| StockFetcher Forums · Filter Exchange · MODIFIED CONNORS RSI(2) FILTER | << 1 ... 14 15 16 17 18 ... 22 >>Post Follow-up |
| saratur 14 posts msg #95716 - Ignore saratur |
8/18/2010 12:28:59 AM Kevin - I have done some backtesting on the long-short system with your composite filters, at one month granularity So far I completed one year back. The simulated returns are significantly lower than the long term returns you received for the individual filters, or from what one may extrapolate from the real time test on this thread. It might be due to variation in exits or other parameters, market unfavorable to the system during this year – or errors in my backtest. To some extent I hope for the latter… Kevin – and/or anyone else following this thread – could you please check my results (all, or just a spot-check). If more details on the backtest will be useful, please post or email me at saratur2@gmail.com I could not figure out a way to test with StockFetcher stops and targets based on the ATR of each stock, or something similar. If anyone knows how to do this, please yell . In the test below I used fixed 3% stoploss 6% target. I did get somewhat better results using Connors’ standard 5 DMA exit and/or limited trade length. Test: Kevin’s composite filters, select by Composite score, top 5 (each long and short). Exits: Stoploss 3%, Profit target 6%, maximum 5 days . Price > $1 . I have relaxed volume to 200k shares (sinced I have noticed that some stocks in Kevin’s real time test are at lower volume than the original 500k ). Return is calculated for each month, using SF daily backtest estimated equity. A backtest of 4 months was used to derive the results for each quarter so as to minimize effects of discontinuity in stock selection. Results do not include commissions nor short borrow fees. Month end Long Short Long-Short Equity 7/30/2010 1.77% 2.52% 2.14% 1.002782472 6/30/2010 -7.43% -2.28% -4.86% 0.981754416 5/28/2010 -5.76% -14.12% -9.94% 1.031857827 4/30/2010 0.82% 4.00% 2.41% 1.145775539 3/31/2010 12.54% 13.47% 13.01% 1.118824742 2/26/2010 6.54% -5.31% 0.62% 0.990050484 1/29/2010 -5.95% -0.14% -3.05% 0.983998808 12/31/2009 5.13% -1.22% 1.96% 1.014912788 11/30/2009 3.03% 4.35% 3.69% 0.995433964 10/30/2009 -9.29% -0.11% -4.70% 0.960003596 9/30/2009 6.13% 0.45% 3.29% 1.007346035 8/31/2009 -5.47% 0.52% -2.48% 0.975236619 average: 0.17% 0.18% 0.17% The average monthly return is 0.17%, total gain after one year 0.28% . After commissions this would be a loss - which could vary widely, depending on the brokerage. Each position turns over appx 80 times a year. If commissions are $4/trade, at $5000 per positions those will be 12.8% / year . |
| Eman93 4,750 posts msg #95717 - Ignore Eman93 |
8/18/2010 1:26:07 AM Yea this is hard... if it was easy everyone would be rich....LOL Kevin I would have to say that the VXX/SPY oscillator is a thing of beauty .... if it triggers take the trade that day put you stop right below you last swing low.......... I think you make out well from looking at the 2 year chart anyway.... I have beaten the filter buy a day only that's it......... would not use it for exit though.... exit must be managed..... great entries a few whipsaws and losses are too be tolerated... the long runs make up for them in spades. |
| Kevin_in_GA 4,599 posts msg #95722 - Ignore Kevin_in_GA |
8/18/2010 9:36:38 AM Kevin - I have done some backtesting on the long-short system with your composite filters, at one month granularity So far I completed one year back. The simulated returns are significantly lower than the long term returns you received for the individual filters, or from what one may extrapolate from the real time test on this thread. It might be due to variation in exits or other parameters, market unfavorable to the system during this year – or errors in my backtest. To some extent I hope for the latter… ++++++++++++ I'm not surprised - if you look back at the trades I have selected from the list, they reflect a personal and subjective filter as well as the objective data filters. No way one could trade them all. Also, I only hold 5 long and 5 short at any time, which means you must select from the larger list. Also I have opted not to trade on some days, keeping a portion of the 40,000 in cash for that week. Honestly this is a method that is "backtest challenged" - that is why I backtest and posted all of the results from each element of the composite filter earlier. I have recently been looking at improved BB filters that I am adding in, but have not posted yet because they are still a work in progress. That is why I have recently reduced the volume requirement from 500000 to 200000, to be consistent with other backtest data on these systems. This filter has evolved significantly from the simple RSI(2) filter I laid out in the first post on this thread. This reflects a personal adjustment to meet my desired trading time frames and frequency, as well as trying to figure out what a good mechanical approach would be to set entries and exits. Still struggling a bit on that part, as you can see from recent posts ... |
