Using accounting earnings and aggregate economic indicators to estimate firm-level systematic risk

2021 ◽  
Author(s):  
Ray Ball ◽  
Gil Sadka ◽  
Ayung Tseng
Keyword(s):  
Systematic Risk ◽  
Economic Indicators ◽  
Firm Level ◽  
Accounting Earnings ◽  
Level Systematic

scholarly journals Heterogeneous Beliefs and Risk-Neutral Skewness

2012 ◽  
Vol 47 (4) ◽  
pp. 851-872 ◽  
Author(s):  
Geoffrey C. Friesen ◽  
Yi Zhang ◽  
Thomas S. Zorn
Keyword(s):  
Factor Analysis ◽  
Latent Variables ◽  
Stock Options ◽  
Systematic Risk ◽  
Heterogeneous Beliefs ◽  
Firm Level ◽  
Cross Sectional ◽  
Skewness Factor ◽  
Risk Neutral ◽  
Using Data

AbstractThis study tests whether belief differences affect the cross-sectional variation of risk-neutral skewness using data on firm-level stock options traded on the Chicago Board Options Exchange from 2003 to 2006. We find that stocks with greater belief differences have more negative skews, even after controlling for systematic risk and other firm-level variables known to affect skewness. Factor analysis identifies latent variables linked to risk and belief differences. The belief factor explains more variation in the risk-neutral skewness than the risk-based factor. Our results suggest that belief differences may be one of the unexplained firm-specific components affecting skewness.

Firm location and systematic risk: the real estate channel

2020 ◽  
Vol 19 (3) ◽  
pp. 387-409
Author(s):  
Xiang Gao ◽  
John Topuz
Keyword(s):  
Asset Pricing ◽  
Real Estate ◽  
Abnormal Returns ◽  
Systematic Risk ◽  
Local Economy ◽  
Firm Risk ◽  
Firm Level ◽  
Content Type ◽  
Land Availability ◽  
Real Estate Prices

Purpose This paper aims to investigate whether the cyclicality of local real estate prices affects the systematic risk of local firms using a geography-based measure of land availability as a quasi-exogenous proxy for real estate price cyclicality. Design/methodology/approach This paper uses the geography-based land availability measure as a proxy for the procyclicality of real estate prices and the location of a firm’s headquarters as a proxy for the location of its real estate assets. Four-factor asset pricing model (market, size, value and momentum factors) is used to examine whether firms headquartered in more land-constrained metropolitan statistical areas have higher systematic risks. Findings The results show that real estate prices are more procyclical in areas with lower land availability and firms headquartered in these areas have higher systematic risk. This effect is more pronounced for firms with higher real estate holdings as a ratio of their tangible assets. Moreover, there are no abnormal returns to trading strategies based on land availability, consistent with stock market betas reflecting this local real estate factor. Research limitations/implications This paper contributes to the literature on local asset pricing factors, the collateral role of firms’ real estate holdings and the co-movement of security prices of geographically close firms. Practical implications This paper has important managerial implications by showing that, when firms decide on the location of their buildings (e.g. headquarters building, manufacturing plant and retail outlet), the location’s influence on systematic risk should be part of the decision-making process. Originality/value This paper is among the first to use a geography-based measure of land availability to study whether the procyclicality of local real estate prices influences firm risk independent of the procyclicality of the local economy. Thus, both the portfolio formed and firm-level analyses provide a more direct evidence of the positive relation between the procyclicality of local real estate prices and firm risk.

scholarly journals Testing the Monthly Calendar Anomaly of Stock Returns in Pakistan: A Stochastic Dominance Approach

2019 ◽  
Vol 58 (1) ◽  
pp. 83-104 ◽  
Author(s):  
Abdul Rashid ◽  
Saba Kausar
Keyword(s):  
High Risk ◽  
Stock Returns ◽  
Stochastic Dominance ◽  
Stock Prices ◽  
Stock Exchange ◽  
Abnormal Returns ◽  
Systematic Risk ◽  
January Effect ◽  
Firm Level ◽  
High Beta

In this paper, we first examine the presence of monthly calendar anomaly in Pakistan Stock Exchange (PSX) using aggregate and firm-level monthly stock returns. Secondly, we classify the sample firms into low-beta, medium-beta, and high-beta firms to examine the monthly anomaly of stock returns for firms having different level of systematic risk. By considering the stochastic dominance approach (SDA), we employ the simulation based method of Barrett and Donald (2003) to identify the dominant month over the period from January 2000 to December 2017. We find significant evidence of the existence of the January effect in both firm and market stock returns. We also find that the January effect exists more prominently in both low-risk and high-risk firms categorised based on their systematic risk. On the other end of the continuum, for moderately risky firms, there is strong evidence of the presence of the December effect. One of possible explanations of the January effect is the yearend bonus received in the month of January. Such bonuses are generally used to purchase stocks, causing the bullish trend of stock prices in January. However, the evidence of the January anomaly in both low-beta and high-beta portfolios returns is puzzling, suggesting that investors may invest in both low- and high-risk stocks when enthusiastically investing in stock market. The findings of the paper suggest that investors may get abnormal returns by forecasting stock return patterns and designing their investment strategies by taking into account the January and December effects and the level of systematic risk associated with the firms. JEL Classification: G02, G12, G14 Keywords: Behavioural Finance, Stochastic Dominance Approach, Monthly Anomaly, January Effect, December Effect, TOY Anomaly, Abnormal Returns, KS Type Test, PSX

