Reducing Max DD

Research
1

Hi guys,

I hope you’re all well!

Coming on here to get some opinions, pretty new to ranking systems and currently very fixated on mastering this platform.

What are some effective ways you use to reduce downdraw, currently getting decent returns with a 1.3 sharpe over 10 years but the Max DD is 42%, also, does the anyone know if the platform can calculate parametric & HS Var and ES?

Any advice would be much appreciated, unfortunately I can’t make the strategy live to share the link due to my membership.

Thank you :slight_smile:

2

The most practical way to reduce drawdown is to select low-volatility stocks. Here are four good tools (all lower better):

  • VolM%ShsOut
  • MedianVol(252) / LoopMedian("SharesCur(Ctr)",252)
  • PctDev(63,1)
  • Beta3Y

The first two are measures of share turnover, the third is price volatility, and the fourth is beta.

Another way to approach this is to favor stocks with stable fundamentals. For example, LoopRelStdDev("Recvbl(Ctr,Qtr)",16) will favor stocks whose receivables don't jump up and down every quarter. You can use all sorts of measures instead of Recvbl here. The short list: AstTot, LiabTot, Sales, AstTurn, RAndD, DivPaid. See Why Low-Variability Investing Works - Portfolio123 Blog

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3

I have found that introducing a mild technical can reduce headwinds and often drawdowns. Things like:

RSI(20, 0) >= 30

Rating(“Core: Momentum”) >= 20.0

Try different parameter values. Implement as a Buy Rule or in a Universe Definition.

Cheers,

Rich

EDIT: I have also found including “Between(WeeksIntoQ, 0, 14) = TRUE” in the Universe Definition to have an impact (sometimes good, sometimes bad, sometimes indifferent). It is an indicator that the company is serious about financials.

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4

I guess you are talking about a single simulation and if so then you now have a few more ideas. If, not then combine your strategy with a levered short index fund. Better yet develop a number of systems with low correlation and mild leverage then add a short levered index fund (TNA say).

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in simulation, buy rule:
SubSecWeight < 30

in simulation, sell rule:
Eval(Weight > 20, 0.25, 0)

my current best live strategy uses this type of buy rule, which may also help to reduce DD:
RankPos <=45 & RatingPos("R2") <=45 & RatingPos("R3") <=45 & RatingPos("R4") <=45
where R1...RN are correlated ranking system

and this one for sure:
!Ticker("SPCX") :slight_smile:

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6

It cannot.

Also, there are limited tools that rely on modern portfolio theory, like a covariance matrix, here. As you can tell from respondents, it’s a bit anathema to the site’s culture.

So that may rule out metrics / tools like the ones you mentioned.

Good luck!

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8

A part of all mentioned you could use strategies of market timming, mostly to try to reduce the bigs DD..but there is no free lunch of course

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Thank you - much appriciated Yuval :slight_smile:

10

Thank you, I’ll check these out and see if they improve the sharpe :slight_smile:

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Yeah, it was a single strategy I’ve been focusing on, I have thought about combining systems but I think what I’ve built at the minute seems to be pretty robust

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Thank you, I’ll give these a go :slight_smile:

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Yeah, slightly annoying - I think its a more explanatory metric that max DD.

I’d of also liked to use a monte carlo sim too, that would be a great addition to the platform.

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I have tried using different buy & sell signals to time different regimes; however, I think you’re right - there’s no holy grail and ultimately there is no free lunch. What I’ve built has done well, I’ve managed to reduce DD to 35%

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