The purpose of this study is to contribute to the literature by studying the effects of

This study makes a contribution to the literature by applying the Markov-Switching Bayesian VAR models for the first time to investigate the nonlinear linkage between gold prices and stock market index. Analyses have been done in the period from 1986:04 to 2013:11. The Bayesian approach to econometrics provides a general method for combining modeller's beliefs with the evidence contained in the data. In contrast to the classical approach to estimate a set of parameters, Bayesian statistic presupposes a set of prior probabilities about the underlying parameters to be estimated. We use gold prices (USD/oz.) and S&P 500 Stock Price Index as an endogenous, the crude oil prices (Brent-$/barrel) as an exogenous variable in the analysis. We investigate the number of regime by LR test and The Markov Chain Monte Carlo (MCMC) algorithm and Sims & Zha (1998) prior distribution are employed to estimate the models.

The purpose of this article is to compare stable, integrated and long-memory generalized autoregressive conditional heteroscedasticity (GARCH) models in forecasting the volatility of returns in the Turkish foreign exchange market for the period 1990-2005 and for the subperiod that covers the floating exchange rate regime 2001-2005. In the first period, we found that long-memory GARCH specifications capture the temporal pattern of volatility for returns in US and Canadian dollars against Turkish lira. For the same period, the temporal pattern of volatility for returns Australian dollar, Japanese yen, Euro and British pound against Turkish lira are best captured by stable GARCH specifications. We found that in the subperiod, only the stable GARCH models are relevant and the return series no longer exhibit the long-memory properties. It was also concluded that all return series except British pound against Turkish Lira have asymmetric effects. Our analysis has shown that when long memory, asymmetry and power terms in the conditional variance are employed, together with the skewed and leptokurtic conditional distribution (of innovations), the most accurate out-of-sample volatility is produced for the first and subperiod. Thus is useful for financial decisions which utilize such forecasts.

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Bu makalenin amacı, Türkiye için ham petrol fiyatları ve benzin fiyatlarındaki ani değişimlerin sanayi üretimine etkisinin incelenerek literatüre katkı yapmaktır. Analizler 2005:10-2014:02 dönemi için değişkenlerin doğrusal olmayan özelliklerini yakalamakta başarılı olan Markov Değişim Vektör Otoregresif (MS-VAR) modelleri ile yapılmıştır. LR testi ile analiz döneminde iki rejim olduğu, ham petrol ve benzin fiyatlarındaki değişimin sanayi üretimine etkisinin bu rejimlere bağlı olarak değiştiği bulunmuştur. Ayrıca petrol ve benzin fiyatlarının sanayi üretimine geçiş etkisi olduğu ortaya konulmuştur.

Developing countries are more sensitive to developments in global markets and capital movements. Therefore, their financial stress should not be high enough to put the economic recovery in danger when faced with problems originating from financial markets. In this paper, it is aimed to provide benefit to policymakers by creating a financial stress index that covers the period from 1990:01 to 2017:02 for Turkey in order to monitor financial stability. The variables included in the index are chosen among the variables that define the high stress conditions in financial markets. Markov regime switching models have been defined for this financial stress index, with the help of these models, low stress, normal stress and high stress periods in financial markets have been determined. The findings have been reached that high stress periods concentrated in the crisis years

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