A Workflow for Statistical and Indicator Analysis of Price Data

Summary

This analysis workflow loads historical bars into a tabular dataset and plots closing prices to inspect gaps. It applies a Ljung–Box test for serial dependence, an augmented Dickey–Fuller test for stationarity, and autocorrelation and partial autocorrelation plots. It then estimates average true range, compares volatility with a cost allowance, summarizes percentage price changes, and can calculate selected technical indicators. Resampling supports analysis at multiple time intervals, while a chart routine illustrates price crossings of bands built from a moving average and standard deviation.

The code offers descriptive diagnostics rather than a validated trading system. It provides no sample results, predictive tests, or out-of-sample evidence, and its statistical interpretations and implementation choices require review; for example, price levels may need different treatment from returns, and the stated growth calculation divides by current close. The workflow does not establish profitable signals or account for execution effects.

Key ideas

• The workflow combines visual inspection with tests for serial dependence and stationarity.
• It summarizes price changes and ATR-based volatility alongside configurable technical indicators.
• It resamples bars to compare diagnostics across multiple time intervals.
• Its band-crossing chart illustrates candidate signals but does not demonstrate profitability.
• Statistical interpretation and implementation details should be checked before drawing conclusions.

Tags

From a private course collection; the original is not published.