A vector time series model of the form A(L)y(t)+B(L)x(t)=e(t), is known as a vector autoregressive model with exogenous variables (VARX model) and involves a regressand vector y(t) and a regressor vector x(t). This chapter provides a method for the recursive fitting of subset VARX models. It...

In this chapter, a procedure is presented to use the bootstrap in choosing the best approximation in terms of forecasting performance for the equivalent state-space representation of a vector autoregressive model. It is found that the proposed procedure, which uses each approximant's forecasting...

The necessary and sufficient condition to test for 'overall causality', i.e., the presence of Granger-causality and instantaneous causal relations, in a bivariate and trivariate autoregressive model with recursive form is discussed. It is argued that the conventional AR model (the reduced form...

This chapter uses a modified block Choleski decomposition method and tree pruning algorithms to attain the best multivariate subset autoregression for each size (number of non-zero coefficient matrices). Model selection criteria are then employed to select the optimum multivariate subset AR. A...

The recursive algorithm to select the optimum multivariate real subset autoregressive model (AR) [1] is generalized to apply to multichannel complex subset AR's. It is initiated by fitting all 'forward' and 'backward' one-lag AR's. The method then allows one to develop successively all complex...

The paper comprises the preface and chapter 1 of the book titled "Financial and Economic Forecasting" (Authors: Penm-Penm-Terrell; Publication date: October 2002). The preface provides explanatory remarks at the beginning of the book. It briefly introduces theoretical developments and empirical...

A vector autoregressive model with exogenous variables (VARX model) involves a regressand vector y(t) and a regressor vector x(t). This chapter provides a method for the recursive fitting of subset VARX models. It suggests the use of ascending recursions in conjunction with an order selection...

We investigate and construct forecasting models for the exchange rate of the Indonesian rupiah against the US dollar. Monthly data for three variables; exchange rate, interest rate and foreign reserves were employed in the Economic Forecasting Program (EFP) to obtain the forecasting results. The...

In this chapter, we analysing and forecasting the New Taiwanese Dollar against the US dollar. Forecasting models were tested using the three variables; exchange rate, money supply and Balance Remittance. Both VAR and VARMA models accurately predicted turning points and no false fluctuations were...

In this chapter, economic forecasting techniques were used to forecast the exchange rate of the New Taiwan (N.T.) dollar, given that there is a tolerable amount of favourable trade balance between Taiwan and the US. To test this monthly data for the economic variables; Taiwanese exchange rate...