| wkloss 231 posts msg #95764 - Ignore wkloss |
8/21/2010 2:02:27 PM Kevin, Since this project seems to be at a fork in the road, I wanted to offer some ideas. I'm wondering if there really are any short term mechanical systems that work consistently. Chuck LeBeau claims that the most profit per daycomes from trades in the 15-20 range. After that, gains diminish on a % per day basis. Eliminate a lot of the time and effort necessary to trade a short term system and your real return increases. Another consideration is capital. Unless you can generate a good weekly % gain consistently, trading a small $ account may not generate enough total dollars to justify your time. The more you have to replace mechanical rules with judgement, the system demands more of your attention. Increasing the trade length may offer some other benefits. From your previous posts, I get the impression you don't care much for options. If you don't want to use options as a stock substitute, you still have the ability to use protective puts. Some option spread strategies profit whether the stock goes up (for longs) or justs stays flat. Having the ability to use these strategies to enhance your system is a good thing whether you use them on every trade or not. This is a long winded way of saying that trend trading on a slightly longer time frame might be less work and more profit. I still hope your system development goes as planned and you identify an indicator that becomes the basis for a profitable mechanical system. If you are looking for a different direction, hopefully some of the ideas above might help. Bill |
| Kevin_in_GA 4,599 posts msg #95765 - Ignore Kevin_in_GA |
8/21/2010 6:09:57 PM Actually, not a fork in the road - I still have complete faith in the basic tenet of equal dollars long and short. It is the specific filters I am using that I want to rigorously validate. Consequently I have spent the last week re-evaluating the Connors filters and their applicability to broader set of stocks (remember, they were optimized against only 20 ETFs). The conclusion I have come to is that they are, on the whole, only marginal indicators for good trades when looking at the broader stock market. In fact, several of them offer no advantage whatsoever when back-tested against my usual selection rules of "close above 1 and average volume(50) above 500,000". Admittedly, the selections to date have worked out OK, but the back testing shows that this may have been a bit more luck than I want in a trading system. Also, each Connors filter has its own exit criteria that determine its profitability and win % - these are not a common exit, which has led me to look for different exit strategies that can be "unversally" applied even though the filters were not designed to exit at those points. Bottom line - this system is robust, but the specific rules driving stock selection, entry and exit need to be improved. |
| wkloss 231 posts msg #95767 - Ignore wkloss |
8/21/2010 8:40:04 PM You wrote" I still have complete faith in the basic tenet of equal dollars long and short." I didn't mean to question that part of your concept and I assumed the long/short could be applied to longer time frames. You wrote "but the specific rules driving stock selection, entry and exit need to be improved. " I view these rules as the system. Now I understand you are building trading rules around the long/short concept. This is the 1st part of the Forum I read each day. Very interesting stuff. |
| Kevin_in_GA 4,599 posts msg #95769 - Ignore Kevin_in_GA |
