Variation In Stock Returns Research Articles

Valuation and Returns on Stock Return Volatility

ABSTRACT This paper provides an accounting-based valuation model that predicts that cross-sectional variation in firm-level returns to investments in both stock and stock return volatility are related to cross-sectional variation in firm-level fundamentals. The model predicts that expected stock returns have a positive quadratic relation with stock return variance and a negative quadratic relation with gains to trading in stock return variance. Consistent with these predictions, firms with high model-implied expected stock returns have high future stock return variance, and the relation is roughly quadratic. In contrast, firms with high expected stock returns have low future returns to trading in stock return variance through option contracts because these firms have high option-implied variance relative to future realized variance, i.e., low variance risk premia (VRP). The study provides a framework for using fundamentals for trading in individual stocks and options. JEL Classifications: G12; G14; G17.

Exploring Downside Co-Skewness and Upside Co-Kurtosis: Implications for Asset Pricing Models

This study examines how the investors' preferences for downside co-skewness and upside co-kurtosis may influence the asset pricing. We analyze data from 2000 to 2021, encompassing 2874 companies listed on the Shanghai Stock Exchange. Our methodology includes both time series and cross-sectional analyses, employing the Fama-Macbeth approach. Our findings reveal that the estimated values for downside co-skewness and upside co-kurtosis contribute to a significant premium, one that remains unexplained by traditional market factors such as size, value, profitability, and investment. Furthermore, when these higher-order co-moments are incorporated into the Capital Asset Pricing Model (CAPM), they demonstrate significant explanatory power in understanding the variations in stock returns. This augmented CAPM, with downside co-skewness and upside co-kurtosis, exhibits a superior goodness-of-fit compared to conventional asset pricing models. This suggests a crucial link between these higher-order risk factors and stock valuation, offering new insights into the complexities of investor behavior and market dynamics.

PENGARUH LEVERAGE KEUANGAN, LIKUIDITAS, EARNING PER SHARE DAN RETURN ON ASSET TERHADAP RETURN SAHAM PADA PERUSAHAAN MANUFAKTUR SEKTOR FOOD AND BEVERAGE DI BURSA EFEK INDONESIA

The aim of this research is to determine and explain the influence of financial leverage, liquidity, earnings per share (EPS), and return on assets (ROA) on stock returns in manufacturing companies in the food and beverage sector on the Indonesian Stock Exchange. either simultaneously or partially. The population in this study was 72 companies. The sampling technique used was purposive sampling technique to obtain a sample of 24 companies with a research period of 4 years. The analysis technique used is a multiple linear regression model with descriptive statistical tests, classical assumption tests, and hypothesis testing. The results of the t test research show that the Financial Leverage variable (Debt to Equity Ratio) has a negative and insignificant effect on stock returns, Liquidity (Current Ratio) has a positive and significant effect on stock returns, Earning Per Share (EPS) has a positive and significant effect on stock returns, Return on Assets (ROA) has a positive and significant effect on stock returns in Manufacturing Companies in the Food and Beverage Sector on the Indonesian Stock Exchange. And the results of the F test show that the independent variables, namely Financial Leverage (Debt to Equity Ratio), Liquidity (Current Ratio), Earning Per Share (EPS) and Return On Assets (ROA) have a significant effect on the dependent variable, namely Stock Returns in Food Sector Manufacturing Companies. and Beverage on the Indonesian Stock Exchange. The coefficient of determination is 40.3%, meaning that variations in Financial Leverage (Debt to Equity Ratio), Liquidity (Current Ratio), Earning Per Share (EPS) and Return on Assets (ROA) are able to explain variations in stock returns of 40.3%. Meanwhile, the remaining 59.7% is influenced by other variables.

COAALA: A Novel Approach to Understanding Extreme Stock–Bond Comovement

Abstract This article proposes a novel copula model to understand the dependence between extreme variations in stock and government bond returns. This model is used to introduce a tail-based extension of the safe haven concept, which we refer to as a tail risk dampener. Our findings reveal significant cross-country differences in stock–bond local tail dependence and tail risk dampening abilities. Some countries’ bond market can lessen the impact on portfolio returns of extreme negative stock returns, while for others no such negative tail comovement is found. This tail comovement is also not always aligned with global comovement between stocks and bonds. The article concludes that a comprehensive understanding of the comovement and the resulting diversification potential between stock and bond returns necessitates complementing global measures of dependence with local tail measures.

