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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

Keywords

Article
Publication date: 2 October 2017

Yen-Hao Hsieh and Wei-Ting Chen

The purpose of this study is to create a value variation measurement model to define the relationship among various roles in resource management within a service system;…

337

Abstract

Purpose

The purpose of this study is to create a value variation measurement model to define the relationship among various roles in resource management within a service system; and divide value creation into two states (i.e. cocreation and codestruction) and use them as crucial indicators for value variation by adopting the service-dominant logic and using the Markov switching model.

Design/methodology/approach

This study proposed that variations in value are similar to changes in economy because both are abstract, indefinable and not easy to identify. Therefore, this study used the Markov switching model to define the state of value through value cocreation and codestruction; analyze value variations in a service system; and provide a numerical evaluation method by using the concept of probability to depict state transitions. In addition, open data from the Kaohsiung City Government’s 1999 call center were collected to address the aforementioned research objectives. The 1999 call center (service provider) offers citizens (customers) efficient consultant services to help them solve problems regarding the city government’s affairs or policies. Thus, this call center can be considered a complex service system.

Findings

This study revealed that the call center can utilize the analysis results of the Markov switching model on answer rates to predict service quality patterns. In addition, most first call resolution rates occurred under State 1 (value cocreation). To address problems caused by accidental or rare events, the call center should formulate policies to increase people and technical resources and improve service system effectiveness.

Originality/value

Enterprises currently focus on catering to customers’ needs and offering services through comprehensive service procedures to sustainably generate multiple values for customers, helping them to create values. Previous studies have mostly focused on analyzing the values of a service system and have failed to extensively explore actual value variations. Thus, the value variation measurement model proposed in the present study was able to analyze value variations of a set of call center data and illustrate value variations by using state transitions.

Details

Journal of Business & Industrial Marketing, vol. 32 no. 8
Type: Research Article
ISSN: 0885-8624

Keywords

Abstract

Details

Nonlinear Time Series Analysis of Business Cycles
Type: Book
ISBN: 978-0-44451-838-5

Book part
Publication date: 26 April 2014

Panayiotis F. Diamandis, Anastassios A. Drakos and Georgios P. Kouretas

The purpose of this paper is to provide an extensive review of the monetary model of exchange rate determination which is the main theoretical framework on analyzing…

Abstract

Purpose

The purpose of this paper is to provide an extensive review of the monetary model of exchange rate determination which is the main theoretical framework on analyzing exchange rate behavior over the last 40 years. Furthermore, we test the flexible price monetarist variant and the sticky price Keynesian variant of the monetary model. We conduct our analysis employing a sample of 14 advanced economies using annual data spanning the period 1880–2012.

Design/methodology/approach

The theoretical background of the paper relies on the monetary model to the exchange rate determination. We provide a thorough econometric analysis using a battery of unit root and cointegration testing techniques. We test the price-flexible monetarist version and the sticky-price version of the model using annual data from 1880 to 2012 for a group of industrialized countries.

Findings

We provide strong evidence of the existence of a nonlinear relationship between exchange rates and fundamentals. Therefore, we model the time-varying nature of this relationship by allowing for Markov regime switches for the exchange rate regimes. Modeling exchange rates within this context can be motivated by the fact that the change in regime should be considered as a random event and not predictable. These results show that linearity is rejected in favor of an MS-VECM specification which forms statistically an adequate representation of the data. Two regimes are implied by the model; the one of the estimated regimes describes the monetary model whereas the other matches in most cases the constant coefficient model with wrong signs. Furthermore it is shown that depending on the nominal exchange rate regime in operation, the adjustment to the long run implied by the monetary model of the exchange rate determination came either from the exchange rate or from the monetary fundamentals. Moreover, based on a Regime Classification Measure, we showed that our chosen Markov-switching specification performed well in distinguishing between the two regimes for all cases. Finally, it is shown that fundamentals are not only significant within each regime but are also significant for the switches between the two regimes.

Practical implications

The results are of interest to practitioners and policy makers since understanding the evolution and determination of exchange rates is of crucial importance. Furthermore, our results are linked to forecasting performance of exchange rate models.

Originality/value

The present analysis extends previous analyses on exchange rate determination and it provides further support in favor of the monetary model as a long-run framework to understand the evolution of exchange rates.

Details

Macroeconomic Analysis and International Finance
Type: Book
ISBN: 978-1-78350-756-6

Keywords

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. 39 no. 4
Type: Research Article
ISSN: 1086-7376

Keywords

Open Access
Article
Publication date: 16 June 2022

Fatma Mathlouthi and Slah Bahloul

This paper aims at examining the co-movement dependent regime and causality relationships between conventional and Islamic returns for emerging, frontier and developed…

Abstract

Purpose

This paper aims at examining the co-movement dependent regime and causality relationships between conventional and Islamic returns for emerging, frontier and developed markets from November 2008 to August 2020.

