Standard Deviation Of Stock Returns Research Articles

Digitalization and predictability in the BRICS countries: what can be learned from information about the dynamics of stock prices

The study aims to identify the impact of digitalization on predictability in the BRICS countries’ stock markets. It is based on an analysis of the dynamics of stock markets volatility during the 1990-2023 period. The paper seeks to prove that the standard deviation of stock returns is determined by the volume of incoming new information, and higher volatility of returns indicates lower predictability. Digitalization may cause a reduction in uncertainty as it uses more data, improves their quality and develops data analysis methods. On the other hand, digitalization may lead to increased uncertainty due to the emergence and development of new industries, in which it is more difficult to predict cash flows in comparison with traditional industries because of increased complexity of supply chains and technologies. Based on quantitative analysis, it has been revealed that digitalization has led to a statistically significant decrease in the volatility of stock markets in the BRICS countries. In 2015-2023, relative to the period of the 1990s-2006, volatility in Russia decreased by 1 percentage point, in India by 0.4–0.5 percentage points, in China by 0.8 percentage points, in the UAE (Dubai) by 0.5-0.7 percentage points. Statistically insignificant decreases in volatility were observed in Brazil and South Africa. In the developed capital markets, the decrease in volatility between these two periods was also statistically insignificant, amounting to less than 0.1 percentage points. These findings may indicate that the processes of digitalization in the BRICS countries contributed to an accelerated increase in predictability thanks to an increase in the volume and quality of information and the emergence of new methods of analysis. At the same time, part of the decrease in volatility may be explained by further development and improved efficiency of capital markets. The joint influence of these effects on the complexity of forecasting turned out to be more significant than the impact of innovative technologies and new industries.

Impact of Board Gender Diversity and Derivatives Use on Firm Risk

In the wake of the recent global pandemic, COVID-19, companies need to maintain performance and manage firm risk. Companies should understand what can affect the firm's risk. This paper investigates the impact of board diversity and derivatives use on firm risk. The sample consists of 35 Indonesian LQ45 listed on the Indonesia Stock Exchange with an observation period of 2016–2020. The company's risk is proxied by the standard deviation of stock returns. This study uses a panel data regression model, namely fixed effect regression and random effect regression. The results of this study indicate that female board directorship is negatively associated with firm risk. It shows the significant role of female board directors in the company's board. Meanwhile, the use of derivatives has no significant effect on the firm risk. These results impact the development of literature that examines the influence of board diversity and the use of derivatives for hedging in Indonesia so that companies can determine company policies to reduce risk.

The Impact of Uncertainty in Macroeconomic Variables on Stock Returns in the USA

In this research paper, the impact of macroeconomic uncertainty on stock returns in the United States of America is examined. To measure this macroeconomic uncertainty, a survey of Consensus Economics with data ranging from 1989 until 2019 was employed. The survey consists of monthly forecasts for several macroeconomic variables for multiple countries. Four uncertainty measures were developed, based on the standard deviation, interquartile range, high-minus-low and an AR- and GARCH model. By performing linear regressions, a positive relationship between macroeconomic uncertainty and stock returns was identified for, on average, 13 out of 49 sectors, which is consistent with economic theory. Furthermore, the standard deviation of stock returns was regressed on macroeconomic uncertainty. A positive relationship was found for, on average, 41.7 out of 49 sectors. The results are discussed at a general level, at the level of the macroeconomic variables and at the sector level.

Construction and Simulation of Market Risk Warning Model Based on Deep Learning

The market is intricate and complicated, and the existing risk warning models have problems of low efficiency and poor generalization in predicting market risk data. Aiming at the problems, this study takes stock market risk warning as the research object and proposes a market risk warning model based on LSTM-VaR. 15 variables in the three categories of basic transaction data, statistical technical indicators, and moving interval data are selected as the stock market characteristic indicators, the LSTM(Long Short Term Memory) prediction model is constructed and the standard deviation of stock returns is predicted. Based on the predicted results, the probability distribution of return rate under the conditional distribution is obtained, and the VaR(Value at Risk) is calculated. 1% and 5% sample quantiles are taken as the warning line, and the LSTM-VaR warning model is obtained. The results show that the RMSE value of the model is the smallest, which is 0.013762, when the activation function of the LSTM-VaR model is the Leaky ReLu function, the training periods epochs are 10, the time window length N is 9, the batch size is 8, the number of neurons in each layer is 50, the dropout probability is 0.1, and adam is used as the optimizer. Compared with traditional prediction models such as MLP, the proposed model has better performance and can well realize market risk warning.

