6 key money management strategies: the cornerstone of successful trading

Effective money management is a cornerstone of successful trading. It involves systematically applying strategies to control risk, safeguard trading capital, and ultimately, enhance profitability.

In this article, we are going to briefly break down the most well-known money management strategies, practical examples, and who they are suitable for, so you can fine-tune your trading strategy.

What is money management?

Money management is a fundamental practice in trading and investing. It refers to the set of techniques and strategies used to manage the invested money and reduce the risks associated with the investment.

Essentially, money management seeks to optimise the return on investments and minimise losses, establishing a risk management system and control of the invested capital. To achieve this, various techniques are employed, such as asset diversification, setting loss and gain limits, and appropriately sizing positions for each trade based on the available capital.

Top 6 money management strategies

Next, we’ll introduce you to the top 6 money management strategies:

  • Kelly Criterion
  • Fixed Fractional Position Sizing
  • Optimal F
  • Secure F
  • 2% rule
  • Fixed ratio

1. Kelly Criterion

Kelly Criterion – also known as Kelly strategy, Kelly bet, or Kelly formula – is one of the oldest strategies for asset allocation and money management introduced by John L. Kelly in 1956 in “A New Interpretation of Information Rate”.

The formula has two components: the win probability of the trade (divide the number of successful trades by total number of trades) and the win/loss ratio (average gain divided by average loss):

The Kelly Criterion is a percentage (i.e., less than 1), and it means the number of positions you should employ. For example, if your percentage is 7%, then you should invest 7% in each of the assets in your portfolio.

2. Fixed Fractional Position Sizing

Fixed Fractional Position Sizing is a method introduced by Ralph Vince. It forms the basis for most modern money management algorithms. Other strategies like the Fixed-Ratio by Ryan Jones, are essentially modifications of this foundational strategy.

Fixed fractional position sizing is a method where a trader decides to risk a fixed percentage (the ‘fraction’) of their current trading capital or account balance on each trade. This fraction is pre-determined and remains constant for each trade, irrespective of the trading outcomes.

It’s a dynamic strategy that adjusts to the trader’s portfolio size, increasing when profits are made and decreasing with losses. The goal is to manage risk, preserve capital, and take advantage of compounding to enhance profitability.

The formula can be applied to determine the number of contracts (shares, lots, etc.) a trader should trade given a certain level of risk. The trader predetermines a certain percentage of their total account balance that they are willing to risk on each trade and uses this to calculate the number of contracts to trade.

The formula is:

Number of Contracts = fixed fraction of account you want to risk * (equity/trade risk)

In a practical example, assume you have £50,000 in your trading account. You decide to risk 2% of this capital in each trade (which is f), and you limit the risk per trade to £200 (i.e., using a stop-loss order).

Number of Contracts (N) = 0.02 * (£50,000 / £200) = 5 contracts

This means you should trade 5 contracts.

If a trade resulted in a loss, your account balance would decrease, and so would the number of contracts traded on the next trade (assuming the risk per contract remains the same). Conversely, if a trade resulted in a profit, your account balance and the number of contracts traded on the next trade would increase (again, assuming the risk per contract remains the same).

3. Optimal F

Optimal F, or Optimal Fraction, is a money management concept developed by Ralph Vince. It is designed to maximise the geometric return of a trading system or strategy by determining the optimal amount of capital to risk on each trade.

The basic principle of Optimal F is to find the fraction of capital that should be risked on each trade to optimise the growth of the trading account over time. It involves a complex mathematical process that considers both the historical return and risk characteristics of the trading strategy.

The Optimal F strategy isn’t a fixed percentage like the Fixed Fractional strategy. Instead, it can vary based on the historical performance of your trading strategy, including the win rate and the average win/loss ratio.

While the Optimal F strategy can theoretically maximise your returns, it also often involves a very high level of risk, often risking a significant portion of the account on each trade. Therefore, it’s often modified or used with caution in practice. Traders often risk less than the calculated Optimal F to provide a buffer against potential drawdowns.

To calculate the Optimal F, you would typically use a formula or process that considers your trading strategy’s historical performance, including factors like the win rate, the average win/loss ratio, and the distribution of wins and losses. The exact formula can vary and may involve complex statistical or optimisation methods. Because of this, many individuals decide to opt for calculators rather than calculating it manually.

Due to the high level of risk that comes with using the Optimal F strategy, it’s not recommended for everyone, especially those who are risk-averse or who do not have a deep understanding of statistical analysis and trading.

In addition to the problem of the high risk, there is another issue related to optimisation. Optimisation is a powerful tool, but it comes with the risk of over-optimisation. Over-optimisation, also known as curve fitting, occurs when a model is too finely tuned to past data and therefore performs poorly on new, unseen data.

In the context of Optimal F, over-optimisation can occur when the optimal fraction is calculated based on a specific set of historical data that isn’t representative of future market conditions. The Optimal F strategy is highly sensitive to the sequence of wins and losses. If the historical data used to calculate Optimal F includes an unusually successful sequence of trades, for example, the calculated Optimal F might be higher than what would be safe or practical in future trading.

The risk of over-optimisation can be mitigated by using out-of-sample data to validate the optimized strategy, or by applying robustness checks. It’s also a good practice to use conservative estimates when calculating Optimal F, to provide a buffer against unexpected market conditions or losing streaks.

Without optimisation, a trader would not be using their capital as efficiently as possible. They may be risking too little on each trade, which could lead to lower returns. Alternatively, they might be risking too much, exposing their account to larger drawdowns and potentially risking a significant portion, or even all, of their capital.

