On the Relation between EGARCH Idiosyncratic Volatility and Expected Stock Returns

2014 ◽  
Vol 49 (1) ◽  
pp. 271-296 ◽  
Author(s):  
Hui Guo ◽  
Haimanot Kassa ◽  
Michael F. Ferguson
Keyword(s):  
Stock Returns ◽  
Stock Return ◽  
Return Time ◽  
Idiosyncratic Volatility ◽  
Model Parameters ◽  
Risk Return ◽  
Look Ahead ◽  
Monthly Return ◽  
Expected Stock Returns ◽  
Estimation Of Model Parameters

AbstractA spurious positive relation between exponential generalized autoregressive conditional heteroskedasticity (EGARCH) estimates of expected monthtidiosyncratic volatility and monthtstock returns arises when the monthtreturn is included in estimation of model parameters. We illustrate via simulations that this look-ahead bias is problematic for empirically observed degrees of stock return skewness and typical monthly return time series lengths. Moreover, the empirical idiosyncratic risk-return relation becomes negligible when expected monthtidiosyncratic volatility is estimated using returns only up to montht− 1.

scholarly journals PENGARUH HUMAN CAPITAL (LABOR INCOME) TERHADAP EXPECTED STOCK RETURNS

2018 ◽  
Vol 12 (1) ◽  
pp. 58-79
Author(s):  
Caecilia Atmini Susilandari
Keyword(s):  
Human Capital ◽  
Asset Pricing ◽  
Stock Returns ◽  
Stock Return ◽  
Idiosyncratic Risk ◽  
Labor Income ◽  
Pricing Model ◽  
Asset Pricing Model ◽  
Industry Level ◽  
Expected Stock Returns

This research intended to analyse the use of premium as the proxy of human capital (labor income) in the industry level as one of the factors to measure the expected stock returns other than market, smb, hml, umdand liquidity variable that can be applied in Indonesia.The analysis coveres the human capital (labor income) in the industry level to cross section of stock return and the effect of human capital (labor income) to idiosyncratic risk in the asset pricing model. It usesincome percapita to measure the premium variabel in the period of 2001 – 2011 and 30 stocks portfolio chosen based on the biggest market capitalization value in six sector in the period of 2001 – 2011

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.

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.

Is There an Intertemporal Relation between Downside Risk and Expected Returns?

2009 ◽  
Vol 44 (4) ◽  
pp. 883-909 ◽  
Author(s):  
Turan G. Bali ◽  
K. Ozgur Demirtas ◽  
Haim Levy
Keyword(s):  
Stock Returns ◽  
Value At Risk ◽  
Risk Measures ◽  
Downside Risk ◽  
Expected Returns ◽  
Significant Relation ◽  
Macroeconomic Variables ◽  
Portfolio Returns ◽  
Risk Return ◽  
Expected Stock Returns

AbstractThis paper examines the intertemporal relation between downside risk and expected stock returns. Value at Risk (VaR), expected shortfall, and tail risk are used as measures of downside risk to determine the existence and significance of a risk-return tradeoff. We find a positive and significant relation between downside risk and the portfolio returns on NYSE/AMEX/Nasdaq stocks. VaR remains a superior measure of risk when compared with the traditional risk measures. These results are robust across different stock market indices, different measures of downside risk, loss probability levels, and after controlling for macroeconomic variables and volatility over different holding periods as originally proposed by Harrison and Zhang (1999).

scholarly journals Time-Varying Risk and the Relation between Idiosyncratic Risk and Stock Return

2021 ◽  
Vol 14 (9) ◽  
pp. 432
Author(s):  
Chengbo Fu
Keyword(s):  
Stock Returns ◽  
Stock Return ◽  
Idiosyncratic Risk ◽  
Point Of View ◽  
Time Varying ◽  
Total Risk ◽  
Risk Return ◽  
Long Run ◽  
Book To Market Ratio ◽  
The 1960S

This paper studies the historical time-varying dynamics of risk for individual stocks in the U.S. market. Total risk of an individual stock is decomposed into two components, systematic risk and idiosyncratic risk, and both components are studied separately. We start from the historical trend in the magnitude of risk and then turn to the relation between idiosyncratic risk and stock returns. The result shows that both components of risk for individual stocks are changing over time. They increased from the 1960s to the 1990s/2000s and then declined until today. This paper also studies the risk-return tradeoff by investigating the relation between idiosyncratic risk and stock return in the long run. Stocks are sorted into portfolios for analysis and the whole sample period is further decomposed into decades for subgroup analysis. Multivariable regressions are used to study this relation as we control for beta, size, book-to-market ratio, momentum and liquidity. From a historical point of view, we show that the relation between idiosyncratic risk and stock return is time-varying, and it did not exist in certain decades. The results indicate that the risk-return tradeoff also varied in history.

