Are there quant basket traders out there? I need a hand from those of you who use qualitative methods to size and time the opening and the closing of the basket trades --instead of I shut when I feel pleased with my profit--
I'm not myself a basket trader. My motivation comes from the fact that I'm trying to develop a system that a number of instances, mainly at the ranging phases, is equivalent or at least very similar to basket trading.
I tried to find whether there is an optimal method to start and shut a commerce under the premise that the instrument is mean reverting. I found a very complied method seeking to address this dual stopping problem (in the pdf). The alternative is based on the subjective cost of remaining in the market more versus the anticipated increase of the payoff. But the interest rates are low today. It can be interesting for people using choices, due to the time decay, but it does not appear to match my needs.
Additionally, I found a very easy method that comes in keeping up a lot size linearly proportional and contrary to the space of this price to the expression measured in deviations. In brief I add on my losers at every standard dev. A grid. But I don't get the rational behind the thought. Say the price is at the mean. I'm flat. It extends 1 SD below the mean. I start a lot long. It goes to the next SD below the mean. I add another 1 lot long. If the price returns at 1 SD will I shut one lot to keep the linear exposure?
In case the price goes into the 3rd SD I have 3 positions open and a floating reduction of (2 1 0=-RRB- 3 times the SD. I just get 3 SD if it returns right to the mean but a 6 SD floating reduction should it hit the 4th SD. At first it seems better to hold on and wait the price to come back to the mean and find a 6 SD profit. But since the price is wandering up and down before returning to the mean possibly the method is logical. If price goes -1, -2, -1, -2, -1, -2, -1, 0 the profit is 4 instead of 3. For sure I dislike the idea of adding about the losers while the price is moving against my positions. Especially because I'm aware the range won't last forever and I certainly don't wish to add against a breakout. I assessed the ranges don't continue long enough to offset this reduction.
Because of the mean reversion assumption the probability of winning can't be utilized: per assumption/definition it is 100%! I kept thinking and discovered that it'd make sense to weight the exposure by the probability of being at a given level. I use the usual supply to keep it easy. The most probable place of the price is on the mean. But it is the goal level so no profit. The farther from the mean the more profit but also the probability of being there. It's better to be exposed when there is more potential. Let us multiply the potential profit (the space in SD) by the probability N(x), N the standard supply:
The exposure is highest in 1 SD above or below the mean. Employing the formulation I scale my losers out. Sounds good in case of a breakout of this range. But I also scale out of the winners. And if the price ping-pongs between two amounts I take a reduction even when the price eventually reverts! Definitely not good. I feel like the exposure can't be solely dependent on the job of the price in the range.
How do you handle it?
https://www.forexforum.co.za/attachm...1757115554.pdf