Rsi 2 strategy

Developed by Larry Connors, the 2-period RSI strategy is a mean-reversion trading strategy designed to buy or sell securities after a corrective period. The strategy is rather simple. Connors suggests looking for buying opportunities when 2-period RSI moves below 10, which is considered deeply oversold. Conversely, traders can look for short-selling opportunities when 2-period RSI moves above 90. This is a rather aggressive short-term strategy designed to participate in an ongoing trend. It is not designed to identify major tops or bottoms. Before looking at the details, note that this article is designed to educate chartists on possible strategies. We are not presenting a standalone trading strategy that can be used right out of the box. Instead, this article is meant to enhance strategy development and refinement.
There are four steps to this strategy and levels are based on closing prices. First, identify the major trend using a long-term moving average. Connors advocates the 200-day moving average. The long-term trend is up when a security is above its 200-day SMA and down when a security is below its 200-day SMA. Traders should look for buying opportunities when above the 200-day SMA and short-selling opportunities when below the 200-day SMA.
Second, choose an RSI level to identify buying or selling opportunities within the bigger trend. Connors tested RSI levels between 0 and 10 for buying, and between 90 and 100 for selling. Connors found that returns were higher when buying on an RSI dip below 5 than on an RSI dip below 10. In other words, the lower RSI dipped, the higher the returns on subsequent long positions. For short positions, the returns were higher when selling-short on an RSI surge above 95 than on a surge above 90. In other words, the more short-term overbought the security, the greater the subsequent returns on a short position.
The third step involves the actual buy or sell-short order and the timing of its placement. Chartists can either watch the market near the close and establish a position just before the close or establish a position on the next open. There are pros and cons to both approaches. Connors advocates the before-the-close approach. Buying just before the close means traders are at the mercy of the next open, which could be with a gap. Obviously, this gap can enhance the new position or immediately detract with an adverse price move. Waiting for the open gives traders more flexibility and can improve the entry level.
The fourth step is to set the exit point. In his example using the S&P 500, Connors advocates exiting long positions on a move above the 5-day SMA and short positions on a move below the 5-day SMA. This is clearly a short-term trading strategy that will produce quick exits. Chartists should also consider setting a trailing stop or employing the Parabolic SAR. Sometimes a strong trend takes hold and trailing stops will ensure that a position remains as long as the trend extends.
Where are the stops? Connors does not advocate using stops. Yes, you read right. In his quantitative testing, which involved hundreds of thousands of trades, Connors found that stops actually “hurt” performance when it comes to stocks and stock indices. While the market does indeed have an upward drift, not using stops can result in outsized losses and large drawdowns. It is a risky proposition, but then again trading is a risky game. Chartists need to decide for themselves.
Trading Examples.
The chart below shows the Dow Industrials SPDR (DIA) with the 200-day SMA (red), 5-period SMA (pink) and 2-period RSI. A bullish signal occurs when DIA is above the 200-day SMA and RSI(2) moves to 5 or lower. A bearish signal occurs when DIA is below the 200-day SMA and RSI(2) moves to 95 or higher. There were seven signals over this 12-month period, four bullish and three bearish. Of the four bullish signals, DIA moved higher three of the four times, which means these signals could have been profitable. Of the three bearish signals, DIA moved lower only once (5). DIA moved above the 200-day SMA after the bearish signals in October. Once above the 200-day SMA, the 2-period RSI did not move to 5 or lower to produce another buy signal. As far as a gain or loss, it would depend on the levels used for the stop-loss and profit taking.
The second example shows Apple (AAPL) trading above its 200-day SMA for most of the timeframe. There were at least ten buy signals during this period. It would have been difficult to prevent losses on the first five because AAPL zigzagged lower from late February to mid-June 2011. The second five signals fared much better as AAPL zigzagged higher from August to January. Looking at this chart, it is clear that many of these signals were early. In other words, Apple moved to new lows after the initial buy signal and then rebounded.
