What it means
Every trading strategy answers a handful of questions. What is the opportunity, such as a trend, a price gap or a mispricing between related assets?
What triggers an entry, where is the exit if the trade goes wrong, and where is the exit if it goes right? Strategies fall into broad families.
Trend-following strategies buy rising markets and sell falling ones, mean-reversion strategies bet that prices return to an average, and arbitrage strategies exploit small price differences between markets. Some are discretionary, relying on a trader's judgement, while others are systematic, following coded rules.
Risk rules are what separate a strategy from a hunch. They set the maximum loss per trade, the maximum share of the account in one position and the maximum overall exposure.
A common guideline is to risk only a small fixed percentage of capital, often 1% or less, on any one trade. Testing is also vital, and backtesting applies the rules to historical data to see how the strategy would have performed, while forward testing runs it with small money in live markets.
Both have pitfalls, since a strategy can be fitted too closely to the past, a problem known as overfitting, and may fail when conditions change. A sensible check is to hold back part of the data and test the rules on it only once.
Costs make or break many strategies. Commissions, spreads, taxes and the price impact of large orders all reduce returns, and high-frequency strategies are especially sensitive.
A method that looks profitable before costs may lose money after them. Businesses use the same discipline for treasury and hedging, where the strategy might be to hedge 50% of expected currency receipts using forward contracts.
The aim there is to reduce uncertainty, and the policy should state the rules, limits and review dates in the same clear way.
In practice
Real-world examples.
Example
A part-time investor adopts a trend-following strategy on a broad share index. She buys when the price rises above its 200-day average and sells when it falls below. The rules are written down and applied without exception.
Example
A commodity processor uses a hedging strategy that fixes the price on 60% of expected purchases up to nine months ahead. The remaining 40% is bought at market. The strategy limits the impact of price spikes on the budget.
Example
A quantitative fund runs a pairs strategy, buying one bank share and selling a similar one when their prices drift apart. It closes both trades when the gap narrows. The fund reviews performance monthly and stops the strategy if the results fall outside tested limits.
Formula
Calculation
Reward to risk ratio = (target price - entry price) / (entry price - stop price)
Position size = (account size x risk per trade %) / (entry price - stop price)
Suppose a trader has a $50,000 account, risks 1% per trade, and plans to buy at $100 with a stop at $95 and a target of $115. Risk per share = 100 - 95 = $5. Reward per share = 115 - 100 = $15. Reward to risk = 15 / 5 = 3 to 1. Maximum loss = 0.01 x 50,000 = $500, so position size = 500 / 5 = 100 shares, costing $10,000.Case study
Seen in the real world.
Quillfeather Trading is a fictional small firm used as an illustrative example. It backtested a strategy that appeared to return 40% a year, but the test ignored trading costs and used an unrealistically tight set of rules. When the firm included a realistic spread and commission, the return fell to 6%.
The partners then ran the strategy with small capital for three months and saw results close to the second figure. In this illustrative story they decided not to scale it up and put the effort into a different idea. The lesson is that testing with realistic costs protects capital before it is put at risk.
The firm now keeps a one-page record for every strategy it considers. The record lists the logic, the assumed costs, the test period, the live results and the decision taken, so that past experiments are not repeated by accident.
Watch out
Common mistakes.
- Trading without written rules. Decisions made in the moment are more likely to be driven by emotion.
- Optimising a strategy until it fits past data perfectly. Overfitted strategies often fail on new data.
- Ignoring costs and taxes. A strategy must be profitable after all expenses, not just before them.
Questions
People also ask.
How do I know if a strategy works?
Test it on historical data, include realistic costs, then trade it with small capital and compare results with expectations.
Can one strategy suit every market?
Rarely, because trend, range and volatility conditions change, so strategies are usually matched to particular markets and periods.
When should a strategy be stopped?
Define the stop condition in advance, such as a loss beyond a set drawdown or a persistent gap between live results and tested results.
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