8/21/2010 9:50:00 PM Thanks. I have decided to "jettison" the Connors filters after a more robust backtest showed relatively mediocre performance. I am finalizing a completely new set of filters for this approach. The key attributes that each component must demonstrate are as follows: 1. Each filter must be independently validated against all traded stocks meeting my price and volume criteria. 2. Each filter is to be backtested from 1/1/2007, and must have generated at least 200 trades since then (for statistical robustness). Monte Carlo analysis will be done on each filter against a 10 stock portfolio – 1000 iterations per filter to be sure that the returns and win percentages are accurate and not biased by a few key trades. 3. All filters have the same basic entry requirements - for longs to be above the MA(100) but below the MA(10), and for shorts to be below the MA(100) but above the MA(10). 4. All filters are to use the same exit - close above/below the MA(10). This is the only exit criteria used in each filter. The last point is actually where my thinking is perhaps unique. Most filters are all about the entry conditions, and usually have not clearly delineated profitable exits. In this case I actually started with the EXIT planned out, then used optimization software to develop each separate filter entry. Compare this to the Connors' filters, which use %B, RSI(2), RSI(4) or cross of the MA(5) - when you get a 6/6 on these filters, you need to make a call as to which exit makes the most sense - too confusing, which usually leads to missed opportunity. So far on each of 3 separate filters (separate long and short versions) they all show at least 4% average gain in less than 10 days, typically with win percentages from 78-90% on at least 200 trades since 1/1/2007. The challenge is that I would also like these filter sets to be providing a relatively uniform number of trades each week - rather than be clustered around only a small set of dates and then go for long periods without any new trades being signaled. Once I have them assembled I'll know more about this and may add additional sets to generate greater coverage. |
| Kevin_in_GA 4,599 posts msg #95783 - Ignore Kevin_in_GA |
8/22/2010 11:52:08 PM Did not really do anything last week, but instead spent time redesigning my entire stock filter set – now it will most likely give fewer signals, but each one should have a much higher likelihood of being profitable. Filters are based on a sum of five factors: position relative to BB, CMO, W %R, TSI, and RSI. Mostly using Oversold/Overbought signals and momentum measures for these filers right now. Simple and responsive if you make sure that you have "pre-selected" good candidates based on MAs and Price ROC. Long Plays selected from the new filters: NTY (scoring 3/5) MDCO (scoring 3/5) Short Plays selected from the new filters: DYN (scoring 1/5) Only one decent short play from Friday – Gammon Gold (GRS) looks good, but it is currently above its MA(100), which I use to exclude short plays. It is reading 3/5 on the new filters if you ignore this rule. It is still below its MA(200), so if gold futures are looking negative it might be worth taking a stab at this one. Remember - all exits for these are based on a close above/below the MA(10). I’ll post a more detailed description on how these new filters were constructed and validated – all have been developed using data on 1670 stocks from 1/1/2007 until 6/30/2010, each generally yields a 4% return within 5 days, at a win percentage of 75% or higher. WAAY better stats than what I was getting using the Connors filters as described in his book! Fewer trades, so balancing longs and shorts might be tricky … |
| campbellb75 101 posts msg #95784 - Ignore campbellb75 modified |
8/23/2010 12:44:27 AM Hey Kevin- You haven't updated this thread with the new filter you're using, right? The results sound interesting. I modified your last one to use ATR profit targets and stop losses and was trading it with my IB simulated trading account. Did pretty well at first, but last week it was pretty choppy. Looking forward to seeing how this new one does. Thanks. |
| Kevin_in_GA 4,599 posts msg #95795 - Ignore Kevin_in_GA modified |
8/23/2010 2:24:08 PM New filters As promised, I have spent most of the last week playing with new optimization software from StrataSearch (which I highly recommend if you want to be glued to your computer for days on end – it’s very cool to watch these optimizations progress at a dizzying pace). As I had stated before, I am not convinced that the Connors filters, which were developed and optimized against a small set of highly liquid ETFs, can be effectively used against the broader market of stocks. In fact, in my quick testing of several of the Connors filters showed surprisingly low returns when used on stocks over the past few years. Also, each filter has been validated against a specific exit criterion, and they are not all the same. Therefore, when my filter returns a 6/6 on the Connors filters, which exit does one use? This led me to step back and begin with a clean sheet of paper. Literally. 