Regime-switching in stock index and Treasury futures returns and measures of stock market stress

2009 ◽  
pp. n/a-n/a ◽  
Author(s):  
Naresh Bansal ◽  
Robert A. Connolly ◽  
Chris Stivers
Keyword(s):  
Stock Market ◽  
Regime Switching ◽  
Stock Index ◽  
Treasury Futures

META-ANALYSIS ON AMERICAN PRESIDENTIAL ELECTION - 2016 AND AMERICAN STOCK MARKET

2020 ◽  
Vol 38 (1) ◽  
Author(s):  
Farhan Ahmed ◽  
Salman Bahoo ◽  
Sohail Aslam ◽  
Muhammad Asif Qureshi
Keyword(s):  
Content Analysis ◽  
Stock Market ◽  
Event Study ◽  
Presidential Election ◽  
Republican Party ◽  
Stock Exchange ◽  
Meta Analysis ◽  
Composite Index ◽  
Stock Index ◽  
Political Event

This paper aims to analyze the efficient stock market hypothesis as responsive to American Presidential Election, 2016. The meta-analysis has been done combining content analysis and event study methodology. The all major newspapers, news channels, public polls, literature and five important indices as Dow Jones Industrial Average (DJIA), NASDAQ Stock Market Composit Indexe (NASDAQ-COMP), Standard & Poor's 500 Index (SPX-500), New York Stock Exchange Composite Index (NYSE-COMP) and Other U.S Indexes-Russell 2000 (RUT-2000) are critically examined and empirically analyzed. The findings from content analysis reflect that stunned winning of Mr Trump from Republican Party worked as shock for American stock market. From event study, findings confirmed that all the major indices reflected a decline on winning of Trump and losing of Ms. Clinton from Democratic. The results are supported empirically and practically through the political event like BREXIT that resulted in shock to Global stock index and loss of $2 Trillion.

scholarly journals The Regime-Switching Behaviour of Exchange Rates and Frontier Stock Market Prices in Sub-Saharan Africa

2021 ◽  
Vol 14 (3) ◽  
pp. 122
Author(s):  
Maud Korley ◽  
Evangelos Giouvris
Keyword(s):  
Stock Market ◽  
Stock Markets ◽  
Regime Switching ◽  
Markov Switching ◽  
Sub Saharan Africa ◽  
Var Model ◽  
High Volatility ◽  
Sub Saharan ◽  
The Relationship ◽  
Fx Market

Frontier markets have become increasingly investible, providing diversification opportunities; however, there is very little research (with conflicting results) on the relationship between Foreign Exchange (FX) and frontier stock markets. Understanding this relationship is important for both international investor and policymakers. The Markov-switching Vector Auto Regressive (VAR) model is used to examine the relationship between FX and frontier stock markets. There are two distinct regimes in both the frontier stock market and the FX market: a low-volatility and a high-volatility regime. In contrast with emerging markets characterised by “high volatility/low return”, frontier stock markets provide high (positive) returns in the high-volatility regime. The high-volatility regime is less persistent than the low-volatility regime, contrary to conventional wisdom. The Markov Switching VAR model indicates that the relationship between the FX market and the stock market is regime-dependent. Changes in the stock market have a significant impact on the FX market during both normal (calm) and crisis (turbulent) periods. However, the reverse effect is weak or nonexistent. The stock-oriented model is the prevalent model for Sub-Saharan African (SSA) countries. Irrespective of the regime, there is no relationship between the stock market and the FX market in Cote d’Ivoire. Our results are robust in model selection and degree of comovement.

scholarly journals Asymmetric Reactions of China’s Stock Market to Short-Term Interest Rates

2016 ◽  
Vol 8 (5) ◽  
pp. 260 ◽  
Author(s):  
Fang Fang ◽  
Weijia Dong ◽  
Xin Lv
Keyword(s):  
Stock Market ◽  
Interest Rates ◽  
Stock Returns ◽  
Regime Switching ◽  
Developed Countries ◽  
Short Term ◽  
Bear Market ◽  
Bull Market ◽  
Negative Effect ◽  
Markov Regime Switching Model

