Deep dives into AI forecasting, systematic trading infrastructure, and the engineering behind Mintzy's financial intelligence platform.
Every trader has asked this question at some point: Can I really make ₹1 crore from the stock market? While some believe it's completely impossible, others think all it takes is finding the right multibagger stock.
Ask experienced traders about their most memorable milestone, and many won't talk about their first crore. Instead, they'll remember the day their portfolio first crossed ₹10 lakh.
A few years ago, this question would have sounded like science fiction. Today, it's one of the most debated topics in finance. Can AI really beat the market, or is it just an overhyped research tool?
Information is no longer scarce—everyone has access to the same live price feeds and reports. The real advantage today comes from intelligence infrastructure that separates signal from noise.
Every few years, someone claims Warren Buffett's style is obsolete in the age of algorithms and AI. If he were 25 years old today in 2026, would he still become the investor we know?
Social media is flooded with claims of turning small accounts into fortunes. Can you really make a living from trading? Yes, but very few do because of how they approach the profession.
Traders constantly search for faster execution, secret indicators, or more charts. But most trading struggles aren't caused by missing information—they are caused by how that information is processed.
One of the biggest misconceptions in trading is that success belongs to those who make the most accurate predictions. In reality, the market has never paid anyone for being right.
When AI stops being a research assistant and becomes an operator—Mintzy supplies the intelligence layer while Claude runs the systematic execution workflow.
Commercial banks face immense risks from bad debt. Discover how advanced models, specifically Random Forest, are being used to predict loan defaults with up to 89.11% accuracy to improve overall risk management.
Mintzy Seed transforms raw market data into clear trading signals. No complex configuration, no hidden logic — just practical insights traders can actually act on.
Tackling the challenge of imbalanced datasets using SMOTE. We compare Random Forest, XGBoost, LSTM, and more using metrics like AUC-PR to find the best model for predicting financial risk.
