Bayesian analysis of the distribution of volatility of daily stock returns

PurposeThis study investigates the effects of the COVID-19 outbreak on daily stock returns for the six major affected WHO Regions, namely: Africa, Americas, Eastern Mediterranean, Europe, South-East Asia and Western Pacific.Design/methodology/approachThis study uses an event study method and panel-data regression models to examine the effect of the daily increase in the number of COVID-19 confirmed cases on daily stock returns from 1 March to 1 August 2020 for the leading stock market in major affected countries in the WHO regions.FindingsThe results reveal an adverse impact of the daily increasing number of COVID-19 cases on stock returns and stock markets fell quickly in response to the pandemic. The findings also suggest that negative market reaction was strong during the early stage of the outbreak between the 26th and 35th days after the initial confirmed cases. We further find that stock markets in the Western Pacific region experienced more negative abnormal returns as compared to other regions. The results also confirm that feelings of fear among investors turned out to be a mediator and a transmission channel for the effect of COVID-19 outbreak on the stock markets.Research limitations/implicationsThis study contributes to financial literature in two ways. First, we contribute to existing literature that has examined the effect of various catastrophes and crises on the stock markets Second, we contribute to the recent emerging literature that examines the impact of COVID-19 on financial markets.Practical implicationsThe study may have implications for policymakers to deal with this outbreak without triggering uncertainty in stock markets and reassure investors' confidence. The study may also be of interest to investors, managers, financial analysts by revealing how the stock markets quickly respond to outbreaks.Originality/valueThis study is the first study to examine the impact of the COVID-19 outbreak on the leading stock markets of the WHO regions.

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A Reexamination of Finite- and Infinite-Variance Distributions as Models of Daily Stock Returns

Journal of Business and Economic Statistics ◽

10.1080/07350015.1992.10509888 ◽

1992 ◽

Vol 10 (1) ◽

pp. 73-81 ◽

Cited By ~ 16

Author(s):

Alan L. Tucker

Keyword(s):

Stock Returns ◽

Infinite Variance ◽

Daily Stock Returns

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Margin requirements and Stock Market Volatility in Bangladesh

SDMIMD Journal of Management ◽

10.18311/sdmimd/2012/2741 ◽

2012 ◽

Vol 3 (2) ◽

pp. 29

Author(s):

A. F. M. Mainul Ahsan ◽

Mohammad Osman Gani ◽

Md. Bokhtiar Hasan

Keyword(s):

Stock Returns ◽

Stock Price ◽

Stock Exchange ◽

Price Volatility ◽

Market Volatility ◽

Stock Market Volatility ◽

Margin Requirements ◽

Margin Requirement ◽

Daily Stock Returns ◽

The Impact

Officially margin requirements in bourses in Bangladesh were initiated on April 28, 1999, to limit the amount of credit available for the purpose of buying stocks. The goal of this paper is to measure the impact of changing margin requirement on stock returns' volatility in Dhaka Stock Exchange (DSE). The impact of margin requirement on stock price volatility has been extensively studied with mixed and ambiguous results. Using daily stock returns, we found mixed evidence that SEC's margin requirements have significant impact on market volatility in DSE.

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Semi-monthly effect in stock returns: new evidence from Bombay Stock Exchange

Investment Management and Financial Innovations ◽

10.21511/imfi.14(3-1).2017.01 ◽

2017 ◽

Vol 14 (3) ◽

pp. 160-172 ◽

Cited By ~ 2

Author(s):

Shakila B. ◽

Prakash Pinto ◽

Iqbal Thonse Hawaldar

Keyword(s):

Health Care ◽

Stock Returns ◽

Stock Exchange ◽

Consumer Durables ◽

Empirical Results ◽

Significant Difference ◽

The Mean ◽

Daily Stock Returns ◽

New Evidence ◽

Care Index

Semi-monthly effect is a kind of calendar anomalies which is less explored in the financial literature. The main objective of this paper to investigate the presence of semi-monthly effect in selected sectoral indices of Bombay Stock Exchange (BSE). The study uses the daily stock returns of five sectoral indices viz S&amp;P BSE Auto Index, S&amp;P BSE Bankex, S&amp;P BSE Consumer Durables Index, S&amp;P BSE FMCG Index and S&amp;P BSE Health Care Index for the period of 10 years starting from 1st April 2007 to 31st March 2017. The data were analyzed using two approaches namely calendar days approach and trading days approach. To test the equality of mean returns for the two halves of the month, Mann-Whitney U test is used. The empirical results of the study did not provide any evidence for the presence of semi-monthly effect in the selected sectoral indices. Nevertheless, BSE Auto Index showed significant difference in the mean returns of first half and second half of trading month during the study period.

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Dispersion in Analysts' Earnings Forecasts as a Measure of Uncertainty

Journal of Accounting Auditing & Finance ◽

10.1177/0148558x9801300305 ◽

1998 ◽

Vol 13 (3) ◽

pp. 245-270 ◽

Cited By ~ 110

Author(s):

Orie E. Barron ◽

Pamela S. Stuerke

Keyword(s):

Stock Returns ◽

Earnings Forecasts ◽

Positive Association ◽

Cash Flows ◽

Financial Reports ◽

Forecast Dispersion ◽

Additional Information ◽

Price Reactions ◽

Daily Stock Returns ◽

Future Cash Flows

This study examines whether dispersion in analysts' earnings forecasts reflects uncertainty about firms' future economic performance. Prior research examining this issue has been inconclusive. These studies have concluded that forecast dispersion is likely to reflect factors other than uncertainty about future cash flows, such as uncertainty about the price irrelevant component of firms' financial reports (Daley et al. [1988]; Imhoff and Lobo [1992]). Abarbanell et al. (1995) argue that, if forecast dispersion after (i.e., conditional on) an earnings announcement reflects uncertainty about firms' future cash flows and this uncertainty causes investors to desire additional information, then dispersion will be positively associated with both (a) the level of demand for more information and (b) the magnitude of price reactions around the subsequent earnings release. In this study, we construct a measure of informational demand using the incidence of analyst forecast updating after dispersion is measured. We find a positive association between dispersion in earnings forecasts after an earnings release and this measure of informational demand. We also find a positive association between forecast dispersion and the magnitude of price reactions around subsequent earnings releases. These associations are most apparent when potentially stale (or outdated) forecasts are removed from measures of forecast dispersion. These associations also persist after controlling for other measures of uncertainty (e.g., beta and the variance of daily stock returns), consistent with dispersion in analysts' earnings forecasts serving as a useful indicator of uncertainty about the price relevant component of firms' future earnings.

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