Time Series Analysis in Finance
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Updated
Feb 20, 2024 - R
Time Series Analysis in Finance
Modeling Value-at-Risk of a Mongolian Exchange Rae (MNT/USD) using the GARCH type model in Python
Time Series Forecasting with ARIMA GARCH
Financial time series forecasting using R
[PL] My master thesis from PUEB
Time Series Analysis - Yen for the Future
Detailed implementation of various time series analysis models and concepts on real datasets.
Forecasting stock price volaitlity using GARCH models
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.
Testing various time-series tool to predict future movements in the value of the Japanese yen versus the U.S. dollar.
Project for "Advanced time series analysis" course
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.
Time Series Analysis
This project aims to model different Time Series data (mostly Stock data) by carrying out detailed analysis and fitting appropriate models.
Welcome to the repository for my conference paper on stock market analysis and predictive models. In this paper, I explore various models to analyze and predict stock market trends. I have employed a combination of traditional time series models and modern machine learning techniques to provide insights into stock price movements.
Statistical analysis with R by using financial data
Análise via modelos GARCHs para preços da PETR4 utilizando o R.
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