What is strategy expectancy and why it’s key to understanding returns

Why returns mean nothing without understanding the mechanics

Investors often look at a strategy’s final returns and draw conclusions about its quality.
However, the same result can be achieved in very different ways:

• through a consistent sequence of trades
• through rare but large movements
• through the accumulation of hidden risk

Without understanding the internal logic of the strategy, it’s impossible to assess how sustainable that result is.
This is where the key concept comes in – expectancy.

What expectancy is in simple terms

Expectancy (mathematical expectation) is a metric that answers the question:
How much does a strategy earn on average per trade?

The formula looks like this:

Expectancy = (сhance of winning × average profit) − (chance of losing × average loss)

In simple terms, it’s the balance between:

• how often the strategy wins
• and how much it earns or loses on each trade

Why a high win rate doesn’t guarantee success

One of the most common mistakes is focusing on the percentage of winning trades.

For example:

Strategy A:

• 80% winning trades
• average profit +1%
• average loss −5%

Strategy B:

• 40% winning trades
• average profit +5%
• average loss −1%

At first glance, Strategy A looks “safer.”
But in terms of expectancy, Strategy B is much more sustainable.

The reason:
Profit size matters more than frequency of wins.

How positive expectancy is created

A strategy has only two ways to generate profit:

1) Through high accuracy
The strategy often predicts the market direction correctly.
But this approach usually:

• is sensitive to market changes
• requires very stable signals

2)  Through payoff asymmetry
Profit in individual trades significantly exceeds losses.
This approach is more sustainable because:

• it doesn’t require high accuracy
• it handles market noise better
• it works in different market conditions

This is why many algorithmic strategies focus on:
small losses + large gains

The connection between expectancy and risk management

Even a strategy with positive expectancy can lose money if risk management is violated.

Key factors include:

• position size
• sequence of losses
• drawdown control

Expectancy shows the potential,
but risk management determines whether it is realized in practice.

Why strategies with positive expectancy can temporarily lose money

This is one of the most challenging concepts for investors.

Even with positive expectancy, there can be:

• losing streaks
• long periods without profit
• deviations from the average result

This is not a flaw in the strategy.
It’s normal behavior for any probabilistic model.

IQ Security Fund approach

At IQ Security Fund, strategies are built around sustainable positive expectancy.

This means:

• each trade has limited risk
• losses are quickly capped
• profits are generated from strong market moves
• results don’t rely on “guessing”

The core idea is simple:
It’s not about how the strategy performs on a single trade,
but how it performs over a series of trades.

Why expectancy is the most important metric for strategy quality

Unlike:

• raw returns
• win rate
• individual successful periods

Expectancy reveals the true economics of a strategy.

It answers the key question:
Does the strategy have a statistical edge?

• If not – the result is random.
• If yes – it will materialize over the long run.

Expectancy is the foundation of any sustainable strategy.

For an investor, it’s important to understand:

• how profit is generated
• how balanced risk and return are
• whether the strategy has a long-term edge

Because ultimately, profit is made not by the strategy that shows the best month,
but by the strategy with positive mathematical expectation – and the discipline to realize it.