Time-Series Forecasting: Predicting stock prices based upon Yahou Finance Data of Tesla, Inc. (TSLA) NasdaqGS - NasdaqGS Real Time Price. Currency in USD.
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date: 23/12/22
Time series data is a sequence of data points that are collected at regular intervals over a period of time. These data points are typically collected at a fixed time interval, such as every minute, hour, day, or month. Time series data is often used to analyze trends and patterns over time, such as changes in stock prices, weather patterns, or website traffic. It is often used in fields such as finance, economics, and meteorology.
Time series forecasting is the process of using historical data to make predictions about future events. It is a common technique that is used in a wide variety of fields, including finance, economics, and meteorology, to name a few. There are many reasons why time series forecasting is useful:
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1: Understanding trends and patterns: Time series forecasting can help you understand how a particular metric or variable changes over time, which can be useful for identifying trends and patterns. This can be helpful for making informed decisions about the future.
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2: Making predictions: Time series forecasting allows you to make predictions about future events based on past data. This can be useful for predicting future demand for a product, forecasting sales revenue, or predicting future weather patterns.