As with all trading strategies, it is important to study the signals and look for ways to improve the results. The key is to avoid curve fitting, which decreases the odds of success in the future. As noted above, the RSI(2) strategy can be early because the existing moves often continue after the signal. The security can continue higher after RSI(2) surges above 95 or lower after RSI(2) plunges below 5. In an effort to remedy this situation, chartists should look for some sort of clue that prices have actually reversed after RSI(2) hits its extreme. This could involve candlestick analysis, intraday chart patterns, other momentum oscillators or even tweaks to RSI(2).
RSI(2) surges above 95 because prices are moving up. Establishing a short position while prices are moving up can be dangerous. Chartists could filter this signal by waiting for RSI(2) to move back below its centerline (50). Similarly, when a security is trading above its 200-day SMA and RSI(2) moves below 5, chartists could filter this signal by waiting for RSI(2) to move above 50. This would signal that prices have indeed made some sort of short-term turn. The chart above shows Google with RSI(2) signals filtered with a cross of the centerline (50). There were good signals and bad signals. Notice that the October sell signal did not go into effect because GOOG was above the 200-day SMA by the time RSI moved below 50. Also, note that gaps can wreak havoc on trades. The mid-July, mid-October and mid-January gaps occurred during earnings season.
Conclusions.
The RSI(2) strategy gives traders a chance to partake in an ongoing trend. Connors states that traders should buy pullbacks, not breakouts. Conversely, traders should sell oversold bounces, not support breaks. This strategy fits with his philosophy. Even though Connors' tests show that stops hurt performance, it would be prudent for traders to develop an exit and stop-loss strategy for any trading system. Traders could exit longs when conditions become overbought or set a trailing stop. Similarly, traders could exit shorts when conditions become oversold. Keep in mind that this article is designed as a starting point for trading system development. Use these ideas to augment your trading style, risk-reward preferences, and personal judgments. Click here for a chart of the S&P 500 with RSI(2).
Suggested Scans.
RSI(2) Buy Signal.
This scan searches for stocks that have just had an RSI(2) Buy Signal.
RSI(2) Sell Signal.
This scan searches for stocks that have just had an RSI(2) Sell Signal.
Further Study.
From the creators of the RSI(2) strategy, this book details more trading strategies and includes a chapter on exits. Connors also shows the details of his back-tests and provides guidelines to improve trading results.

“RSI-2 Strategy” from Larry Connors.
Here is the backtest that I made, from the « RSI-2 Strategy » of Larry Connors.
He’s also the co-author of the « Cumulative RSI » Strategy.
It took me 5 minutes to write the code, as the rules are very simple : no need to detail them.
Even if the strategy is positive on many stocks, indices, I don’t find it that great.
But you are free to test it and why not improve it.
The picture shows the CAC40 for the last 20 years.
Share this.
No information on this site is investment advice or a solicitation to buy or sell any financial instrument. Past performance is not indicative of future results. Trading may expose you to risk of loss greater than your deposits and is only suitable for experienced investors who have sufficient financial means to bear such risk.
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ne pensez vous pas que ligne 41 il faudrait C3v >90 plûtot que C3v <90??
Félicitations pour ce site.
There is an error at line 41.It should be :
On the CAC40, it gives better result with the error…Sorry for it.
My apologies to all :
with this new line, backtest show less brute gains, but far less drawdown and better profit factor (from 1,5 to >2).
Test it if you want 🙂
Here is the new picture :
Even for bigger Ut (here 15 mn)
May be it will be optimize.
RSI is an oscillator made for price centering. This strategy bet on mean reverting phenomena. I’m pretty sure that 2 bars of 1 minute can’t define this! 🙂
You are right, this system isn’t designed for day trading.
In my opinion, RSI with short periods work well for daily candles (there are plenty of strategies with RSI2, RSI5, etc.), but not for intraday trading, where there can happen big moves.
Good start. Works decently during stock runaway bull market. I have tested it over 80 year period (DJ industrial) and it is not profitable during many years.

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More Trading Tips for Stock Traders at: TradingTips.
Other recommended sites for traders at: WealthPire.
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technical indicator and trading strategy you should know:
much earlier TradingTips episode. In fact, it was.
featured in Episode #10. RSI-2 isn't really a new indicator,
but a particular application of RSI -- a two-period RSI --
and a set of trading rules for using it. The results?
