I have purchased the book. As a previous poster noted, much of it is derived from previous work put in the public domain by Connors. However, that doesn't mean it is useless. It never ceases to amaze me how many posters argue opinions without any facts to back up their argument. If you have ever backtested, or much more importantly, actually TRADED strategies, one would realize there IS an edge in trading reversion to the mean systems. If you don't think big institutions use this kind of info, or pay others to find a quantitative edge, then you are a fool. Think of Tom DeMark and how many hedge funds and others have paid for valuable information that is proven to give an edge. And know that most of it is PRICE BASED, not your typical bland 'MACD crossover' crap that IS useless. The RSI that Connors uses is one of the few price derivative indicators that actually has merit and can provide an edge. To wit, the author of this book has a chapter on one of the RSI systems that can be employed on liquid ETFs. Using the backtest from the inception of the ETF, or back to 1992 (whichever has more history) and testing it through 12/31/2008, Connors states that in this particular system the SPY trade worked 82.1% of the time with an average gain for all trades of +1.23%, and holding the trade on average for 5.2 days. I decided to code it and run it from 1/1/2009 through the present (7/3/2009)...here are the results: Long trades = 1 Win = 1 Lose = 0 Avg Win = +0.48% Avg Loss = 0 Short Trades = 6 Win = 5 Lose = 1 Avg Win = +4.09% Avg Loss = (4.36%) I know this is a small sample size given the limited amount of data available, but we can see as a whole the 'system' was correct 85.7% of the time with an average profit for ALL trades of +2.37%, giving a profit factor of 4.74. The database I use apparently has more history than the one Connors used, as I tested the strategy on the SPY and came up with more trades than he. I then went to the particular trades to validate that the parameters were indeed met. Here are the results for the SPY going from 1/1/1989 through 12/31/2008: Long Trades = 125 Win = 105 (84%) Loss = 20 (16%) Avg Win = +1.64% Avg Loss = (1.69%) Avg All = +1.12% Max Consecutive Winners = 13 Trades Max Consecutive Losers = 1 Trade Avg Winner Held = 4.14 Days Avg Loser Held = 11.15 Days Profit Factor = 5.36 Short Trades = 39 Win = 24 (61.5%) Lose = 15 (38.5%) Avg Win = +2.15% Avg Loss = (2.86%) Avg All = +0.30% Max Consecutive Winners = 7 Trades Max Consecutive Losers = 3 Trades Avg Winner Held = 5.08 Days Avg Loser Held = 14.47 Days Profit Factor = 1.28 Combining the results we come up with 78.7% winning trades for an average gain of 0.93% and a profit factor of 3.05. Not too shabby, and definitely gives one an edge. Personally, I would incorporate a time-based stop on this system as every trade that went beyond 10 days, with 3 exceptions, was a loser. Oh, and I might note if Monday is another down day in the SPY, AND we manage to hold ABOVE the 200 Day Moving Average, a Long signal will likely fire for this strategy on the close that day. A few other observations - This strategy, as well as others in the book, were robust and consistent across the other ETF's that were tested. The strategies are part of a larger framework that may tell one when to 'step on the gas' or 'ease up' relative to the securities one is trading. For example, if one initiates a trade in a stock shortly after the open when one of these signals is in play, then one might consider adding to their size (managing the risk appropriately, of course)... Lastly, ideas that come from books like this are a starting point for further research into other ideas. I will elaborate a bit more on that with a strategy I wrote based on ideas such as these presented in Connors' book.
why not provide a bit of data to back up your claims? you are some kind of programmer, no? as you can see, bentedges ran the data and reached a conclusion about the validity of the strategies in the book. what do you have to counter the results? surf
These results are not statistically significant. Less, much less, than 1 trade per month. If you try to trade this system the market will fade it right away. Look at the short trades. Their number is totally insignificant for a period of 20 years. The profit factor is 1.28, close to noise level. This is probably an over-fitted system and far from being an edge. For a period of 20 years you should have 1,000 or more trades to even start considering using the system.
