I have to admit that much of what I write about caters to the more experienced trader. So, to balance the scales, this blog is for the ‘newbie’.
Ten to Fifteen Percent of my net income goes to continuing education - in the form of e-books, books and seminars. Most fail to add to my bottom line but at least I know what’s out there. Occasionally, I am pleasantly surprised.
The distinguishing factor is not the cost of the item or the mode of delivery: sometimes it’s an e-book that costs US$97.00 (e.g. Forex Trading Strategy), sometimes it’s a course that costs US$6000.00 (e.g. This is a very good course; the one run by http://tradewithpride.com).
The distinguishing factors are: is the material useful and does it suit my personality? Thirty-years in the markets gives me the experience to know what and what is not likely to work; and what is and what is not likely to work for me. The two are linked but not interchangeable.
The newbie does not have the knowledge or experience to make this judgement. So, here are a few guidelines to help you decide if the latest e-book offering is worth following.
The first rule is don’t believe the hype. You won’t make a large fortune from pennies at a cost of US$67.00 to US$167.00. The best you can hope for is a system that will produce a positive expectancy. Let’s go back to my favourite formula for trading success:
(Avg$Win x Win Rate) - (Average$Loss x Loss Rate) = >$1.00
Go through the e-book, looking for this info. If the book doesn’t supply it, program (or have someone program) the rules and test them - most of you would probably use TradeStation or Mestastock.
Let’s say the book provides the data. Examine the data to see what is producing the Expectancy Return.
- If the expectancy is produced by a high win rate on any timeframe other than a very short-term one, then it’s either not robust (i.e. the results will not be replicated) or the results aren’t genuine. In this probability game, you have one of two choices:
- a) a high win rate over a short time-frame with a small AVG$win or
- b) a low win rate over a longer timeframe with a larger AVG$win
In all my years of trading, I have yet to see a successful approach that does not fall into one of the two categories.
Secondly, make sure the entry signals are normalized using a volatility benchmark - usually they are not. This means that once the current volatility fails to match the test sample, the results can be vastly different.
Let me give you an example.
This week I downloaded the newest FX offering. It’s a volatility breakout system: work out an average price; use a price filter above the average to buy and a price filter below the average for a sell. There is a trailing stop rule of 40% i.e. if the market has achieved 40% of the target pips, bring your stop to breakeven.
The author provides:
- Some generic suggestions of what the profit target should be (”30-50 pips’ or ‘75-100′ pips). On a risk:reward basis, the stops are .75:1 (for targets of ‘75-100′ pips) or 1:1 (for targets of ‘30-50 pips’).
- He also provides some TradeStation optimization of various pairs. For example for the AUDUSD, the optimization is an 89 pip profit target with a stop loss of 59 pips and a breakeven stop of 60% (not 40% of the generic rules).
Ok what’s the problem with the system rules? Think about this for a moment before reading on.
The rules will work for the volatility conditions at the time the author wrote the e-book! If conditions change, the suggested parameters will be ineffective.
Let’s take the AUDUSD:
- From March 29 2006 to July 24 2007, the Average True Range (ATR) was 63 (with a standard deviation of 24).
- Since July 24 2007 to date, the AUDUSD’s Average True Range (ATR) has been 120 points (with a standard deviation of 59).
- In short in the past 12 months, the volatility has doubled!
What does this tell me?
- The e-book was probably tested in the post July 24 2007 period. This is a lower probability of pocketing 89 points daily if the ATR is 69 points than when the ATR is 120 points.
- The other reference points all suffer from the same drawback: when conditions change, they don’t apply.
So, let me recap this second point: ensure any advocated system rules normalize its parameters with a volatility benchmark. The ATR is as good as any for this type of measurement.
Thirdly, test the system over a variety of conditions trending, congestion etc. I know some, if not all, will be reluctant to do this. But think of it this way: if you don’t, you have no way of knowing how the system will behave over different conditions.
Finally make sure you have some rules for position sizing, portfolio risk, per contract risk and for the increase and decrease of exposure (as your equity increases or decreases). In other words: make sure you have some meaningful money management rules.
Refer this blog post to a friend or colleague…
