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Relative Strength Index (RSI) Calculator

Calculate RSI to measure momentum and identify potential overbought or oversold conditions.

RSI Formulas

RSI Formula
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Relative Strength
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Average Gain
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Examples

Neutral 14-day RSI on a slowly rising stock

A trader runs a standard 14-period RSI on a stock that has drifted higher over the past three weeks. Over the look-back window, the average gain on up days is $0.50 and the average loss on down days is $0.30.

ResultRS = 0.50 / 0.30 = 1.67, so RSI = 100 - 100/(1 + 1.67) = 62.5 — a neutral reading.

First compute relative strength: RS = average gain / average loss = 0.50 / 0.30 = 1.6667. Substitute into Wilder's formula: RSI = 100 - 100/(1 + 1.6667) = 100 - 100/2.6667 = 100 - 37.5 = 62.5. The value sits between 30 (oversold) and 70 (overbought), so momentum is firmly bullish but not yet in stretched territory. A trader using the classic Wilder thresholds would treat this as a continuation reading rather than a reversal signal.

Frequently asked questions

How do I interpret an RSI value?

RSI runs from 0 to 100. The classic Wilder thresholds treat readings above 70 as overbought (price may be due for a pullback) and below 30 as oversold (price may be due for a bounce). Values between 30 and 70 are considered neutral, with 50 acting as the centerline that separates net bullish from net bearish momentum over the look-back window.

Why is 14 periods the default?

Wilder chose 14 in his 1978 book New Concepts in Technical Trading Systems because it balanced responsiveness with smoothness on daily charts. Fourteen daily bars is roughly three trading weeks, long enough to filter day-to-day noise but short enough to react to real shifts in momentum. The number is a convention, not a mathematical optimum — you can change it, but published overbought/oversold thresholds (70/30) were calibrated against the 14-period default.

What is RSI divergence and why does it matter?

Divergence happens when price makes a new high (or low) but RSI fails to confirm it by making its own new high (or low). Bearish divergence — price higher, RSI lower — suggests weakening upside momentum and a possible top. Bullish divergence — price lower, RSI higher — suggests downside exhaustion. Divergence is a warning signal, not a trade trigger; most traders wait for a price-based confirmation before acting.

Why does RSI stay overbought for weeks in strong trends?

In a strong uptrend, average gains keep outpacing average losses, so RSI can sit above 70 — sometimes above 80 — for weeks without reversing. Selling every overbought reading in a runaway trend is one of the most common ways traders lose money using RSI. Many practitioners shift to trend-following thresholds (80/20) or pair RSI with a trend filter such as a 200-day moving average in trending markets.

Should I use a shorter or longer RSI period?

Shorter periods (e.g., 7 or 9) make RSI more sensitive: it generates more overbought and oversold signals, suiting short-term traders. Longer periods (e.g., 21 or 25) smooth the line and produce fewer, more reliable signals for swing or position traders. Changing the period also changes how often 70/30 levels are touched, so back-test any non-standard setting on your own instrument before trading it.

What is the difference between RSI and MACD?

RSI is a bounded oscillator (0 to 100) that measures the speed and magnitude of recent price changes, mainly used to spot overbought/oversold conditions and divergence. MACD is an unbounded indicator built from two moving averages, used mainly to identify trend direction and momentum crossovers. The two are complementary: RSI excels at extremes, MACD excels at trend confirmation, and many traders use them together.

What is Wilder smoothing and does this calculator use it?

Wilder's original smoothing is a modified moving average where each new value = (previous average × (n-1) + current value) / n. It's similar to an exponential moving average and produces a smoother RSI than a simple moving average of gains and losses. This calculator takes pre-computed average gain and average loss values, so you can feed it either simple-average or Wilder-smoothed inputs — just be consistent across comparisons.

Sources

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