Realized semibetas in the Australian stock market

ABSTRACT This study examines the explanatory power of the CAPM and downside risk asset pricing models (the downside beta and the realized semibeta models) for the next-month firm-level cross-sectional stock return variation in the Australian stock market. We show that the CAPM beta, downside beta, semibeta BetaNP, and semibeta BetaNN negatively predict future stock returns, which is inconsistent with the findings in the original study by Bollerslev, Patton, and Quaedvlieg (2022). The BetaNN measures the individual stock movement in the same direction as the downward stock market, while BetaNP measures individual stock downward with the upward stock market. These findings are robust, not subsumed by conventional cross-sectional asset pricing factors, and consistent with the existing Australian downside risk study.

Corporate taxes, partisan politics, and stock returns

This paper studies the effect of partisan politics on stock returns in the U.S. by exploring different measures of corporate taxes. The results support the partisan politics cycle effect on equity returns. The cross-sectional analysis shows that the measures of corporate taxes impact stock returns but only when interacting with partisanship. Moreover, the time-series analysis shows that an investment strategy based on these results provides abnormal returns and that investors only partially anticipate them. The findings are consistent with a cash-flow-based explanation, in contrast with a risk-based explanation, and highlight the relevance of the political orientation of the governments in explaining the variation of stock returns.

Macroeconomic shocks and stock market returns

ABSTRACT We examine how structural macroeconomic disturbances impact US stock market returns. Our analysis uncovers a significant negative correlation between stock market returns and both systematic and monetary shocks. Our findings indicate that monetary policy shocks exert a substantial influence on US stock market returns. Forecast error variance decomposition of stock market returns shows systematic and monetary shocks explain 95% of stock return variance. An examination of industry-level stock returns indicates industries engaged in essential goods have greater resilience to shocks, indicating a reduced sensitivity to market fluctuations.

Impact of Automobile Companies Stock Returns on Indian Stock Market Indices with Special Reference to Nifty Fifty Index

The Nifty Fifty Index has a free-float market capitalization-weighted index.it represents the weighted average of the top 50 Indian companies listed on the National Stock Exchange ,and it is one of the main stock indices being used in India, besides the BSE Sensex of the Bombay Stock Exchange. The Nifty 50 index represents 62% of the free float market capitalization of the stocks listed in the NSE (NATIONAL STOCK EXCHANGE) as on September 30,2022.sectors ‘s stocks are performing more consistently and provide high return with high risk in (NSE)NATIONAL STOCK EXCHANGE ,these stocks are emerging as most reliable stock in capital market. Nifty Fifty Index also influenced by the variation in Automobile Industry which happened due to market fluctuation .The Automobile Sector has influenced by micro and macro indicators So in this, researcher found a relationship between Nifty Fifty Index and different selected Automobile companies by the application of some statistical tools like as regression to examine the impact of different companies stock return on Nifty fifty Index and correlation to check the relationship between Nifty Fifty and Automobile Sector Companies. And for this study data of 18 years from 1 January 2003 December 2022 has been taken. After the application of test this can be concluded that nifty fifty Index have impact of Automobile companies’ stock return variation on it and Nifty fifty index and Automobile companies are highly positively correlated with each other. At last it can be recommended that one variable can be used for forecasting another variable. So it can be concluded that development of economy and capital market has a relationship with performance of Automobile Industry in stock market and its return providing capacity. This study is going to be helpful for those investors who prefer to invest in Automobile Sector.

The 1929 crash of the New York stock exchange as a liquidity crisis

AbstractWhat caused the 1929 crash of the New York Stock Exchange? This paper quantitatively studies liquidity during the 1929 crash of the NYSE. I evidence that the crash represented a liquidity crisis due to the liquidation of brokers’ margin loans. Applying recent estimators of effective spreads and liquidity conditions from contemporary finance literature suggests a four‐fold increase in spreads during the crash at the aggregate level. At the individual stock level, quoted bid‐ask spreads suggest that liquidity explains one‐fifth of the variance in daily stock returns during the crash.

Testing multifactor asset pricing models in the stock market

lthough the superiority of Fama-French (FF) five-factor model in capturing the United States (US) equity returns, this model performs poorly in other stock markets (Fama & French, 2017). Using the monthly data of nearly 600 Vietnamese published firms from 2008 to 2022, the primary purpose of this paper is to analyze and examine the performance of four famous multifactor asset pricing models: the capital asset pricing model (CAPM), the Carhart four factor model, and the FF three-factor and five-factor models. We document the preference for the Carhart four-factor model over other models in producing a precise description to Vietnamese stock returns. The CAPM cannot give a reasonable explanation to the variation of Vietnamese stock returns, implying that market risk only accounts for a small proportion of the risk of holding Vietnamese stocks. Furthermore, adding the profitability and investment factors does not improve the explanatory power of asset pricing models in Vietnam, inconsistent with the result reported in the US stock market (Fama & French, 2015, 2020).

