Acceso al sitio web del Consejo de Políticas de Infraestructura

   
ARTÍCULO
TITULO

Short Term Portfolio Investment and BI Rate: Do They Determine the Stabilization of Rupiah Exchange Rate in Indonesia?

Chenny Seftarita    
Fitriyani Fitriyani    
Cut Zakia Rizki    
Diana Sapha    
Abd. Jamal    

Resumen

This study aims to investigate the influence of short-term portfolio investments and BI interest rate on fluctuation of rupiah exchange rate in Indonesia. The data used is quarterly data from 2010 to 2016 collected from Indonesia Central Bank. Using the Autoregressive Distributed Lag (ARDL) method, the result showed that rupiah exchange rate was strongly influenced by shocks in the private debt securities, joint stock price index, and BI Rate, both in the long run and short run. Moreover, it is found that there was a short-run and long-run balance relationship between Short Term Portfolio Investments and BI rate against the rupiah exchange rate. Thus, it is recommended that in order to stabilize the exchange rate, it is necessary to maintain the stability of short-term portfolio investments.  

PÁGINAS
pp. 18 - 28
MATERIAS
ECONOMÍA

 Artículos similares

       
 
C. Tamilselvi, Md Yeasin, Ranjit Kumar Paul and Amrit Kumar Paul    
Denoising is an integral part of the data pre-processing pipeline that often works in conjunction with model development for enhancing the quality of data, improving model accuracy, preventing overfitting, and contributing to the overall robustness of pr... ver más
Revista: Forecasting

 
Juan M. Lujano-Rojas, Rodolfo Dufo-López, Jesús Sergio Artal-Sevil and Eduardo García-Paricio    
Assessing the training process of artificial neural networks (ANNs) is vital for enhancing their performance and broadening their applicability. This paper employs the Monte Carlo simulation (MCS) technique, integrated with a stopping criterion, to const... ver más
Revista: Forecasting

 
Daniel Manfre Jaimes, Manuel Zamudio López, Hamidreza Zareipour and Mike Quashie    
This paper proposes a new hybrid model to forecast electricity market prices up to four days ahead. The components of the proposed model are combined in two dimensions. First, on the ?vertical? dimension, long short-term memory (LSTM) neural networks and... ver más
Revista: Forecasting

 
Priscila Espinosa and Jose M. Pavía    
Subnational jurisdictions, compared to the apparatuses of countries and large institutions, have less resources and human capital available to carry out an updated conjunctural follow-up of the economy (nowcasting) and for generating economic predictions... ver más
Revista: Forecasting

 
Amal Al Ali, Ahmed M. Khedr, Magdi El Bannany and Sakeena Kanakkayil    
Despite the obvious benefits and growing popularity of Machine Learning (ML) technology, there are still concerns regarding its ability to provide Financial Distress Prediction (FDP). An accurate FDP model is required to avoid financial risk at the lowes... ver más