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Buy an RSI dip below 30 only while price is above its 200-day average; sell at RSI 60 or after 20 sessions.
RSI Oversold in an Uptrend on Nifty IT from Dec 2005 to Nov 2026: CAGR 0.7%, max drawdown 20.0%, win rate 40.0% over 10 trades, vs buy-and-hold 10.7%.
As of · Hypothetical backtest by Jivani Markets on Nifty IT daily data; re-run weekly
| Measure | RSI Oversold in an Uptrend | Buy and hold Nifty IT |
|---|---|---|
| CAGR (annual return) | 0.7% | 10.7% |
| Total return | 15% | 736% |
| Max drawdown | −20.0% | −65.7% |
| ₹10 lakh became | ₹11.5 lakh | ₹83.6 lakh |
| Win rate | 40.0% | — |
| Trades (closed) | 10 | — |
| Winning / losing trades | 4 / 6 | — |
| Profit factor | 2.66 | — |
| Sharpe ratio | 0.16 | — |
| Volatility (annual) | 5.4% | — |
| Time in the market | 4% | 100% |
| Average holding | 19 sessions | — |
| Charges and slippage paid | ₹56,256 | — |
# RSI Oversold in an Uptrend on Nifty IT
universe("NIFTY IT", asset="index")
settings(
timeframe="1d",
entry_timing="next_open",
cost_model="retail",
slippage_model="tiered",
start="2006-01-01",
benchmark="NIFTY IT",
allow_short=False,
participation_ignore_zero_volume=True,
)
exit_when(rsi(14) > 60)
time_exit(bars=20)
buy(all_of(crosses_below(rsi(14), 30), close() > sma(200)), size=percent_of_equity(100))
| Year | Strategy | Buy and hold |
|---|---|---|
| 2026* | 0.0% | −14.3% |
| 2025 | 0.0% | −12.6% |
| 2024 | −0.5% | +22.0% |
| 2023 | +6.2% | +24.1% |
| 2022 | −0.8% | −26.0% |
| 2021 | 0.0% | +59.6% |
| 2020 | 0.0% | +54.9% |
| 2019 | 0.0% | +8.4% |
| 2018 | −2.5% | +23.8% |
| 2017 | 0.0% | +12.2% |
| 2016 | 0.0% | −7.3% |
| 2015 | +2.3% | 0.0% |
| 2014 | +6.8% | +17.8% |
| 2013 | 0.0% | +58.0% |
| 2012 | 0.0% | −1.9% |
| 2011 | 0.0% | −18.1% |
| 2010 | +8.2% | +28.8% |
| 2009 | 0.0% | +166.0% |
| 2008 | 0.0% | −54.6% |
| 2007 | −0.1% | −11.4% |
| 2006 | −4.4% | +39.9% |
| Bought | At | Sold | At | Return |
|---|---|---|---|---|
| 18 Apr 2024 | 33,797.02 | 17 May 2024 | 33,713.21 | −0.5% |
| 26 Oct 2023 | 30,229.28 | 17 Nov 2023 | 32,240.47 | +6.4% |
| 25 Jan 2022 | 34,542.09 | 23 Feb 2022 | 34,333.52 | −0.8% |
| 24 Oct 2018 | 14,146.69 | 26 Nov 2018 | 13,816.19 | −2.6% |
| 23 Apr 2015 | 11,588.41 | 22 May 2015 | 11,567.32 | −0.4% |
| 16 Dec 2014 | 10,710.29 | 13 Jan 2015 | 11,527.93 | +7.4% |
| 20 Mar 2014 | 9,160.76 | 21 Apr 2014 | 9,381.45 | +2.2% |
| 26 May 2010 | 5,537.09 | 21 Jun 2010 | 6,009.27 | +8.2% |
| 1 Mar 2007 | 5,177.96 | 30 Mar 2007 | 5,187.51 | −0.1% |
| 23 May 2006 | 3,807.25 | 20 Jun 2006 | 3,646.52 | −4.4% |
From 30 Dec 2005 to 9 Nov 2026, these RSI Oversold in an Uptrend rules on the Nifty IT index returned a CAGR of 0.7% after costs, less than the 10.7% a year from buying and holding the index, with a worst fall of 20.0% against 65.7% for buy-and-hold. It made 10 trades and was invested 4% of the time. This is a hypothetical test on past data, not a recommendation, and past performance is not indicative of future results.
40.0%: 4 of 10 closed trades made money after charges and slippage. On a ₹10 lakh account the average winning trade made ₹61,516 and the average losing trade lost ₹15,406; the profit factor (gross profit ÷ gross loss) was 2.66. A high win rate with small wins can still lose money, so read it with the CAGR and drawdown.
Buy: RSI(14) crosses below 30 while the close is above the 200-day SMA. Sell: RSI(14) rises above 60, or 20 sessions pass. One position at a time with all of the capital; out of the market (in cash, earning nothing) between trades. Daily candles, long only, orders filled at the next session's open.
Buying and holding the Nifty IT index over the same dates returned 10.7% a year with a worst fall of 65.7%; the strategy returned 0.7% a year with a worst fall of 20.0%. A strategy that is out of the market part of the time usually gives up some return in rising years in exchange for missing part of the falls; the year-by-year table on this page shows where each one gained or lost.
Retail delivery charges (STT, exchange and SEBI fees, stamp duty and GST) and size-based slippage on every buy and sell; signals are read on the daily close and filled at the next session's open; price return only, so dividends are left out of both the strategy and buy-and-hold. An index cannot be bought directly; a fund or ETF that tracks it adds its own expense ratio and tracking error, and pays dividends this price-index test leaves out.
Yes. The "Run it yourself" link opens these exact rules in the Jivani Markets backtest builder, where you can change the indicator settings, add a stop-loss, pick other stocks or indices and re-run it on the latest data.