Category Archives: RSI

Backtesting Options: Selling SPY Puts on RSI(2)

Let’s try the good old strategy for RSI(2) mean reversion.
Buy on Rsi(2)<30
Sell on Rsi(2)>60
Execution is on the Open of the next day.
This is what trading the SPY etf looks like.

How about using the same signals and selling 10, 1-point away from the floor price, front month Puts.*
Again, we sell 10 Puts right below the SPY price. 
So if SPY is at 145.7 we would sell the (floor(145.7)-1) 144 strike Put.
We sell the front month before the 11th of the month, otherwise we shift to the next month.
We cover the position on an Rsi(2) sell signal or let it expire.
All Buy and sells are on the next day Close and on the ask for buy orders and bid for sell orders.**

Of course there are money management differences: The top chart reflects %-of-equity money management (hence, the compounding), while the bottom does not (it buys 10 contracts, rain or shine) . But otherwise, I am surprised at the similarity in the shape of the equity curve. Where is the extra time premium I would expect on buying the fear? 
How about selling further out of the money Puts. 1–>5 points away from the current price:

Similar results. Any thoughts?

*Many thanks to Dave. for his help.
**I will caution the reader that backtesting options is fairly involved and may contain errors including but not limited to: historical data errors, programming errors, underestimation of slippage and execution costs, unrealistic assumptions on price fills, etc. I use EOD data, so there is no information on the open/high/low of the day. 

Connors RSI – Part 1

One of the readers of this blog, Mark, alerted me to a new indicator/system published from Connors/Alvarez : The ConnorsRSI.

What is the ConnorsRSI?

It consists of three components:
a. Short term Relative Strength, i.e., RSI(3).
b. Counting consecutive up and down days (streaks) and “normalizing” the data using RSI(streak,2). The result is a bounded, 0-100  indicator.
c. Magnitude of the move (percentage-wise) in relation to previous moves. This is measured using the percentRank() function.

The formula given is:
ConnorsRSI(3,2,100) = [ RSI(Close,3) + RSI(Streak,2) + PercentRank(percentMove,100) ] / 3

Bottom line: Connors/Alvarez have used similar indicators in the past. What is happening here is that they are creating a more robust indicator by averaging the three. They are “normalizing” the three indicators (rsi, consecutive moves and magnitude of move) to a 0-100 range and then averaging.

Connors/Alvarez propose a strategy that uses the Connors RSI coupled with other rules and filters on large section of U.S. Stocks.
In this post we’ll test the indicator on one security only, the SPY etf (as a proxy for the SP500).

Test A –
Instrument – SPY
1. Using ConnorsRSI(3,2,100) – We ‘ll call it Crsi.
2. Buy on Crsi<15
3. Sell on Crsi>70
4. Buy /Sell on the next bar Open price.
5. Commision of $0.005.

Test B –
The obvious question is whether the parameters are “fitted” to the data. What about using other parameters:
ConnorsRSI(a,b,c)
a–>2-4
b–>2-4
c–>80-140
BuyThreshold –>5-50
BuyThreshold –>50-95

Test C –
What about before 1994? We ‘ll use ^GSPC (the SP500 Index).
Same parameters as “Test A”

Detailed results Test A

All trades
Initial capital 100000
Ending capital 336322.84
Net Profit 236322.84
Net Profit % 236.32%
Exposure % 6.55%
Net Risk Adjusted Return % 3606.42%
Annual Return % 6.30%
Risk Adjusted Return % 96.17%

All trades 179
Avg. Profit/Loss 1320.24
Avg. Profit/Loss % 0.73%
Avg. Bars Held 4.77

Winners 136 (75.98 %)
Total Profit 439687.37
Avg. Profit 3233
Avg. Profit % 1.71%
Avg. Bars Held 3.93
Max. Consecutive 11
Largest win 15964.53
# bars in largest win 3

Losers 43 (24.02 %)
Total Loss -203364.52
Avg. Loss -4729.41
Avg. Loss % -2.37%
Avg. Bars Held 7.42
Max. Consecutive 3
Largest loss -35059.29
# bars in largest loss 10

Max. trade drawdown -58157.34
Max. trade % drawdown -23.75%
Max. system drawdown -58157.34
Max. system % drawdown -23.28%
Recovery Factor 4.06
CAR/MaxDD 0.27
RAR/MaxDD 4.13
Profit Factor 2.16
Payoff Ratio 0.68
Standard Error 20256.9
Risk-Reward Ratio 0.5
Ulcer Index 3.5
Ulcer Performance Index 0.26
Sharpe Ratio of trades 2.23
K-Ratio 0.0404

7 Winning Trading Systems Reviewed – Pt. 3: RSI 25 75

Read pt.1
REad pt.2
Back in 2009 Larry Connors and Cesar Alvarez published several short term trading systems in their book “High Probability ETF Trading”. They described 7 mean reverting strategies. 
What happens, then once a strategy becomes public domain? Do they loose their edge?
All tests are performed on a set of 20 ETFs:

DIA,EEM,EFA,EWH,EWJ,EWT,EWZ,FXI,GLD,ILF,IWM,IYR,QQQQ,SPY,XHB,XLB,XLE,XLF,XLI,XLV
Tthe strategy can hold  up to 10 ETFs at any time.

Strategy 3:  RSI 25-75

The rules:
These rules are presented as found on the internet. Please refer to the original book for more info.

ETF is above MA(200)
4 period RSI<25
BUY on the close of the day these criteria are met.

*Aggresive version: Buy another unit if the 4-period RSI falls below 20

SELL on the close when

4 period RSI>55

For SHORT/COVER.

ETF is below MA(200)
4 period RSI>75
SHORT on the close of the day these criteria are met.


COVER on the close when

4 period RSI<45



“Out of Sample” – 01/1/2009-9/5/2012
Profit = 31651.69 (31.65%), CAR = 7.78%, MaxSysDD = -16739.86 (-13.38%), CAR/MDD = 0.58, # winners = 376 (73.44%), # losers = 136 (26.56%) 

*Aggresive Verion :”Out of Sample” – 01/1/2009-9/5/2012
Profit = 39137.94 (39.14%), CAR = 9.41%, MaxSysDD = -21294.28 (-15.50%), CAR/MDD = 0.61, # winners = 382 (74.61%), # losers = 130 (25.39%) 


These results are good and trade-able at 8 to 9% annual return vs 13-15% draw-downs. Keep in mind these are “out-of-sample” results after the strategy has been published. Although they underperform the market (SP500) they have superior statistics (reward/risk) and will outperform when leveraged.

* All tests performed are not guaranteed to be correct. Please verify any results for yourself. Amibroker code is available upon request.