Design/methodology/approach

First, the authors used the Markov-switching autoregression (MS–AR) model to capture the regime-switching behavior in the stock market returns. Second, the authors applied the Markov-switching regression and vector autoregression (MS-VAR) models in order to study, respectively, the co-movement and causality relationship between returns of conventional and Islamic indexes across market states.

Findings

Results show the presence of two different regimes for the three studied markets, namely, stability and crisis periods. Also, the authors found evidence of a co-movement relationship between the conventional and Islamic indexes for the three studied markets whatever the regime. For the Granger causality, it is proved only for emerging and developed markets and only during the stability regime. Finally, the authors conclude that Islamic indexes can act as diversifiers, or safe-haven assets are not strongly supported.

Originality/value

This paper is the first study that examines the co-movement and the causal relationship between conventional and Islamic indexes not only across different financial markets' regimes but also during the COVID-19 period. The findings may help investors in making educated decisions about whether or not to add Islamic indexes to their portfolios especially during the recent outbreak.

Details

Journal of Capital Markets Studies, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2514-4774

Keywords

Book part
Publication date: 9 September 2020

Yiying Cheng

Recently, there has been much progress in developing Markov switching stochastic volatility (MSSV) models for financial time series. Several studies consider various MSSV…

Abstract

Recently, there has been much progress in developing Markov switching stochastic volatility (MSSV) models for financial time series. Several studies consider various MSSV specifications and document superior forecasting power for volatility compared to the popular generalized autoregressive heteroscedasticity (GARCH) models. However, their application to option pricing remains limited, partially due to the lack of convenient closed-form option pricing formulas which integrate MSSV volatility estimates. We develop such a closed-form option pricing formula and the corresponding hedging strategy for a broad class of MSSV models. We then present an example of application to two of the most popular MSSV models: Markov switching multifractal (MSM) and component-driven regime switching (CDRS) models. Our results establish that these models perform well in one-day-ahead forecasts of option prices.

Details

Advances in Pacific Basin Business, Economics and Finance
Type: Book
ISBN: 978-1-83867-363-5

Keywords

Book part
Publication date: 30 November 2011

Massimo Guidolin

I survey applications of Markov switching models to the asset pricing and portfolio choice literatures. In particular, I discuss the potential that Markov switching models

Abstract

I survey applications of Markov switching models to the asset pricing and portfolio choice literatures. In particular, I discuss the potential that Markov switching models have to fit financial time series and at the same time provide powerful tools to test hypotheses formulated in the light of financial theories, and to generate positive economic value, as measured by risk-adjusted performances, in dynamic asset allocation applications. The chapter also reviews the role of Markov switching dynamics in modern asset pricing models in which the no-arbitrage principle is used to characterize the properties of the fundamental pricing measure in the presence of regimes.

Details

Missing Data Methods: Time-Series Methods and Applications
Type: Book
ISBN: 978-1-78052-526-6

Keywords

Article
Publication date: 21 April 2011

Anastasios G. Malliaris and Ramaprasad Bhar

The equity premium of the S&P 500 index is explained in this paper by several variables that can be grouped into fundamental, behavioral, and macroeconomic factors. We…

Abstract

The equity premium of the S&P 500 index is explained in this paper by several variables that can be grouped into fundamental, behavioral, and macroeconomic factors. We hypothesize that the statistical significance of these variables changes across economic regimes. The three regimes we consider are the low‐volatility, medium‐volatility, and high‐volatility regimes in contrast to previous studies that do not differentiate across economic regimes. By using the three‐state Markov switching regime econometric methodology, we confirm that the statistical significance of the independent variables representing fundamentals, macroeconomic conditions, and a behavioral variable changes across economic regimes. Our findings offer an improved understanding of what moves the equity premium across economic regimes than what we can learn from single‐equation estimation. Our results also confirm the significance of momentum as a behavioral variable across all economic regimes

Details

Review of Behavioural Finance, vol. 3 no. 1
Type: Research Article
ISSN: 1940-5979

Keywords

Book part
Publication date: 6 January 2016

Catherine Doz and Anna Petronevich

Several official institutions (NBER, OECD, CEPR, and others) provide business cycle chronologies with lags ranging from three months to several years. In this paper, we…

Abstract

Several official institutions (NBER, OECD, CEPR, and others) provide business cycle chronologies with lags ranging from three months to several years. In this paper, we propose a Markov-switching dynamic factor model that allows for a more timely estimation of turning points. We apply one-step and two-step estimation approaches to French data and compare their performance. One-step maximum likelihood estimation is confined to relatively small data sets, whereas two-step approach that uses principal components can accommodate much bigger information sets. We find that both methods give qualitatively similar results and agree with the OECD dating of recessions on a sample of monthly data covering the period 1993–2014. The two-step method is more precise in determining the beginnings and ends of recessions as given by the OECD. Both methods indicate additional downturns in the French economy that were too short to enter the OECD chronology.

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