Markov switching

Although gold is no longer a central cornerstone of the international monetary and financial system, it still attracts considerable attention from researchers and investors. Nowadays, many investors manage their risk with valuable assets such as gold. This paper examines the dynamic relationships between gold and stock markets in the Tehran Stock Exchange. We have applied the Markov switching method to study the role of gold as a hedge or safe haven for the Tehran Stock Exchange risk from 1998 to 2018. The high dependence and low dependence regimes used in the Markov switching model are based on empirical results that show two regimes for all markets under investigation: a low volatility regime and a high volatility regime. The study's findings show that gold can act as a strong hedge and cannot act as a safe haven for risk of The Tehran stock exchange.

The financial sector plays a central role in economic development and growth, and due to playing an intermediary role in allocating resources to all sectors of the economy, by reducing financing costs and encouraging savings and their efficient use, a major contribution. In the long-term economic growth of the government in oil-exporting countries, relying on oil revenues, it is possible to enter the financial markets extensively and make various changes in it. The main goal of policymakers from such changes is to stimulate economic growth. But studies in this area show that fiscal development does not necessarily lead to economic growth. However, in recent decades, the role of financial development in economic growth has been forgotten. Therefore, this study examines the impact of the development of financial institutions on economic growth. The statistical population of the present study consists of MENA member countries in the period 1980 to 2019. In order to conduct this research, due to the nonlinear relationship between the research variables, the PSTR model and Markov switching time series pattern have been used. Financial depth, accessibility and efficiency are also variables in the development of financial institutions that have been considered in this study. The results indicate that all three components of the financial institutions development index have a significant effect on the economic growth variable.

This study seeks to rigorously assess the relationship between Iran’s stock market index and monetary policy within the framework of the Markov Switching Vector Autoregressive (MS-VAR) model. The MS-VAR methodology is particularly well-suited for capturing regime-dependent dynamics and structural shifts in macroeconomic and financial time series. For this purpose, quarterly data spanning from Spring 2009 to Fall 2023 have been employed. All estimations were conducted using EViews 12 and OX Metrics 7 software. As a preliminary step, the Hodrick-Prescott filter was applied to differentiate between two distinct market regimes. Combined with a univariate Markov Switching model, this approach enabled the identification of cyclical fluctuations in the stock market, distinguishing bull from bear market phases. The results indicate that Regime 1 (bear market) demonstrates greater persistence and stability relative to Regime 2 (bull market), suggesting asymmetric market dynamics. Subsequently, the study investigates the effects of monetary policy—proxied by the interbank market rate and liquidity growth—on the growth of the stock market index within the MS-VAR framework. The findings suggest that monetary policy has different effects during bull and bear market phases. The stock index exhibits a prompt and asymmetric response to changes in both the interbank market rate and liquidity growth. Specifically, in both bull and bear market regimes, an increase in the interbank interest rate exerts a contractionary effect on stock index growth, with a more pronounced negative impact observed during periods of market recession. Moreover, liquidity growth consistently contributes positively to stock index growth across both regimes, with a more pronounced effect under bull market conditions. Variance decomposition analysis further reveals that, in both regimes, shocks to the stock index itself account for the largest proportion of its fluctuations. Nonetheless, the relative importance of monetary policy instruments varies by regime: In both expansionary and recessionary phases of the stock market, shocks stemming from the interbank market rate play a more prominent role in explaining stock index volatility compared to liquidity shocks. Finally, the presence of nonlinear interactions among the variables is statistically validated based on the Likelihood Ratio (LR) test.