Time Series Forecast

Time series forecast is an important method in quantitative trading used to predict future price movements, based on linear regression model for prediction.

Calculation Principle

Time series forecast is calculated using the following formula:

y = a + b × (x + timeperiod)

Where:

• y: Predicted value
• a: Intercept
• b: Slope
• x: Time series
• timeperiod: Forecast period

Parameter Description

• Input Parameters: One K-line data series
• timeperiod: Calculation period, default 14
• Output: Predicted value

Usage Recommendations

1. Adjust calculation period according to actual needs
2. Pay attention to data time span
3. Consider data frequency
4. Pay attention to data alignment
5. Recalculate periodically
6. Pay attention to result interpretation
7. Combine with other technical indicators
8. Pay attention to forecast accuracy
9. Consider forecast confidence intervals

Notes

• Ensure data quality
• Pay attention to data preprocessing
• Consider the impact of extreme values
• Pay attention to the impact of calculation period
• Consider data stationarity
• Pay attention to result stability
• Consider the impact of sample size
• Pay attention to trend persistence
• Consider changes in market environment
• Pay attention to forecast limitations
• Pay attention to forecast timeliness