Monthly Trading Statistics Calculator
Calculate monthly trading statistics: win rate, average RR, expectancy, and profit factor. Enter values for instant results with step-by-step formulas.
Reviewed for accuracy by Daniel Agrici, Founder & Lead Developer
Monthly Trading Statistics Calculator
Calculator
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Formula: Expectancy = (Win Rate x Avg Win) - (Loss Rate x Avg Loss)
Worked example — Win Rate: 55% | Profit Factor: 2.04 | Expectancy: 0.467R | Monthly: 2.8%
Formula
Expectancy = (Win Rate x Avg Win) - (Loss Rate x Avg Loss)
Expectancy measures the average profit or loss per trade. Profit factor is gross profits divided by gross losses. The Kelly Criterion determines optimal position sizing based on win rate and payoff ratio. All metrics work together to provide a complete performance assessment.
Worked Examples
Example 1: Profitable Day Trader Monthly Review
Problem:A day trader took 40 trades in a month, winning 22 and losing 18. Average win was $250 and average loss was $150. Account size is $100,000.
Solution:Win Rate: 22/40 = 55% Avg Risk-Reward: $250 / $150 = 1.67 Gross Profit: 22 x $250 = $5,500 Gross Loss: 18 x $150 = $2,700 Net Profit: $5,500 - $2,700 = $2,800 Profit Factor: $5,500 / $2,700 = 2.04 Expectancy: (0.55 x $250) - (0.45 x $150) = $137.50 - $67.50 = $70 per trade Expectancy in R: $70 / $150 = 0.467R Monthly Return: $2,800 / $100,000 = 2.8%
Result:Win Rate: 55% | Profit Factor: 2.04 | Expectancy: 0.467R | Monthly: 2.8%
Example 2: Swing Trader with High RR Low Win Rate
Problem:A swing trader took 15 trades, won 5 (33% win rate), with $800 average wins and $300 average losses on a $50,000 account.
Solution:Win Rate: 5/15 = 33.3% Avg Risk-Reward: $800 / $300 = 2.67 Gross Profit: 5 x $800 = $4,000 Gross Loss: 10 x $300 = $3,000 Net Profit: $4,000 - $3,000 = $1,000 Profit Factor: $4,000 / $3,000 = 1.33 Expectancy: (0.333 x $800) - (0.667 x $300) = $266.67 - $200 = $66.67 per trade Expectancy in R: $66.67 / $300 = 0.222R Monthly Return: $1,000 / $50,000 = 2.0%
Result:Win Rate: 33.3% | Profit Factor: 1.33 | Expectancy: 0.222R | Monthly: 2.0%
Frequently Asked Questions
What are the most important monthly trading statistics to track?
The five most critical monthly trading statistics are win rate, average risk-reward ratio, expectancy, profit factor, and maximum drawdown. Win rate tells you how often you profit, but it means little without context from the risk-reward ratio. Expectancy combines both metrics to show your average profit per dollar risked. Profit factor divides gross profits by gross losses and should be above 1.5 for a robust strategy. Maximum drawdown shows your worst peak-to-trough decline and indicates whether your strategy could survive adverse market conditions. Tracking these five statistics monthly creates a performance dashboard that reveals whether your trading edge is strengthening, weakening, or remaining stable over time.
What is a good win rate for a trading strategy?
A good win rate depends entirely on your average risk-reward ratio because the two metrics are interconnected. A scalping strategy might have a 70% win rate but only average 0.8R per win, while a trend-following strategy might win only 35% of trades but average 3R per win. Both can be highly profitable. Generally, win rates between 40% and 60% are most common among consistently profitable traders. Win rates above 70% often indicate a strategy that takes profits too quickly, leaving significant gains on the table. Win rates below 30% can be profitable but are psychologically challenging because of long losing streaks. The key metric is not win rate alone but the combination of win rate and average R-multiple, expressed as expectancy.
How do I calculate and interpret profit factor?
Profit factor is calculated by dividing gross profits by gross losses over a period. A profit factor of 1.0 means you broke even, below 1.0 means you lost money, and above 1.0 means you were profitable. Industry benchmarks suggest that a profit factor of 1.5 is the minimum for a viable strategy, 2.0 is good, and above 2.5 is excellent. Very high profit factors (above 4.0) over a small sample may indicate either an exceptional period or insufficient data for reliable assessment. Profit factor is useful because it is simple to calculate and understand. However, it does not capture the distribution of wins and losses, so a strategy could have a good profit factor while still having dangerously large individual losses that could blow an account.
What is trading expectancy and how do I use it?
