T his study investigates the short-run and long-run impact of real exchange rate misalignment and volatility on Indonesian export to the US by exploiting the disaggregated data of export volume. The proxy of real exchange rate misalignment was obtained by estimating the fundamental equilibrium exchange rate (FEER) model, and the exchange rate volatility measured by employing the GARC...

â  using of prediction models is one of the methods of financial performance prediction. financial ratios are employed as predictive variable in prediction models. the main purpose of this study is to compare the incremental information content of accrual and cash ratios for prediction and evaluation of the financial performance of business entities by data mining models. in align with research...

Time-series prediction has been a very well researched topic in recent studies. Some popular approaches to this problem are the traditional statistical methods e.g. multiple linear regression and moving average, and neural network with the Multi Layer Perceptron which has shown its supremacy in time-series prediction. In this study, we used a different approach based on evolving clustering algo...

this paper is about cointegration relation among price index in tehran stock exchange (tepix) and some of the macroeconomic variables, including consumer price index (cpi), exchange rate, housing starts and industrial utilization starts. we are looking for a relation and also the direction of the causal effects among above mentioned variables, using quarterly data from 1369 to 1377. avoiding sp...

Absrracf In this paper, the KIII dynamic neural network i s introduced and it is applied to the prediction of complex temporal sequences. I n our approach, Klll gives a step-by-step prediction of the direction of the currency exchange rate change. Previously, various multiplayer perceptron (MLP) networks and recurrent neural networks have been successfully implemented for this application. Resu...

This study proposes a novel neural-network-based fuzzy group forecasting model for foreign exchange rates prediction. In the proposed model, some single neural network models are first used as predictors for foreign exchange rates prediction. Then these single prediction results produced by each single neural network models are fuzzified into some fuzzy prediction representations. Subsequently,...

We propose a prediction model called Rival Penalized Competitive Learning (RPCL) and Combined Linear Predictor method (CLP), which involves a set of local linear predictors such that a prediction is made by the combination of some activated predictors through a gating network (Xu et al., 1994). Furthermore, we present its improved variant named Adaptive RPCL-CLP that includes an adaptive learni...

t he investigation of exchange rate pass-through is an important issue in international finance. the relationship between exchange rate pass-through and exchange rate arrangements such as the dollarization regime has been examined in recent decades. for this purpose, the main objective of this study is to investigate the effect of exchange rate pass-through on the domestic inflation in selecte...