1.Summary Stats

Describe quantitatively key metrics for location, dispersion, distribution shape, and dependencies.

2.Statistical Testing

Examine significance and verify assumptions (e.g., Normality, stationary, cointegration).

3.Data Fitting

Construct fitting curves using Interpolation, smoothing, or non-parametric fitting algorithms.

4.Transform

Transform your sample data values for the best results.

5.Statistical Sampling

Sort, Shuffle, or draw (subset or random) a set of observations from your sample data.

6.Smoothing

Remove noise and uncover important components: level, trend, and seasonality.

7.ARMA/ARIMA

Capture serial correlations with ARMA family models for accurate forecasts.

8.ARCH/GARCH

Model variance variability with GARCH family models for volatility forecasts.

9.Date & Calendar

Account for dates and calendar-related issues for best results.

10.Forecasting Performance

Evaluate, track and compare the accuracy of forecasting processes or models.

11.Factor Analysis

Uncover patterns or investigate relationships among correlated variables.

12.Spectral Analysis

Decompose time series into a spectrum of primary components (e.g., DFT, Filtering).

13.Portfolio Analysis

Analyze portfolio for returns, variance, and covariance, simulate correlation of assets and calculate portfolio value at risk (VaR).

14.Utilities

Process data in text format, handle missing value occurrences, and manipulate arrays in Excel.