filmov
tv
Prediction of Stock Market Price Using R Programming Language
Показать описание
#datascience #machinelearning #prediction
Download source code:-
library(quantmod): Quantitative Financial Modelling Framework (use to load a variety of data from different sources).
library(tseries): tseries stands for Time Series Analysis and Computational Finance. Imports: graphics, stats, utils, quadprog, zoo, quantmod, and other statistical operations like ADF test, p value test.
library(timeSeries): Basic functions such as scaling and sorting, sub-setting, mathematical operations, and statistical functions.
library(forecast): Provides Methods and tools for displaying and analyzing univariate time series forecasts including exponential smoothing via state space models and automatic ARIMA modelling.
Arima Model: (auto-regressive integrated moving average)
ARIMA models provide another approach to time series forecasting. Exponential smoothing and ARIMA models are the two most widely used approaches to time series forecasting and provide complementary approaches to the problem. While exponential smoothing models are based on a description of the trend and seasonality in the data, ARIMA models aim to describe the autocorrelations in the data.
Team members:-
Shreyas Rathod
Anup Singh
Vikaskumar Dubey
Shivam Dubey
Special thanks to:-
Dr. Anand Khandare
Dr. Prachi Janrao
Shailesh Sangle
Ashwini Patil
Anushree Patkar
Download source code:-
library(quantmod): Quantitative Financial Modelling Framework (use to load a variety of data from different sources).
library(tseries): tseries stands for Time Series Analysis and Computational Finance. Imports: graphics, stats, utils, quadprog, zoo, quantmod, and other statistical operations like ADF test, p value test.
library(timeSeries): Basic functions such as scaling and sorting, sub-setting, mathematical operations, and statistical functions.
library(forecast): Provides Methods and tools for displaying and analyzing univariate time series forecasts including exponential smoothing via state space models and automatic ARIMA modelling.
Arima Model: (auto-regressive integrated moving average)
ARIMA models provide another approach to time series forecasting. Exponential smoothing and ARIMA models are the two most widely used approaches to time series forecasting and provide complementary approaches to the problem. While exponential smoothing models are based on a description of the trend and seasonality in the data, ARIMA models aim to describe the autocorrelations in the data.
Team members:-
Shreyas Rathod
Anup Singh
Vikaskumar Dubey
Shivam Dubey
Special thanks to:-
Dr. Anand Khandare
Dr. Prachi Janrao
Shailesh Sangle
Ashwini Patil
Anushree Patkar
Комментарии