scholarly journals The COVID-19 Pandemic and Herding Behaviour: Evidence from India’s Stock Market

2020 ◽  
Vol 11 (3) ◽  
pp. 366-390
Author(s):  
Rosy Dhall ◽  
Bhanwar Singh
Keyword(s):  
Stock Market ◽  
Strong Evidence ◽  
Stock Exchange ◽  
Trading Strategies ◽  
The Novel ◽  
Sample Period ◽  
Full Sample ◽  
Bear Market ◽  
Industry Level ◽  
Outbreak Period

This article examines the herding behaviour at the industry level from national stock exchange (NSE). The novel contribution of this article is to examine the herding behaviour during the whole, pre- and post-coronavirus disease 2019 (COVID-19) pandemic outbreak period. We deployed the popular model proposed by Chang et al. (2000) to examine herd formation. Using daily stock closing prices of 191 firms, which constitute the 12 industry indices for the period from 1 January 2015 to 1 June 2020, the results for the full sample period (1 January 2015 to 1 June 2020) and before COVID-19 outbreak period (1 January 2015 to 29 January 2020) indicate the non-existence of herding formation at the industry level, but they do suggest a strong evidence of anti-herding behaviour. In addition, during the bull and bear market conditions, we found evidence of herding behaviour during the post-COVID-19 outbreak period (1 January 2020 to 1 June 2020). Further, the findings suggest that COVID-19 pandemic caused the formation of herding behaviour at the industry level. The study facilitates investors to devise their trading strategies in the regime of the COVID-19 pandemic.

scholarly journals Did the Stock Market Regime Change after the Inauguration of the New Cabinet in Japan?

2014 ◽  
Vol 2 (1) ◽  
pp. 98
Author(s):  
Chikashi Tsuji
Keyword(s):  
Stock Market ◽  
Stock Price ◽  
Price Index ◽  
Stock Exchange ◽  
Markov Switching ◽  
Sample Period ◽  
Full Sample ◽  
Markov Switching Models ◽  
Switching Models ◽  
Market Regime

This paper explored whether the Japanese stock market regime changed after the inauguration of the new Abe cabinet in Japan. Our application of Markov switching models to the Japanese stock price index returns and examinations of the price spreads in terms of the Japanese stock price indices derive the following evidence. First, (1) after the Abe cabinet started, regime of the Japanese stock markets changed. Second, (2) the regimes as to the JASDAQ Index and Tokyo Stock Exchange (TSE) Mothers Index more strongly and earlier changed than that of TOPIX. Third, (3) in our full sample period from January 4, 2011 to March 20, 2014, average positive price spreads over TOPIX were observed as to the JASDAQ, TSE Mothers, TOPIX Small, and TSE Second Section Index.

scholarly journals Does the Croatian Stock Market Have Seasonal Affective Disorder?

2021 ◽  
Vol 14 (2) ◽  
pp. 89
Author(s):  
Tihana Škrinjarić ◽  
Branka Marasović ◽  
Boško Šego
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Affective Disorder ◽  
Seasonal Affective Disorder ◽  
Stock Exchange ◽  
Trading Strategies ◽  
Future Research ◽  
Winter Solstice ◽  
Daily Data ◽  
Depressive Episodes

This paper explores mood anomalies, specifically the seasonal affective disorder (SAD) effect on the Zagreb Stock Exchange (ZSE). SAD is defined as a syndrome of depressive episodes in human behavior due to the changing of the season. Thus, the motive of this research is to gain better insights into the investors’ sentiment regarding SAD effects. The purpose of the research is to observe how investors’ sentiment affects the return and risk series on ZSE and if this could be exploitable. Using daily data on stock market return CROBEX for the period January 2010—February 2021, SAD effects are tested to explore if seasonal changes affect the stock returns and risk. Besides the SAD variable in the model, some control variables are included as well: Monday, tax, and COVID-19 effect. The results indicate that SAD effects exist on ZSE, even with controlling for mentioned effects; and asymmetries around winter solstice exist. Implications of such findings can be found in simulating trading strategies, which could incorporate such information to gain profits. Limitations of the research focus on one market, observing static parameters of the estimated models, and observing simple trading strategies. Thus, future research should focus on international diversification possibilities, time-varying models, and fully exploring the exploitation possibilities of such findings.

