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SPTS is a comprehensive statistical trading package offering advanced mathematical functions including t-tests, correlations, regressions, and distribution analysis for traders seeking deeper quantitative insights.
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SPTS performs complex statistical analyses using mathematical functions not native to Pine Script. It includes capabilities for one-tailed and two-tailed t-tests, Pearson correlations, quadratic correlations, R-squared assessments, linear and multiple regressions, normality tests, and basic ARIMA modeling.
Users can input different variables and receive detailed statistical outputs, including p-values, correlation coefficients, and distribution characteristics. The package is designed to mimic advanced statistical software like SPSS and Excel within the TradingView environment
Why it may be useful
Traders need sophisticated statistical tools to validate trading hypotheses and understand market relationships. SPTS provides comprehensive mathematical analysis capabilities directly within TradingView, eliminating the need for external software.
By offering functions like t-tests, correlation assessments, and regression models, traders can quantitatively evaluate market dynamics, assess asset relationships, test trading strategies, and make more informed decisions. The package bridges the gap between complex statistical analysis and practical trading applications
When to explore it
SPTS is most effective when traders need rigorous quantitative analysis of market data. It's particularly useful for evaluating correlations between different assets, testing trading hypotheses, assessing market efficiency, and understanding complex market relationships.
Traders can use it to compare risk profiles, analyze pairs trading strategies, evaluate volatility, and perform in-depth statistical assessments. The package is ideal for mathematically-oriented traders who want to move beyond basic technical indicators and dive into more sophisticated statistical modeling
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What we’ve verified
Access, alerts and repainting behaviour have not been independently verified for this indicator. Check the creator’s current publication and settings.
General descriptions and classifications are recovered research. Verified details above identify the specific checks we have completed. Check the creator’s current publication for later changes.




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