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The analogy incorrectly compares a binary outcome (cancer / no cancer) with a continuous variable (stock price returns, which may have skewed magnitudes dependi

The analogy incorrectly compares a binary outcome (cancer / no cancer) with a continuous variable (stock price returns, which may have skewed magnitudes depending on upside or downside). So while it is nominally correct about the formula for "stocks up" or "stocks down", it does not help for an actual trading situation where "stocks down" could have a negative return mean much larger than the corresponding positive mean return of "stocks up", for example.

gnaritas 11y ago
A trade is a binary outcome, trade wins or trade loses.
- vegabook 11y ago
  That is useless in the real world. Trade loses is inevitably a larger absolute value P&L than trade wins. Trade wins frequency > trade loses frequency. Trade loses size > trade wins size. You need both and the analysis only does the former.
  - gnaritas 11y ago
    Bayes is about working with incomplete information, you don't need all the data, you just need a slight edge. Just because it's not a complete analysis of all necessary input doesn't make it useless. Beyond that, you can directly control your win and loss size with targets and stops, so they're not necessarily unknown, and you certainly know your win/loss ratio which of course you'd want to plug in, at least for money management reasons, especially if you're using any variant of the Kelly formula for position size.
    - vegabook 11y ago
      Trade win:lose ratio > 1 is an elementary mistake in algorithmic backtesting. Not knocking Bayes. Only saying the analysis is incomplete. Cancer/noCancer is not a good analogy.
      - gnaritas 11y ago
        > Trade win:loss ratio > 1 is an elementary mistake in algorithmic backtesting Who said anything about that? Perhaps I was unclear, it's not about the ratio, it's about the streaks, you need to understand patterns of your wins and losses as it's critical to applying money management. If you only win 30% of the time, you could still make a killing if you can withstand the losing streaks without much drawdown or if the winners are big enough.
        vegabook 11y ago
        Obviously I agree. My simple point is that the OP is making claims about a binary outcome, which could lead one to infer that stock trading binary up/down outcomes are all that matter.
        gnaritas 11y ago
        OK, point made.
tjradcliffe 11y ago
Reality is continuous. Human categories--like cancer--only have sharp edges because we draw them with an act of selective attention. The edge of our attention is discontinuous. Nothing else (that doesn't involved quantum mechanics or integer counting of attentionally-isolated objects) is. "Cancer" is not a simple thing. Two people with "breast cancer" may have very similar or almost completely different diseases. As others here have pointed out, the magnitude and frequency of wins and losses matter even though trades are binary win/lose (which they can be because we've created an entire category of imaginary objects called dollars that can be counted). Bayes rule is as applicable to any area of significant uncertainty, including win/loss magnitude. It is universal.
clairity 11y ago
then somebody should tell those guys who create the binomial options pricing model (and by extension, black-scholes) how flawed their approach is! =P https://en.wikipedia.org/wiki/Binomial_options_pricing_model https://en.wikipedia.org/wiki/Binomial_options_pricing_model seriously though, the example is just a model, and a simple one at that. it's certainly useful to call out where and how the model breaks down, but it's also useful to understand the conditions under which a model performs well. like most models, this one is not designed for black swan events (to which you allude). also, the author acknowledges your point at the end: "...it is only part of a financial modeling solution" and "one needs ... to learn more through careful experimentation and study". you'd need to include some information about the magnitude of losses and gains, to be sure. i do like that he used a relatable example like sentiment analysis though.
- zhte415 11y ago
  Black-Scholes is pretty flawed in assuming normal distributions, which financial markets don't show. Following power laws or Omega metrics can be informative. The more, the merrier.

gnaritas 11y ago

A trade is a binary outcome, trade wins or trade loses.

vegabook 11y ago
That is useless in the real world. Trade loses is inevitably a larger absolute value P&L than trade wins. Trade wins frequency > trade loses frequency. Trade loses size > trade wins size. You need both and the analysis only does the former.
- gnaritas 11y ago
  Bayes is about working with incomplete information, you don't need all the data, you just need a slight edge. Just because it's not a complete analysis of all necessary input doesn't make it useless. Beyond that, you can directly control your win and loss size with targets and stops, so they're not necessarily unknown, and you certainly know your win/loss ratio which of course you'd want to plug in, at least for money management reasons, especially if you're using any variant of the Kelly formula for position size.
  - vegabook 11y ago
    Trade win:lose ratio > 1 is an elementary mistake in algorithmic backtesting. Not knocking Bayes. Only saying the analysis is incomplete. Cancer/noCancer is not a good analogy.
    - gnaritas 11y ago
      > Trade win:loss ratio > 1 is an elementary mistake in algorithmic backtesting Who said anything about that? Perhaps I was unclear, it's not about the ratio, it's about the streaks, you need to understand patterns of your wins and losses as it's critical to applying money management. If you only win 30% of the time, you could still make a killing if you can withstand the losing streaks without much drawdown or if the winners are big enough.
      - vegabook 11y ago
        Obviously I agree. My simple point is that the OP is making claims about a binary outcome, which could lead one to infer that stock trading binary up/down outcomes are all that matter.
        gnaritas 11y ago
        OK, point made.

tjradcliffe 11y ago

Reality is continuous. Human categories--like cancer--only have sharp edges because we draw them with an act of selective attention. The edge of our attention is discontinuous. Nothing else (that doesn't involved quantum mechanics or integer counting of attentionally-isolated objects) is. "Cancer" is not a simple thing. Two people with "breast cancer" may have very similar or almost completely different diseases. As others here have pointed out, the magnitude and frequency of wins and losses matter even though trades are binary win/lose (which they can be because we've created an entire category of imaginary objects called dollars that can be counted). Bayes rule is as applicable to any area of significant uncertainty, including win/loss magnitude. It is universal.

clairity 11y ago

then somebody should tell those guys who create the binomial options pricing model (and by extension, black-scholes) how flawed their approach is! =P https://en.wikipedia.org/wiki/Binomial_options_pricing_model https://en.wikipedia.org/wiki/Binomial_options_pricing_model seriously though, the example is just a model, and a simple one at that. it's certainly useful to call out where and how the model breaks down, but it's also useful to understand the conditions under which a model performs well. like most models, this one is not designed for black swan events (to which you allude). also, the author acknowledges your point at the end: "...it is only part of a financial modeling solution" and "one needs ... to learn more through careful experimentation and study". you'd need to include some information about the magnitude of losses and gains, to be sure. i do like that he used a relatable example like sentiment analysis though.

zhte415 11y ago
Black-Scholes is pretty flawed in assuming normal distributions, which financial markets don't show. Following power laws or Omega metrics can be informative. The more, the merrier.