Corporate payout policy: does product market competition matter? Evidence from Australia

PurposeThe purpose of this paper is to examine the impact of product market competition on dividend payout and share repurchases in Australia in which a full dividend imputation system has been in place since 1987.Design/methodology/approachPanel data estimation with industry and year-fixed effects is employed to examine the role of industry competition on dividend payout and share repurchases. The paper uses a sample of ASX200 non-financial firms, including 4,272 observations over the period 1992–2015. To address the endogeneity problem, the authors utilize the event of Australia–United States Free Trade Agreement (AUSFTA), which became effective on 01 January 2005, and perform a difference-in-difference analysis.FindingsThe authors find that firms operating in competitive markets are likely to pay more dividends and repurchase more shares to reduce agency costs. The positive relation between industry competition and dividends is stronger among firms where the CEO and the Chairman of the Board are the same person and among firms with higher market-to-book ratio and higher standard deviation of stock returns. The study results are robust when the authors account for the impact of franking credit on dividend payment. In the difference-in-difference analysis, the authors find strong evidence of a casual relation that product competition drives changes in dividend policy.Practical implicationsThe findings are consistent with the notion that intense product market competition can mitigate agency conflicts between managers and shareholders and with the information signalling explanation of market competition. As such, regulators may want to introduce policies that encourage more market competition (e.g. market deregulation) to enhance market efficiency.Originality/valueThis study incorporates product market competition in explaining the firm payout policy.

Stock Volatility and the Great Depression

Abstract Stock return volatility during the Great Depression has been labeled a “volatility puzzle” because the standard deviation of stock returns was 2 to 3 times higher than any other period in American history. We investigate this puzzle using a new series of building permits and leverage. Our results suggest that volatility in building permit growth and financial leverage largely explain the high level of stock volatility during the Great Depression. Markets factored in the possibility of a forthcoming economic disaster. Received September 30, 2017; editorial decision August 27, 2018 by Editor Philip E. Strahan. 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

Theoretical decompositions of the cross-sectional dispersion of stock returns

The cross-sectional standard deviation of stock returns, or dispersion as it is frequently called, has attracted an increasing amount of attention in recent years. In the fund management industry, ...

The Impact of Web-Based Disclosure on the Capital Market Risk

This paper evaluates the Web-based voluntary disclosure practices in a sample of 180 French listed firms. The main objective is to investigate the impact of Internet-based disclosure on capital market risk. Three measures are used to present the capital market risk: total risk is measured by the standard deviation of stock returns, and systematic risk and idiosyncratic risk are the beta and standard deviation of the residuals generated from the market model, respectively. Following the method of Gajewski and Li, the Web-based disclosure is measured by an index of 40 items. The empirical results show that total risk and idiosyncratic risk vary inversely with the strength of Internet disclosure. This indicates that improved online disclosure can reduce investors’ uncertainty in the capital market. However, systematic risk is not influenced by the disclosure practice. Furthermore, capital concentration and board size are negatively associated with total and idiosyncratic risk. This study extends the prior research by investigating the influence of online disclosure on capital risk in the French stock market. I am particularly concerned about the technical features of Internet disclosure and its impact on capital risk. Online information is generally considered to be user-friendly, yet it is now necessary to analyze the effect of this convenience provided by Internet technology on the capital market.

Differences of Opinion and Price Reversals: Evidence from the Taiwan Stock Exchange

This paper examines the impact of differences of opinion (DIFOPN) on long-term price reversals using all of the common stocks listed on the Taiwan Stock Exchange over the period of 1990–2008. We choose winners and losers ranked by their cumulative abnormal returns (CARs) over the three-year formation period. The performance of the winners and losers is evaluated over the subsequent one-year holding periods. The empirical results indicate that DIFOPN are generally positively related to price reversals in the holding period for both winners and losers. When DIFOPN are measured by the financial analysts' forecasts of earnings per share and by the standard deviation of stock returns, the association between DIFOPN and price reversals is significantly different from zero. This relationship is robust when such control variables as market-to-book ratios, size, and beta are included.

