Expectancy Calculator
Free Expectancy Calculator for trading performance. Enter your numbers to see returns, costs, and optimized scenarios instantly.
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Adjust values & calculateStrategy Analysis
Formula
Expectancy calculates the average expected profit or loss per trade. It multiplies the probability of winning by the average win and subtracts the probability of losing multiplied by the average loss. A positive expectancy means the strategy is profitable over many trades. Monthly expectancy multiplies per-trade expectancy by the number of trades per month.
Last reviewed: December 2025
Worked Examples
Example 1: Day Trading Strategy Expectancy
Example 2: Swing Trading High RR Strategy
Background & Theory
The Expectancy Calculator applies the following established principles and formulas. Foreign exchange markets facilitate the conversion of one currency into another and serve as the largest and most liquid financial markets in the world, with daily turnover exceeding seven trillion US dollars. Exchange rates are quoted as currency pairs, expressing the price of one unit of a base currency in terms of a quote currency. For example, a EUR/USD rate of 1.0850 means one euro buys 1.0850 US dollars. The smallest standardized price movement in most pairs is the pip, typically the fourth decimal place, with a value of 0.0001 per unit for USD-denominated pairs. The bid price is the rate at which a dealer will buy the base currency, while the ask price is the rate at which it will sell. The spread between bid and ask represents the dealer's compensation and varies with liquidity and volatility. Leverage amplifies both gains and losses by allowing traders to control positions larger than their deposited margin. A 100:1 leverage ratio means a one-percent adverse move eliminates the entire margin, making position sizing and risk management critical. Two parity conditions from international economics anchor exchange rate theory. Purchasing Power Parity (PPP) holds that exchange rates should adjust over time so that identical goods trade at equivalent prices across countries: S = P_d / P_f, where S is the spot rate and P_d and P_f are domestic and foreign price levels. PPP performs well over long horizons but poorly in the short run due to trade barriers, non-tradable goods, and capital flows. Covered Interest Rate Parity (CIRP) is a near-arbitrage condition stating that forward exchange rate premiums or discounts exactly offset interest rate differentials between two currencies: F/S = (1 + r_d) / (1 + r_f). Deviations from CIRP create riskless arbitrage opportunities that traders rapidly eliminate. Uncovered Interest Rate Parity posits that high-yielding currencies should depreciate to offset their interest advantage, though empirical evidence is mixed and the carry trade — borrowing in low-rate currencies to invest in high-rate ones — has generated persistent returns.
History
The history behind the Expectancy Calculator traces back through the following developments. For much of the nineteenth century and early twentieth century, the international monetary system operated under the classical gold standard, under which each participating currency was fixed to a defined weight of gold, making bilateral exchange rates effectively constant. The system provided price stability and facilitated global trade but constrained governments' ability to respond to economic downturns. World War One shattered the gold standard as nations suspended convertibility to finance wartime expenditures. The interwar period saw attempts to restore gold convertibility, most notably the British return to the gold standard in 1925 at the pre-war parity, a decision criticized by John Maynard Keynes as deflationary. The Great Depression forced widespread currency devaluations and the effective collapse of the international gold standard by the early 1930s. The Bretton Woods Conference of July 1944 established a new order in which member currencies were pegged to the US dollar, while the dollar alone was convertible into gold at 35 dollars per troy ounce. The International Monetary Fund and World Bank were created at the same conference to oversee the system. Bretton Woods delivered exchange rate stability during the postwar growth era but came under strain as US deficits and European dollar accumulation outpaced American gold reserves. On August 15, 1971, President Nixon announced the suspension of dollar-gold convertibility — the so-called Nixon Shock — effectively ending the Bretton Woods system. By 1973, major currencies had transitioned to floating exchange rates determined by market supply and demand, a regime that has persisted. On September 16, 1992, hedge fund manager George Soros shorted the British pound against the European Exchange Rate Mechanism constraints, forcing the UK's withdrawal in what became known as Black Wednesday. Electronic trading platforms emerged in the 1990s and 2000s, replacing voice-brokered interbank markets and dramatically reducing transaction costs for institutional and retail participants alike.
Frequently Asked Questions
Formula
Expectancy = (Win Rate × Avg Win) − (Loss Rate × Avg Loss)
Expectancy calculates the average expected profit or loss per trade. It multiplies the probability of winning by the average win and subtracts the probability of losing multiplied by the average loss. A positive expectancy means the strategy is profitable over many trades. Monthly expectancy multiplies per-trade expectancy by the number of trades per month.
