This text presents a study of various models based on jump processes in the context of foreign exchange (FX) rates modeling. Quality of FX rate log-returns fit is assessed for models such as Merton and Kou jump-diffusions, normal inverse Gaussian, variance gamma, and Meixner. The study is...

Theory suggests that commodity futures price levels and returns data may exhibit both nonlinear and nonreversible features. This paper attempts to provide a thorough empiri- cally investigation of these claims. The data set is composed of 25 individual continuous contract commodity futures...

During the recent decades, neural network models have been focused upon by researchers due to their more real performance and on this basis different types of these models have been used in forecasting. Now, there is this question that which kind of these models has more explanatory power in...

This paper employs a new econometric technique to estimate the core inflation in Turkey measured as the shifting means in levels between 1955 and 2014. Using monthly series, we determine the number of shifts using the BIC, the hv-block cross-validation, the Lin-Teräsvirta parameter constancy...

This paper examines the well know day of the week effect on stock returns. Various approaches have been developed and applied in order to examine calendar effects in stock returns and to formulate appropriate financial and risk portfolios. We propose an alternative approach in the estimation of...

This paper proposes a powerful methodology wavelet networks to investigate the effects of international F/X markets on emerging markets currencies. We used EUR/USD parity as input indicator (international F/X markets) and three emerging markets currencies as Brazilian Real, Turkish Lira and...

This paper extends the Nelson-Siegel linear factor model by developing a flexible macro-finance framework for modeling and forecasting the term structure of US interest rates. Our approach is robust to parameter uncertainty and structural change, as we consider instabilities in parameters and...

We use factor augmented vector autoregressive models with time-varying coefficients to construct a financial conditions index. The time-variation in the parameters allows for the weights attached to each financial variable in the index to evolve over time. Furthermore, we develop methods for...

We use Bayesian factor regression models to construct a financial conditions index (FCI) for the U.S. Within this context we develop Bayesian model averaging methods that allow the data to select which variables should be included in the FCI or not. We also examine the importance of different...

Maturity transformation coupled with open foreign exchange positions expose financial intermediaries to unexpected changes in interest and exchange rates. This paper proposes to measure the degree of banks exposure to market risks by taking the variance of the total differential of the bank...