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Article
Publication date: 30 September 2013

Deniz Kebabci Tudor

The purpose of this paper is to examine the effects of parameter uncertainty in the returns process with regime shifts on optimal portfolio choice over the long run for a…

Abstract

Purpose

The purpose of this paper is to examine the effects of parameter uncertainty in the returns process with regime shifts on optimal portfolio choice over the long run for a static buy-and-hold investor who is investing in industry portfolios.

Design/methodology/approach

This paper uses a Markov switching model to model returns on industry portfolios and propose a Gibbs sampling approach to take into account parameter uncertainty. This paper compares the results with a linear benchmark model and estimates without taking into account parameter uncertainty. This paper also checks the predictive power of additional predictive variables.

Findings

Incorporating parameter uncertainty and taking into account the possible regime shifts in the returns process, this paper finds that such investors can allocate less in the long run to stocks. This holds true for both the NASDAQ portfolio and the individual high tech and manufacturing industry portfolios. Along with regime switching returns, this paper examines dividend yields and Treasury bill rates as potential predictor variables, and conclude that their predictive effect is minimal: the allocation to stocks in the long run is still generally smaller.

Originality/value

Studying the effect of regime switching behavior in returns on the optimal portfolio choice with parameter uncertainty is our main contribution.

Details

Studies in Economics and Finance, vol. 30 no. 4
Type: Research Article
ISSN: 1086-7376

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Article
Publication date: 15 June 2010

Cuicui Luo, Luis A. Seco, Haofei Wang and Desheng Dash Wu

The purpose of this paper is to deal with the different phases of volatility behavior and the dependence of the variability of the time series on its own past, models…

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Abstract

Purpose

The purpose of this paper is to deal with the different phases of volatility behavior and the dependence of the variability of the time series on its own past, models allowing for heteroscedasticity like autoregressive conditional heteroscedasticity (ARCH), generalized autoregressive conditional heteroscedasticity (GARCH), or regime‐switching models have been suggested by reserachers. Both types of models are widely used in practice.

Design/methodology/approach

Both regime‐switching models and GARCH are used in this paper to model and explain the behavior of crude oil prices in order to forecast their volatility. In regime‐switching models, the oil return volatility has a dynamic process whose mean is subject to shifts, which is governed by a two‐state first‐order Markov process.

Findings

The GARCH models are found to be very useful in modeling a unique stochastic process with conditional variance; regime‐switching models have the advantage of dividing the observed stochastic behavior of a time series into several separate phases with different underlying stochastic processes.

Originality/value

The regime‐switching models show similar goodness‐of‐fit result to GARCH modeling, while has the advantage of capturing major events affecting the oil market. Daily data of crude oil prices are used from NYMEX Crude Oil market for the period 13 February 2006 up to 21 July 2009.

Details

Kybernetes, vol. 39 no. 5
Type: Research Article
ISSN: 0368-492X

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Article
Publication date: 28 February 2020

Mobeen Ur Rehman and Nicholas Apergis

This study aims to investigate the impact of sentiment shocks based on US investor sentiments, bearish and bullish market conditions. Earlier studies, though very few…

Abstract

Purpose

This study aims to investigate the impact of sentiment shocks based on US investor sentiments, bearish and bullish market conditions. Earlier studies, though very few, only consider the effect of investor sentiments on stock returns of emerging frontier Asian (EFA) markets.

Design/methodology/approach

This study uses the application of regime switching model because of its capability to explore time-varying causality across different regimes unlike traditional linear models. The Markov regime switching model uses regime switching probabilities for capturing the potential asymmetries or non-linearity in a model, in this study’s case, thereby adjusting investor sentiments shocks to stock market returns.

Findings

The results of the Markov regime switching method suggests that US sentiment, bullish and bearish market shocks act as a main contributors for inducing variation in EFA stock market returns. The study’s non-parametric robustness results highlight an asymmetric relationship across the mean series, whereas a symmetric relationship across variance series. The study also reports Thailand as the most sensitive market to global sentiment shocks.

Research limitations/implications

The sensitivity of the EFA markets to these global sentiment shocks highlights their sensitivity and implications for investors relying merely on returns correlation and spillover. These findings also suggest that spillover from developed to emerging and frontier equity markets only in the form of returns following traditional linear models may not be appropriate.

Practical implications

This paper supports the behavioral aspect of investors and resultant spillover from developed market sentiments to emerging and frontier market returns across international equity markets offering more rational justification for an irrational behavior.

