Idiosyncratic Volatility of Small Public Firms and Entrepreneurial Risk

2016 ◽  
Vol 06 (01) ◽  
pp. 1650002 ◽  
Author(s):  
David P. Brown ◽  
Miguel A. Ferreira
Keyword(s):  
Stock Returns ◽  
Small Firms ◽  
Idiosyncratic Risk ◽  
Business Owners ◽  
Idiosyncratic Volatility ◽  
Expected Returns ◽  
Liquidity Premium ◽  
Public Firms ◽  
Increasing Functions ◽  
Rule Out

The average idiosyncratic volatility of small public firms is a positive predictor of future stock returns. This is true for returns of both large and small firms. We consider several economic arguments for this result, including a liquidity premium, and we rule out all but one of them. Our evidence supports the entrepreneurial risk hypothesis, which states that small firms’ idiosyncratic risk is a proxy for risk faced by private business owners, who also happen to be significant shareholders of stock. Expected returns are increasing functions of entrepreneurial risk, and therefore returns are predictable using proxies for this risk, which include small-firm idiosyncratic volatility.

What Drove the Increase in Idiosyncratic Volatility during the Internet Boom?

2010 ◽  
Vol 45 (5) ◽  
pp. 1253-1278 ◽  
Author(s):  
Jason Fink ◽  
Kristin E. Fink ◽  
Gustavo Grullon ◽  
James P. Weston
Keyword(s):  
Investor Sentiment ◽  
Idiosyncratic Risk ◽  
Idiosyncratic Volatility ◽  
The Internet ◽  
Present Evidence ◽  
Public Firms ◽  
Specific Risk ◽  
Increasing Trend ◽  
Public Firm ◽  
Firm Maturity

AbstractAggregate idiosyncratic volatility spiked nearly fivefold during the Internet boom of the late 1990s, dwarfing in magnitude a moderately increasing trend. While some researchers argue that this rise in idiosyncratic risk was the result of changes in the characteristics of public firms, others argue that it was driven by the changing sentiment of irrational traders. We present evidence that the marketwide decline in maturity of the typical public firm can explain most of the increase in firm-specific risk during the Internet boom. Controlling for firm maturity, we find no evidence that investor sentiment drives idiosyncratic risk throughout the Internet boom.

scholarly journals Pricing Liquidity Risk with Heterogeneous Investment Horizons

2020 ◽  
pp. 1-36 ◽  
Author(s):  
Alessandro Beber ◽  
Joost Driessen ◽  
Anthony Neuberger ◽  
Patrick Tuijp
Keyword(s):  
Stock Returns ◽  
Risk Premium ◽  
Liquidity Risk ◽  
Asset Returns ◽  
Spillover Effects ◽  
Expected Returns ◽  
Pricing Model ◽  
Liquidity Premium ◽  
Asset Pricing Model ◽  
Illiquid Asset

We develop an asset pricing model with stochastic transaction costs and investors with heterogeneous horizons. Depending on their horizon, investors hold different sets of assets in equilibrium. This generates segmentation and spillover effects for expected returns, where the liquidity (risk) premium of illiquid assets is determined by investor horizons and the correlation between liquid and illiquid asset returns. We estimate our model for the cross-section of U.S. stock returns and find that it generates a good fit, mainly due to a combination of a substantial expected liquidity premium and segmentation effects, while the liquidity risk premium is small.

scholarly journals The idiosyncratic risk during the Covid-19 pandemic in Indonesia

2021 ◽  
Vol 18 (4) ◽  
pp. 57-66
Author(s):  
Winston Pontoh ◽  
Novi Swandari Budiarso
Keyword(s):  
Stock Returns ◽  
Stock Exchange ◽  
Systematic Risk ◽  
Stable Condition ◽  
Efficient Market Hypothesis ◽  
Idiosyncratic Risk ◽  
Fourth Period ◽  
Public Firms ◽  
Specific Risk ◽  
Close Relationship