In a previous post I stated I would show a simple strategy that can give one an edge based off of ideas from other's strategies. One of the great things about learning from others is that it helps you to think and branch out into other ideas that very well may be profitable (provided one is willing to put in the time, effort and energy.) A few things to note that I feel are important: 1. The KISS principle. Simple IS better. If you have 47 parameters or some such nonsense, the strategy will NOT be robust and there is a strong possibility it will blow up at some point in the future. 2. Generally speaking, a strategy should work across multiple time frames and securities (with minor adjustments.) This goes back to #1 and being a robust system. For example, if one uses a moving average in their strategy of say, 150 days, but they then try to optimize it by going to 168 days and the results are a bit better, but then they test 135 days and the system deteriorates badly, then they need to look at the structure of the strategy and if it is sound. 3. Risk management, and in particular, position sizing, are very important in the big picture. A guy that throws his whole wad into one great strategy, or for that matter into each trade, is bound to blow up. The inevitable drawdown will kill them, which leads me to... 4. The toughest thing with any strategy is following the rules and not letting emotions or ego get involved. When I was working at a hedge fund some years back, there was a dedicated programmer/trader who found a great system to trade the Q's. (Aside - he used to work for Ned Davis Research, and has since returned to that organization. This is a research firm that funds pay tens of thousands to get their insight, but I digress...) Anyway, so this system performed well in the backtesting and out-of-sample testing, so they started trading it. Long story short, after a few months it went into the inevitable drawdown with like 4 losing trades in a row. One of the principals said, "We're not taking any more signals from that system." Yep, you guessed it - the strategy went on a fantastic run that would've (helped) make their year. Again, if one has did the work, it's time to check the emotions and ego at the door. All too often a trader wants to be 'right' when all they should worry about is trading with discipline. If the strategy is sound, the profits will follow. Now, onto this very simple system that anyone can follow without having to be a programmer. It doesn't make many trades, but when it speaks, I listen. Again, it isn't the holy grail, but as part of the bigger picture in the context of a total, diversified long/short portfolio, it will add alpha. Oh, and yes, this did come from ideas from others...in particular, Zweig and Connors. This strategy was designed for ETF's, but is able to work with individual stocks...I personally use other strategies for stocks. And I would be surprised if something similar hasn't already been put in the public domain. RULES for LONGS: 1. The closing price is ABOVE the 200 day moving average. 2. Enter the trade on the close when the price is 3% or more BELOW the 5 day moving average. 3. Exit the trade at the close when the closing price is ABOVE the 5 day moving average. RULES for SHORTS: 1. The closing price is BELOW the 200 day moving average. 2. Enter the trade on the close when the price is 3% or more ABOVE the 5 day moving average. 3. Exit the trade at the close when the closing price is BELOW the 5 day moving average. Very simple, right? And purely price structure with no fancy indicators necessary. Here are the results for some commonly traded ETFs going back to their inception (at least 5 years of data.) : QQQQ # Trades = 109 Winning Trades = 83 (76.15%) Losing Trades = 26 Long Avg Win = 2.44% Long Avg Loss = (3.26%) Long Combined Avg = 1.07% Short Avg Win = 3.82% Short Avg Loss = (6.09%) Short Combined Avg = 1.47% Largest Win = 12.89% Largest Loss = (21.86%) (DIVERSIFY!) Max Consecutive Winners = 12 Max Consecutive Losers = 3 Winning Avg Held = 3.14 Days Losing Avg Held = 7.15 Days Profit Factor = 2.17 SPY # Trades = 29 Winning Trades = 23 (79.3%) Losing Trades = 6 Long Avg Win = 2.7% Long Avg Loss = 0 - no losers Long Combined Avg = 2.7% Short Avg Win = 3.39% Short Avg Loss = (4.36%) Short Combined Avg = 1.18% Largest Win = 11.18% Largest Loss = (11.05%) Max Consecutive Winners = 5 Max Consecutive Losers = 1 Winning Avg Held = 3.09 Days Losing Avg Held = 9.0 Days Profit Factor = 2.71 EEM # Trades = 35 Winning Trades = 25 (71.4%) Losing Trades = 10 Long Avg Win = 2.32% Long Avg Loss = (3.72%) Long Combined Avg = 0.19% Short Avg Win = 5.5% Short Avg Loss = (3.91%) Short Combined Avg = 3.41% Largest Win = 20.34% Largest Loss = (8.39%) Max Consecutive Winners = 5 Max Consecutive Losers = 4 Winning Avg Held = 3.04 Days Losing Avg Held = 6.7 Days Profit Factor = 2.90 GLD # Trades = 15 Winning Trades = 11 (73.3%) Losing Trades = 4 Long Avg Win = 2.46% Long Avg Loss = (1.87%) Long Combined Avg = 1.59% Short Avg Win = 4.36% Short Avg Loss = (2.38%) Short Combined Avg = 1.66% Largest Win = 4.71% Largest Loss = (3.61%) Max Consecutive Winners = 3 Max Consecutive Losers = 1 Winning Avg Held = 3.64 Days Losing Avg Held = 6.50 Days Profit Factor = 3.79 SMH # Trades = 85 Winning Trades = 63 (74.1%) Losing Trades = 22 Long Avg Win = 2.47% Long Avg Loss = (1.88%) Long Combined Avg = 1.31% Short Avg Win = 4.20% Short Avg Loss = (4.04%) Short Combined Avg = 2.08% Largest Win = 10.07% Largest Loss = (23.05%) Max Consecutive Winners = 10 Max Consecutive Losers = 2 Winning Avg Held = 2.78 Days Losing Avg Held = 5.45 Days Profit Factor = 3.02 OIH # Trades = 72 Winning Trades = 49 (68.1%) Losing Trades = 23 Long Avg Win = 2.20% Long Avg Loss = (2.72%) Long Combined Avg = 0.81% Short Avg Win = 4.45% Short Avg Loss = (5.74%) Short Combined Avg = 0.96% Largest Win = 17.91% Largest Loss = (15.34%) Max Consecutive Winners = 6 Max Consecutive Losers = 2 Winning Avg Held = 3.35 Days Losing Avg Held = 6.43 Days Profit Factor = 1.69 I Included OIH because a trade just triggered on the close on the last day of the week (Thursday.) It is a long trade, and the closing price of OIH was $92.62. Given that the last 2 trades in OIH were losers, I am thinking this one stands a reasonable possibility of coming in the black...
