نتایج جستجو برای: markov switching model jel classification
تعداد نتایج: 2585897 فیلتر نتایج به سال:
The exchange rate regime in Iran is practically fixed. The Central Bank of Iran (CBI) has committed itself to trying to bring about a particular exchange rate regime to meet two important targets: 1. Sustaining competitiveness of the economy, 2. Acquiring the share of foreign reserves in monetary base in a predetermined level. Since 2001 the share of foreign reserves in monetary base has i...
This paper intends to harmonize two different approaches to the analysis of the business cycle and in doing so it retrieves the stylized facts of the business cycle in Europe. We start with the ‘classical’ approach proposed in Burns and Mitchell (1946) of dating and analyzing the business cycle; we then adopt the ‘modern’ alternative: the Markov-switching time series model proposed in Hamilton ...
This paper derives the moments for a range of Markov switching models. We characterize in detail the patterns of volatility, skewness and kurtosis that these models can produce as a function of the transition probabilities and parameters of the underlying state densities entering the switching process. The autocovariance of the level and squares of time series generated by Markov switching proc...
The main objective of this study was to investigate the effect of monetary policy on changes in the price of financial assets (including foreign exchange, gold and stocks) in Iranian economy. In this regard, this paper answers whether monetary policy could lead to regime changes in asset markets. To answer this question, monthly data during the years 1995 to 2017 and a combination of Markov Swi...
In this paper we discuss the calibration issues of regime switching models built on mean-reverting and local volatility processes combined with two Markov regime switching processes. In fact, the volatility structure of this model depends on a first exogenous Markov chain whereas the drift structure depends on a conditional Markov chain with respect to the first one. The structure is also assum...
Building on the current understanding of neural architecture of the visual cortex, we present a graphical model for learning and classification of motion patterns in videos. The model is composed of an arbitrary amount of Hidden Markov Models (HMMs) with shared Gaussian mixture models. The novel extension of our model is the use of additional Markov chain, serving as a switch for indicating the...
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 m...
We consider whether oil prices can account for business cycle asymmetries. We test for asymmetries based on the Markov switching autoregressive model popularized by Hamilton (1989), using the tests devised by Clements and Krolzig (2000). We select the transformation of the oil price of Lee, Ni and Ratti (1995), based on a linear analysis of the relationship between output growth and the oil pri...
In this paper we demonstrate that there is evidence of an unstable and nonlinear relationship between fundamentals and exchange rates. Modeling this time-varying nature of the importance of fundamentals in a Markov switching framework substantially improves the fit of the real interest rate differential model and leads to parameter estimates, which in one regime are in line with theoretical exp...
This paper develops a tractable dynamic term structure models under jump-diffusion and regime shifts with time varying transition probabilities. The model allows for regime-dependent jumps while both jump risk and regime-switching risk are priced. Closed form solution for the term structure is obtained for an affine-type model under loglinear approximation. JEL Classification: G12, E43, E52
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