Time Series Forecasting with ARIMA GARCH

Financial time series forecasting using R

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.

Modeling Value-at-Risk of a Mongolian Exchange Rae (MNT/USD) using the GARCH type model in Python

Time Series Analysis in Finance

[PL] My master thesis from PUEB

Forecasting stock price volaitlity using GARCH models

Applied Regression and Time Series for Financial Research

Time Series Analysis - Yen for the Future

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

Sentiment analysis of financial news in Russian and application of it's results in volatility modeling

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

Project in Statistics: Timeseries analysis (STAH14) at Lund University. The project it about Bitcoin price and returns, modelled using an AR-GARCH model.

Project for "Advanced time series analysis" course

Apply GARCH (1,1) model into forecasting S&P500. The topic is harder than though so it's still under construction but I'm working on it.

Repository for keeping the code used for project of the course Financial Econometrics / Financial Time Series.

Artigo finalizado em 06/08/2021 como membro do Núcleo de Riscos & Derivativos, para o Clube de Finanças, Liga Acadêmica de Mercado Financeiro da UDESC & UFSC.

Predicting Market Volatility

This is a project which uses Data Science, Machine learning to predict the stock movements, minimize the risk and maximise gains of portfolio using fama-french factors and many other models.Also the sentiment towards stocks are also monitored using sentiment analysis. Garch Model is used to predict the volatility and movements for intraday trading.