KEA had a small DD (-5% aprox) so I could buy a little (was the last darwin in “waitning for a DD” mode). Since then almost every day has done a new ATH.
4 darwins reached the SL (at -25%DD from ATH):
MZO (-88,66, low odds to have a second try, actually is at -40%DD). QRK (-89,08,sold at the lowest and have recovered a significant part of the DD, probably will deserve a second chance). ZUR (-78,55, sold 2 days ago, to soon to make a decision). PWQ (-86,64, sold at the lowest and recovered a little, almost 1 month without trading and his Equity is zero, so I assume the trader has given up, so discarted).
PWQ has been discarted, so I had selected a new random darwin with the selection rules. ITN (in “waiting for a significant DD” mode).
The others darwins are still in the same DD (no new ATH, neither reached the -25%DD SL).
Actual VaR 1,18%
Closed P/L + Rebates(+) + Performance fees paid(-) = -345,04 + 20,83 - 0 = -324,21
Potential increment of the closed p/l (invested darwins touch the SL, with security margin for negative divergence and bad execution) = -490 aprox
Total= -814,21 (-8,14%)
This part is a detailed reflexion about what happened, possible causes and possible improvements in the management. If you’re not interested don’t waste your time.
In absolute terms the actual performance is precfectly tolerable, but considering the low risk, low VaR, low ratio invested/liquidity the problem is evident. In my opinion there are different causes:
The darwins selected for the portfolio. It’s rasonable assume that with the actual selection criteria (“NEW” + less than 3M of TR + Exp<2 + unknown trader) the probability of selecting a non invertible darwin is high. Add to this the filter “NEW”, by default, list the darwins by return, so when I select a darwin normally had been performing well (so more odds to start soon a significant DD).
Only KEA is the exception (at least till now), the rest suffered at least -15%DD from ATH after the first buy.
When I started this experiment I was aware that this could happen, so I’m not going to change the selection criteria (the process was/is: select a darwin, if it’s good it will remain, if it’s bad will be discarted and select again. the bucle will continue till all darwins are good, and meanwhile assume low risk. This is the “ideal” way, maybe I will be tired/bored before…).
But what happened suggest that implement some criterias in the management in order to take defensive decisions if a darwin(s) are having a too much negative impact in the portfolio wouldn’t be a bad idea. I’m not going to implement that yet, it will come in futures updates.
The exit rules. This is a problematic criteria, when sell a darwin? In this experiment the trader is unknow (uncertain about his/her talent to solve problems) and it’s not possible to “look inside” (trading journal, VaR/Rs, evolution of the scores, etc…), so I have to make the decision only looking the TR. But the TR are short (the longest has 7M), so it’s not possible to have an idea of what’s the “normal size” (and also I don’t like this approach, I don’t think that a “past normal DD of X%” it’s extrapolable to the future).
Considering this, I started the portfolio with a standard SL at -25% DD (with a fixed target VaR of 10%, not tolerate at least a -20%DD it’s a nonsense in a B&H portfolio). I was aware that in some cases would be a good decision (MZO case, actually -40% from ATH) and bad decision (QRK actually -15% from ATH).
So I was aware that a significant number of darwins could reach the SL (point 1), and maybe some of them could recover. That’s why I decided to not risk all at the firts try, to assume less potential lost and have a second chance with those that survive (missing a significant part of the recovery).
Although the reasoning has some logic, a “sell low and (maybe) buy high” sounds a mistake. So in this expereiment the SL should be used to make a defenity discard decision, so rise the SL wouldn’t have been a valid solution in ordert to make less problematic the past bad performance of the portfolio. But before evolve the exit/re-entry rule, I want to “complete the mistake” (with a little of luck I will re-buy QRK next motnh).
- The timing of entry. Buying at highs doesen’t seem a good idea (specially with my selection criteria, maybe one of them will be the new HFD, but I don’t think so). So if I want to buy in a DD, have a good timing will be ideal. It’s impossible for me to buy at LOW, so I’m happy with a good average quote of entry (if the DD is small assume a small % of the increment of lost availavle, if the DD continues asumme more %).
Till now I had a simple rules: at -5%DD BL order assuming 50% of the lost availible and at -10%DD BL order assuming the rest [I sarted with -7.5 and -12.5 with the first 2 darwins, but I changed because I wanted to make the firts buy sooner, thats why FLQ has more investment (has a better average price assuming the same lost). It’s interesting to check the effects of this small change: FLQ and WDE are in similar situation right now (-15,13%DD & -14,73%DD) and the open p/l are -0,64% and -7,3% (with +2,5% and -0,07% of divergence), so even discounting the efect of the divergence the consequences of having a better timing are significatives].
Although I think the main cause of what happened to the portfolio is related to the point 1, would have been possible obtain a better timing of entry, and that would mitigated significantly the bad performance.
Criteria improvement: work with BL orders in fixed levels are discarted (if a darwin is in DD with an interesting price could be a lost oportunity if the BL leves is not reached; and choose only 2 fixed leves discretionally is too random).
I want to start buying even if the DD is small (even if the increase of the investment is small, I don’t want to feel that I missed an oportunity). I want to be “full charged” (assume all the available lost) only if the DD is really significiant. So, provisionally, the range will be between -2.5% / -15%. Meanwhile the DD is small i will buy direct to market, if the DD starts to be interesting I will work with BS orders (trying to follow it during the fall without buying). The % of the assumed available lost will depend of how deep is the DD (considering the provisional range).
This criteria should be more efficient with volatile darwins (with drodawnless darwins like HFD or ERQ wouldn’t be an interesitng rule of entry), but considering my selection criteria it could work, so this evolution of the rules of entry starts today (although for now only KEA and ITN can be increased).
I will update the topic when somthing “interesting” happens.