Originality/value

The study’s motivation to use the application of regime switching models is because of its capability to explore time-varying causality across different regimes unlike traditional linear models. The Markov regime switching model uses regime switching probabilities for capturing the potential asymmetries or non-linearity in a model, in the study’s case, thereby adjusting investor sentiments shocks to stock market returns. It is also useful of the adjustment attributable to exogenous events.

Details

Journal of Economic Studies, vol. 47 no. 3
Type: Research Article
ISSN: 0144-3585

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Article
Publication date: 17 January 2022

Mohammadreza Mahmoudi and Hana Ghaneei

This study aims to analyze the impact of the crude oil market on the Toronto Stock Exchange Index (TSX).

Abstract

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.

Details

Studies in Economics and Finance, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1086-7376

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Article
Publication date: 27 September 2011

Robert J. Elliott, Tak Kuen Siu and Alex Badescu

The purpose of this paper is to consider a discrete‐time, Markov, regime‐switching, affine term‐structure model for valuing bonds and other interest rate securities. The…

Abstract

Purpose

The purpose of this paper is to consider a discrete‐time, Markov, regime‐switching, affine term‐structure model for valuing bonds and other interest rate securities. The proposed model incorporates the impact of structural changes in (macro)‐economic conditions on interest‐rate dynamics. The market in the proposed model is, in general, incomplete. A modified version of the Esscher transform, namely, a double Esscher transform, is used to specify a price kernel so that both market and economic risks are taken into account.

Design/methodology/approach

The market in the proposed model is, in general, incomplete. A modified version of the Esscher transform, namely, a double Esscher transform, is used to specify a price kernel so that both market and economic risks are taken into account.

Findings

The authors derive a simple way to give exponential affine forms of bond prices using backward induction. The authors also consider a continuous‐time extension of the model and derive exponential affine forms of bond prices using the concept of stochastic flows.

Originality/value

The methods and results presented in the paper are new.

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Article
Publication date: 5 April 2011

Peixin (Payton) Liu, Kuan Xu and Yonggan Zhao

This paper aims to extend the Fama and French (FF) three‐factor model in studying time‐varying risk premiums of Sector Select Exchange Traded Funds (ETFs) under a Markov

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Abstract

Purpose

This paper aims to extend the Fama and French (FF) three‐factor model in studying time‐varying risk premiums of Sector Select Exchange Traded Funds (ETFs) under a Markov regime‐switching framework.

Design/methodology/approach

First, the original FF model is augmented to include three additional macro factors – market volatility, yield spread, and credit spread. Then, the FF model is extended to a model with a Markov regime switching mechanism for bull, bear, and transition market regimes.

Findings

It is found that all market regimes are persistent, with the bull market regime being the most persistent, and the bear market regime being the least persistent. Both the risk premiums of the Sector Select ETFs and their sensitivities to the risk factors are highly regime dependent.

Research limitations/implications

The regime‐switching model has a superior performance in capturing the risk sensitivities of the Sector Select ETFs, that would otherwise be missed by both the FF and the augmented FF models.

Originality/value

This is the first research on Sector Select ETFs with Markov regime switching.

Details

International Journal of Managerial Finance, vol. 7 no. 2
Type: Research Article
ISSN: 1743-9132

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Article
Publication date: 29 April 2021

Tran Van Phuong Duong, Szu-Hsien Lin, Huei-Hwa Lai and Tzu-Pu Chang

This research examines how macroeconomic variables can precisely predict bull/bear stock markets in China and Taiwan.

Abstract

Purpose

This research examines how macroeconomic variables can precisely predict bull/bear stock markets in China and Taiwan.

Design/methodology/approach

This paper adopts a two-state Markov switching model to characterize the bull and bear markets spanning from 1994 to 2019 and then conduct a bear stock market predictability test by running regressions between the filtered probabilities of bear markets and a series of macroeconomic variables in turn at different horizons of 1, 3, 6, 12 and 24 months.

Findings

This paper shows that inflation rates, changes in real exchange rates, and foreign currency reserve growth are key predictors of bear markets in China, while term spreads, unemployment rates and foreign reserve growth are major factors that can predict bear markets in Taiwan. Remarkably, industrial production growth does not have predictive power for bear markets, which may suggest emerging markets are driven by fund flows rather than real economic activities. Besides, the impact directions of foreign currency reserve growth are opposite, which may be due to different proportions of the financial accounts in their balance of payments.

Practical implications

In practical respect, this paper provides market participants the usefulness, impact direction and implications of bear market predictors when building their market-timing strategies in China and Taiwan stock markets. The government institutions may also thereby make appropriate policies to prevent huge stock market downturns and serious drawbacks.