Trading expectancy is the average amount you expect to make per dollar risked over many trades. It is calculated as: Expectancy = (Win Rate x Average Win) - (Loss Rate x Average Loss). When expressed in R-multiples, a positive expectancy means your strategy has a mathematical edge. For example, an expectancy of 0.35R means you earn $0.35 for every $1 risked on average. To estimate monthly income: multiply expectancy by risk per trade in dollars and then by the number of trades per month. If your expectancy is 0.35R, you risk $500 per trade, and you take 40 trades per month, your expected monthly profit is 0.35 x $500 x 40 = $7,000. This assumes consistent execution without emotional interference, which is why realized expectancy is often lower than calculated expectancy.
How many trades do I need for statistically meaningful results?
For trading statistics to be statistically meaningful, you need a minimum sample size of 30 trades, with 100 or more trades being ideal for reliable conclusions. With fewer than 30 trades, your win rate and other metrics are heavily influenced by randomness and cannot reliably distinguish between a genuine edge and luck. At 100 trades, your statistics begin to converge toward their true values, though they can still fluctuate. Professional quantitative traders often require 200 to 500 trades before concluding a strategy has a genuine edge. When evaluating monthly statistics, understand that a single month of 20-40 trades provides directional guidance but not statistical certainty. Track cumulative rolling statistics over 3-6 months to get a more accurate picture of your true performance parameters.
What is the Kelly Criterion and should I use it for position sizing?
The Kelly Criterion is a mathematical formula that calculates the optimal percentage of your capital to risk on each trade to maximize long-term growth rate. It is calculated as: Kelly % = (Win Rate x Average RR - Loss Rate) / Average RR. For a trader with 55% win rate and 1.5 average RR, Kelly suggests risking about 18% per trade. However, full Kelly sizing is extremely aggressive and produces stomach-churning drawdowns that most traders cannot tolerate psychologically. The standard practice is to use half-Kelly or quarter-Kelly, which significantly reduces drawdowns while still capturing most of the growth potential. Half-Kelly reduces the growth rate by only 25% while cutting drawdown risk roughly in half. Most professional traders risk 1-2% per trade regardless of Kelly calculations.
How do I identify if my trading performance is deteriorating?
Performance deterioration can be identified through several warning signs in your monthly statistics. Watch for a declining rolling win rate over 3 or more consecutive months, a decreasing average R-multiple on winning trades, an increasing average loss size, or a profit factor trending below 1.5 toward 1.0. Other red flags include increasing frequency of maximum loss trades, deteriorating expectancy, or widening deviation between planned and actual risk-reward ratios. Compare your current month statistics against your trailing 6-month average. If your current month falls more than one standard deviation below your average in multiple metrics simultaneously, your edge may be eroding. This could be due to changing market conditions, psychological fatigue, strategy decay, or a combination of factors requiring systematic review.
What is the difference between gross and net trading performance?
Gross trading performance measures profits and losses from trade results alone, while net performance includes all costs associated with trading. These costs include commissions and broker fees, spread costs on each entry and exit, swap or overnight financing charges, platform or data feed subscriptions, and any prop firm challenge or monthly fees. The difference between gross and net can be substantial, especially for high-frequency traders. A scalper making 100 trades per month at $5 round-trip commission pays $500 monthly in commissions alone. If gross profit is $2,000, the net profit is only $1,500, a 25% reduction. When calculating monthly statistics, always use net figures for accurate performance assessment, as a strategy that appears profitable on a gross basis may actually lose money after all costs are included.
How does average risk-reward ratio affect my trading results?
Average risk-reward ratio is the relationship between your average winning trade size and your average losing trade size. An average RR of 1.5 means your winners are 50% larger than your losers. This metric is crucial because it determines the minimum win rate needed for profitability. With a 1:1 RR, you need above 50% wins to profit. With 1:2 RR, you need only 33%. With 1:3, just 25%. Improving your average RR from 1:1 to 1:2 can transform a losing strategy into a profitable one without changing anything about your trade selection. Practical ways to improve your RR include using trailing stops to let winners run, scaling out of positions at multiple targets, and being more selective about entry points to get tighter stop losses relative to your profit targets.
How should I set monthly performance goals for my trading?
Monthly performance goals should be process-oriented rather than outcome-oriented because you cannot control market conditions. Instead of targeting a specific dollar return, set goals around metrics you can control: maintain your planned risk per trade within 10% deviation, execute at least 90% of trades according to your strategy rules, achieve a minimum number of trading setups reviewed per day, and keep your average loss at or below 1R. For outcome metrics, use ranges rather than fixed targets. A reasonable monthly return target for most strategies is 3-8% of account size, understanding that some months will be negative. Set a monthly maximum loss threshold (perhaps 6-8% of account) at which you stop trading and review your approach. This prevents a single bad month from causing catastrophic damage to your account.
References
Reviewed for accuracy by Daniel Agrici, Founder & Lead Developer · Editorial policy
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