Type something and hit enter

ads here
On
advertise here

Among the few others in this forum who both trade actively and play "catch a falling knife", what stats do you use to measure the quality of your decisions and how do those look at the moment?

The "decision quality" stats I like most are to look at the performance (up to today) after I sold of every lot I sold (even though post sale performance doesn't affect my balance) and compare that to performance of every lot I bought (independent of whether I still own it).

As of end of Oct, those stats looked rotten for the sum of Sep and Oct. I sold a bit more than I bought in Sep and the things I sold in Sep were on average down a bit more than the things I bought were down (so Sep was retroactively OK but not exciting). The few things I sold in Oct were down far more than the many things I bought. But overall, the fact that I bought so much more in Oct than I sold brought the whole trading quality stat to negative.

But I keep those stats for any month always changing because they are performance ever since (one end in the month being measured and the other end permanently open), and the "falling knives" I bought in Oct did great today.

The stuff I bought in Sep ended today down 7.1% from purchase date, while the slightly larger amount I sold in Sep ended today down 10% from sale date (so correct on selling more than I bought and correct on buying stocks that didn't do as badly as those I sold).

The mere 4 lots I sold in Oct are now down 4.4% from when I sold. But the big flip is that the 26 lots (5.4 times the dollar total that I sold) are now up 1.3% from purchase. So (viewed just from this moment in time) great decision quality because what I sold went on to do so much worse than what I bought.

Obviously, these stats change every market day forever. So just as today flipped those stats from rotten to good, tomorrow could flip them the other way. But longer term, my choices of what to trade seem to be good.



Submitted November 01, 2018 at 04:40PM by jsf67 https://ift.tt/2qnLJAM

Click to comment