# Strategy portfolios: *one pool of money*

Author: Jiří Fabšic · Jul 6, 2026 · Category: Methodology
Canonical URL: https://www.binaryfintech.com/en/blog/strategy-portfolios/

> Why smoother equity and lower drawdowns come from composing uncorrelated strategies, instruments and asset classes, why a portfolio cannot be computed by adding two backtests — capital is one pool — and how concurrent strategies are tested over a single account.

## TL;DR

- **Smoother equity and lower drawdowns are not made by improving one strategy** — that road ends in overfitting. They are made by composing a portfolio — out of uncorrelated strategies, instruments and asset classes.
- **A portfolio cannot be computed by adding two backtests.** Capital is one pool: funds locked by one strategy are unavailable to the other. The real sequence of events decides the outcome.
- **That is why concurrent strategies are tested as concurrent:** multiple strategies in one engine over one account. The result is one real equity curve — not an arithmetic illusion.

The perfect strategy does not exist. Every strategy has periods when the market does not go its way — and whoever tries to “fix” that with more parameter tuning usually ends up [memorizing the noise of one history](https://www.binaryfintech.com/en/blog/overfitting/). The real path to smoother equity leads elsewhere: **place strategies side by side whose weak periods do not coincide.** The most valuable property of a second strategy is not its return — it is its *lack of correlation* with the first one. And you can compose at many levels: the same strategy on multiple instruments, several strategies of different types side by side, different asset classes — indices, equities, crypto, commodities — and even different settings of the same logic.

## Why non-correlation smooths

The intuition is simple: when strategy A goes through a drawdown, an uncorrelated strategy B has no reason to go through its own in the same week. One's losses meet the other's gains or calm — and the portfolio breathes more steadily than any of its parts. The mathematics agrees: for two strategies with equal risk and zero correlation, the volatility of an equally weighted portfolio drops by roughly 30 % (a factor of √2) — with no discount on expected return. Every additional genuinely independent strategy strengthens the effect.

Correlation here is a number between −1 and +1, computed from **returns**, not from the similarity of rules: +1 means the equity curves breathe in the same rhythm, 0 means independence, −1 a mirror image. Correlation near zero is plenty for smoothing — negative correlation is a rare luxury. One thing always holds, though: **correlation is not a constant.** It tends to be low in calm markets and rises toward +1 in a panic — markets fall together. So we size the portfolio for crisis correlation, not the average one; it is the same humility that [black swans](https://www.binaryfintech.com/en/blog/black-swans-fat-tails/) teach.

This is the right place to smooth equity and reduce drawdowns. Not cosmetics on a single strategy — **portfolio composition.**

## Levels of composition: instrument, universe, type, class

A portfolio is not composed merely of “strategy A + strategy B”. Uncorrelated sources of return can be found at several levels — and the best portfolios combine all of them:

- **Multiple instruments, same strategy.** A trend logic deployed on ten markets is not one system but ten related sources of return: the rules are the same, the stories of the markets are not. Bitcoin, gold and an equity index do not trend in the same weeks — even this simplest level smooths equity noticeably.
- **Whole universes.** One step further: we do not deploy a strategy on a hand-picked market but on a defined [*universe*](https://www.binaryfintech.com/en/blog/instrument-universes/) — a basket of instruments meeting the strategy's conditions (liquidity, volatility, available history). Diversification is then a property of the deployment from day one, not an afterthought — and the universe also guards against the strategy standing or falling with one chosen market.
- **Multiple strategy types.** Trend following, mean reversion, breakout, seasonality: different types profit from different market behaviour, which makes them naturally the least correlated. This is where most of the smoothing comes from.
- **Multiple asset classes.** Indices, equities, commodity futures, currencies, crypto, prediction markets — each class lives its own macro story. A crypto panic may mean nothing to grain seasonality.
- **Settings and combinations of the same logic.** The finest level: the same strategy in several settings or timeframes. Siblings stay similar — correlation will be higher than between unrelated strategies — but it spreads the sensitivity to a single “tuned” number we described in [overfitting](https://www.binaryfintech.com/en/blog/overfitting/).

