Common techniques to contain portfolio volatility and DDs at MM platforms (Millennium/Citadel/P72 or similar)

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Would someone with actual work experience at a MM platform (Millennium/Citadel/P72/BAM or similar) be kind enough to offer a high-level overview of common techniques that are used to contain (a) portfolio volatility and (b) draw downs, to the platform's required parameters for a pod? I am thinking L/S equity but feedback from any strategy (e.g. macro) would be great.

 

Thank you!

Comments (15)

 
Most Helpful
Aug 24, 2020 - 1:35pm

The short answer is that there is no good answer. I can provide some context on how it works in general in the Macro / Macro Adjacent space and I'd imagine it is not too dissimilar for Equity L/S space.

Risk management provides portfolio volatility / VaR risk targets and drawdown limits. They also provide a variety of tools to measure portfolio risk against these measures. This means that PMs can easily calculate their own portfolio volatility (with desired vol / corr. parameters) and VaR (again with desired percentiles / time frame / other parameters). Often, there are also other risk management tools such as stress test paremeters, what-if position analysis that allows for simulation with additional positions, et al...

In terms of how PMs actually put these tools to use to try to manage against targets / limits. I think there are basically 3 main buckets:

1) Position sizes: This is incredibly obvious, but worth saying nonetheless.

2) Position mixes: Uncorrelated / diversifying positions with positive expected alpha are obviously unbelievably Sharpe additive to a portfolio.

3) Hedge overlays: These can make sense in periods of time when there are large numbers of positions that are less liquid and there are highly correlated more liquid proxies that can be used to hedge positions and quickly cut down on risk.

4) Position structuring: Often times, it can be beneficial to risk management to use options structures to minimize downside and still allow for upside potential. This can vary from vanilla concepts like option spreads to more esoteric structuring approaches.

Like most things in life, it is easier said than done.

Edit: added bullet 4.

 
Aug 24, 2020 - 2:03pm

Thank you @yahoo, that is insightful and eloquently put. I understand how hard are these to achieve but enumerating them is a good start (and what I was looking for).

Following up on your points:
• On (1):
    i. In your experience, is volatility targeting one of the common ways to set/calculate position sizes in such portfolios? What other techniques are common?
    ii. Is it safe to assume that the number of positions should be large? If so, again in your experience, what would you call a sufficiently large number of positions to achieve the desired effect?
• On (4):
    i. Are options structures OK/allowed in general, or are there restrictions usually on what instruments can be used by each strategy/team/pod?

I am grateful that you are taking the time to respond to this thread.

 

 
  • Quant in HF - Other
Aug 24, 2020 - 2:33pm

> 2) Position mixes: Uncorrelated / diversifying positions with positive expected alpha are obviously unbelievably Sharpe additive to a portfolio.

 

This implies quite strong prior to a covariance matrix. (Un) Surprisingly, "diversified" portfolio with 100s/1000s stocks can move as volatile as concentrated one in stressful environments. 

 
Aug 24, 2020 - 3:11pm

Thank you for sharing your thoughts. What you say is right (in my experience).

If I am not mistaken in a macro strategy one has more choice of (theoretically and empirically) uncorrelated assets to diversify with. In equities one would be theoretically protected from the volatility of "stressful environments" because of market (and sector) neutral L/S positioning.

 
Aug 25, 2020 - 7:14am

Hi @MMPM, thank you for taking the time to share your thoughts.

 

That's right about pairs. I was asking more along the lines of how positions are sized, typical number of names in the investment universe, number of concurrent positions, partial deployment of capital, etc. in order to target volatility and drawdown parameters given by risk management. I think I could have phrased my question better!

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