Risk Management & Leverage is one of several modules in my Trading Foundations Masterclass, and a thorough understanding of the content in this module is a pre-requisite to becoming a consistent and successful trader.
This article introduces crucial aspects of trading that is often overlooked by traders who focus on finding the perfect strategy. The reality is that there are countless strategies, indicators, and signals to choose from, and it can be tempting for new traders to spend all their time trying to identify the best one. However, effective risk management is what allows those strategies to be successful and determines whether a trader makes it or goes bust.
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The degree of acceptable risk and reward varies from one trader to the next, but there are some general guidelines to follow when developing a risk management strategy.
It is prudent that traders should not risk more than a small percentage of their total trading capital on any single trade.
For beginner, novice, and even experienced traders, it is a good idea to keep risk per trade at 1% or lower of total trading capital. Even expert traders should aim to keep risk rates in the single digits.
If a trader has $500k of capital allocated to trading and opens a trading account with $100k, and is using a strategy that risks 10% of the entry size per trade, they would need to ensure that each trade entry is $50k or less to keep the loss at around $5k (1% of $500k).
On the other hand, if the strategy only risks 2% of entry size per trade, the trader could use 2.5x leverage to bring the entry size up to $225k while still keeping the loss at $5k.
While a strategy with a high win rate may seem appealing, it is important to also consider risk management when developing a trading strategy.
Even a strategy with a low win rate, such as 33%, can make millionaires if it is paired with effective risk management.
On the other hand, a strategy with a high win rate, such as 99%, can be risky if it lacks proper risk management and can lead to the end of a trader’s career.
Imagine for a moment a strategy with a low win rate such as 33%, but a high reward to risk ratio such as 0.3% risk for 1% reward. In this case, a trade might look something like in the depiction below:
Although the strategy has a low win rate, the risk is calculated so that the trader has a statistical advantage over the long-term. A quick simulation (table below to the left) is run with the following parameters: $100,000 starting capital with 33% win rate at a 1% gain, and 66% lose rate with a 0.3% drawdown.
Similarly, a 99% win rate with poor risk management can be simulated but with a loss resulting in account liquidation (table below to the right).
The Win/Loss column for the 33% strategy is calculated via (Google Sheets):
=IF(RANDBETWEEN(1,3) > 2, "WIN", "LOSS")
The Win/Loss column for the 99% strategy is calculated via (Google Sheets):
=IF(RANDBETWEEN(1,100) < 100, "WIN", "LOSS")
Even with a very unlucky start with 17 out of 20 trades being losses in the 33% strategy, the final account value is almost $15k greater than the initial balance over the course of 100 trades.
On the other hand, the 99% win rate strategy with a 1% reward per trade (but with poor risk management) quickly increase the account size by $142k before being liquidated with a single loss.
The reward-to-risk ratio, also known as the “R,” is a common way of measuring the potential risk and reward of a trade. When a trade has a 2:1 reward-to-risk ratio, it is referred to as a “2R” trade. Similarly, a trade with a 3:1 reward-to-risk ratio is called a “3R” trade, and so on. So if the stop loss is 2% away from the entry, the target would be 6% away for a 3R trade.
When entering a trade, it’s important to have clear targets and stop losses defined beforehand with reasons for each. For advanced traders, it is sometimes acceptable to adjust targets and stop losses with proper reasoning, but stop losses should almost never be adjusted to allow for a larger loss than previously defined.
When determining a stop loss, it’s essential to base it on some type of analysis rather than a desired or arbitrarily defined risk level. Targets on the other hand, are sometimes subjective and depend on the trading style and strategy of each trader, and may be arbitrarily defined or based on the stop loss.
For instance, a trader might have a solid rationale for entering a trade and have a well-defined invalidation point, but there could be several options for a target. In this case, the trader might choose to exit the trade at a 2:1 reward-to-risk ratio if confident that the target will be reached, even if the price could potentially move further into potential profits.
It’s essential to keep in mind that all trading strategies will go through statistically unusual periods of losses. Many traders, especially those new to the market, may be tempted to abandon a strategy after a string of losses. However, it’s crucial to test strategies over a longer period of time and to adjust risk so that an unusually long loss streak can be tolerated.
The table below provides a quick reference for the probability of experiencing a losing streak of
x losses using a strategy with win rate
p over the course of a 50-trade period.
