What is Fixed Ratio Money Management?

Feb 1, 2021

Have you heard of fixed ratio money management? How does it compare to the popular fixed fractional approach? Here I’ll explain how fixed ratio works, and see how it stacks up against fixed fractional money management.

The fixed ratio money management approach was introduced by Ryan Jones in his book The Trading Game: Playing by the Numbers to Make Millions.

Like other money management approaches, it increases your lot size as your account grows, thereby compounding your trading returns.

It is a lesser-known alternative to the ever-popular fixed fractional (or fixed risk) money management approach. In the fixed fractional approach, you risk a fixed % of account equity per trade. Lot sizes are computed using the number of pips risked per trade.

Here is an example of fixed fractional money management. Suppose you want to risk 1% of a USD 10000 account, and you place a EURUSD trade with a 100-pip stop loss.

But what if you don’t know how many pips you’re risking per trade? Perhaps you don’t have a predetermined stop loss, or you are using indicator-based exits.

Fixed ratio money management can help you out.

Fixed Ratio Money Management Calculations

Calculating the required account equity for each lot size can be a little confusing. Let’s start with some definitions:

Lot increment

The amount that your lot sizes increase/decrease each time. Since we are dealing with forex, we’ll use a 0.01 lot increment.

Delta

The profit you need to accumulate, per lot increment, before you can increase your lot size by one increment.

The delta determines the aggressiveness of your money management. The smaller the delta, the faster your lot sizes increase, and the more risk you assume.

Equity Step

The additional profits you need to accumulate before you can increase sizing again.

Equity Step = Number of lot increments taken so far * Delta

Let’s illustrate fixed ratio with an example.

Suppose you start trading 0.01 lots with a $10000 account. You use a delta of $2000.

To compute how much equity you need to start trading 0.02 lots (blue box), you first compute the equity step as follows:

Equity step = 1 lot increment * $2000 Delta = $2000

Required equity = $10000 + $2000 = $12000

Likewise, if you’re trading 0.07 lots now, and will be reaching 0.08 lots soon (red box):

Equity step = 7 lot increments * $2000 Delta = $14000

Required equity = $14000 + $52000 = $66000

Notice how your chosen delta value remains constant, although the required equity step from the previous lot size increases with time.

Your lot sizes can be calculated using the equation:

So how does fixed ratio compare against fixed fractional money management?

To find out, let’s apply these two money management approaches to a EURUSD strategy and compare their return/max drawdown.

Baseline Trend Strategy

We will use a M30 EURUSD trend following strategy, which was automatically generated using StrategyQuant’s genetic algorithm. This strategy uses an oscillator of a moving average and the stochastic indicator for entries. A 60-pip stop loss helps with risk management. This stop loss distance will be used when computing lot sizes with the fixed fractional approach.

The backtest below shows the strategy’s performance over the past 17 years, using a fixed 0.1 lot size on a $10000 account. 

The equity curve contains a good mix of flat periods, run-ups, and drawdowns – perfect to test the effects of money management. Once we implement money management, we should expect both profits and drawdowns to increase.

Fixed Fractional Money Management

AlgoWizard offers fixed fractional as one of its default money management methods. This means you can very quickly add it to your strategy.

At the top right of your screen, you will find your current money management method.

Click on the method to open the money management settings.

We’ll select Risk fixed % balance and configure its settings. The strategy automatically detects the 60-pip stop loss, so we do not need to input the pips risked per trade.

  1. This is the % of your account that you risk per trade. Anything above 3% is pretty aggressive. Let’s be conservative and select 1%.
  2. This is the number of decimal places your lot size will contain. Since we can trade increments of 0.01 lots in forex, select 2.
  3. This is the ‘backup’ lot size that will be used if the fixed fractional computation fails for some reason. 0.01 is the minimum.
  4. This is the maximum lot size that can be traded. It overrides the fixed fractional computation. For testing purposes, I’ll input 5 lots. It will never be reached since we only risk 1% of the account.

Now let’s redo the backtest!

The blue chart labelled Volume shows the progression of the lot sizes. It doubled from the initial 0.16 to 0.32 lots, corresponding to a doubling of the account size.

The backtest metrics are shown above. Both net profit and drawdown have increased, but notice that the return/drawdown ratio has decreased from 4.74 to 4.09.