Not statistically significant? I disagree. If a very small town in the midwest has 125 people that are not related by blood, but that same small town has a cancer rate that is 5X higher than the state average, would that be considered statistically significant? Would one be able to safely say there is potential causation? As for being an over-fitted system, it is obvious you have very little, if any experience in backtesting. This strategy from Connors works across multiple markets and asset classes, even if it is designed for use with ETF's. Saying the market will fade it right away is just silly and has no basis in fact. The profit factor being 1.28 on the short side has more to do with the simple fact that bear market rallies are the most vicious, as well as the general upward trend in equity markets. Furthermore, if we take this same strategy and employ it across a wide swatch of equity securities such as say...hmmm...the S&P 500, what would the results be? Want 1000+ trades? Lets see: Test Period: 8/98 to 6/30/09 Assumes 2% of equity per position, no margin, and EXCLUDES dividends. # Trades = 15,450 Winning Trades = 10,209 (66.08%) Losing Trades = 5241 Avg Win = 3.54% Avg Loss = (5.82%) Max Consecutive Win = 36 Max Consecutive Loss = 17 Total Avg Win/Loss per Trade = 0.40% Total Net Profit = +197.12% Annualized Gain = +10.06% Max Drawdown = (16.87%) 5/8/2009 Best Monthly Return = 10.21% Worst Monthly Return = (9.28%) Total Market Exposure = 78.92% Hmmm...what has been the return for the buy and hold S&P investor over the past 10 or 12 years or so INCLUDING dividends? Yep, even though this strategy wasn't meant to be for equities, it sure does seem to have a robust quality about it, huh? Maybe that Connors fellow has a clue what he is talking about. One might even be tempted to say there is an 'edge.'
You do realize that's not a good assumption. In fairness, however, that is a good system in that it's simple, based on common sense, and has a built-in loss limit, sort of, in the 5-day average rule. But really, most markets, if being held overnight, need to have a hedge put on them because it is a simple fact that there are many many times when you get a wild morning swing that then reverses, and if you're on the wrong side of that swing and you don't have a hedge, you'll sell right into the panic and find yourself watching while the thing goes off and returns to a profit later that morning when it goes back your way. Which is why I use options. If it does swing the wrong way, I'll close the hedge position for whatever profit it made, and let the rest of the day do what it wants, if I'm holding a position like this where you only trade on the close. Makes it far more likely that you'll hold through the crazy swings and not do something stupid. Which, by the way, is why I like and trade GDX: options in $1 increments, and they're liquid. Makes hedging very easy, and even profitable from time to time.
http://www.amazon.com/High-Probabil...=sr_1_1?ie=UTF8&s=books&qid=1245796871&sr=8-1 solid methods = consistent profits over time surf
Yes, perhaps not a 'good' assumption, as I understand the coin flip analogy and statistics. Nevertheless, with the OIH historically having the max consecutive trades go bad at 2, and given they are at/near support, I think taking 2-5% of one's equity for a trade makes a ton of sense. There are a few other factors I could throw in related to systems/strategies, but won't go into that. I think options are good from the perspective of hedging and limited speculative purposes, but the primary reason I don't trade them is because we've now introduced more variables into the mix, i.e. implied volatility and time decay. I tend to use pairs as my main strategy, and while that is not without its own risks, I don't need to bump that risk up by adding other elements to the mix. I appreciate your comment...trade 'em well!
Oh, btw, in addition to the OIH, the other big proxies for the market like SPY and QQQQ will likely trigger at the close on Monday if it is a down day. Just FYI. Turnaround tuesday for a trade in these securities might just work, but I'll take a look at the evidence when/if we cross that bridge.
An annualized gain of 10.06% with a 16.87% drawdown is not particularly impressive. Drawdown is arguably the most important thing to consider, since it helps one guess how much leverage to use (or not to use).