Position sizing as the pre-trade bound on loss and exposure

Size sets the bound before the trade

Position sizing is the rule for how much to have on during a trade. It is the part of the method that is supposed to meet a stated return or drawdown objective. The quantity is chosen before entry from account equity, stop distance, and a chosen risk unit, and it remains the bound throughout the position.

The planned loss is the exposure that size is designed to keep bounded. It is not the capital spent on the shares or contracts.

Beliefs come before the sizing rule

A trading method has to match the trader’s circumstances and beliefs, including time available and willingness to monitor, or it will not be followed competently. Beliefs fall into three groups that affect design: who the trader is and what lifestyle allows, what the markets and the system should do, and thought patterns that produce disruptive emotion.

A belief inventory is a written account of personal constraints, objectives, and emotional patterns that must fit the trading method before size and system design begin. Emotional issues should be identified before system design. Otherwise the trader is unlikely to build a method that can be followed, and buy-and-hold is not a substitute for learning to accept losses.

Objectives choose the algorithm

Objectives that combine a target gain with a maximum drawdown imply different sizing rules. Simulations can identify a size that maximizes the chance of hitting the gain without breaching the drawdown.

Percent risk is one sizing algorithm. It limits loss on a trade to a chosen fraction of account equity, given the distance from entry to the stop. Percent volatility is another. It scales position size to a volatility measure so exposure stays comparable across instruments or conditions. Each objective can require a different algorithm even when the underlying system is unchanged.

A drawdown limit is a chosen ceiling on peak-to-trough equity decline that the sizing rule is designed not to breach.

R-multiples turn the bound into quantity

Limiting total exposure to one risk unit of equity sets share quantity from stop distance. A $50,000 account with a $500 risk unit and a $20 per-share stop buys 25 shares. That 25-share quantity is the planned loss, not the capital spent.

Expectancy is the average result per trade expressed in R-multiples. An R-multiple is a loss or gain expressed as a multiple of the planned risk unit on a trade, so results and drawdowns can be compared independently of dollar size. A high-quality system, judged by expectancy and how variable that expectancy is, makes it easier to use size to meet objectives. Size can still fail even a strong system if the entire stake is risked on one trade.

If a system’s expectancy is 0.8R over 100 trades a year, the expected yearly result is about 80R. A simulated average peak drawdown of 20R can be used to choose size so that those R results stay inside a capital bound.

Execution keeps the bound intact

A sequence of large mistakes can reverse a positive expectancy path. Fifty-two errors of 4R each turn an 80R gain into a 128R loss. Execution quality is part of keeping size-bounded risk intact.