Explaining the time series of stock returns

Abstract: 
 Objective: In this paper, we test and compare the explanatory power of the two asset pricing models: the conventional CAPM and the empirical Fama and French three-factor model (1993) in the Moroccan stock market.
 Method: According to the Fama and French (1993) methodology, we analyze monthly data covering the sample period from July 2012 to June 2020.
 Results: The main findings support the superiority of the Fama and French three-factor model. The mimic risk factors pertained to the size and the book-to-market ratio have a significant role in explaining the Moroccan returns. Moreover, results show the existence of weak value effect but significant size effect. Despite the preeminence of the Fama and French model in describing the time-series of sock returns, the model leaves an unexplained fraction of the variation of Moroccan stock returns.
 Originality/Relevance: Our study is the first to compare the two popular models in the financial literature in the Moroccan stock which is an emerging market. Thus, our study corroborates others studies conducted in emerging markets and confirms the hypothesis that the characteristics of those markets impact the explanatory power of asset pricing models.

A two-dimensional innovation activity factor and stock pricing: Evidence from the Chinese stock market

This paper confirms that innovation activities can bring about excess stock returns in the Chinese stock market. Using monthly data on A-share stocks from May 2007 to December 2022, we find a significant innovation premium in the Chinese stock market by constructing a composite indicator that includes both innovation input and output. Then, we propose a six-factor model by incorporating the innovation factor into the Fama-French five-factor model. Time-series regressions show that the proposed model works well in explaining the variation of excess stock returns, and the innovation factor makes a significant marginal contribution to the explanatory power. Further tests show that the results remain robust for value-weighted returns, individual stocks, and different boards. The proposed model effectively reduces the root mean square errors compared to traditional pricing models. Our study adds significant evidence verifying the value of innovation in financial markets, and also provides practical implication for better enterprise innovation managment and public services.

Oil Shocks, Monetary Policy, and Stock Returns: A Case of Oil-based Economy

This paper investigates the dynamic effects of oil price shocks on the Saudi stock market. It differs from previous work by examining the role of monetary transmission of oil shocks to stock returns via interest rate and credit channels. A Structural Vector Autoregressive model (SVAR) is used to trace the impacts of the underlying shocks. The results provide robust evidence in favor of a positive relationship between oil price volatility and stock market returns, which is aligned with the prevailing view on the oil impact in net oil-exporting countries. Variance decomposition results indicate that oil shocks are the key source of fluctuations in stock markets as they explain more than 25% of stock return variations. On the other hand, a weak over-all effect of monetary policy is concluded by this study using the two monetary policy channels. Unlike interest rate, credit channel is found to be relatively effective in the monetary policy transmission to stock market. The response of stock returns showed a positive significant impact of credit shocks, but a negligible effect of interest rate shocks. The outcome of this paper is considered plausible in an oil-based economy with fixed-exchange rate regime.

Early career experience of executives and stock price informativeness

This paper examines the impact of early career experience through economic recessions of executives on stock price informativeness. We find that firms with a greater percentage of executives who start their careers during recessionary periods are positively associated with stock price informativeness, as measured by firm-specific stock return variation. Moreover, we document that the association is more pronounced for firms with poor external monitoring. These findings indicate that the early career experiences of executives significantly affect the extent to which stock prices convey firm-specific information, and that external monitoring and executives’ experiences during economic downturns exhibit a substitutive relationship. This paper points out the importance of considering the heterogeneous characteristic of executives to better understand corporate transparency.

