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A Complete Guide to Time Series Analysis of Stocks.

Download Complete guide to Time Series Analysis of Stocks using Arima in R programming

Introduction:

Time series analysis is a major branch in statistics that mainly focuses on analyzing data set to study the characteristics of the data and extract meaningful statistics in order to predict future values of the series. There are two methods in time series analysis, namely: frequency-domain and time- domain. The former is based mostly on Fourier Transform while the latter closely investigates the auto correlation of the series and is of great use of Box-Jenkins and ARCH/GARCH methods to perform forecast of the series.

Stock price prediction is an important topic in finance and economies which has spurred the interest researchers over the years to develop better predictive models. The Auto Regressive Integrated Moving Average (ARIMA) models have been explored in literature for Time Series prediction. This paper presents extensive process of building stock price predictive model using the ARlMA model.

Nowadays, the stock markets have attracted the interest of many people for investing in the money and buying shares, due to its high returns. High returns also indicate the presence of high risk in investing and volatility of the stock prices. Recently, people are more interested in building appropriate models for prediction of stock prices to reduce the risk in investing and getting high Stock returns.

Published stock data obtained from Bombay Stock Exchange (BSE) are used with stock price predictive model developed. Results obtained reveal that the ARIMA model has a strong potential or short-term prediction and can compete favorably with existing techniques for stock price prediction. Later, we will use ARCH model to tackle the problem of volatility in the prices.

Before proceeding towards the basic assumptions, data description, data analysis and interpretations, first we will learn the basic terminologies that are involved in this field including Stock Markets, the two most popular Indian Stock Exchanges and their Stock indices.