scholarly journals Diffusion Entropy Analysis: Stability of Indian Stock Market

2019 ◽  
Vol 8 (4) ◽  
pp. 9358-9362
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Global Financial Crisis ◽  
Stock Exchange ◽  
Significant Drop ◽  
Bear Market ◽  
Diffusion Entropy ◽  
The Usa ◽  
The Stability ◽  
Indian Stock Market

The large amount of available data of stock markets becomes very beneficial when it is transformed to valuable information. The analysis of this huge data is essential to extract out the useful information. In the present work, we employ the method of diffusion entropy to study time series of different indexes of Indian stock market. We analyze the stability of Nifty50 index of National Stock Exchange (NSE) India and SENSEX index of Bombay Stock Exchange (BSE), India in the vicinity of global financial crisis of 2008. We also apply the technique of diffusion entropy to analyze the stability of Dow Jones Industrial Average (DJIA) index of USA. We compare the results of Indian Stock market with the USA stock market (DJIA index). We conduct an empirical analysis of the stability of Nifty50, Sensex and DJIA indexes. We find significant drop in the value of diffusion entropy of Nifty50, Sensex and DJIA during the period of crisis. Both Indian and USA stock markets show bull market effects in the pre-crisis and post-crisis periods and bear market effect during the period of crisis. Our findings reveal that diffusion entropy technique can replicate the price fluctuations as well as critical events of the stock market.

COVID-19 pandemic sentiment and stock market behavior: evidence from an emerging market

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Byomakesh Debata ◽  
Kshitish Ghate ◽  
Jayashree Renganathan
Keyword(s):  
Stock Market ◽  
Emerging Market ◽  
Sample Period ◽  
Market Behavior ◽  
Market Returns ◽  
Full Sample ◽  
Content Type ◽  
Time Frequency ◽  
Search Volume ◽  
Google Search

PurposeThis study aims to examine the relationship between pandemic sentiment (PS) and stock market returns in an emerging order-driven stock market like India.Design/methodology/approachThis study uses nonlinear causality and wavelet coherence techniques to analyze the sentiment-returns nexus. The analysis is conducted on the full sample period from January to December 2020 and further extended to two subperiods from January to June and July to December to investigate whether the associations between sentiment and market returns persist even several months after the outbreak.FindingsThis study constructs two novel measures of PS: one using Google Search Volume Intensity and the other using Textual Analysis of newspaper headlines. The empirical findings suggest a high degree of interrelationship between PS and stock returns in all time-frequency domains across the full sample period. This interrelationship is found to be further heightened during the initial months of the crisis but reduces significantly during the later months. This could be because a considerable amount of uncertainty regarding the crisis is already accounted for and priced into the markets in the initial months.Originality/valueThe ongoing coronavirus pandemic has resulted in sharp volatility and frequent crashes in the global equity indices. This study is an endeavor to shed light on the ongoing debate on the COVID-19 pandemic, investors’ sentiment and stock market behavior.

scholarly journals Beta Coefficients of Polish Blue Chip Companies in the Period Of 2005–2011

2012 ◽  
Vol 12 (2) ◽  
pp. 90-102 ◽  
Author(s):  
Wiesław Dębski ◽  
Ewa Feder-Sempach
Keyword(s):  
Financial Markets ◽  
Strong Evidence ◽  
Stock Exchange ◽  
Good News ◽  
Market Model ◽  
Bear Market ◽  
The World ◽  
Warsaw Stock Exchange ◽  
Financial Decision ◽  
Blue Chip

