Built by a trader.
For serious traders.
Progressive Trinity started as a personal problem. The tools available to retail traders in India were either too simple to be useful or too expensive to be accessible. So we built what we needed — and kept going until it was institutional grade.
The problem was always the same.
Professional fund managers at institutional desks have Bloomberg terminals, quant teams, and decades of backtested models. They know the regime before they place a trade. They know the historical base rate of every setup. They size positions to their edge.
Retail traders in India — even experienced ones — were making the same decisions with forum tips, basic screeners, and gut feel. The information asymmetry was structural, not accidental.
Progressive Trinity was built to close that gap. Not to simplify institutional tools — to make the actual tools accessible.
Trinity Architecture
Three independent engines. Each one validates a different dimension of an opportunity. All three must align for a high-conviction signal.
One number. Three dimensions.
Every instrument in the universe receives a DNA Score from 0 to 100, updated daily. It combines Quality (Fundamental pillar), Timing (Technical pillar), and Edge (Quantitative pillar) into a single conviction score. A score above 80 triggers a HIGH confidence signal with 2.5% position sizing. Below 60 is LOW — 0.75% maximum.
We start with the business. Piotroski F-Score measures financial health across nine criteria. Beneish M-Score detects earnings manipulation. Free cash flow analysis cuts through accounting noise. The PTQ Forensic Score combines all three into a single quality verdict. If the business is deteriorating, no technical setup or quant signal can save the trade.
Timing matters. A fundamentally strong business in a distribution phase is a losing trade. Our 32-indicator confluence engine combines Fibonacci retracements, Ichimoku cloud, RSI positioning, 200-day EMA, and Bollinger Bands into a single timing score. Chart pattern detection confirms setups across daily and weekly timeframes — multi-timeframe confirmation only.
The mathematical edge. Z-score measures how far a price has deviated from its statistical mean — our entry trigger for mean reversion. The Hurst exponent classifies market regimes: below 0.5 means mean-reverting, above 0.5 means trending. We only trade when the regime supports the strategy. Kalman filter removes noise. Markov chains model state transitions. XGBoost predicts win probability.
Four principles we don't compromise on
Six years in the making
Three markets. One platform.
Ready to trade with the edge?
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