This is because the strategy’s deep drawdowns occurred after the lot sizes had increased significantly, resulting in larger gross losses. Conversely, if the strategy had all its worst drawdowns at the start of the backtest, the return/drawdown would have increased.

Since variable lot sizing has been applied, % Drawdown is more relevant than $ drawdown.

Take note of the 4.09 return/drawdown and the 14.56% drawdown. We will use these metrics to see how fixed ratio money management compares.

Fixed Ratio Money Management

When you start trading the account, accumulated profits are zero, so you need to decide on a starting lot size.

Since the fixed fractional approach above started with 0.16 lots, we’ll make 0.16 our starting lot size.

Remember how the delta value controls the aggressiveness of the fixed ratio approach?

To ensure a fair comparison with the fixed fractional approach, we’ll tailor the delta value such that we get a similar maximum drawdown of 14.56% over the backtest. 

I tried an initial $2000 delta and it only produced a 10% drawdown, so I repeatedly decreased the delta as shown below.

Turns out a $70 delta gives a 14.85% drawdown. That’s close enough for me.

With this delta value, I reran the backtest with fixed ratio money management.

The equity curve looks pretty similar to the fixed fractional one. Lot sizes also doubled from the initial 0.16, although both profits and drawdowns are now higher.

The return/drawdown is now 4.37, compared to 4.09 for the fixed fractional approach. Other performance metrics such as expectancy and profit factor are marginally higher too.

Why These Differences?

For the fixed ratio approach, only the accumulated profits and delta value were required when calculating lot sizes; individual trade risk was not considered.

For each lot size, I decided to find out the % of the account I was risking per trade with the fixed ratio approach.

In the table below, Mid Point of Required Equity refers to the average of the required equities for the current lot size and the next larger lot size.

The risk per trade is calculated as Lot Size * 60-pip stop loss * $10/pip.

It seems that you’re risking a larger % of your account during the earlier stages of the backtest. As lot sizes continue to increase past 0.33, the percentage continues to drop.

Contrast this with the fixed fractional approach, where 1% of your account is risked every trade.

This unequal approach to trade risk is likely the reason behind the differences.

Verdict: Fixed Fractional vs. Fixed Ratio Money Management

So fixed ratio outperformed the fixed fractional approach in the above example. Does this mean fixed ratio is universally better?

No!

Money management, like any other strategy parameter, can be optimized to suit a particular backtest. For the particular sequence of trades in the backtest above, fixed ratio money management just happened to perform better.

In fact, the fixed ratio’s unequal approach to individual trade risk doesn’t sound good to me. Since you never know when your strategy will underperform, why risk a larger amount at any point in time?

The fixed fractional approach is easier to calculate (and program), and risk is distributed evenly. This is probably the reason for its enduring popularity.

I’d conclude that fixed ratio is certainly a viable alternative to the fixed fractional approach, but I can’t think of any reason why it would consistently outperform the latter. If you’re unsure, or new to trading, I recommend sticking to the simpler and more conservative option – Fixed fractional money management.

When discussing portfolio trading under the strategy development section, my money management approach was simply to trade a fixed number of lots for every unit of account equity. For example, I would trade 0.1 lots for every $1000 of equity. This is very similar to the fixed fractional approach, except that you do not consider your pips risked per trade.

Wrapping Up

For the EURUSD strategy above, fixed ratio money management marginally outperformed the fixed fractional approach.

If you trade a different strategy or market, your mileage may well vary. I cannot think of any money management approach that is universally superior to all the others.

Personally, I consider money management to be one of the least important strategy elements. You could experiment with different money management approaches to create a fantastic looking backtest, but that’s just another sneaky form of curve fitting. Market conditions could change anytime, and the sequence of trades in your backtest are unlikely to occur in future.

I only have two recommendations if you’re having a difficult time selecting a money management approach:

  1. Use a compounding approach, such that your strategy’s edge gets amplified as your account grows. Both the fixed fractional and fixed ratio approaches above produced much higher profits than the fixed lots backtest.
  2. Be conservative. Even a good strategy will eventually suffer a losing streak. You have to stay in it to win it.

With those recommendations in mind, stick to the simplest money management approach that you’re comfortable with. 

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