PENILAIAN RISIKO TERHADAP PERLUASAN PENDAPATAN NON-BUNGA PERBANKAN DI INDONESIA

Growth in non-interest income in excess of interest income on banks in Indonesia became the motivation and background in this research. The condition is one of the bank’s efforts to stabilize revenue, or referred to diversify income. Research in the fi eld of bank income diversifi cation, especially in the developed countries give mixed results and contradictory, while in Indonesia is still relatively little is reviewing this phenomenon. Aims of the study, the fi rst to test the effect of non-interest income of the bank’s accounting and market risk. Second, examine the effect of non-interest income from fee based on accounting and market risk. The object of research is banking in Indonesia, with a sample of banks listed on the Indonesia Stock Exchange (BEI) from the year 2010 to 2012. The research data were mostly obtained from the Stock Exchange and the Bank of Indonesia Banking Directory (DPI). Non-interest income is proxied by two variables: net non-interest income and fee-based revenue. Risk is measured on the basis of accounting and the market, the risk is proxied by the variable accounting standard deviation of ROA, while the market risk variable is proxied by the standard deviation of stock returns.

Risk and return in the Chinese stock market: Does equity return dispersion proxy risk?

We examine whether equity return dispersion, measured by the cross-sectional standard deviation of stock returns, is systematically priced in the cross-section of stock returns in China. We find that return dispersion carries a positive price of risk even after controlling for market, size, book-to-market, and idiosyncratic volatility effects. We observe that stocks with greater sensitivities to equity return dispersion yield higher average returns. The finding of a significant return dispersion effect is robust to alternative portfolio sorts based on the well-established risk factors as well as industry portfolios. We argue that equity return dispersion captures the fundamental uncertainty associated with economic transitions and the flexibility of adaptability to fundamental economic restructuring that cannot be captured by market and firm level factors. To that end, return dispersion serves as a more meaningful proxy for risk in this emerging market that has experienced a significant economic transition during much of the sample period.

Tobin’s q, RoA, Diversification and Risk

This study aims to explain the link between corporate diversification, firm performance and risk. To test the research hypotheses, a sample of 63 companies listed in Tehran Stock Exchange over the period 2008-2012 was taken. We construct two models with Tobin’s q, RoA, Size, Debt, Growth and Standard deviation of stock returns. Analysis of the research models is based on panel(data) analysis. In these models the presence or absence of effects models (fixed or random) is reviewed and finally the best model is estimated. Inference is based on significant level or p-value, thus likely that any value or significance level of the test is less than 0.05 is rejected at the 95 percent confidence level. The results indicate that there is no significant relationship between diversification strategy, firm performance and risk.

Return Dispersion, Size, and the Cross-Section of Stock Returns - Evidence from the German Stock Market

This paper investigates whether return dispersion (RD), proxied by the cross-sectional standard deviation of stock returns, captures variation in returns across German stocks between 1989 and 2010. I address existing evidence based on U.S. equity data that RD may serve as a proxy economic state variable. In the out-of-sample test I confirm the countercyclical character of RD and show that it loads significantly negatively on future equal-weighted average market return. Sorting stocks by their absolute loadings on RD, I uncover the negative pattern in simple average portfolio returns. Further analysis indicates that the negative relationship between absolute loadings on RD and future returns is present only in micro stock subgroup. This finding casts doubt on the RD as proxy for state variable. Instead, it suggests its relation to mispricing and idiosyncratic risk components. As a secondary results I confirm the existence of reversed size effect in German stock market over the considered period.

The Impact of Internet-Based Disclosure on Capital Market Risk

This study examines the relationship between Internet-based disclosure and capital market risk. Based on prior research, an index of 49 items is developed to evaluate the level of Internet-based voluntary disclosure in France. Three measures are used to present the capital market risk: total risk is measured by the standard deviation of stock returns, and systematic risk and idiosyncratic risk are the beta and standard deviation of the residuals generated from the market model, respectively. A series of corporate governance factors are also introduced in order to analyze their effect on capital market risk. The results show that total risk and idiosyncratic risk vary inversely with the strength of Internet disclosure. This indicates that improved online disclosure can reduce investors’ uncertainty in the capital market. However, systematic risk is not influenced by the disclosure practice. Furthermore, capital concentration and board size are negatively associated with total and idiosyncratic risk.

A Comparison of Corporate Bankruptcy Models in Australia: The Merton vs. Accounting-based Models

Actuaries have long employed logistic type regression models in their analysis of renewal rates for property and casualty insurance products. This paper introduces an application of such methodology to the prediction of corporate bankruptcy. This is an example of a widerfield area of endeavor where actuaries have the potential to add real value. The results presented in the paper have implications for levels of risk-based capital to be held by insurers and other financial organizations. This paper examines how effectively the default likelihood indicator (DLI) estimated from the Merton model can predict corporate bankruptcy in Australia during 1990-2003. In addition, the performance of the Merton model and the three most popular bankruptcy models, i.e., Altman (1968), Zmijewski (1984), and Shumway (2001) are also compared. Our findings suggest that the Merton model is the most informative model in explaining corporate bankruptcy, followed by the Shumway model. Among accounting and market-based variables in bankruptcy models, only two variables, namely the ratio of total liabilities to total assets (TL/TA) and the idiosyncratic standard deviation of stock returns are most significant in predicting corporate bankruptcy. Finally, the results from our comparative study of bankruptcy prediction models suggest developing a multivariable logistic regression model which includes both financial ratios and Merton’s default likelihood indicator as predictors. We assess the predictive ability of this model by comparing 95% confidence intervals for the predicted probability of default for firms that default and firms that are not observed to default.

