Stock Buy Signals
March 16th, 2009 by jackieannpatterson | No Comments | Filed in Moving Average, Objective Trading, Strategy Development, Technical StrategiesHere is part 2 about stock entry strategy or the buying process. The previous article talked about stock screening, which is the background investigation to select a pool of candidate stocks to buy when the time is right. The trigger or market timing signal is the topic of this article.
Why You Need to Time Your Entry
Once you have a universe of candidates, you need an entry signal or trigger. Stocks can sit around looking good enough to buy for a long time, and you need a discrete event to say “Buy Now”. Hard experience has taught me that “when I have time to complete research” and “when I feel excited about stocks” are not the best entry conditions. In retrospect, it was usually a price extreme that got me pumped enough to research stocks and hit the buying point. I’ve found that exercising the judgement to pick a better entry point can be more financially rewarding than just jumping in. Personally, I suspect that even a random entry point would be better than emotion-driven buying, and backtesting can help identify strategies that do better than random.
How To Time Your Entry
I see three broad categories that can be used as in entry signal: news events, clock or calendar events, and price events, especially as indicated by objective technical analysis. Let’s compare them.
News Events
If you’re new to the stock market, reacting to news events may seem the most natural thing in the world. However, a little experience shows that the market anticipates and prices in news before it happens. This is called discounting. As an example, remember the recent situation with Steve Jobs and Apple. It follows the saying, “Buy the rumor, sell the news”, only in reverse because bad news is what moves the market lately. Here’s what happened: Amid rumors of Jobs’ recurring illness, the price of AAPL declined, all the while Apple insisted Jobs was healthy. Then Jobs announced that he was taking a medical leave of absence. If the rumor of illness prompted a decline, then one might think that the news of his departure would tank the stock – he has had an unquestionable impact on the company, after all. What actually happened, though, is that AAPL traded down to a new 52 week low in after-hours trading on January 14, the day of Jobs’ departure. The following day, the price opened low, but regained most of it to close at near the high of the day. Price bounced around the lows for 3 days, and then began an ascent that ended 3 weeks and 30% later. The market had already priced in the news and the reaction went in the opposite direction, as it often does. The upshot of this example is that it is difficult, if not impossible, to form an objective strategy around the news because the news may be priced into the market and always must be subjectively interpreted.
Calendar Events
The second type of entry signals, clock and calendar events, are more objective than the news, but that’s not saying they’re 100% reliable. Some of the people who use this category of signals are
- day-traders who never hold overnight
- pro traders who only hold overnight
- investors following the adage to “sell in May and go away”
- small-cap investors who show up in December
- commodity traders following the seasonal fundamentals
- and those folks who mine the charts looking for the dates when a stock almost always seems to go a certain way
Some of the calendar-driven moves truly are driven by the calendar. Others are due to coincidence, while still others are illusion. Backtesting – either automatically or by manually checking the charts – can weed out the pretenders by determining which have been profitable in the past, and that is a useful first step. I think you owe it to yourself to take it one step further and look for a plausible cause for the move rather than betting good money on a pattern that came about by chance.
Technical Indicator Signals
The same can be said of technical indicator signals – you need to understand why they work — plus you need to make sure they are objective. Aronson’s book makes a good case for using objective indicators rather than relying on subjective information for trading decisions. A signal is objective if there is no “wiggle room” in describing it, if any two people always see it the same way (not like pattern recognition) and/or you could program it into a computer. Elder’s first book gives good descriptions of technical indicators grounded in crowd behavior.
You can also think through the implications of the strategy. For example, consider the trend-following strategy of buying when price hits a new high. A new high doesn’t guarantee that the price will keep going, but all runaway stocks had to make new highs along the way. A good thing to know is how many stocks making new highs go on to make a profit for investors holding for, say, one year. Backtesting is one good way to estimate this info. Sign up for email alerts to find out when new highs will be featured in BackTesting Report.
Backtesting can also help us overcome our human tendency to become overconfident in a signal because we can easily spot on a chart the times that the signals worked and all too easily overlook the false signals. A false signal is where the signal comes but the stock price doesn’t go in the expected direction long enough for the trader to profit. It’s expensive to learn about false signals and our little foibles of human cognition in live trading.
The previous article used the example of price above the moving average to illustrate a potential stock screen. A corresponding signal using moving averages is price crossing the moving average, or moving averages crossing each other. They offer objective, discrete events to replace emotional guesswork with rational decision-making. To find out more, check out the BackTesting Report MA Buy Signal package.
Updated on 3/17/09 to add: (BacktestingBlog is an Amazon Associate. )
Updated on 3/19/09 to add: (Author has a position in stocks mentioned in this article. )
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book cites a few studies that prove our human tendency for loss aversion. To codify that, write a system with: 
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