scholarly journals Volatility risk and stock return predictability on global financial crises

2017 ◽  
Vol 7 (1) ◽  
pp. 33-66 ◽  
Author(s):  
Worawuth Kongsilp ◽  
Cesario Mateus
Keyword(s):  
Stock Returns ◽  
Financial Crises ◽  
Stock Return ◽  
Return Predictability ◽  
Idiosyncratic Volatility ◽  
Stock Return Predictability ◽  
Volatility Risk ◽  
Content Type ◽  
Bull Markets ◽  
Recent Financial Crisis

Purpose The purpose of this paper is to investigate the role of volatility risk on stock return predictability specified on two global financial crises: the dot-com bubble and recent financial crisis. Design/methodology/approach Using a broad sample of stock options traded on the American Stock Exchange and the Chicago Board Options Exchange from January 2001 to December 2010, the effect of different idiosyncratic volatility forecasting measures are examined on future stock returns in four different periods (Bear and Bull markets). Findings First, the authors find clear and robust empirical evidence that the implied idiosyncratic volatility is the best stock return predictor for every sub-period both in Bear and Bull markets. Second, the cross-section firm-specific characteristics are important when it comes to stock returns forecasts, as the latter have mixed positive and negative effects on Bear and Bull markets. Third, the authors provide evidence that short selling constraints impact negatively on stock returns for only a Bull market and that liquidity is meaningless for both Bear and Bull markets after the recent financial crisis. Practical implications These results would be helpful to disclose more information on the best idiosyncratic volatility measure to be implemented in global financial crises. Originality/value This study empirically analyses the effect of different idiosyncratic volatility measures for a period that involves both the dotcom bubble and the recent financial crisis in four different periods (Bear and Bull markets) and contributes the existing literature on volatility measures, volatility risk and stock return predictability in global financial crises.

Measuring gambling activity in options market

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Bei Chen ◽  
Quan Gan
Keyword(s):  
Stock Returns ◽  
Stock Price ◽  
Stock Return ◽  
Return Predictability ◽  
Capital Gains ◽  
Gambling Activity ◽  
Cross Sectional ◽  
Content Type ◽  
Option Returns ◽  
Model Free

PurposeThis paper investigates how the gambling measure captures market bubble events, and how it predicts stock return and option return.Design/methodology/approachThis paper proposes a gambling activity measure by jointly considering open interest and moneyness of out-of-the-money (OTM) individual equity call options.FindingsThe new measure, CallMoney, captures excessive optimism during the dot-com bubble, the oil price bubble and the pre-GFC stock market bubble. CallMoney robustly and negatively predicts both OTM and at-the-money call option returns cross-sectionally. The option return predictability of CallMoney is stronger when stock price is further from its 52-weeks high, capital gains overhang is lower, and when information uncertainty of the underlying stock is higher. CallMoney also robustly and negatively predicts cross-sectional stock returns.Originality/valueThe gambling measure has the advantages of being economically intuitive, model-free, easy to measure. The measure performs more robustly than existing lottery measures with respect to option and stock return predictability and more reliably captures the overpricing of options and stocks. The work helps understanding the gambling related anomalies in equity option returns and stock returns.

On ethnicity of idiosyncratic risk and stock returns puzzle

Humanomics ◽  
2016 ◽  
Vol 32 (1) ◽  
pp. 48-68 ◽  
Author(s):  
Naseem Al Rahahleh ◽  
Iman Adeinat ◽  
Ishaq Bhatti
Keyword(s):  
Stock Returns ◽  
Financial Crises ◽  
Factor Model ◽  
Idiosyncratic Risk ◽  
Idiosyncratic Volatility ◽  
Content Type ◽  
Country Level ◽  
Expected Stock Returns ◽  
The Relationship ◽  
Three Factor

Purpose – The purpose of this paper is to understand the controversial issue of whether stock returns and idiosyncratic risks are related positively or negatively in case of Singaporean ethically poor screened stocks. Design/methodology/approach – To achieve the major objectives of this paper, it uses a multiple regression to explore the relationship between expected stock returns and idiosyncratic risk. The paper replicates the Lee and Faff’s (2009) three-factor capital asset-pricing model (CAPM) model in creating the six size/book-to-market portfolios from which it constructs the small minus big (SMB) and high minus low (HML) portfolios that capture the size and book-to-market equity factors, respectively. Findings – The basic finding of the paper is that there is a strong relation between idiosyncratic risk and the expected stock returns. In more details, we observe that the portfolio of stocks with the highest idiosyncratic volatility generates higher average returns (4.36 per cent) than the portfolio of stocks with the lowest idiosyncratic volatility (0.79 per cent) over the sample period. The paper observes that the stock’s idiosyncratic volatility is inversely correlated with the size of the underlying firm. Moreover, there is a pattern of relationships nearer the periods of financial crises: Asian and global financial crises. Research limitations/implications – This paper uses only a three-factor model on a single country. So it cannot be generalized to a multi-country level in the Association of Southeast Asian Nations (ASEAN) region, as the structure of each member country is different. Practical implications – This paper provides guidelines for policymakers and foreign investors in Singapore about the relationship. This research can also be extended to other ASEAN countries to understand this puzzle. Social implications – Ethically sensitive and faithful investors with small investment can benefit from the findings of this paper. Originality/value – The work reported in this paper is original, unpublished and is also not under consideration for publication elsewhere.

Predicting short-to-medium horizon returns

2021 ◽  
pp. 251-272
Author(s):  
Jesper Rangvid
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Return ◽  
Return Predictability ◽  
Yield Spread ◽  
Dividend Yield ◽  
Important Lesson ◽  
Stock Return Predictability ◽  
Long Run ◽  
Short Run

This chapter lays out what we know about stock return predictability on the short-to-medium horizon. It recognizes that most of the fluctuations in the stock market are unpredictable, but characterizes those that are. Another important lesson of this chapter is that stock markets are very volatile in the short run but appears to be less so in the long run. Paradoxically, this implies that it looks as if we can say a little more about the future movements in the stock market when dealing with the longer run (several years). From today until tomorrow, or next week, we can say very little. The chapter illustrates how stock returns are somewhat predictable by indicators such as the yield spread and the dividend yield.

scholarly journals Stock Return Predictability with Financial Ratios: An Empirical Study of Listed Manufacturing Companies in Sri Lanka

2018 ◽  
Vol 8 (4) ◽  
pp. 471
Author(s):  
Saradhadevi Anandasayanan
Keyword(s):  
Stock Returns ◽  
Stock Return ◽  
Predictive Power ◽  
Stock Exchange ◽  
Return Predictability ◽  
Financial Ratios ◽  
Series Data ◽  
Manufacturing Companies ◽  
Dividend Yield ◽  
Stock Return Predictability

This study attempts to investigate financial ratios’ predictive power, using the yearly time series data during the period of 2012-2017 for 33 listed manufacturing companies in Colombo Stock Exchange. This study specifically identifies the financial ratios, which are acknowledged as the predictors of stock returns in the share market, to test the stock return predictability. The financial ratios include the ratio of dividend yield, earnings per share, and earnings yield which are most useful and effective on stock return predictability in order to cover a wide range of predictions which have been used by all most all the previous researches. The stock return predictability is analyzed by regressing the dividend yield, earning per share and earning yield respectively on the yearly stock returns from 2012 to 2017. The results show high predictability power, since the R2-value is high and the coefficients are very significant and autocorrelation corrected standard errors. The results reveal that the three ratios hold a somehow predictive power regarding stock returns of the Listed Manufacturing Companies in Colombo Stock Exchange.

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