Originality/value

It highlights the “fund-driven market hypothesis” and “foreign currency reserve effects” that commonly dominate Taiwan and China stock markets since both are highly affected by international funds.

Details

International Journal of Emerging Markets, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-8809

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Article
Publication date: 28 April 2020

Juan Carlos Cuestas and Bo Tang

This study investigates the spillover effects between exchange rate changes and stock returns in China. The authors find that no significant interconnections exist between…

Abstract

Purpose

This study investigates the spillover effects between exchange rate changes and stock returns in China. The authors find that no significant interconnections exist between stock returns and exchange rates changes.

Design/methodology/approach

Although the conventional structural VAR (SVAR) approach fails to examine the contemporaneous effects, the Markov switching SVAR model captures the volatile structure of the Chinese financial market. The regime-switching estimates indicate that volatile structure tends to be significant during two financial crisis periods.

Findings

Notwithstanding the fact that exchange rate changes cannot Granger-cause stock returns in the long run, its contemporaneous spillover effects on stock returns are found to be statistically significant.

Originality/value

This study aims to shed light on the spillover effects between exchange rate changes and stock returns in China, as the Chinese currency is becoming flexible and China’s stock market has undertaken important reforms. The spillovers between the two markets are of topical importance due to the increasing connections between China and the global economy.

Details

International Journal of Emerging Markets, vol. 16 no. 3
Type: Research Article
ISSN: 1746-8809

Keywords

Open Access
Article
Publication date: 3 July 2021

Faik Bilgili, Fatma Ünlü, Pelin Gençoğlu and Sevda Kuşkaya

This paper aims to investigate the pass-through (PT) effect in Turkey by using quarterly data for the period 1998: Q1-2019: Q2 to understand the dynamic potential effects…

Abstract

Purpose

This paper aims to investigate the pass-through (PT) effect in Turkey by using quarterly data for the period 1998: Q1-2019: Q2 to understand the dynamic potential effects of exchange rates on domestic prices.

Design/methodology/approach

The paper launches several nonlinear models in which the basic determinants of domestic prices in Turkey are determined through Markov regime-switching models (MSMs). Hence, this research follows the variables of the consumer price index (CPI), USD exchange rate, gross domestic product (GDP; demand side of the economy), industrial production index (production side of the economy), economic uncertainty and geopolitical risk index for Turkey.

Findings

This work explores that the exchange rate and demand side of the economy (GDP) follow a positive nonlinear relationship with CPI at both regimes. The production side of the economy (IP) affects negatively the CPI during regime 0. Economic uncertainty influences the CPI positively at Regime 1, while geopolitical risk has a negative association with CPI at Regime 0. Eventually, the paper provides some policy proposals associated with the impacts of GDP, IP, economic uncertainty and geopolitical risk on CPI in Turkey.

Originality/value

One may claim that any PT model, which does not observe the possible structural or regime shifts in estimated parameters, might fail to estimate the coefficients unbiasedly and efficiently. Hence, this work differs from available relevant works in the literature since this paper considers linearity or nonlinearity important and reveals that the relevant PT model follows a nonlinear path rather than a linear path, this nonlinear path is converged strongly by MSMs and estimates the significant regime shifts in the constant term and, in parameters of independent variables of PT by MSMs.

Details

Applied Economic Analysis, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN:

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Article
Publication date: 26 July 2021

TrungTuyen Dang, Zhang Caihong, ThiHong Nguyen, NgocTrung Nguyen and Cuong Tran

This study aims to examine the transmission mechanism of factors on the characteristic fluctuation of Vietnamese coffee bean export price (PVN).

Abstract

Purpose

This study aims to examine the transmission mechanism of factors on the characteristic fluctuation of Vietnamese coffee bean export price (PVN).

Design/methodology/approach

Applying Markov switching–vector autoregressive model.

Findings

Significantly, the empirical results showed that the transmission of independent variables on PVN is non-linear, and the fluctuation of PVN is affected by many factors, especially PVN in the previous period. In addition, the effect of Robusta coffee price was the greatest with coefficient is 0.28785, and the correlation between PVN and it was also the highest in both regimes with coefficients are 0.5317 and 0.3959, respectively.

Originality/value

These obtained results are in accordance with reality, as Vietnam is the largest exporter of Robusta coffee in the world.

Details

Journal of Asia Business Studies, vol. 15 no. 5
Type: Research Article
ISSN: 1558-7894

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