Note: For the geeks, the table was generated using the recursive formula:
F(n) is the probability of experiencing
x consecutive losses in a trading period of
n total trades with a win rate of
It’s important to consider the probability of experiencing a losing streak over a longer period of time, even if the probability seems low in the short term.
Without understanding the statistics of losing streaks, long-time successful traders might liquidate an account after just one seemingly unlikely losing streak, unaware that it was highly probable that it would happen.
For instance, a strategy with a 50% win rate has a 2.04% chance of experiencing a 10-trade losing streak over a 50-trade period. However, over the course of 1000 trades, which is easily achievable for many traders, the probability of experiencing a 10-trade losing streak increases to almost 40%.
Note that working with statistics for algorithmic trading is much easier than for discretionary trading, but the concepts apply nonetheless.
In addition to defining risk and planning for losses, it’s important to understand what is required to recover from a series of losses.
A common misconception is that if an asset drops 50%, it only needs to appreciate 50% to recover. However, this is not the case. For example, if an asset falls from $2 to $1, representing a 50% drawdown, the price must actually increase 100% to return to its original value.
This concept also applies to a trading account. If there is a 50% account drawdown, an increase of 100% is required to bring the account value back up to its pre-drawdown level.
To determine the recovery percentage required to offset a drawdown, the following formula can be used:
This formula calculates the recovery rate
R given a drawdown rate
D. For example, with a 20% drawdown, you can use the formula to calculate the recovery rate required to return to the original value:
So in this case, a 25% recovery rate is required to offset the 20% drawdown and return to the original value.
The table below can be used as a quick reference to determine recovery rates:
Note: It is essential to control emotions during a drawdown and avoid revenge trading or breaking risk management rules. Managing emotions is a crucial aspect of trading psychology, which is covered in more detail in a separate module.
Leverage is a tool that allows traders to control a larger position in a market with a smaller amount of capital. It can be thought of as a loan provided by the broker to the trader, allowing the trader to amplify their potential profits (and losses).
If a trader has $1,000 and wants to control a position worth $10,000, they could use leverage of 10:1 (which is 10x). This means that the trader only has to put up $1,000 of their own capital, while the broker provides the remaining $9,000 as a loan. If the position increases in value by 10%, the trader would make a profit of $1,000 (10% of $10,000), while only risking their own $1,000 capital. However, it’s important to note that leverage also amplifies potential losses (i.e., a 10% drawdown with 10x leverage would result in a 100% loss), so it’s crucial to use it carefully and in accordance with proper risk management practices.
While leverage can be used to reduce risk and potentially amplify profits, it’s important for traders to understand how to use it properly. If used improperly, leverage can amplify losses and lead to debt upon liquidation.
Exchange Risk Mitigation
In the cryptocurrency trading space, leverage can be used to prevent catastrophic losses by utilizing it on Centralized Exchanges (CEXs). It may seem counterintuitive, but the strategy is to keep the majority of crypto assets in self-custody solutions (such as a hardware wallet) while only allowing a small portion to reside on a CEX. This way, traders can use leverage on the small account (following proper risk management practices) to compensate for the lack of available trading funds. This protects traders from institutional failures such as the collapse of FTX.
If a trader has $1,000,000 in USDT and uses it to open a $1,000,000 account on FTX for spot trading, the collapse would have wiped out the trader. However, if the trader opened a $10,000 account on FTX and kept the rest in a crypto wallet while using 10x or 25x leverage to enter trades, the trader would still have plenty of resources even after the FTX collapse.
Low Volatility Trading
Additionally, leverage can be used to improve the risk-to-reward ratio when trading in low volatility markets. For instance, if $BTC is trading in a narrow range of 1%, there may be few opportunities for profitable trades due to the costs involved. In such cases, leverage can be used to compensate for the lack of volatility.
Consider a trader with $100,000 in trading funds who aims to risk 1% of their capital per trade. If they wish to enter a trade within this 1% range with a 0.2% stop loss and a 0.8% target (a 4R trade), they can leverage their trade entry by 5x to maintain their risk management strategy of 1% of total capital per trade.
Expert Trading Strategies
For traders with a high level of experience, there may be situations where using leverage to increase rewards is justified, despite the increased risk. Strategies that significantly increase risk beyond 1% of total capital should be thoroughly tested and proven over long periods of time and through multiple market cycles. It is not recommended for traders who are less than experts to employ these advanced strategies.
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