Amazing. So amazing, in fact, that Connors recommends.
against using stop-losses!
in detail, step-by-step.
stock can be used in conjunction with RSI-2.
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RSI And How To Profit From It.
We all know there are no magic indicators but there is one that certainly acted like magic over the past 10 years or so. What indicator is it? Our reliable RSI. In this article we are going to look at two trading models that were first talked about in the book, “Short Term Trading Strategies That Work” by Larry Connors and Cesar Alvarez. It has been well established in various articles that a 2-period RSI on the daily chart of the stock index markets has been a fantastic tool for finding entry points. Sharp price drops in the S&P E-Mini futures during bullish markets have historically (since the year 2000) been followed by reversals. These reversals can often be detected by using the standard RSI indicator with a period value of two. Place this indicator on a daily chart and look for points when the indicator falls below five, for example. These extreme low points are buying opportunities.
Values below 5 are green. These are buy points.
RSI(2) System.
We can turn this into a simple trading model to test the effectiveness of the RSI(2) indicator on the E-mini S&P. In short, we wish to go long on the S&P when it experiences a pullback in a bull market. We can use a 200-day simple moving average to determine when we are in a bull trend and using a 2-period RSI to locate high probability entry points. We can then exit when price closes above a 5-day simple moving average. The rules are clear and simple:
Price must be above its 200-day moving average. Buy on close when cumulative RSI(2) is below 5. Exit when price closes above the 5-day moving average. Use a $1000 catastrophic stop loss.
The system backtest was performed from September 1997 through March 2012. A total of $50 for commissions and slippage was deducted per round trip. Below is a chart of what this system would look like along with the system results.
RSI(2) System Results.
Percent Winners: 67%
These results are great considering we have such a simple system. This demonstrates the power the RSI(2) indicator has had now for well over a decade. Just with this concept alone you can develop several trading systems. For now, let’s see if we can we improve upon these results.
Accumulated RSI(2) Strategy.
Larry Conners adds a slight twist to the RSI(2) trading model by creating an accumulated RSI value. Instead of a single calculation we will be computing a running daily total of the 2-period RSI. In this case, we are going to use the total of the 2-period RSI for the past three days. When you keep an accumulated value of the RSI(2) you smooth out the values. Below is a chart comparing the standard 2-period RSI indicator with an accumulated 2-period RSI indicator. You can see how much smoother our new indicator is. This is done to reduce the number of trades in hopes of capturing the quality trades. In short, it’s an attempt to improve the efficiency of our original trading model.
Accumulated RSI in top pane. Standard RSI in lower pane.
Price must be above its 200-day moving average. Buy on close when cumulative RSI(2) of the past three days is below 45. Exit when RSI(2) of the close of current day is above 65. Use a $1000 catastrophic stop loss.
Accumulated RSI(2) System Results.
Percent Winners: 67%
S&P Cash Market.
What would the 2-period RSI system look like trading 100 shares of the S&P cash market going back to 1993? It does rather well.
Conclusions.
So which one is better? The accumulated strategy worked as intended. It increased the efficiency of the standard RSI(2) trading model by reducing the number of trades, yet produced about the same amount of net profit. As a bonus, the drawdown was slightly smaller. While both systems do a fantastic job, the accumulation strategy may do a slightly better job. The Accumulated RSI(2) strategy will work well on the mini Dow as well as the two ETFs, DIA and SPY.
The EasyLanguage code is available below as a free download. There is also a TradeStation workspace. Please note, the trading concept and the code as provided is not a complete trading system. It is simply a demonstration of a robust entry method that can be used as a core of a trading system. So, for those of you who are interested in building your own trading systems this concept may be a great starting point.
Get The Book.
TradeStation RSI(2) WorkSpace.
2013 Update:
An additional article was published in 2013 which updates the RSI system and explores it in more detail. Read it here.
About the Author Jeff Swanson.
Jeff is the founder of System Trader Success – a website and mission to empowering the retail trader with the proper knowledge and tools to become a profitable trader the world of quantitative/automated trading.
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