This is time series analysis of Tata Steel Stock Data
Time series data is a sequence of data points in chronological order that is used by businesses to analyze past data and make future predictions. These data points are a set of observations at specified times and equal intervals, typically with a datetime index and corresponding value. Common examples of time series data in our day-to-day lives include:
Measuring weather temperatures
Measuring the number of taxi rides per month
Predicting a company’s stock prices for the next day
Components of Time Series
Time series data consist of four components:
Trend Component: This is a variation that moves up or down in a reasonably predictable pattern over a long period.
Seasonality Component: is the variation that is regular and periodic and repeats itself over a specific period such as a day, week, month, season, etc.,
Cyclical Component: is the variation that corresponds with business or economic 'boom-bust' cycles or follows their own peculiar cycles, and
Random Component: is the variation that is erratic or residual and does not fall under any of the above three classifications.
About the Stock Data Now that our data has been converted into the desired format, let’s take a look at its various columns for further analysis.
The Open and Close columns indicate the opening and closing price of the stocks on a particular day.
The High and Low columns provide the highest and the lowest price for the stock on a particular day, respectively.
The Volume column tells us the total volume of stocks traded on a particular day.
The volume weighted average price (VWAP) is a trading benchmark used by traders that gives the average price a security has traded at throughout the day, based on both volume and price. It is important because it provides traders with insight into both the trend and value of a security.