Factor Models Under Firm Characteristics in Emerging Markets: A Study of Taiwan Stock Returns

2000 ◽  
Author(s):  
Anlin Chen ◽  
Eva Tu
Keyword(s):  
Emerging Markets ◽  
Stock Returns ◽  
Factor Models ◽  
Firm Characteristics

When the Market Went Viral: COVID-19, Stock Returns, and Firm Characteristics

2020 ◽  
Author(s):  
Avijit Bansal ◽  
Balagopal Gopalakrishnan ◽  
Joshy Jacob ◽  
Pranjal Srivastava
Keyword(s):  
Stock Returns ◽  
Firm Characteristics

scholarly journals Choosing Factors for the Vietnamese Stock Market

2021 ◽  
Vol 14 (3) ◽  
pp. 96
Author(s):  
Nina Ryan ◽  
Xinfeng Ruan ◽  
Jin E. Zhang ◽  
Jing A. Zhang
Keyword(s):  
Stock Returns ◽  
Factor Model ◽  
Five Factor Model ◽  
Explanatory Power ◽  
Factor Models ◽  
Marginal Contribution ◽  
Return On Equity ◽  
Factor Modeling ◽  
Three Factor ◽  
Better Than

In this paper, we test the applicability of different Fama–French (FF) factor models in Vietnam, we investigate the value factor redundancy and examine the choice of the profitability factor. Our empirical evidence shows that the FF five-factor model has more explanatory power than the FF three-factor model. The value factor remains important after the inclusion of profitability and investment factors. Operating profitability performs better than cash and return-on-equity (ROE) profitability as a proxy for the profitability factor in FF factor modeling. The value factor and operating profitability have the biggest marginal contribution to a maximum squared Sharpe ratio for the five-factor model factors, highlighting the value factor (HML) non-redundancy in describing stock returns in Vietnam.

A Transaction-Cost Perspective on the Multitude of Firm Characteristics

2020 ◽  
Vol 33 (5) ◽  
pp. 2180-2222 ◽  
Author(s):  
Victor DeMiguel ◽  
Alberto Martín-Utrera ◽  
Francisco J Nogales ◽  
Raman Uppal
Keyword(s):  
Transaction Costs ◽  
Stock Returns ◽  
Firm Characteristics ◽  
Pricing Models ◽  
Oxford University ◽  
Asset Pricing Models ◽  
Economic Rationale ◽  
Underlying Stocks ◽  
Different Characteristics ◽  
Published Paper

Abstract We investigate how transaction costs change the number of characteristics that are jointly significant for an investor’s optimal portfolio and, hence, how they change the dimension of the cross-section of stock returns. We find that transaction costs increase the number of significant characteristics from 6 to 15. The explanation is that, as we show theoretically and empirically, combining characteristics reduces transaction costs because the trades in the underlying stocks required to rebalance different characteristics often cancel out. Thus, transaction costs provide an economic rationale for considering a larger number of characteristics than that in prominent asset-pricing models. 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.

Conditional stock liquidity premium: is Warsaw stock exchange different?

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Szymon Stereńczak
Keyword(s):  
Emerging Markets ◽  
Stock Returns ◽  
Stock Exchange ◽  
Emerging Market ◽  
Market Liquidity ◽  
Investment Horizon ◽  
Liquidity Premium ◽  
Stock Liquidity ◽  
Content Type ◽  
Bear Market

Purpose This paper aims to empirically indicate the factors influencing stock liquidity premium (i.e. the relationship between liquidity and stock returns) in one of the leading European emerging markets, namely, the Polish one. Design/methodology/approach Various firms’ characteristics and market states are analysed as potentially affecting liquidity premiums in the Polish stock market. Stock returns are regressed on liquidity measures and panel models are used. Liquidity premium has been estimated in various subsamples. Findings The findings vividly contradict the common sense that liquidity premium raises during the periods of stress. Liquidity premium does not increase during bear markets, as investors lengthen the investment horizon when market liquidity decreases. Liquidity premium varies with the firm’s size, book-to-market value and stock risk, but these patterns seem to vanish during a bear market. Originality/value This is one of the first empirical papers considering conditional stock liquidity premium in an emerging market. Using a unique methodological design it is presented that liquidity premium in emerging markets behaves differently than in developed markets.

scholarly journals Systematic illiquidity, characteristic illiquidity, and stock returns: Timeseries analysis

2022 ◽  
Vol 9 (2) ◽  
pp. 72-80
Author(s):  
Soltane et al. ◽  
Keyword(s):  
Emerging Markets ◽  
Stock Returns ◽  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Systematic Risk ◽  
Timeseries Analysis ◽  
The Relationship

The objective of this research is to investigate the relationship between illiquidity and stock prices on the Tunisian stock exchange. While previous researches tended to focus on one form of illiquidity to examine this relationship, our study unifies three forms of illiquidity at the same time. Indeed, we simultaneously consider illiquidity as systematic risk, as a characteristic of the market, and as a characteristic of the stock. The aggregate illiquidity of the market is the average of individual stock illiquidity. The illiquidity risk is the sensitivity of the stock price to illiquidity shocks. Shocks of market illiquidity are estimated by the innovations in the expected market illiquidity. Results show that investors on the Tunisian stock exchange do not require higher returns when they expect a rise of market illiquidity, whereas investors on U.S markets are compensated for higher expected market illiquidity. In addition, shocks of market illiquidity provoke a fall in stock prices of small caps, while large caps are not sensitive to market illiquidity shocks. This differs slightly from results based on U.S. data where illiquidity shocks reduce all stock prices but most notably those of small caps. Robustness tests validate our findings. Our results are consistent with previous studies which reported that the “zero-return” ratio predicts significantly the return-illiquidity relationship on emerging markets.

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