Industry Tax Planning and Stock Returns

2019 ◽  
Vol 94 (5) ◽  
pp. 219-246 ◽  
Author(s):  
Shane M. Heitzman ◽  
Maria Ogneva
Keyword(s):  
Stock Returns ◽  
Risk Premium ◽  
Systematic Risk ◽  
Tax Planning ◽  
Equity Returns ◽  
Firm Level ◽  
Industry Level ◽  
Planning Strategies

ABSTRACT We find evidence that equity returns increase with the propensity for tax planning in a firm's industry. This risk premium is imposed on all firms in the industry, even those that are less aggressive than their peers. The industry-based risk premium coexists with a firm-specific discount associated with active tax planning strategies that carry low systematic risk. The discount on tax planning at the firm level, however, is dwarfed by the premium on tax planning at the industry level, and is concentrated in industries that are less likely to attract scrutiny from the tax authority.

Predicting Market Betas

Paradigm ◽  
2018 ◽  
Vol 22 (2) ◽  
pp. 160-174
Author(s):  
T.G. Saji
Keyword(s):  
Predictive Power ◽  
Systematic Risk ◽  
Least Square ◽  
Firm Level ◽  
Indian Context ◽  
Level Data ◽  
Historical Relationship ◽  
Indian Stock Market ◽  
Returns On Investment ◽  
Empirical Methodology

This research, using firm-level data on NSE listed stocks for the period of 2008–2015, seeks empirical evidence on the significance of company characteristics in prediction of market betas in Indian context. The empirical methodology involves two-stage statistical procedure where an exploratory factor framework determines the historical relationship between firms’ fundamentals and systematic risk at first, and a generalized least square (GLS) technique of panel regression modelling estimates their predictive power thereafter. The search process discovers debt ratios and returns on investment predict market betas in Indian stock market. The study strongly suggests that the use of 1-year lagged historical betas along with the measures of financial leverage and overall profitability produces better predictions than the benchmark predictions solely based on historical betas. However, the analysts need to consider the industry differences in systematic risk to enhance the predictive power of the model.

scholarly journals The Systematic Risk and Leverage Effect in the Corporate Sector of Pakistan

2000 ◽  
Vol 39 (4II) ◽  
pp. 951-962
Author(s):  
Muhammad Nishat
Keyword(s):  
High Risk ◽  
Stock Returns ◽  
Risk Premium ◽  
Emerging Market ◽  
Systematic Risk ◽  
Institutional Development ◽  
Relative Price ◽  
Accounting Earnings ◽  
Stock Volatility ◽  
Market Portfolio

Poor corporate financing policies, non-competitive role of institutional development, a tendency towards the underpricing of initial offering resulted in high levered stocks in Karachi stock market (KSE). The KSE is termed as high risk high return emerging market where investors seek high risk premium Nishat (1999). The leverage is the most important factor which determines the firms risk premium [Zimmer (1990)]. Hamada (1969) and Bowman (1979) have demonstrated the theoretical relationship between leverage and systematic risk. Systematic risk of the leverage firm is equal to the without leverage systematic risk of the firm times one plus the leverage ratio (debt equity). Bowman (1979) established that systematic risk is directly related to leverage and the accounting beta (covariability of a firms’ accounting earnings with the accounting earnings of the market portfolio). One explanation of time-varying stock volatility is that leverage changes as the relative price of stocks and bonds change. Schwert (1989) demonstrated how a change in the leverage of the firm causes a change in the volatility of stock returns. Haugen and Wichern (1975) analysed the relationship between leverage and relative stability of stock value based on actuarial science1 and found that the duration of the debt is an important attribute in assessing the effect of leverage on stock volatility. If the leverage is persistent, or changing over time due to the issuance of additional debt, or if the firms are trying to return back the debt, this will change the risk of holding common stock. Kane, Marcus, and McDonald (1985) argued that a well defined metric for the advantage of debt financing is the difference in rates of return earned by optimally levered and unlevered firms, net of a return premium to compensate for potential bankruptcy costs.

