This study presents a financial stress index for Turkey on a daily basis. The index covers the time period between 01.08.2002 and 31.01.2013, and it presents the summation of stress levels collected through the Banking Sector, Public Sector, Stock Market and Foreign Exchange Market. So as to enable the financial institutions and policy makers to determine the financial stress on the sub-markets and financial sector, and manage the monetary policy, an indicator with high frequency was aimed to be provided. By use of the financial stress analysis, the Turkish Economy has been broken down into six different periods, namely (i) the high stress period (ii) the normal stress period (iii) the global crisis stress period (iv) the low stress period (v) the increasing stress period (vi) the decreasing stress period and the analyses related to each of these periods are presented.
Bu çalışmada, Türkiye'de reel döviz kurları ile ihracat ve ithalat arasındaki etkileşim Granger nedensellik testi kullanılarak araştırılmıştır.Granger nedensellik ilişkisini belirlemeden önce, birim kök ve eşbütünleşme analizi yapılmıştır. Zaman serisi teknikleri kullanılarak elde edilen bulgulara göre, reel döviz kurları ile ihracat ve ithalat arasında eşbütünleşme ilişkinin varlığı görülmüştür. Diğer taraftan, reel döviz kuru ile ihracat ve ithalat arasında bulunan nedensellik ilişkisi, ihracat ve ithalattan reel döviz kuruna doğru tek yönlü bir ilişki biçiminde olmaktadır.
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<p>This study investigates the effect of the COVID-19 pandemic on the residential real estate prices in Turkey. This study indicates the effect of COVID-19, loan package, macroeconomic and behavioral control variables on abnormal returns of residential real estate prices during the event window. This study consists of three econometric steps. Firstly, the abnormal returns of the residential real estate prices are obtained by using an event study. Secondly, the effect of the COVID-19 pandemic on abnormal returns of residential real estate prices was estimated by panel data analysis for regional and city levels. According to the findings of the city level, the COVID-19 pandemic has a negative effect on abnormal returns of residential prices, as expected. However, the regional analysis shows mainly a positive COVID-19 effect.</p>
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The study investigates the accuracy of bagging ensemble models (i.e., bagged artificial neural networks (BANN) and bagged regression trees (BRT)) in monthly crude oil price forecasting. Two ensemble models are obtained by coupling bagging and two simple machine learning models (i.e., artificial neural networks (ANN) and classification and regression trees (CART)) and results are compared with those of the single ANN and CART models. Analytical results suggest that ANN based models (ANN & BANN) are superior to tree-based models (RT & BRT) and the bagging ensemble method could optimize the forecast accuracy of the both single ANN and CART models in monthly crude oil price forecasting.
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