HARA utility maximization in a Markov-switching bond–stock market

2017 ◽  
Vol 17 (11) ◽  
pp. 1715-1733 ◽  
Author(s):  
M. Escobar ◽  
D. Neykova ◽  
R. Zagst
Keyword(s):  
Stock Market ◽  
Utility Maximization ◽  
Markov Switching ◽  
Hara Utility

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 A multivariate regime-switching GARCH model with an application to global stock market and real estate equity returns

2018 ◽  
Vol 22 (3) ◽  
Author(s):  
Markus Haas ◽  
Ji-Chun Liu
Keyword(s):  
Real Estate ◽  
Stock Market ◽  
Regime Switching ◽  
Markov Switching ◽  
Garch Model ◽  
Equity Returns ◽  
Out Of Sample ◽  
High Volatility ◽  
Simple Recursion ◽  
Global Stock

AbstractWe consider a multivariate Markov-switching GARCH model which allows for regime-specific volatility dynamics, leverage effects, and correlation structures. Conditions for stationarity and expressions for the moments of the process are derived. A Lagrange Multiplier test against misspecification of the within-regime correlation dynamics is proposed, and a simple recursion for multi-step-ahead conditional covariance matrices is deduced. We use this methodology to model the dynamics of the joint distribution of global stock market and real estate equity returns. The empirical analysis highlights the importance of the conditional distribution in Markov-switching time series models. Specifications with Student’stinnovations dominate their Gaussian counterparts both in- and out-of-sample. The dominating specification appears to be a two-regime Student’stprocess with correlations which are higher in the turbulent (high-volatility) regime.

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 Detection of structural regimes and analyzing the impact of crude oil market on Canadian stock market: Markov regime-switching approach

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammadreza Mahmoudi ◽  
Hana Ghaneei
Keyword(s):  
Stock Market ◽  
Crude Oil ◽  
Stock Return ◽  
Stock Exchange ◽  
Markov Switching ◽  
Stock Index ◽  
Var Model ◽  
Content Type ◽  
Oil Market ◽  
The Impact

Purpose This study aims to analyze the impact of the crude oil market on the Toronto Stock Exchange Index (TSX). Design/methodology/approach The focus is on detecting nonlinear relationship based on monthly data from 1970 to 2021 using Markov-switching vector auto regression (VAR) model. Findings The results indicate that TSX return contains two regimes: positive return (Regime 1), when growth rate of stock index is positive; and negative return (Regime 2), when growth rate of stock index is negative. Moreover, Regime 1 is more volatile than Regime 2. The findings also show the crude oil market has a negative effect on the stock market in Regime 1, while it has a positive effect on the stock market in Regime 2. In addition, the authors can see this effect in Regime 1 more significantly in comparison to Regime 2. Furthermore, two-period lag of oil price decreases stock return in Regime 1, while it increases stock return in Regime 2. Originality/value This study aims to address the effect of oil market fluctuation on TSX index using Markov-switching approach and capture the nonlinearities between them. To the best of the author’s knowledge, this is the first study to assess the effect of the oil market on TSX in different regimes using Markov-switching VAR model. Because Canada is the sixth-largest producer and exporter of oil in the world as well as the TSX as the Canada’s main stock exchange is the tenth-largest stock exchange in the world by market capitalization, this paper’s framework to analyze a nonlinear relationship between oil market and the stock market of Canada helps stock market players like policymakers, institutional investors and private investors to get a better understanding of the real world.

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