And composition does not stop at a pair of strategies — **the same logic repeats floor by floor upward.** Strategies compose into sub-portfolios: say, trend with mean reversion, longs with shorts, or a profit engine with its hedge. Sub-portfolios compose into segments with clear roles — for example bonds as the calm foundation, equities with dividends and indices as the core, crypto as the declared risk component. The specific combinations are always just examples — the principle is general: **compose uncorrelated sources and test the concurrency honestly.** At the very top sits the only number that is actually lived: **one equity curve of the whole portfolio.**

*Figure: Composing upward: instruments and universes carry strategies, strategies carry sub-portfolios, segments then form one portfolio with one equity curve. The combinations on each floor are illustrative examples, not a prescription.*

## Why you cannot add two backtests

Now the treacherous part. A shortcut suggests itself: I have a backtest of strategy A, a backtest of strategy B — I add the equity curves and I have a “portfolio”. **I do not.** I have a chart of a portfolio that could never have existed, for three reasons:

1. **Capital is one pool.** When strategy A opens a position, it locks funds — and at that moment they are *not* available to strategy B. Standalone backtests never see this collision: each assumes it has the whole pool to itself. Adding two such runs produces a portfolio that, in total, spends more money than it has.
1. **Collisions over entries.** Both strategies may want to enter at the same moment. Live, the one with funds remaining enters — the other does not get the trade. Which trade is lost is decided by the sequence of events, not arithmetic.
1. **Compounding over time.** Capital compounds and reallocates continuously: strategy A's January profit changes the position sizes of strategy B in February. Two separate backtests know nothing of this coupling.

Running strategies concurrently is, plainly, **the real handling of a single pool of money** — and that is how it must be tested.

## Time in the market: capital tetris

In [the sizing article](https://www.binaryfintech.com/en/blog/position-sizing-kelly/) we showed why to measure the share of time in the market (market exposure). When composing a portfolio, this metric becomes the key: **low-exposure strategies complement each other.** One strategy's gaps are filled by the other's positions — the same capital serves two independent sources of profit, and its utilization rises without concentrating risk. The ideal pair for a portfolio: uncorrelated signals *and* complementary exposures.

*Figure: One strategy's gaps are filled by the other's positions. The same pool of capital works more of the time — on two independent sources of profit.*

High utilization by itself is not the goal, though — it becomes the real thing only when the capital works in **the best, or at least decently profitable, strategies** the portfolio has to offer. And every strategy deserves one more forward-looking question: **how much capital will it probably demand over its whole life cycle** — from deployment through growing positions to the day it is retired. Strategies are not eternal: they are born, they carry, they end. Plan a strategy's capital appetite all the way to retirement, and concurrency will not surprise you with two strategies asking for the same money at the worst possible moment.

## How we test concurrent strategies

Our engine runs **multiple strategies at once, over a single account and a single pool of capital** — each with its own logic, its own timing and its own risk profile. Collisions are resolved the way an exchange resolves them: funds locked by an open position are locked for everyone, and an order without sufficient free funds is rejected — in testing and live, along [the same path](https://www.binaryfintech.com/en/blog/event-driven-backtesting/). The result is one real portfolio equity curve plus a per-strategy breakdown — and since a portfolio is just another testable unit to the engine, the whole chain applies to it: [walk-forward](https://www.binaryfintech.com/en/blog/walk-forward-analysis/) and [Monte Carlo](https://www.binaryfintech.com/en/blog/monte-carlo-simulation/) over the portfolio as a whole.

That is exactly what our [BXF](https://bxf.binaryfintech.com) platform is built around: you compose a portfolio at all of the levels above — across strategies, instruments, whole universes and asset classes, from stocks and futures to crypto and prediction markets — and test it as a single whole, on a single equity curve.

## What to watch in a portfolio

- **Correlation of strategy returns** — computed from realized returns (daily or weekly), not from signal similarity. Low correlation is the ticket into the portfolio.
- **Exposure overlap in time** — how often both want to be in the market at once. High overlap means crowding over the same capital and less benefit from composition.
- **Portfolio drawdown vs. component drawdowns** — the goal is for the portfolio to fall less than its worst part. If it does not, the strategies are not as independent as they looked.
- **Capital utilization** — how much of the time the pool actually works, and whether it works in the most profitable strategies available.
- **Risk concentration** — no single strategy should dominate total risk, or the portfolio is just one bet dressed up as diversification.

## Composition > tuning

One last thought worth keeping: when the equity curve is not smooth enough, instinct says tune the strategy. Resist it. Tuning beyond reason manufactures [overfitted fragility](https://www.binaryfintech.com/en/blog/overfitting/); composing uncorrelated, individually sober strategies manufactures **robust portfolios**. You do not buy a smooth equity curve from one perfect strategy — you assemble it from several imperfect ones that complement each other.

**Reading:** Related articles: [How much to bet: Kelly and time in the market](https://www.binaryfintech.com/en/blog/position-sizing-kelly/) · [A backtest that behaves like the live market](https://www.binaryfintech.com/en/blog/event-driven-backtesting/) · [Overfitting](https://www.binaryfintech.com/en/blog/overfitting/) · [Monte Carlo](https://www.binaryfintech.com/en/blog/monte-carlo-simulation/) · [How many strategies is too many](https://www.binaryfintech.com/en/blog/how-many-strategies/). The full journey from idea to production: [the strategy testing protocol](https://www.binaryfintech.com/en/blog/strategy-testing-protocol/).