The Six Variables That Shape a Trading System
A trading system can be described as a set of rules, but its long-term results depend on several interacting variables. The study notes list six: reliability (win rate), reward-to-risk ratio, trading costs, trade frequency or opportunity, position sizing, and the capital scale of the account, which the outline labels as trading psychology. Reliability asks what percentage of trades or investments are profitable. Reward-to-risk asks how large profits are relative to losses at the smallest trading unit, such as one share or one futures contract. For example, if a failed trade loses $1 per share and a successful trade gains $1 per share, the relative size is equal. If a winner gains $10 while a loser loses $1, the relative size is very different. Trading costs include execution costs and commissions; every trade acts as a drag on account size. Frequency concerns how often opportunities appear. Position sizing determines how many units are traded, so per-share profit or loss is multiplied by the number of shares. Capital scale determines how heavily the first four variables affect the account. A $20 cost means far more to a $1,000 account than to a $1,000,000 account. The source asks whether one variable matters more than others and suggests all six are important. Yet many traders focus only on reliability, the desire to be right, and ignore the other mechanisms. That fixation is a central theme in the study notes.
The Snowball Analogy: How Expectancy Works
The snowball analogy illustrates how the first four variables combine. A person hides behind a large snow wall. Snowballs are thrown at it. White snowballs are like winning trades: they stick and make the wall larger. Black snowballs are like losing trades: they melt holes equal to their size. The wall's size represents initial capital. Reliability is the percentage of white snowballs. Reward-to-risk is the relative size of white and black snowballs. If white snowballs are golf-ball sized and black snowballs are 1.83 meters in diameter, one black snowball can destroy the wall even if white snowballs arrive all day. If white snowballs are giant boulders and black snowballs are golf-ball sized, one white snowball per day may build enough protection against many small black snowballs. Trading costs act like slight damage from every snowball, white or black. Frequency is how often snowballs are thrown. Position sizing is how many snowballs are thrown at once. A single golf-ball-sized black snowball makes a small hole; 10,000 at once can destroy the wall unless it is very large. Expectancy is the average effect of one snowball. In the source's numerical example, 60 white snowballs add 6.792 cubic meters, 40 black snowballs remove 3.396 cubic meters, and total damage from 100 snowballs is 0.283 cubic meters. Net effect equals 6.792 minus 3.396 minus 0.283, or 3.113 cubic meters. Divided by 100, each snowball adds 0.031 cubic meters on average. In trading, that average effect is expectancy per trade per risk dollar. If positive, capital tends to grow over many trades; if negative, capital tends to shrink.
