How a book is built, and how we test it

From a whole universe to what you actually hold

Both equity strategies run the same disciplined pipeline each month — no overrides, no gut calls. Here's the path from index to portfolio. (MultiAsset rotates eight ETFs by score instead — there is no universe to rank.)

1. The universe. Every eligible name in the index — a broad, rules-defined starting field.
2. Multi-factor score. Each stock scored on peer-reviewed factors — momentum, trend, volatility & liquidity.
3. Ranked by conviction. Sorted highest-first, so only the strongest signals make the cut.
4. Sector-capped. No more than two names per industry — diversification is structural, not promised.
5. Your portfolio. The top names, held equal-weight until next month's rebalance.

How the list narrows, this month

All four counts come from this month's run. MultiAsset is not shown: it holds all 8 of its ETFs and only changes their weights, so there is nothing to narrow.

What the model looks at

Each candidate gets one score built from four families of signals that are well documented in the research: momentum, trend, volatility and liquidity — all of them read from prices and traded volumes. The exact signals and how they are weighted are MindForge’s own and are not published; what is published is the method around them:

• Monthly. The books are re-scored once a month, on the same beat as their backtests. Nothing trades in between.
• Equal weight in the stock books. Every holding is the same size, so no single name decides a month. MultiAsset weights its ETFs by score instead, because it allocates across asset classes rather than picking names.
• At most two per industry. A sector that dominates the ranking still cannot dominate the book.
• No discretion. No name is added, removed or resized by hand.

When this kind of model struggles

Books that rank stocks on their recent trends tend to do best when markets rise steadily and leadership persists. They have historically done worst in sharp rebounds after a fall, when the previous quarter’s laggards lead the bounce — the pattern documented by Kent Daniel and Tobias Moskowitz in “Momentum Crashes” (Journal of Financial Economics, 2016). In a broad fall most stocks fall together, and a book of recent leaders usually falls too.

Members see the market each book is moving in on their dashboard’s “Market weather” card, and anyone can see it on the Learn hub. None of it changes the model; it explains the month.

Built on fifty years of research

Factor investing is not a trend — it is peer-reviewed finance that has held up for fifty years. Every signal these models use has to clear five tests: persistent, pervasive, robust, investable, intuitive.

The fifty years, in four steps

• 1964 — CAPM — The first model. Sharpe, Lintner & Treynor showed that the only risk earning a return is market beta — undiversifiable systematic risk. This became the universal benchmark for separating genuine skill from factor exposure.
• 1992 — Beyond CAPM — the multi-factor era. Nobel laureate Eugene Fama and Kenneth French proved CAPM was incomplete. Additional return factors were shown to systematically explain stock returns that market beta could not. The multi-factor era of academic finance began.
• 1997 — The factor zoo expands. Over the following decades, researchers including Jegadeesh, Titman and Carhart documented further factor premia in equity markets, each surviving rigorous out-of-sample testing. Multi-factor models became the dominant framework for explaining cross-sectional returns.
• 2026 — MindForge — Applied to India. We apply academically validated factors to Indian listed equities and ETFs. Every strategy is built on factors that are persistent, pervasive, robust, investable and intuitive.

How the backtests are run

Each book is simulated month by month over its own window: the same universe, the same ranking, the same cap and the same sizing as today, with a cost on every trade and 20% short-term tax on every month that books a gain. The strategies page sets out the steps and the three places the simulation flatters us; the disclosures page has the full method.

• The strategies page: each book’s backtest beside its index
• Backtest methodology, in full

A backtest is a simulation, not a record. Every simulated figure on this site says “backtest” where it appears; only the live record is measured from published picks.