Abstract Risk plays a significant role in various aspects of financial decision throughout the world financial markets. Beta parameter is one of the commonly used coefficient to estimate the systematic risk associated with stocks. Beta is mostly calculated using single index market model by W. Sharpe. This study examined the beta parameter under bull and bear market conditions on the Warsaw Stock Exchange (WSE). This paper analyses the beta responses for bad and good news for 44 stocks (14 stocks from the WIG20 index and 30 stocks from the mWIG40 index) over the last six years of trading at the WSE. Beta was calculated using monthly returns over the period 2005-2011, separately for the bull and the bear market. Our analysis finds strong evidence that beta is different in bull and bear market phase.

The Predictability and Profitability of Simple Moving Averages and Trading Range Breakout Rules in the Pakistan Stock Market

2020 ◽  
Vol 23 (01) ◽  
pp. 2050001
Author(s):  
Salma Khand ◽  
Vivake Anand ◽  
Mohammad Nadeem Qureshi
Keyword(s):  
Stock Market ◽  
Transaction Costs ◽  
Empirical Evidence ◽  
Predictive Power ◽  
Moving Averages ◽  
Sample Period ◽  
Excess Returns ◽  
Full Sample ◽  
Fixed Length

This paper inspects whether variable- and fixed-length moving averages (VMA and FMA), and trading range breakout (TRB) rules have prognostic capability and can earn profits superior to buy-and-hold plan, when applied on KSE-100 index of Pakistan stock market during the full sample period January 1, 1997 to December 31, 2013. Full sample results provided empirical evidence for VMA rule that it has significant predictive power and is able to generate profits superior to simple buy-and-hold plan even after inclusion of transaction costs. The highest mean buy returns yielded by VMA, FMA and TRB rules are seen in noncrises periods. The overall implication of this study is that traders in the Pakistan stock market can utilize this information to obtain excess returns on a regular basis.

scholarly journals Dynamic Analyses of Contagion Risk and Module Evolution on the SSE A-Shares Market Based on Minimum Information Entropy

Entropy ◽  
2021 ◽  
Vol 23 (4) ◽  
pp. 434
Author(s):  
Muzi Chen ◽  
Yuhang Wang ◽  
Boyao Wu ◽  
Difang Huang
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Exchange ◽  
Interactive Effect ◽  
Investment Strategies ◽  
Chinese Stock Market ◽  
Bear Market ◽  
Regulatory Policies ◽  
Aggregation Effect ◽  
Bear Markets

The interactive effect is significant in the Chinese stock market, exacerbating the abnormal market volatilities and risk contagion. Based on daily stock returns in the Shanghai Stock Exchange (SSE) A-shares, this paper divides the period between 2005 and 2018 into eight bull and bear market stages to investigate interactive patterns in the Chinese financial market. We employ the Least Absolute Shrinkage and Selection Operator (LASSO) method to construct the stock network, compare the heterogeneity of bull and bear markets, and further use the Map Equation method to analyse the evolution of modules in the SSE A-shares market. Empirical results show that (1) the connected effect is more significant in bear markets than bull markets and gives rise to abnormal volatilities in the stock market; (2) a system module can be found in the network during the first four stages, and the industry aggregation effect leads to module differentiation in the last four stages; (3) some stocks have leading effects on others throughout eight periods, and medium- and small-cap stocks with poor financial conditions are more likely to become risk sources, especially in bear markets. Our conclusions are beneficial to improving investment strategies and making regulatory policies.

scholarly journals Dynamic Return-Volume Relations in the Saudi Stock Market: Evidence from Quantiles Regressions

2015 ◽  
Vol 7 (11) ◽  
pp. 84
Author(s):  
Othman Alwagdani
Keyword(s):  
Stock Market ◽  
Trading Volume ◽  
Explanatory Power ◽  
Dependence Structure ◽  
Sample Period ◽  
Market Returns ◽  
Full Sample ◽  
Post Market ◽  
The Mean ◽  
Returns Forecasting

