Can a Long Short-Term Memory Model Produce Accurate Stock Price Predictions?: A Deep Learning Approach to Predicting Apple Inc. Stock Price.

[R] Statistical analysis of financial data conducted in R

Pharma Sales Analysis and Forecasting using ARIMA, PROPHET and NEURAL NETWORKS

Time Series Analysis of Zillow data

ACF || PACF || ARIMA || SARIMA

Predict the apple stock market price for next 30 days. There are Open, High, Low and Close price has been given for each day starting from 2012 to 2019 for Apple stock.

Trabalho realizado para aprovação na disciplina de Análise de Séries Temporais. Foi realizado a análise e modelagem da serie temporal da entrega de fertilizantes ao mercado brasileiro em mil toneladas no período mensal de janeiro de 1998 até abril de 2020 (Fonte: ANDA)

Experimental notebooks on blink detection problem by analizing it with simple thresholds, timeseries approach and a ml model.

Predictive analysis and GARCH model on stock returns. I demonstrate how to use the PACF (partial autocorrelation function) and ACF (autocorrelation function) on a non stationary time series.

Autoregression is a time series model that uses observations from previous time steps as input to a regression equation to predict the value at the next time step.

This repository contains source code implementation of assignments for NTU's MSAI course AI6123 on Time Series Analysis (2019 Sem 2).

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

Auto ARIMA Model

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.

Demonstração de AutoCorrelação de Série Temporais no Python com Gráficos Interativos e Gráficos Analíticos ACF e PACF

total raw governmental industry employment data from January 1 1939 to October 30 2019. Time Series analysis to forecast employment from October 2019-October 2020.

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.

Time Series Forecasting Methods to forecast Daily Post Publications on Medium

This model predicts furniture sales on account of 4 year sales record.