Conservatism in the CAPM and L-CAPM standards often emphasizes systematic risk to explain the phenomenon of the risk-return relationship and ignores idiosyncratic risk with the assumption that the risk can be diversified. The effect of the Covid-19 outbreak raises the question of whether the idiosyncratic risk can still be ignored considering that the risk has a close relationship to firm-specific risk. This study sets a portfolio consisting of 177 active public firms in the Indonesia Stock Exchange before and after the Covid-19 pandemic. On portfolio set, idiosyncratic risk is estimated by the standard CAPM and L-CAPM in the observation range from January 2, 2019, to June 30, 2021. The results of the analysis show that L-CAPM and CAPM produce significantly different idiosyncratic risks. Empirical evidence shows that the highest firm-specific risk is in the third period and has a stable condition since the fourth period. This condition is confirmed by regression results that idiosyncratic risk together with systematic risk positively affects stock returns in the fourth period as suggested by the efficient market hypothesis. Uniquely, both systematic risk and idiosyncratic risk based on L-CAPM do not show a significant effect on stock returns in the fifth period, so it is a strong indication that liquidity is an important factor that must be considered in making investments.

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.

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.

Strategic Risk Shifting and the Idiosyncratic Volatility Puzzle: An Empirical Investigation

2020 ◽  
Author(s):  
Zhiyao Chen ◽  
Ilya A. Strebulaev ◽  
Yuhang Xing ◽  
Xiaoyan Zhang
Keyword(s):  
Stock Returns ◽  
Risk Premium ◽  
Empirical Investigation ◽  
Empirical Support ◽  
Idiosyncratic Risk ◽  
Market Risk ◽  
Idiosyncratic Volatility ◽  
Risk Shifting ◽  
Market Risk Premium ◽  
Strategic Risk

We find strong empirical support for the risk-shifting mechanism to account for the puzzling negative relation between idiosyncratic volatility and future stock returns. First, equity holders take on investments with high idiosyncratic risk when their firms are in distress and receive less monitoring from institutional holders as well as when the aggregate economy is in a bad state. Second, the strategically increased idiosyncratic volatility decreases equity betas, particularly in bad states when the market risk premium is high. The negative covariance between the equity beta and the market risk premium causes low and negative returns and alphas in firms with high idiosyncratic volatility. This paper was accepted by Tomasz Piskorski, finance.

Does idiosyncratic risk matter? Evidence from mergers and acquisitions

2019 ◽  
Vol 20 (4) ◽  
pp. 313-329
Author(s):  
Pascal Nguyen ◽  
Younes Ben Zaied ◽  
Thu Phuong Pham
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Prices ◽  
Firm Value ◽  
Stock Price ◽  
Negative Relationship ◽  
Idiosyncratic Risk ◽  
Idiosyncratic Volatility ◽  
Content Type ◽  
Acquisition Announcements

Purpose This paper aims to investigate whether idiosyncratic volatility is a priced risk factor in the Australian stock market. Design/methodology/approach The authors use the change in idiosyncratic volatility around acquisition announcements and the related stock price revaluation to test whether the idiosyncratic risk is priced. If the idiosyncratic risk is priced, increases (decreases) in idiosyncratic volatility should be associated with decreases (increases) in the acquirer’s stock price, as the latter’s future cash flows are discounted at a higher (lower) rate. The sample consists of 2,656 completed acquisitions by Australian listed firms over the period January 1990 to October 2014 for which deal value represents more than 5 per cent of the acquirer’s market value. Findings Increases (decreases) in idiosyncratic risk are associated with significant decreases (increases) in firm value. This negative relationship is robust to the presence of outliers; is unaffected by the incidence of the 2007-2008 financial crisis; holds using alternative measures of idiosyncratic risk; and is more significant after excluding the resources sector. Firms with a higher idiosyncratic risk prior to the acquisition, and firms avoiding stock to pay for the acquisition, experience a more significant stock price increase in relation to a decrease in idiosyncratic risk. Research limitations/implications Considering the small size of the Australian economy, investors may have less scope to mitigate idiosyncratic risk. As a consequence, idiosyncratic risk is associated with the positive excess return, contrary to what standard asset pricing theory assumes. The results support Merton’s (1987) hypothesis that investors are exposed to idiosyncratic risk due to imperfect portfolio diversification and receive compensation for bearing that risk. Practical implications The pricing of idiosyncratic risk may also explain why the Australian stock market has historically offered a high equity risk premium. A practical implication would be for international investors to take advantage of the diversification constraints of local investors to capture higher risk premiums and achieve superior returns. Originality/value While prior studies demonstrate that stocks with higher idiosyncratic risk are associated with higher subsequent returns, the authors show that an increase in idiosyncratic risk is associated with a decrease in stock prices using acquisition announcements as shocks to a firm’s idiosyncratic risk. In other words, the results arise from within-firm variations rather than from cross-sectional differences in stock returns.

