PROJECT TITLE :
A Prediction Approach for Stock Market Volatility Based on Time Series Data
Due to its widespread application in numerous practical domains, time series analysis and forecasting are crucial. When we talk about time series data, we're talking about a set of data points that occur at regular intervals of time.
The stock market is one of the most complicated financial systems because it consists of many different stocks, each with a different price that changes dramatically over time. Stock market forecasting entails figuring out long-term market trends.
All the stock market investors aim to maximize the returns over their investments and minimize the risks associated. Stock markets being highly sensitive and susceptible to quick changes, the main aim of stock-trend prediction is to develop new innovative approaches to foresee the stocks that result in high profits.
This research tries to analyze the time series data of the Indian stock market and build a statistical model that could efficiently predict the future stocks.
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