I've been calling this ratio "acceleration" in my head, so I'll do the same in this post. The question is, is this relationship used anywhere and if so, how? My thought process is as follows.

Risk is typically quantified through standard deviation. But how good of a proxy for risk is SD really? Upside deviation is not risk, it's the definition of reward!

So "acceleration" might quantify upside variance per unit of downside variance. I can imagine a momentum strategy using an "acceleration-weighted" allocation scheme. Like riding a rising wave.

This could also be some obscure Greek that I'm not aware of, or have a completely different use. Just wondering. Thanks.

  • $\begingroup$ The gains vs losses idea reminded me of the Omega Ratio en.wikipedia.org/wiki/Omega_ratio . But it is not based on upside variance vs downside variance, so your idea is different. $\endgroup$
    – noob2
    May 13 '20 at 14:54
  • $\begingroup$ This has sent me down a rabbit hole of risk/reward metrics I did not know existed. Really appreciate the link. My issue with the Omega Ratio from the very brief reading I just did is that it's based on Black-Scholles, which also uses standard deviation as the risk measure. But there is obviously a lot more to read about it. $\endgroup$
    – user46252
    May 13 '20 at 15:30
  • $\begingroup$ This may help: rdocumentation.org/packages/PerformanceAnalytics/versions/2.0.4/… $\endgroup$
    – Polar Bear
    Dec 26 '20 at 6:51
  • $\begingroup$ @PolarBear This is literally the thing I described. Thank you! It's volatility skewness huh...I will have to read more into this! $\endgroup$
    – user46252
    Dec 30 '20 at 16:01

We have used it as a criterion for portfolio selection, for example in An Empirical Analysis of Alternative Portfolio Selection Criteria and Risk-Reward Optimisation for Long-Run Investors: An Empirical Analysis. What we found there, however, is that reducing the downside was more important than increasing the upside.

  • $\begingroup$ These papers are oddly and incredibly specific to what I had in mind. Thank you! I've been developing this idea with cryptocurrencies in mind. Technical analysis is rampant in the crypto space and there is so much volatility. I wonder how these methodologies would behave with a portfolio of altcoins. $\endgroup$
    – user46252
    May 13 '20 at 14:48
  • $\begingroup$ A concern for cryptoassets would be liquidity and the costs of trading. The models described in the papers worked well when there was a reasonably-large cross-section of equities to choose from. The asymmetric risk functions picked up not only a "low risk" effect, but also momentum (see papers.ssrn.com/sol3/papers.cfm?abstract_id=2975529). The question is whether such effects are at work in cryptoassets as well. $\endgroup$ May 15 '20 at 7:04

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