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 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 GLOBALIZATION OF INTERNATIONAL FINANCIAL MARKETS

2019 ◽  
pp. 133-141
Author(s):  
I. I. Tubolec ◽  
O. V. Tkalich
Keyword(s):  
Real Estate ◽  
Stock Market ◽  
Financial Markets ◽  
Financial Market ◽  
Financial Institutions ◽  
Precious Metals ◽  
International Financial Institutions ◽  
Financial Infrastructure ◽  
Debt Market ◽  
Global Stock

The article deals with one of the components of globalization - the globalization of financial markets. The article considers financial markets, which are the component of globalization. The study investigates the international financial institutions that together form the international financial infrastructure and the main subjects of financial globalization. The study investigates the international financial institutions, which collectively form the international financial infrastructure and main subjects of financial globalization. The segments of the global financial market, which include the global debt market, the global stock market, other global financial markets (precious metals, real estate insurance), the global currency market, are considered. The article considers the segments of the global financial market, such as the global debt market, the global stock market, the global currency market and other global financial markets (precious metals, real estate insurance etc.). The article presents the prospects of global financial markets, such as high world standards, higher level of diversification, higher liquidity and professional risk management. It is established that the basis of the globalization of the financial system lies in the interaction of such phenomena as: technological progress; growing competition: on the one hand, between lending and financial institutions in the financial markets, and on the other hand, between the financial markets themselves, due to the significant development of information technology and telecommunications; restructuring of credit and financial; wide internationalization of business due to the increasing transnational nature of corporations; consolidation of regional integration associations (in Europe - Economic and Monetary Union); weakening of the firm control over the implementation of international agreements related to the movement of capital stock exchanges; - macroeconomic stabilization and reform in a number of developing and transition countries that have created a favorable climate for foreign investors; widespread use of the "principle of the lever". We investigated that the integration of international capital markets, merger of financial institutions, the tendency to increase speculative operations in the financial markets and financial crises are the global trends in the development of international financial markets in the requisition of globalization. It is proved that the, the emergence of the global financial space is represented by an increase in international financial flows, volumes of all types of international transactions, an increase in the number of companies and financial groups that operate outside of the national financial systems.

scholarly journals A Competitive Model to Forecast a Stock Market Index

2020 ◽  
Vol 2 (2) ◽  
pp. 1
Author(s):  
Nhan Nguyen-Thanh ◽  
Kun-Huang Huarng
Keyword(s):  
Stock Market ◽  
Root Mean Square ◽  
Garch Model ◽  
Mean Square ◽  
Financial Forecasting ◽  
Stock Market Index ◽  
Market Index ◽  
Out Of Sample ◽  
Competitive Model ◽  
Mean Square Errors

This study proposes a competitive model using the Box–Jenkins approach to implement a Box–Jenkins ARIMA-GARCH model in order to improve financial forecasting. Differing from previous studies, we consider optimizing the lagged terms, which assist in capturing the relationships more properly. The competitive model is then used to forecast the stock market index in Taiwan. This study conducts out-of-sample forecasting and compares the root mean square errors (RMSEs) against previous studies. The results show that the competitive model outperformed in terms of both RMSEs and consistency.

scholarly journals What Does Vietnam Gain When Its Currency Depreciates?

Economies ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 185
Author(s):  
Nguyen Thi Thanh Binh
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Regime Switching ◽  
Stock Price ◽  
Time Series Data ◽  
Series Data ◽  
The Us ◽  
High Volatility ◽  
Short Run ◽  
The Impact

The study investigates how the depreciation of the Vietnam dong (VND) against the US dollar (USD) affected export turnover and the stock market in Vietnam during the period from 2000 to 2020. A Markov triple regime-switching model is developed for time-series data involving multistructural breaks. Empirical results reveal that the impact of exchange rates on export turnover and stock price existed both in the long and short run. In the short run, the depreciation of VND led to (i) an increase in export turnover after 12 months; (ii) a decrease in export turnover of the high-growing regime in the short term; (iii) a reduction in stock returns in most cases. In addition, the common cycle from order receipt, preparation, production, and export is about 12 months for all states. The high volatility of export turnover was associated with high export growth. The commonly used phrase of “high risk, high return” seems to not be true for Vietnam’s stock market. The results of this study suggest the feasibility of a slight appreciation of VND against USD, which is the key to escape from being labeled a currency manipulator by the US Treasury.