Changing Prices, Accounting Earnings and Systematic Risk

1987 ◽  
Vol 14 (1) ◽  
pp. 1-25 ◽  
Author(s):  
Thakol Nunthirapakorn ◽  
James A. Millar
Keyword(s):  
Systematic Risk ◽  
Accounting Earnings

What is good and bad with the regulation supporting the SME’s credit access

2020 ◽  
Vol 28 (4) ◽  
pp. 569-586 ◽  
Author(s):  
Pietro Vozzella ◽  
Giampaolo Gabbi
Keyword(s):  
Systematic Risk ◽  
Capital Requirements ◽  
Basel Iii ◽  
Bank Capital ◽  
Large Firms ◽  
Regulatory Capital ◽  
Firm Level ◽  
Data Set ◽  
Content Type ◽  
Asset Correlation

Purpose This analysis asks whether regulatory capital requirements capture differences in systematic risk for large firms and micro-, small- and medium-sized enterprises (MSMEs). The authors explore whether bank capital regulations intended to support SMEs’ access to borrowing are effective. The purpose of this paper is to find out whether the regulatory design (particularly the estimate of asset correlations) positively affects the lending process to small and medium enterprises, compared to large corporates. Design/methodology/approach The authors investigate the appropriateness of bank capital requirements considering default risk of loans to MSMEs and distortions in capital charges between MSMEs and large firms under the Basel III framework. The authors compiled firm-level data to capture the proportions of MSMEs and large firms in Italy during 2000–2014. The data set is drawn from financial reports of 708,041 firms over 15 years. Unlike most empirical studies that correlate assets and defaults, this study assesses a firm’s creditworthiness not by agency ratings or by sampling banks but by a specific model to estimate one-year probabilities of default. Findings The authors found that asset correlations increase with firms’ size and that large firms face considerably greater systematic risk than MSMEs. However, the empirical values are much lower than regulatory values. Moreover, when the authors focused on the MSME segment, systematic risk is rather stable and varies significantly with turnover. This analysis showed that the regulatory supporting factor represents a valuable attempt to treat MSME loans more fairly with respect to banks’ capital requirements. Basel III-internal ratings-based approach results show that when the supporting factor is applied, the Risk-Weighted-Assets (RWA) differences between MSMEs and large firms increase. Research limitations/implications The implications of this research is that banking regulators to make MSMEs support more effective should review asset correlation estimation criteria, refining the fitting with empirical evidence. Practical implications The asset correlation parameter stipulated by the Basel framework is invariant with economic cycles, decreases with borrowers’ probability of default and increases with borrowers’ assets. The authors found that those relations do not hold. This way, asset correlations fall below parameters defined by regulatory formula, and SMEs’ credit risk could be overstated, resulting in a capital crunch. Originality/value The original contribution of this paper is to demonstrate that the gap between empirical and regulatory capital charge remains high. When the authors examined the Basel III-IRBA, results showed that when the supporting factor is applied, the RWA differences between MSMEs and large firms increase. This is particularly strong for loans to small- and medium-sized companies. Correctly calibrating asset correlations associated with the supporting factor eliminates regulatory distortions, reducing the gap in capital charges between loans to large corporate and MSMEs.

Pengaruh Faktor Fundamental, Risiko Sistematis Dan Ekonomi Makro Terhadap Return Saham Syariah Yang Tergabung Di Jakarta Islamic Index (JII) Pada Periode 2010 – 2014

2017 ◽  
Vol 24 (1) ◽  
pp. 54-70
Author(s):  
Hasanah Setyowati ◽  
Riyanti Ningsih
Keyword(s):  
Exchange Rate ◽  
Stock Exchange ◽  
Systematic Risk ◽  
Secondary Data ◽  
Analysis Model ◽  
Macroeconomic Factors ◽  
Return On Equity ◽  
Equity Ratio ◽  
Regression Techniques ◽  
The Exchange Rate

This study aimed to obtain empirical evidence on the influence of fundamental factors, systematic risk and macroeconomics on the returns Islamic stock of companies incorporated in the Jakarta Islamic Index in 2010-2014. The variables used were the fundamental factors that are proxied by Earning Per Share (EPS), Return on Equity (ROE), Debt to Equity Ratio (DER); Systematic risk is proxied by Beta Shares; macroeconomic factors is proxied by the inflation rate and the exchange rate. The samples of this study are the enterprises incorporated in Jakarta Islamic Index (JII) at the Indonesian Stock Exchange. The sampling method was using purposive sampling. There were 12 samples of Islamic stocks that meet the criteria to be used as samples. The analysis model used is multiple linear regression techniques and the type of data used is secondary data. The study found that all variables, which are Earning Per Share (EPS), Return on Equity (ROE), Debt to Equity Ratio (DER), Beta stock, inflation and the exchange rate do not significantly affect the return of sharia stock either simultaneously or partially.

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