R Time series packages not included in CRAN Task View: Time Series Analysis

Financial Time Series Analysis

A stock price prediction model based on ARMA and GARCH

Detailed implementation of various time series analysis models and concepts on real datasets.

Machine learning model built for IBM Hack 2020 challenge. ⚙️

Test various time-series Models to predict future movements in the value of the Japanese yen versus the U.S. dollar.

Demonstration of time series analysis using various concepts and models.

In this section, we will perform time series analysis by participating in the Gdz Elektrik Datathon 2023 competition.

In this section, we will estimate airline passengers using time series methods.

In this section, we will examine the Statistical Methods in time series analysis.

A thorough analysis studying the correlations and patterns of natural disasters across time and region in the United States using Python.

Predicts future movements in the value of the Canadian dollar versus the Japanese yen using Time Series Modelling and Regression Analysis.

Forecasted with Time Series Analysis and Regression for a potential outlook on the volatility of the yen. For the regression analysis, the preparation of the data required lagging returns, and after was used for a Linear Regression model. As for the Time Series Analysis, a Hodrick-Prescott filter was used which was followed by ARMA and ARIMA for…

This repository holds 2 Jupyter notebooks and one csv file on Time Series analysis for the A Yen for the Future exercises. The purpose of this code is to demonstrate understanding of time series work in Python: ARMA, ARIMA and related concepts.

📈 Application of neural networks in the prediction of PETR4.SA shares, compared with statistical models

The project involves the analysis and forecasting of time series on financial data.

In this project, I will use time series models to forecast the future outcome of the yen versus the US dollar.

In the second semester of 2021 - 2022, I took the course "Stochastic Process", which included programming exercises and projects in MATLAB language in the above files and you can see.

ARIMA model from scratch using numpy and pandas.

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.