scholarly journals Active portfolio management in the Andean countries’ stock markets with Markov-Switching GARCH models

2019 ◽  
Vol 14 (PNEA) ◽  
pp. 601-616 ◽  
Author(s):  
Oscar V. De la Torre-Torres ◽  
Dora Aguilasocho-Montoya ◽  
José Álvarez-García
Keyword(s):  
Stock Market ◽  
Portfolio Management ◽  
Stock Markets ◽  
Markov Switching ◽  
Investment Strategy ◽  
Garch Models ◽  
Stock Market Index ◽  
Active Portfolio Management ◽  
High Volatility ◽  
Andean Countries

In the present paper we test the benefits of using two-regime Markov-Switching (MS) models in the stock markets of the MSCI Andean index (Chile, Colombia and Perú). We tested this with either, constant, ARCH or GARCH variances and Gaussian or t-Student log-likelihood functions. By performing 996 weekly simulations from January 2000 to January 2019 with each MS model, we tested the next investment strategy for a U.S. dollar based investor: 1) to invest in the risk-free asset if the probability of being in the high-volatility regime at t+1 is higher than 50 % or 2) to do it in the stock market index otherwise. Our results suggest that the Gaussian MS-GARCH models are the most suitable to generate alpha in the Chilean stock market and the Gaussian MS-ARCH in the Colombian one. For the Peruvian case, we found that is preferable to perform passive investing instead of active trading.

THE TIMING OF PORTFOLIO ADJUSTMENTS: A REGIME-SWITCHING APPROACH

2012 ◽  
Vol 11 (05) ◽  
pp. 909-933 ◽  
Author(s):  
GUOBIN FAN ◽  
YONG ZENG
Keyword(s):  
Asset Allocation ◽  
Regime Switching ◽  
Markov Switching ◽  
Copula Function ◽  
Dependence Structure ◽  
Regime Changes ◽  
Equivalent Rate ◽  
Out Of Sample ◽  
Switching Characteristics ◽  
Rate Of Returns

The fact that the relationships among the returns of financial assets tend to be nonlinear and time-varying has important implications for asset allocation. To describe these two features, this paper first combines a copula function with the Markov switching technique to model the dependence structure across assets and then builds on this Markov Switching Copula model to present a procedure for the timing of portfolio adjustments. Our empirical evidence confirms that the dependence structure between high-risk and low-risk stocks in the Shanghai and Shenzhen markets is not static but switches between regimes over the course of the sample horizon considered in this paper. More importantly, as a result of such regime-switching characteristics of their dependence structure, our analysis of the out-of-sample asset allocation performance indicates that employing the procedure proposed in this paper to identify regime changes and decide when to adjust portfolio weights allows investors with the Constant Relative Risk Aversion utility to achieve both higher realized returns and higher certainty equivalent rate of returns than does the use of strategies based on static models.

scholarly journals Risk Analysis Of Hedge Funds: A Markov Switching Model Analysis

2013 ◽  
Vol 30 (1) ◽  
pp. 243 ◽  
Author(s):  
Frederic Teulon ◽  
Khaled Guesmi ◽  
Saoussen Jebri
Keyword(s):  
Risk Analysis ◽  
Hedge Funds ◽  
Regime Switching ◽  
Emerging Market ◽  
Markov Switching ◽  
Hedge Fund ◽  
Markov Switching Model ◽  
Market Strategy ◽  
Switching Model ◽  
High Volatility

The paper applies Markov Regime Switching GARCH Model (SW-GARCH) to investigate the volatility behavior of strategies hedge fund monthly returns for the period 1997-2011. The results highlight two different regimes: The first regime is characterized by a high volatility for all strategies hedge fund monthly returns. The second is characterised by lower volatility and positive average returns (except Emerging Market strategy). Our results helped to capture even the short-lived crises along with the material crises of 2001 and 2008.

Sign in / Sign up

Export Citation Format

Share Document