On Wednesday, I participated in the #雪ball private Zhuozhi fund tea party# , thank you very much for the organization of Xueqiu and the hospitality of Zhuozhi, hand in homework as usual, and write study notes.
Before the main text, let’s make two points: First of all, many bigwigs participated in this event @二哥 Eat Goose Eggs @大白华@爱丽亚雅娜, what I recorded is more of my personal interest, It is definitely not comprehensive, and you can also pay attention to the posts of the big guys; secondly, this is essentially a roadshow of Insight, and there are certain tendencies. For example, some indicators of excellent performance of Insight are highlighted. For Xiaolei, I have no way to judge the weight of these indicators when we choose to quantify, or whether there are other indicators to consider. This may require more comparisons with other roadshows, so I hope golfers can read this dialectically. Note, any opinions are welcome. In addition, I have written a quantitative study note before, and everyone is welcome to correct me.
1. Stable excess returns
This is probably the one indicator that Zhuozhi emphasizes the most. The net value can fluctuate with the index, but the excess should be a line with an upward slope, and the straighter the better, especially when the market style is switched, the excess may remain stable. You can refer to the blue line in the figure below. Obviously the blue line on the left is good, and the blue line on the right is the excess shock.
Of course, there is also a bad performance that although the fluctuation is small, it is almost sideways, as shown in the following figure:
2. Unified management vs PM system
This is a point of personal interest to me, and I didn’t understand the specific difference before this.
Let’s talk about Zhuozhi first. They have 6 strategy groups, and each strategy may have a different focus, such as low, medium and high frequency, deep learning/linear learning… It is not ruled out that there will be repeated factors, algorithms, etc. between each group , but unified coordination and management can try to ensure that there will not be too much waste of resources, repeated calculations, etc. between each group. The company will have a set of algorithms that give different weights to different strategies every day.
Besides the PM system, this should also be the model adopted by many quantitative companies, that is to say, there will be different fund managers under a quantitative company, each of whom manages a part of the funds independently, and there may be some mechanism within the company to allocate weights to investors. Says a bit like FOF. I personally understand that this approach may generate strong incentives, but there may also be a convergence of strategies among the various PMs. In addition, from the perspective of the company, the PM system may have relatively weak control, and the resignation of the top PM may cause relatively large losses.
3. Who is suitable for quantitative entrepreneurship?
This question was asked by Mr. Zhang. The reason for asking is that I found that there are quite a lot of entrepreneurship in quantitative aspects. Many investors are concerned about scale and like to find little dark horses, but the uncertainty of small dark horses is very high, so I would like to ask Zhang In general, what qualities should a founder possess? The answer is two points:
The first is to have core skills to earn the first pot of gold; the second is to have the ability to organize and manage when the scale is large (1 billion to 2 billion).
I don’t know if everyone is happy with this answer, if the information I got myself is too small or don’t touch it.
4. Hashrate vs Speed
According to Zhuozhi, some quantifications emphasize computing power, such as how much supercomputing, but ignore speed. That is to say, if the speed is slow, no matter how good your calculation results are, you may miss the best execution window. Speed is more of a competition between the underlying framework and hardware. Acuity may have emphasized speed in the framework design. A big guy asked why other companies couldn’t update it. I understand that this may involve the problem of mobilizing the whole body.
5. Some other indicators
Zhuoshi also introduced some other indicators, which I think can be used for reference when selecting quantification. In order to be lazy, I directly paste the content in their PPT:
6. Gossip: What books do fund managers read?
As mentioned at the beginning, the road show does not rule out bias, I am the porter of the content, and I do not make investment suggestions.
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