콘텐츠 바로가기
로그인
컨텐츠

Category Open

Resources

tutorial

Collection of research papers and materials on development issues

home

Resources
Economy Financial Policy

Print

변동환율제하에서 미시구조적 정보를 이용한 원/달러 환율의 단기변동 분석

Related Document
Frame of Image


Full Text
Title 변동환율제하에서 미시구조적 정보를 이용한 원/달러 환율의 단기변동 분석
Similar Titles
Material Type Reports
Author(Korean)

박해식 외

Publisher

[서울]:한국금융연구원

Date 1999-09
Series Title; No 금융조사보고서 / 99-08
Pages 81
Subject Country South Korea(Asia and Pacific)
Language Korean
File Type Documents
Original Format pdf
Subject Economy < Financial Policy
Holding 한국금융연구원; KDI 국제정책대학원

Abstract

In this paper, we attempt to explain the short-term behavior of won/dollar exchange rates observed during the floating exchange rate regime using the microstructure information in the inter-bank market in Korea. First, we construct the hourly measure of excess demand for dollar to proxy for the trading pattern of market participants. To construct this time series, we rely on the bid/ask prices of the inter-bank market collected on a two-minute interval.
We then estimate the bivariate structural VAR consisting of the actually observed won/dollar exchange rate and the proxied trading pattern of market participants to see if private information, as opposed to public information, is relevant for explaining hourly movements of won/dollar exchange rates. It is found that private information accounts for more than 30% of variations in won/dollar exchange rates, and that its effect on the won/dollar exchange rate last for more than 10 hours.
Next, we construct the trading pattern of market participants on a daily basis using the same data set employed to build the hourly measure. We then examine the hypothesis that private information is useful for predicting daily won/dollar exchange rate movements. We find that the forecast model using both private and public information reduces out-of-sample forecast errors of an alternative model relying only on public information by 20~25%. The out-of-sample forecast of the model including both private and public information is also found to be more accurate than the random walk model.