How does ESG explain excess returns in emerging market? An Asset-Pricing Approach

Objective: Previous studies found several important risk factors for the capital market in explaining stock performance. However, most studies only consider conventional investment factors without considering sustainable ones. This study examines Environmental, Social, and Governance (ESG) performance’s effect as a risk factor in a multi-factor model. Design/Methods/Approach: This study employs secondary data from the company’s financial reports, annual reports, and Thomson Reuters ESG score data. The sample for this study were companies listed on the LQ45 index during the 2015-2019 period, which were selected using the purposive sampling method and produced a selection of 19 non-financial companies that met the criteria. Findings: The results show that ESG negatively affects 21 out of 30 portfolios, and the four-factor ESG model is better at explaining excess returns than the three-factor Fama-French model. Originality/Value: This study provides new insights by including ESG as a risk factor in the three-factor Fama-French model in explaining stock returns. The existence of the ESG variable allows us to identify whether sustainability is an essential determinant in explaining the average portfolio return. This study adds new insights, where using sustainability reports in the form of ESG can capture cross-sectional variations in stock returns, not only on market factors, size factors, and book-to-market factors. Practical/Policy implication: Given the established evidence that ESG factors can mitigate risk, investors are encouraged to thoroughly evaluate a company’s sustainability report to assess the efficacy of its ESG performance. For managers of companies, this serves as the foundation for developing strategies that will enhance the long-term profitability and sustainability of the organization.

Pricing cloud stocks: Evidence from China

AbstractUsing factor models, we examine two pricing issues of cloud stocks in China's stock market. In particular, we test whether the Fama and French factor models are useful to explain the stock prices of cloud stocks and whether there are abnormal returns unexplained by these models. Using the daily stock prices of 1670 cloud stocks from 2012 to 2022, we find that the factor models explain up to nearly 97% of the stock return variations of the cloud stocks, and mispricing. The results are robust to alternative measure of factors, outliers, sampling period and different approaches of factor modelling.

More Risk, More Information: How Passive Ownership Can Improve Informational Efficiency

Abstract We identify a novel economic mechanism through which passive ownership positively affects informational efficiency in the cross-section of firms. Passive investors’ inelastic demand lowers a firm’s cost-of-capital, inducing it to take more risk. The higher cash flow variance, in turn, incentivizes active investors to acquire more precise private information, pushing up price informativeness for firms with high passive ownership. High passive ownership also implies higher stock prices and higher stock-return variances. An increase in the aggregate size of passive investors amplifies these cross-sectional differences. We also document complementarities in firms’ real investment and investors’ information choices that can cause information crashes. Received May 31, 2020; editorial decision January 4, 2023 by Editor Holger Mueller. 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

Inclusion of debt claims in asset pricing models: Evidence from the CDS Index

Asset pricing theory suggests that the correct proxy for the market portfolio should contain both the debt and equity claims of the economy, whereas prevailing empirical studies fail to include the debt claim. Motived by the discrepancy between the theoretical and empirical models and the difficulty in constructing proxies, the study uses the Credit Default Swaps (CDS) market index as a proxy for the debt market and empirically tests its explanatory power in explaining stock return variations. Employing panel regression and Fama-MacBeth regression of all publicly traded U.S. companies from 2005 to 2020, the study finds a negative relationship between CDS index returns and stock returns. On average, a one standard deviation increase in CDS index return is associated with a 0.02% decrease in daily stock returns. Results of two-stage regressions show that the estimated systematic credit risk is positively priced in stock returns with similar economic magnitude as the well-documented beta risk. These results support asset pricing theories in the inclusion of debt claim and the risk-return tradeoff, while contradicting the credit risk puzzle documented in prior studies.

Idiosyncrasy as a Leading Indicator

AbstractDisequilibrating macro shocks affect different firms’ prospects differently, increasing idiosyncratic variation in forward-looking stock returns before affecting economic growth. Consistent with most such shocks from 1947 to 2020 enhancing productivity, increased idiosyncratic stock return variation forecasts next-quarter real GDP growth, industrial production growth, and consumption growth both in-sample and out-of-sample. These effects persist after controlling for other leading economic indicators.

Good Volatility, Bad Volatility, and VIX Futures Pricing: Evidence from the Decomposition of VIX

Realized semivariance, computed from intraday positive/negative squared returns, provides an accurate measure of the upside/downside variations of stock returns. This article investigates the role of realized semivariance in pricing the CBOE VIX and VIX futures, using a realized semivariance-based model. We obtain the closed-form pricing formula for the VIX index and VIX futures prices, and show that the new model provides superior pricing performance, both in-sample and out-of-sample. We further analytically derive the pricing formulas for the upside/downside components of the VIX (risk-neutral semivariance). Such a decomposition shows that the information gains from the conventional unsigned realized variance are concentrated on pricing the downside part of the VIX; the new realized semivariance-based model provides a larger and more balanced improvement for both the upside and downside components of the VIX. Our results provide strong evidence that the spread between upside/downside variance is the main driver of the asymmetry in return distributions.