For me, those things were answered years ago in the development and testing process. However, we can say this:

1. If you believe the markets decline faster and sharper than they rise, then you may consider the possibility intuitively that your exit may need to be faster than your entry. In Tennessee, we all that "common sense", and it's sometimes a good starting point. :)

2. "do you believe that the tighter the stop point, the greater the loss will be in time". A tight stop point doesn't reduce your risk if it's too tight, say, within the normal daily noise of the market. If a price swings plus or minus 5% in a normal day, then a stop within that is sure to get stopped. If you do that very often, you'll have a lot of small losses which may lead to a larger overall loss.

3. A systems predefined exit point, that is, the initial risk amount at the point of entry, may very well be very different than it's exit point after a position has become profitable. There are all kinds of different exit methods. Though I don't discuss how our systems exit, I will tell you that there ere multiple exit systems involved and they are asymmetric, meaning they are not the same as say, the one that determines how much we risk at the beginning.

All of these things were determined during the design and development stage. The only way to understand how a method or parameter works is to test it and then use it in real time. I tested thousands of exit methods to determine which we'll use as part of a complete system. It's a function of the other parts of the system and our objectives for total return and risk control. I decided nearly a decade ago exactly how I'll exit my positions today. I don't sit around trying to figure out when to sell or what's going to happen next.

Again, good article and definately lends itself to some good independant thinking...

It seems many systems that are publicly known or written about are incomplete. Maybe they are made public by inexperienced researchers. You may consider that no one has any incentive to make public any specific methods that may actually work. For example, if you write to popularize a moving average, you may find that it no longer works so well. If we know it's become popular, we can take advantage of the liquidity that occurs at the signal.