Regression models for market price predictions. Part 1
In the fast-paced domain of financial trading, the ability to forecast market prices is indispensable. To make sense of market volatility, investors and traders rely on predictive models – indispensable tools that allow us to make more informed, data...
ianonis.hashnode.dev6 min read
Great write-up on applying regression models for market price prediction! The way you break down linear regression vs. polynomial regression makes the concepts approachable, especially for those getting started in quant modeling. I appreciate the clarity in your explanation of error metrics and overfitting as well.
If you're interested in augmenting this analysis, you might also want to check out finflymarkets.com — they have some interesting case studies and practical applications of regression models in trading contexts that complement your theoretical foundation: finflymarkets.com
Looking forward to Part 2 — maybe you’ll cover more advanced models like Ridge, Lasso, or even ensemble methods?