Worked Examples
Example 1: Day Trading Strategy Expectancy
Problem: Win rate: 55%, Avg win: $200, Avg loss: $120, 20 trades/month.
Solution: Expectancy = (0.55 × $200) - (0.45 × $120)\n= $110 - $54 = $56 per trade\nMonthly = $56 × 20 = $1,120\nAnnual = $1,120 × 12 = $13,440\nProfit Factor = $110 / $54 = 2.04
Result: $56 per trade | $1,120/month | $13,440/year | PF: 2.04
Example 2: Swing Trading High RR Strategy
Problem: Win rate: 40%, Avg win: $500, Avg loss: $150, 8 trades/month.
Solution: Expectancy = (0.40 × $500) - (0.60 × $150)\n= $200 - $90 = $110 per trade\nMonthly = $110 × 8 = $880\nRisk-Reward Ratio = $500 / $150 = 3.33:1
Result: $110 per trade | $880/month | 3.33:1 RR
Frequently Asked Questions
What is trading expectancy?
Trading expectancy (also called expected value or mathematical edge) is the average amount you expect to win or lose per trade over a large number of trades. It is calculated as: (Win Rate × Average Win) - (Loss Rate × Average Loss). A positive expectancy means your strategy is profitable over time, while a negative expectancy means you will lose money in the long run. Expectancy is the single most important metric for evaluating a trading strategy because it combines both win rate and risk-reward ratio into one number.
How do I calculate expectancy for my trading?
To calculate expectancy: 1) Determine your win rate from at least 30-50 trades (more is better). 2) Calculate your average winning trade amount. 3) Calculate your average losing trade amount. 4) Apply the formula: Expectancy = (Win Rate × Avg Win) - (Loss Rate × Avg Loss). For example, with 55% win rate, $200 average win, and $120 average loss: Expectancy = (0.55 × $200) - (0.45 × $120) = $110 - $54 = $56 per trade. This means you can expect to make $56 on average per trade over time.
What is a good expectancy per trade?
A 'good' expectancy depends on your trading style and account size. Any positive expectancy is technically profitable, but you want enough edge to cover commissions, slippage, and psychological errors. As a guideline, an expectancy of $0.20-0.50 per dollar risked is considered good, while $0.50+ per dollar risked is excellent. In dollar terms, if you risk $100 per trade, an expectancy of $20-50 per trade is solid. The most important thing is that the expectancy remains consistently positive across different market conditions.
Why is expectancy more important than win rate?
Win rate alone tells you nothing about profitability. A 90% win rate strategy that wins $10 per trade but loses $100 per trade has a negative expectancy: (0.90 × $10) - (0.10 × $100) = $9 - $10 = -$1 per trade. Meanwhile, a 35% win rate strategy with 4:1 reward-to-risk has positive expectancy: (0.35 × $400) - (0.65 × $100) = $140 - $65 = $75 per trade. Expectancy captures the full picture by combining win rate with average win and loss sizes. Always optimize for expectancy, not win rate.
How does expectancy relate to profit factor?
Profit factor is a related metric: Gross Profits / Gross Losses, or equivalently (Win Rate × Avg Win) / (Loss Rate × Avg Loss). A profit factor above 1.0 means positive expectancy (profitable), and below 1.0 means negative expectancy (unprofitable). A profit factor of 1.5 means you make $1.50 for every $1 lost, while 2.0 means you make $2 for every $1 lost. Most successful traders have profit factors between 1.3 and 2.5. Extremely high profit factors (above 3.0) over a large sample are rare and may indicate curve-fitting or a very small sample size.
How many trades do I need for a reliable expectancy calculation?
A minimum of 30 to 50 trades is needed for a rough estimate, but 100 or more trades provides a statistically meaningful expectancy figure. The law of large numbers states that actual results converge toward the expected value as the sample size increases. With fewer than 30 trades, random variance can make a losing strategy appear profitable or vice versa. Ideally, the trades should span different market conditions including trending and ranging markets. Many professional traders require at least 200 trades across multiple market cycles before they consider an expectancy figure reliable enough to risk real capital on.
References
Reviewed by Daniel Agrici, Founder & Lead Developer · Editorial policy