Research Article
Hidden Markov Model for Exchange Rate with EWMA Control Chart
@INPROCEEDINGS{10.4108/eai.2-8-2019.2290474, author={Rahmawati Ramadhan and Dodi Devianto and Maiyastri Maiyastri}, title={Hidden Markov Model for Exchange Rate with EWMA Control Chart}, proceedings={Proceedings of the 1st International Conference on Statistics and Analytics, ICSA 2019, 2-3 August 2019, Bogor, Indonesia}, publisher={EAI}, proceedings_a={ICSA}, year={2020}, month={1}, keywords={exchange rate exponentially weighted moving average hidden markov model}, doi={10.4108/eai.2-8-2019.2290474} }- Rahmawati Ramadhan
Dodi Devianto
Maiyastri Maiyastri
Year: 2020
Hidden Markov Model for Exchange Rate with EWMA Control Chart
ICSA
EAI
DOI: 10.4108/eai.2-8-2019.2290474
Abstract
Nowadays, the US dollar exchange rate is still very influential on the exchange rate stability of many countries, including Indonesia. The effect of the US Dollar exchange rate has caused the fluctuation of Rupiah exchange rate. That is one of the cases that can be modeled with the Hidden Markov Model (HMM) as the development of a Markov chain in which its state is not able to be observed directly (hidden), but it is only able to be observed through a set of other observations. In this paper, Exponentially Weighted Moving Average (EWMA) control chart will be used to determine the state of HMM. Based on the EWMA control chart, there are three states which are increase, decrease, and constant. The probability of the changes of exchange rate will be predicted in 2019 with the Baum Welch Algorithm on HMM. By using 240 exchange rate data of US Dollar to Rupiah in 2018, it is predicted the changes of exchange rate in 2019 are increased with a probability of 0.57. The results of HMM have connected to the EWMA control chart where they have eight uncontrolled data with two states increase and six states decrease. Thus, the existence of uncontrolled data implies the probability of increasing of the exchange rate in 2019.