This paper examines the causality patterns between the lagged trading volume and returns of the Saudi stock market (TASI) for the period from2003:01 to April 2013:05, along with two consecutive sub-periods to account for pre- and post- market collapse of 2006. Using the quantile regression approach, the study finds that the return-volume relations are heterogeneous across quantiles with symmetric tendency across the mean for the full sample period. On the contrary, the study could not support the heterogeneous and symmetric effects for the first sub-sample period. The second sub-sample period is characterized by homogenous across quantiles with statistical evidence of symmetry. Thus, the study concludes that the dependence structure between the lagged volume and subsequent market returns seems to be randomly relying on the chosen period which makes volume unsuitable to be used as explanatory power for returns forecasting.

The Initial Analysis of the Share Suitability for the Inclusion into an Active Trading Strategy

2021 ◽  
pp. 80-89
Author(s):  
I. Tolkachev ◽  
Aleksandr Kotov
Keyword(s):  
Stock Market ◽  
Real Number ◽  
Stock Exchange ◽  
Trading Strategy ◽  
Trading Strategies ◽  
Present Stage ◽  
Russian Market ◽  
Initial Analysis ◽  
Trading Volumes ◽  
Russian Stock Market

The article lists the problems inherent to the Russian stock market at the present stage, special attention is paid to the liquidity issues. The authors evaluate the shares of all issuers listed on the Moscow Stock Exchange for the possibility of their inclusion in an active strategy based on average trading volumes. The article calculates the effectiveness of using the methods of average values in assessing the compliance of the selected instruments with the minimum required liquidity values. In the course of the work, the industry features of the Russian market are taken into account. The classifier of the Moscow Exchange is used to distribute issuers by industry. In parallel, the liquidity imbalance between the branches of the Russian stock market is being investigated. The conclusion is given about the real number of stock market instruments suitable for use in active trading strategies. The result of the study is a formed set of shares distributed by industry.

scholarly journals Day-of-the-week effect in Nigerian stock exchange: adaptive market hypothesis approach

2020 ◽  
Vol 17 (1) ◽  
pp. 97-108
Author(s):  
Anthony Olugbenga Adaramola ◽  
Kehinde Oladeji Adekanmbi
Keyword(s):  
Stock Market ◽  
Time Variation ◽  
Stock Exchange ◽  
Market Condition ◽  
Time Varying ◽  
Full Sample ◽  
Day Of The Week ◽  
The Mean ◽  
Autoregressive Conditional Heteroscedasticity ◽  
Over Time

The problems that this study informed are rooted in the uncertainty surrounding the presence of calendar anomalies in the Nigerian stock market and the need to ascertain whether calendar anomaly is changing with time and market condition according to the adaptive market hypothesis. This study evaluates how calendar anomaly behaves over time in the Nigerian stock market through the day-of-the-week effect since the latest trend is to examine time-changing anomaly. The general All Share Index returns of the Nigerian Stock Exchange between 2000 and 2017 are used in the analysis. Secondary daily index returns data for the period are sourced from the NSE Fact Book. The major estimation techniques employed in the study are the mean equations of the generalized autoregressive conditional heteroscedasticity (GARCH) and overlapping sub-period methodology. Moreover, returns are grouped into Up and Down periods depending on the periods that generate positive and negative returns, respectively. This study found out that Monday (MON), Tuesday (TUE), and Friday (FRI) effects are the only adaptive day-of-the-week effects. Thus, three (MON, TUE, FRI) day of the week effects found in the full sample are time-varying in subsample and are affected by market condition. On the whole, MON and Thursday (THUR) effects are found in Bull, while TUE and FRI are found in Bear. The investor must be careful to take time-variation into consideration; otherwise, they may incur a loss by thinking that the day-of-the-week effect is present every time.

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