Skip to content

Time Series

What is time series forecasting

Time series forecasting is a statistical or machine learning technique that uses historical and current data to predict future values over a period of time or a specific point in the future. It involves building models from historical data and using them to make observations

Forecasting has a range of applications in various industries especially the stock market!

Key features

  • Time Series Data- A sequence of data points collected or recorded at regular time intervals, such as daily stock prices.
  • Trends- Long-term movement of data in a certain direction, which can be upward (bullish), downward (bearish), or flat.
  • Seasonality- Repeating short-term patterns within the data, often influenced by specific time periods like quarters or months.
  • Stationarity- A stationary time series has properties like mean and variance that do not change over time, which is essential for many forecasting models.