scholarly journals CHRISTIANO VOL. 7 ED 2

2019 ◽  
Author(s):  
Christiano Lombogia
Keyword(s):  
Linear Regression ◽  
Stock Returns ◽  
Stock Return ◽  
Stock Exchange ◽  
Cash Flows ◽  
Manufacturing Companies ◽  
Information Component ◽  
Partial Regression ◽  
Expected Stock Returns ◽  
Independent Variable

The purpose of this study is to provide empirical evidence to determine the influence of the information component of cash flows from operating, investing and financing activities as well as gross profit on expected stock return at manufacturing companies listed in Indonesia Stock Exchange periode 2012 - 2015. This study used 55 samples from 11 manufacturing companies in the textile and garment sub-sector listed in Indonesia Stock Exchange period 2012 - 2015 by using purposive sampling. The independent variable in this study are cash flow from operating activities, cash flows from investing activities, cash flows from financing activities and gross profit with expected stock returns as the dependent variable. The method used is the partial regression and multiple linear regression. The results showed that there is no significant influence between cash flows from operating, investing and financing activities as well as gross profit on expected stock return.

scholarly journals The Effect of Firm Profitability on Expected Stock Return in ASEAN Stock Market

2021 ◽  
Vol 25 (3) ◽  
pp. 642-655
Author(s):  
Nathania Clara ◽  
Sung Suk Kim
Keyword(s):  
Time Series ◽  
Stock Returns ◽  
Stock Return ◽  
Time Series Data ◽  
Factor Model ◽  
Total Sample ◽  
Series Data ◽  
Operating Profit ◽  
Firm Profitability ◽  
Expected Stock Returns

This research discusses and analyzes the company's profitability related to the company's stock return performance Profitability of the firm is related to the firm's performance of stock return. This study uses time-series data with a total sample of 1,010 firms from five countries in ASEAN (Indonesia, Thailand, Malaysia, Philippines, and Vietnam) from January 2010 to December 2019. Fama-French 3 factor model based on two different profitability showed that profitability positively affects the stock return in ASEAN markets. Fama-MacBeth's (1973) regression confirms that firm profitability scaled by operating profit-to-equity or operating profit-to-assets positively influences expected stock returns in the ASEAN market.DOI: 10.26905/jkdp.v25i3.5598

The Short-Run and Long-Run Components of Idiosyncratic Volatility and Stock Returns

2021 ◽  
Author(s):  
Yunting Liu
Keyword(s):  
Risk Factors ◽  
Stock Returns ◽  
Systematic Risk ◽  
Risk Exposure ◽  
Idiosyncratic Volatility ◽  
Growth Options ◽  
Long Run ◽  
Expected Stock Returns ◽  
Short Run ◽  
Systematic Risk Factors

To capture the dynamics of idiosyncratic volatility of stock returns over different horizons and investigate the relationship between idiosyncratic volatility and expected stock returns, this paper develops and estimates a parsimonious model of idiosyncratic volatility consisting of a short-run and a long-run component. The conditional short-run and long-run components are found to be positively and negatively related to expected stock returns, respectively. The positive relation between the short-run component and stock returns may be caused by investors requiring compensation for bearing idiosyncratic volatility risk when facing trading frictions and hold underdiversified portfolios. The negative relationship between the long-run component and stock returns may reflect the fact that stocks with high long-run idiosyncratic volatility are less exposed to systematic risk factors and, hence, earn lower returns. Moreover, the low-risk exposure of stocks characterized by high idiosyncratic volatility lends support to real-option-based mechanisms to explain this negative relation. In particular, the systematic risk of a firm with abundant growth options crucially depends upon the risk exposure of these options. The value of growth options could rise significantly because of convexity when the increase in idiosyncratic volatility occurs over long horizons. And growth options’ systematic risk could fall because the relative magnitude of their value in relation to systematic risk factors decreases. This paper was accepted by David Simchi-Levi, finance.

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