and the unconditional dual-beta CAPM in explaining the relationship in beta and returns in case of Pakistani market. JEL classification: G12, G15 Keywords: Beta Instability, High Market Beta, Low Market Beta, EGARCH Model, News Asymmetry, Fama and French Three Factor Model

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