1. I started by defining a common exit trigger for ANY filter I will be using. The easiest one to use is a close above/below a short term moving average. Since I don’t want these trades to run for more than a week or so, it should be either the MA(5) or the MA(10). Running some simple Bollinger band screens, the MA(10) was almost always more profitable. OK, MA(10) it is! 2. Statistical measures of price divergence from typical norms has been a key component in the overall strategy to date, and I wanted to keep this in any new filter set I developed. Bollinger bands are the classic measure of price movement from its normal trading range, and so at least one filter will use “close above UBB / close below LBB” as a trigger. 3. I wanted to make sure that I used measures of short term oversold/overbought as part of the filter set. The obvious ones were RSI, Williams %R, and CMO. I also included the True Strength Index (TSI) which is a great but relatively unknown indicator. I actually had to have this coded for StrataSearch so that I could optimize on it for these filters. 4. The final component was to look at the recent price rate-of-change for each stock, and select those which have appreciated within the last month. Testing several indicators against a series of ROC’s quickly showed that the higher the ROC, the better the results were. This was true for both longs and shorts – contrary to my original thinking. However, if you push this too high you get fewer trades that tend to cluster around a few trading periods, then go for a while with no trades at all. The current filters are based on a HIGH ROC, and I may need to reduce this to get a more uniform pace of trades – ideally a few per day both long and short. 5. All filters were optimized using data from 1/1/2007 until 6/30/2010, against 1670 stocks (all currently traded stocks that closed above 1, and had an average volume(50) greater than 500,000). All entries were on the open of the day following the signal being generated, and all exits were also at the open on the day following the close above/below the MA(10). Filter #1. Bollinger Bands Long Plays Back-testing on this shows 302 trades of which 228 were profitable (75.5%). Average trade length was 5 days, and average return per trade was 5.4%. Short Plays Back-testing on this shows 605 trades of which 470 were profitable (77.7%). Average trade length was 6 days, and average return per trade was 5.4%. Filter #2. Chande Momentum Oscillator Long Plays Back-testing on this shows 533 trades of which 411 were profitable (77.0%). Average trade length was 4 days, and average return per trade was 4.8%. Short Plays Back-testing on this shows 760 trades of which 629 were profitable (82.8%). Average trade length was 5 days, and average return per trade was 5.8%. Filter #3. Williams %R Long Plays Back-testing on this shows 465 trades of which 372 were profitable (80.0%). Average trade length was 4 days, and average return per trade was 5.5%. Short Plays Back-testing on this shows 1499 trades of which 1107 were profitable (73.9%). Average trade length was 5 days, and average return per trade was 3.1%. Filter #4. True Strength Index Long Plays Back-testing on this shows 729 trades of which 548 were profitable (75.2%). Average trade length was 4 days, and average return per trade was 4.6%. Short Plays Back-testing on this shows 611 trades of which 511 were profitable (83.7%). Average trade length was 5 days, and average return per trade was 6.7%. Filter #5. Relative Strength Index Long Plays Back-testing on this shows 769 trades of which 581 were profitable (75.5%). Average trade length was 4 days, and average return per trade was 4.5%. Short Plays Back-testing on this shows 789 trades of which 630 were profitable (79.9%). Average trade length was 5 days, and average return per trade was 5.4%. Looking at the average returns and win percentages for these five filters, they are head and shoulders above the Connors filters (which generally give 70% wins with less than 2% average return). I will undoubtedly tweak these over the next week or two, mostly by looking at several ROC regimes and possibly the ROC versus the ROC of the SPX to see when a specific filter set will do better than others based on the overall state of the market. For now, here is the composite filters for longs and shorts. Enjoy. COMPOSITE LONG FILTER: COMPOSITE SHORT FILTER: |
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