A Comparison of Corporate Bankruptcy Models in Australia: The Merton vs. Accounting-based Models

Actuaries have long employed logistic type regression models in their analysis of renewal rates for property and casualty insurance products. This paper introduces an application of such methodology to the prediction of corporate bankruptcy. This is an example of a widerfield area of endeavor where actuaries have the potential to add real value. The results presented in the paper have implications for levels of risk-based capital to be held by insurers and other financial organizations. This paper examines how effectively the default likelihood indicator (DLI) estimated from the Merton model can predict corporate bankruptcy in Australia during 1990-2003. In addition, the performance of the Merton model and the three most popular bankruptcy models, i.e., Altman (1968), Zmijewski (1984), and Shumway (2001) are also compared. Our findings suggest that the Merton model is the most informative model in explaining corporate bankruptcy, followed by the Shumway model. Among accounting and market-based variables in bankruptcy models, only two variables, namely the ratio of total liabilities to total assets (TL/TA) and the idiosyncratic standard deviation of stock returns are most significant in predicting corporate bankruptcy. Finally, the results from our comparative study of bankruptcy prediction models suggest developing a multivariable logistic regression model which includes both financial ratios and Merton’s default likelihood indicator as predictors. We assess the predictive ability of this model by comparing 95% confidence intervals for the predicted probability of default for firms that default and firms that are not observed to default.

Financial Implications of the Decision to Increase Reliance on Contingent Labor*

AbstractThis paper provides the first systematic examination of the financial implications associated with increased reliance on contingent (i.e., temporary/part‐time) labor. Using measures of performance from income statement and balance sheet data, and stock returns, we find that the adoption of this labor practice is associated with superior subsequent performance. Concurrently, no increase in systematic risk and standard deviation of stock returns is observed. The increase in performance with no concurrent increase in systematic risk and standard deviation of returns perhaps explains the increasing popularity of this labor practice.

Forecasting Bankruptcy More Accurately: A Simple Hazard Model

I argue that hazard models are more appropriate for forecasting bankruptcy than the single-period models used previously. Single-period bankruptcy models give biased and inconsistent probability estimates while hazard models produce consistent estimates. I describe a simple technique for estimating a discrete-time hazard model with a logit model estimation program. Applying my technique, I find that about half of the accounting ratios that have been used in previous models are not statistically significant bankruptcy predictors. Moreover, several market-driven variables are strongly related to bankruptcy probability, including market size, past stock returns, and the idiosyncratic standard deviation of stock returns. I propose a model that uses a combination of accounting ratios and market-driven variables to produce more accurate out-of-sample forecasts than alternative models.

Volatility Shifts in Stock Market Returns : A Look at Emerging Markets

The volatility or risk parameter, usually defined as the standard deviation of stock returns, forms the cornerstone of contemporary finance theories. Reliability of results obtained from various financial decision making models depends on the stability, finiteness, and accuracy of risk estimates. This paper by Broca examines the stability of this parameter using weekly market data over 1990-91 in respect of 17 emerging markets identified by the International Finance Corporation. Through an application of nonparametric test procedures, the study detects variance heterogeneity for 6 out of 17 markets. Though not pervasive, a review of major political-economic events over the sample period, with special reference to the Gulf crisis of August 1990, is attempted to partly validate empirical findings.

Simultaneous option prices and an implied risk-free rate of interest: A test of the Black-Scholes models

Two parameters in the Black-Scholes model, the risk-free rate of interest and standard deviation of stock returns, cannot be directly observed. Nevertheless, it is possible to simultaneously solve for the two parameters by using the prices of two different options written on the same security. If the Black-Scholes model is valid, then the implied interest rate from one repair of options should equal the implied interest rate from another pair of options for a given trading day. The analysis reexamines simultaneous option price data from a previous study using the implied interest rate test, and the results support the validity of the Black-Scholes model if we consider the bid/ask spread of option prices and that options are traded over discrete intervals.