Advantages of the Optimal F

Optimal F is designed to maximise the geometric growth of your trading account over time. By calculating the ideal amount of capital to risk on each trade based on historical data, you can theoretically achieve the highest possible return.

Also, the Optimal F strategy helps to determine the most efficient use of capital by adjusting the risk level according to the performance characteristics of your trading system.

Disadvantages of the Optimal F

The main disadvantages include:

  • High risk levels, which may lead to significant psychological stress
  • Risk of over-optimisation
  • Requires accurate data
  • Complexity
  • Difficult to adapt to changing market conditions

4. Secure F

Secure F is a variant of the Fixed Fractional Position Sizing and was introduced by Ryna Systems. The secure fraction is similar to the optimal fraction except for the introduction of a maximum loss restriction that we are willing to tolerate.

Due to the inability of most traders to withstand the high losses implied by the use of the optimal fraction, David Stendahl and Leo Zamansky concluded that introducing a restriction on this maximum risk would help make this strategy more operational.

In this way, a price fluctuation limit is introduced into the model. If the maximum possible loss is set to a very small value, we will be facing a very conservative strategy, so the secure fraction can be adjusted to the risk appetite of each trader.

5. 2% Rule

This is not a strict strategy as it is a variant of Fixed Fractional Position Sizing by Ralph Vince, in which the selected fraction is very small, so we are at a point where we let ourselves be guided by our risk aversion and opt for an ultra-conservative strategy.

The 2% rule is applied as follows: if you start with a capital of £100,000 and open a trade, you should risk no more than £2,000 in any one trade, regardless of the size of the trade. To do so, investors use tools like stop-loss orders to make sure the loss is limited to 2% (or £2,000) of their portfolio.

This strategy is extremely popular among investors. However, if your capital is not considerable, it can be associated with very slow portfolio growth.

6. Fixed ratio

This strategy was developed by Ryan Jones in his book “The Trading Game”. The goal of this strategy is to increase trading size in a more moderate and safe manner than the Fixed Fractional or Optimal F approaches.

In the Fixed Ratio strategy, the trader defines a delta (Δ), which represents a certain amount of profit required to add an additional contract (or trading unit). The delta is set based on the trader’s risk tolerance and can be any value, but it’s usually set to a value that represents a certain percentage of the initial trading account.

As profits are made and the trading account grows, the trader adds additional contracts based on the defined delta. The key difference with the Fixed Fractional approach is that as the account size grows, the delta also increases. This means the trader has to make more profits to add the next contract, making the Fixed Ratio approach more conservative and less likely to suffer large losses.

Here’s a simple example:

  1. You start with an account size of £10,000.
  2. You set a delta of £2,000. This means for every £2,000 in profits, you will add one more contract.
  3. You start trading with 1 contract.
  4. Once your account grows to £12,000 (the initial £10,000 plus £2,000 in profits), you add a second contract.
  5. Now you are trading with 2 contracts, but to add a third contract, you need to earn £2,000 * 2 (the number of current contracts) = £4,000 in profits.
  6. Once your account grows to £16,000, you can add the third contract.

As the account grows, the delta increases, thus making the strategy more conservative as the number of contracts (and consequently the risk) increases. The principle behind this is to protect the trader from large losses that can occur with an aggressive increase in contract size.

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Money management strategies: summary

In conclusion, several money management strategies, such as the Kelly Criterion, Fixed Fractional Position Sizing, Optimal F, and Fixed Ratio have been discussed in detail.

The Kelly Criterion offers a probabilistic approach to risk management, aiming to maximise the expected logarithm of wealth. While theoretically sound, its full implementation often involves risking more than most traders would be comfortable with.

Fixed Fractional Position Sizing, introduced by Ralph Vince, is another widely used approach. By risking a fixed percentage of trading capital on each trade, it dynamically adjusts position size relative to the trader’s current equity, offering a balanced compromise between risk and reward.

Optimal F, another strategy proposed by Vince, is a more aggressive strategy aimed at maximising the geometric growth rate. However, its aggressive nature may result in substantial drawdowns and its dependence on historical data brings risks of over-optimisation.

The Fixed Ratio strategy, introduced by Ryan Jones, offers a method for traders to increase position size conservatively as profits are accrued, which can potentially limit losses and make it more palatable for risk-averse traders.

Ultimately, the best money management strategy depends on individual risk tolerance, trading capital, trading objectives, and the characteristics of the trading system used. Therefore, it’s important for traders to thoroughly understand and carefully consider each strategy’s advantages and disadvantages before deciding which strategy or combination of strategies to implement.

Regardless of the strategy chosen, the primary goal of money management should always be to protect trading capital and ensure the long-term viability of the trading activity.

Remember, no matter how good a trading system might be, without effective money management, long-term success is unlikely.

Money management strategies FAQ

What is the purpose of a money management strategy in trading?

he purpose of a money management strategy in trading is to help manage risk and enhance profitability. It outlines the rules on how much to risk on each trade, which can help protect your trading capital from large losses, enhance the potential for profits, and ensure long-term success in trading.

How do I decide which money management strategy to use?

The choice of money management strategy depends on several factors, including your risk tolerance, trading capital, trading objectives, and the performance characteristics of your trading system. Each strategy has its own advantages and disadvantages. It’s important to thoroughly understand these before making a decision. You may also consider seeking advice from a financial advisor.

Can I trade without a money management strategy?

While it’s physically possible to trade without a money management strategy, it’s not advisable. Trading without a defined money management strategy can lead to significant losses, as you may end up risking too much on each trade or not knowing how to adjust your trading size based on the performance of your trades.

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