This paper investigates how China’s stock market reacts to short-term interest rates, as represented by the Shanghai Interbank Offered Rate (Shibor). We adopt the Markov Regime Switching model to divide China’s stock market into Medium, Bull and Bear market; and then examine how Shibor influences market returns and risk in different market regimes. We find that short-term interest rates have a significant negative effect on stock returns in Medium and Bull market, but could not affect stock returns in Bear market. In addition, different maturities of Shibor have different effects on stock returns. Furthermore, we find that the short-term interest rates have a negative effect on market risk in Bull market, but a positive effect in Bear market. Our findings show that China’s market is quite peculiar and distinctive from the U.S. market or other developed countries’ markets in many ways.

Do Indian stock market sentiments impact contemporaneous returns?

2018 ◽  
Vol 7 (3) ◽  
pp. 332-346
Author(s):  
Divya Aggarwal ◽  
Pitabas Mohanty
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Temporal Dynamics ◽  
Stock Exchange ◽  
Principal Component ◽  
Stock Index ◽  
Content Type ◽  
Investor Sentiments ◽  
Indian Stock Market ◽  
The Impact

Purpose The purpose of this paper is to analyse the impact of Indian investor sentiments on contemporaneous stock returns of Bombay Stock Exchange, National Stock Exchange and various sectoral indices in India by developing a sentiment index. Design/methodology/approach The study uses principal component analysis to develop a sentiment index as a proxy for Indian stock market sentiments over a time frame from April 1996 to January 2017. It uses an exploratory approach to identify relevant proxies in building a sentiment index using indirect market measures and macro variables of Indian and US markets. Findings The study finds that there is a significant positive correlation between the sentiment index and stock index returns. Sectors which are more dependent on institutional fund flows show a significant impact of the change in sentiments on their respective sectoral indices. Research limitations/implications The study has used data at a monthly frequency. Analysing higher frequency data can explain short-term temporal dynamics between sentiments and returns better. Further studies can be done to explore whether sentiments can be used to predict stock returns. Practical implications The results imply that one can develop profitable trading strategies by investing in sectors like metals and capital goods, which are more susceptible to generate positive returns when the sentiment index is high. Originality/value The study supplements the existing literature on the impact of investor sentiments on contemporaneous stock returns in the context of a developing market. It identifies relevant proxies of investor sentiments for the Indian stock market.

scholarly journals Output and Expected Returns in Central and Eastern European Countries

2020 ◽  
Vol 54 (4) ◽  
pp. 41
Author(s):  
Jerzy Gajdka ◽  
Piotr Pietraszewski
Keyword(s):  
Stock Market ◽  
Degrees Of Freedom ◽  
The United States ◽  
Theoretical Background ◽  
Small Sample ◽  
Stock Index ◽  
Stock Market Returns ◽  
Overlapping Data ◽  
State Of The Economy ◽  
Eastern European Countries

<p><strong>Theoretical background</strong>: Although some controversy remains, some aspects of the predictability of aggregate stock market returns in the United States and other industrialized countries appear to be relatively well established. Intertemporal asset pricing models based on the paradigm of investor rationality and market efficiency imply that various macro variables describing the state of the economy may forecast future returns on the aggregate stock market.</p><p><strong>Purpose of the article</strong>: The aim of the article is to present the results of a preliminary study which set out to determine whether the ratio of the stock index to the aggregate output in the economy and future rates of return in the aggregate stock markets in Central and Eastern Europe are significantly related to each other over different time horizons.</p><p><strong>Research methods</strong>: Heteroskedasticity and autocorrelation-consistent estimators with a small sample degrees of freedom adjustment were used in regressions to track overlapping data problem and small sample bias.</p><p><strong>Main findings</strong>: The analysis of the key market indices has shown that they explain much of the variation in the long-horizon future cumulative returns, as well as in cumulative excess returns.</p>

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