C# Console Application: Asks for two files containing historical financial data in the same format as files from Yahoo Finance. Performs the two-step Engel-Granger Test for Cointegration and simulates profits of applying the Pairs Trading Strategy to these stocks. To Project further Includes code to conduct statistical inference and a Function t…

This project forecasts weather using the ARIMA model. Data preprocessing, parameter selection, and model evaluation using multiple metrics are studied. External variables also affect ARIMA model accuracy. The findings aid weather forecasting and disaster preparation.

LSTM analysis including its helper functions, Pandas Profiling, plotting of the time series, Exponential Smoothing, Simple Exp Smoothing, Holt, Augmented Dickey Fuller test.

This repo is about forecasting the Yen movements in order to know whether to be long or short.

Build a forecasting model to predict the sale of a store.

Automating time series stationarity tests

Unemployment Rate Forecasting using Time Series techniques, leveraging Statsmodels, LSTMs, and Facebook's Prophet library to predict future unemployment trends. The project includes model comparison, hyperparameter tuning, and visualization of forecasted results.

This assignment relates to my 6th assignment in Econ 323 - Econometrics Analysis 2. It deals with GDP time series data.

Time Series Analysis of CO2_emission. Study from exercise E3 of 'Physics and Finance'

Industrial Production Index Time Series Forecasting using a range of models including Holt-Winters, ARIMA, SARIMA, LSTMs, and Facebook's Prophet. The project focuses on predicting production trends through model evaluation, tuning, and visualization of forecasted outcomes.

This project uses time series forecasting to predict future milk production. The data used in this project is monthly milk production data from January 1962 to December 1975. The ARIMA (autoregressive integrated moving average) model is used to forecast the milk production. The model is evaluated using various metric.

This repository covers essential techniques for time series analysis and forecasting. It covers data manipulation and visualization using Numpy and Pandas, time series analysis with Statsmodels, ARIMA models, deep learning methods like RNNs, LSTM, GRU, etc. and Facebook's Prophet library.