scholarly journals Idiosyncratic Volatility and Cross-section of Stock Returns: Evidences from India

2016 ◽  
Vol 8 (1) ◽  
pp. 1
Author(s):  
Prashant Sharma ◽  
Brajesh Kumar
Keyword(s):  
Stock Returns ◽  
Cross Section ◽  
Empirical Relationship ◽  
Idiosyncratic Volatility ◽  
Expected Returns ◽  
Cross Sectional ◽  
The Cross ◽  
Highly Correlated ◽  
Indian Stock Market ◽  
The Relationship

<p>The present study examines the cross-sectional pricing ability of idiosyncratic volatility (IV) in Indian stock market and investigates the relationship amongst expected idiosyncratic volatility (EI), unexpected idiosyncratic volatility (UI), and cross-section of stocks returns. The study uses ARIMA (2, 0, 1) model to IV into EI and UI. The stocks returns are regressed on IV, EI and UI using Newey-West (1987) corrections, in order to investigate their empirical relationship.  The study finds that IV is positively related with stock returns. Further the IV significantly explains the cross-section of stock returns in Indian context. After imposing control over UI, as it is highly correlated with unexpected returns, the inter-temporal relationship between EI and expected returns turns out to be positive.</p>

scholarly journals Idiosyncratic risk and the cross-section of stock returns: the role of mean-reverting idiosyncratic volatility

2018 ◽  
Vol 294 (1-2) ◽  
pp. 419-452 ◽  
Author(s):  
Stanislav Bozhkov ◽  
Habin Lee ◽  
Uthayasankar Sivarajah ◽  
Stella Despoudi ◽  
Monomita Nandy
Keyword(s):  
Stock Returns ◽  
Risk Premium ◽  
Empirical Studies ◽  
Idiosyncratic Risk ◽  
Risk Tolerance ◽  
Idiosyncratic Volatility ◽  
Market Participants ◽  
The Mean ◽  
The Difference ◽  
Risk Metric

Abstract A key prediction of the Capital Asset Pricing Model (CAPM) is that idiosyncratic risk is not priced by investors because in the absence of frictions it can be fully diversified away. In the presence of constraints on diversification, refinements of the CAPM conclude that the part of idiosyncratic risk that is not diversified should be priced. Recent empirical studies yielded mixed evidence with some studies finding positive correlation between idiosyncratic risk and stock returns, while other studies reported none or even negative correlation. We examine whether idiosyncratic risk is priced by the stock market and what are the probable causes for the mixed evidence produced by other studies, using monthly data for the US market covering the period from 1980 until 2013. We find that one-period volatility forecasts are not significantly correlated with stock returns. The mean-reverting unconditional volatility, however, is a robust predictor of returns. Consistent with economic theory, the size of the premium depends on the degree of ‘knowledge’ of the security among market participants. In particular, the premium for Nasdaq-traded stocks is higher than that for NYSE and Amex stocks. We also find stronger correlation between idiosyncratic risk and returns during recessions, which may suggest interaction of risk premium with decreased risk tolerance or other investment considerations like flight to safety or liquidity requirements. We identify the difference between the correlations of the idiosyncratic volatility estimators used by other studies and the true risk metric the mean-reverting volatility as the likely cause for the mixed evidence produced by other studies. Our results are robust with respect to liquidity, momentum, return reversals, unadjusted price, liquidity, credit quality, omitted factors, and hold at daily frequency.

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