So one of the key differences between you and other trend-following managers is that you have developed a way of defining when not to play? In any situation or game, you can define a positional advantage for any player—even the weakest one. In
trading, you can define three categories of players: the trade, the floor, and the speculator. The trade has the best
product knowledge and the best ways of getting out of positions. For example, if they are caught in a bad position in
the futures markets, they can offset their risk in the cash market. The floor has the advantage of speed. You can
never be faster than the floor. While the speculator doesn't have the product knowledge or the speed, he does have
the advantage of not having to play. The speculator can choose to only bet when the odds are in his favor. That is an
important positional advantage.
You mentioned before that you used increased volatility as a signal to stop trading a market. How many days of past data do you use to determine your volatility filter? Anywhere from ten to 100 days.
When you say ten to 100, are you trying to be deliberately ambiguous or do you mean you use different time frames within that range? We look at different time windows in that range.
I fully understand the logic of your 1 percent stop-loss rule. However, my one question is: Once you are stopped out of a position without the system providing an opposite signal,* what gets you back into the trade if the market reverses to its original direction? Isn't it possible that you could get stopped out on a moderate price reaction and then miss a subsequent major move? If the market makes a new high, we get back in.
*For example, if a long position is stopped out on a money management rule without a sell signal actually
being generated, the system will still be in a long mode and no buy signal will be generated, no matter how high
prices go. (If, however, a sell signal were generated, the system would begin monitoring for a buy signal.)
