When Linear Regression Fails: The Hidden Pitfalls Every Analyst Should Know
Author(s): Siddharth Mahato Originally published on Towards AI. “All models are wrong, but some are useful.” ~ George Box Linear Regression, perhaps the oldest statistical model, is the perfect example of this truth. Photo by Radek Kilijanek on Unsplash Introduction: The Deceptive …
Quantifying Portfolio Risk Using Python: A Deep Dive into Historical Value at Risk (VaR)
Author(s): Siddharth Mahato Originally published on Towards AI. Risk, the unseen current of finance, flows through every investment decision. To grasp the nature of loss is to truly understand the meaning of gain. This research describes the quantification of VaR using Python …
Beyond ML Loss Function: Cost Functions and Hypothesis Testing in Supply Chain
Author(s): Siddharth Mahato Originally published on Towards AI. Understand how Cost Functions and Statistics can help you go beyond accuracy with visuals and examples. Source: Image on Unsplash Manufacturing is a large and crucial part of the economy. It involves processing and …
Risk-Adjusted Returns with Python (Part 2): Sharpe Ratio versus Treynor Ratio (Friends or Foes)
Author(s): Siddharth Mahato Originally published on Towards AI. Two legendary metrics for measuring risk-adjusted performance. Which one should you trust for your portfolio? Introduction In Part 1, we analyzed and understood about the Treynor Ratio, a metric to measure investment performance based …
Risk-Adjusted Returns with Python (Part 1): The Treynor Ratio
Author(s): Siddharth Mahato Originally published on Towards AI. “Risk comes from not knowing what you’re doing.” — Warren Buffett Most investors chase returns. But ask any seasoned fund manager, and you’ll hear a different question:“Am I being rewarded fairly for the risks …
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