There are 1 repository under hodrick-prescott-filter topic.
Python-written project that utilizes Time Series analysis, along with a Linear Regression model, to forecast the price of the Japanese Yen vs. the US Dollar. ARMA, ARIMA, and GARCH forecasting models included, as well as decomposition using the Hodrick-Prescott filter. In-Sample and Out-of-Sample performance metrics used to evaluate Linear Regression model.
Filters (kalman, hodrick-prescott, moving average) together with comparison and sensitivity analysis (in notebook filters_with_parameters)+var analysis and granger causality test. Test for random walk (CE currencies using yfinance API)
Using time series tools to predict future movements in the value of the Japanese yen versus the U.S. dollar.
This project uses the many time-series tools (Hodrick-Prescott Filter, ARMA, ARIMA and GARCH models, linear regression, etc.) to predict future movements in the value of the Japanese yen versus the U.S. dollar.
(Boosted) Hodrick-Prescott Filter implemented as Julia package
Time Series forecasting and linear regression modelling of currency price action
This project aims to predict future yen prices using time-series models such as ARIMA as well as making out of sample and in sample predictions on Python
In this notebook, I've loaded historical Dollar-Yen exchange rate futures data. I've applied time series analysis and modeling to determine whether there is any predictable behavior.
Time-series forecasting and linear regression modeling in order to predict future movements in the value of the Japanese yen versus the U.S. dollar.
Testing various time-series tool to predict future movements in the value of the Japanese yen versus the U.S. dollar.
This repository is for me to practice Time Series Forecasting.
Business Cycle Regularities in 2 countries
Time Series forecasting and linear regression modelling of currency price action.