scholarly journals Stock market returns, volatility, correlation and liquidity during the COVID-19 crisis: Evidence from the Markov switching approach

2020 ◽  
Vol 37 ◽  
pp. 101775 ◽  
Author(s):  
Małgorzata Just ◽  
Krzysztof Echaust
Keyword(s):  
Stock Market ◽  
Markov Switching ◽  
Market Returns ◽  
Stock Market Returns

Information updating and the bounce-back effect of stock market returns

2016 ◽  
Vol 6 (1) ◽  
pp. 96-107
Author(s):  
Sainan Huang ◽  
Songlin Zeng
Keyword(s):  
Stock Market ◽  
Markov Switching ◽  
Underlying Mechanism ◽  
Marginal Effect ◽  
Market Returns ◽  
Expected Return ◽  
Stock Market Returns ◽  
Content Type ◽  
Volatility Feedback ◽  
Bounce Back

Purpose – Bounce-back effect of stock market returns has been found empirically using different approaches. However, few paper explains the underlying mechanism. The paper aims to discuss these issues. Design/methodology/approach – This paper fills this gap and provides an explanation for bounce-back effect in stock market. Findings – This paper contributes to the literature in threefold. The authors contribute a formal economic model to rationalize the bounce-back effect of stock market returns. It is based on a model of stock return with volatility feedback under the assumption of Markov-Switching market volatility. Originality/value – The authors use the general Markov-Switching bounce-back model, developed by Bec et al. (2015), to provide empirical evidence for the existence of bounce-back effect in stock market. The empirical result shows “W” shape of bounce-back effect, which is exactly the same as predicted by the economic theoretical model. Finally, the authors propose an alternative approach to estimate the magnitude of volatility feedback and the marginal effect on the expected return of an anticipated high variance regime.

scholarly journals Modeling Stock Market Returns of BRICS with a Markov-Switching Dynamic Regression Model

2019 ◽  
Vol 11 (3(J)) ◽  
pp. 10-22
Author(s):  
Diteboho Xaba, ◽  
Ntebogang Dinah Moroke, ◽  
Ishmael Rapoo
Keyword(s):  
Stock Market ◽  
Preliminary Analysis ◽  
Markov Switching ◽  
Market Returns ◽  
Stock Market Returns ◽  
Brics Countries ◽  
Switching Dynamic ◽  
Using Data ◽  
Dynamic Regression Model ◽  
Best Fit

This article adopted a Markov-switching dynamic regression (MS-DR) model to estimate appropriate models for BRICS countries. The preliminary analysis was done using data from 01/1997 to 01/2017 and to study the movement of 5 stock market returns series. The study further determined if stock market returns exhibit nonlinear relationship or not. The purpose of the study is to measure the switch in returns between two regimes for the five stock market returns, and, secondly, to measure the duration of each regime for all the stock market returns under examination. The results proved the MS-DR model to be useful, with the best fit, to evaluate the characteristics of BRICS countries.

Relationship between Foreign Portfolio Investments (FPI), Domestic Institutional Investors, and Stock Market Returns in India

GIS Business ◽  
2017 ◽  
Vol 12 (6) ◽  
pp. 1-9
Author(s):  
Dhananjaya Kadanda ◽  
Krishna Raj
Keyword(s):  
Stock Market ◽  
Institutional Investors ◽  
Negative Relationship ◽  
Trading Strategies ◽  
Market Returns ◽  
Stock Market Returns ◽  
Foreign Portfolio Investment ◽  
Stock Market Return ◽  
Indian Stock Market ◽  
Feedback Trading

The present article attempts to understand the relationship between foreign portfolio investment (FPI), domestic institutional investors (DIIs), and stock market returns in India using high frequency data. The study analyses the trading strategies of FPIs, DIIs and its impact on the stock market return. We found that the trading strategies of FIIs and DIIs differ in Indian stock market. While FIIs follow positive feedback trading strategy, DIIs pursue the strategy of negative feedback trading which was more pronounced during the crisis. Further, there is negative relationship between FPI flows and DII flows. The results indicate the importance of developing strong domestic institutional investors to counteract the destabilising nature FIIs, particularly during turbulent times.

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