The Relative Strength Index is one of the most widely misused indicators in trading. The RSI's real power comes from combining it with context.
def compute_rsi(closes, period=14):
delta = pd.Series(closes).diff()
gain = delta.clip(lower=0).rolling(period).mean()
loss = (-delta.clip(upper=0)).rolling(period).mean()
rs = gain / loss.replace(0, 1e-10)
return 100 - (100 / (1 + rs))
RSI below 30 signals oversold. RSI above 70 signals overbought. But in strong trends, RSI can stay above 70 for weeks.
Only take oversold signals when you are in a bullish macro environment. On BTC, use the 200-day SMA as your macro filter. Price above SMA200 means bull regime — only trade RSI longs. Price below means bear regime.
When RSI drops below 30 AND price touches the lower Bollinger Band simultaneously, the probability of a bounce increases dramatically. This dual confirmation cuts false signals by roughly 40% compared to RSI alone.
Q: What RSI levels should I use for crypto perpetuals on LMEX?
The standard 30/70 levels work in ranging markets. In strong bull trends, price rarely drops below 40, so adjust your oversold threshold to 40-45. Always adapt RSI levels to the current market regime.
Q: How do I avoid RSI false signals in trending crypto markets?
Use the 200-period SMA as a macro filter. Only take RSI long signals when price is above the SMA200 (bull regime) and only take shorts when price is below it (bear regime). This eliminates the majority of counter-trend false signals.
Q: What is the best RSI period for LMEX perpetuals?
RSI(14) is the standard. Shorter periods like RSI(7) give more signals but more noise. Longer periods like RSI(21) give fewer but more reliable signals. Test different periods on LMEX historical data for your specific asset and timeframe.
Q: How do I combine RSI with Bollinger Bands for stronger signals?
The dual confirmation approach — RSI below 30 AND price touching the lower Bollinger Band simultaneously — produces significantly higher win-rate signals than either indicator alone. This catches genuine oversold conditions at statistically extreme price levels.