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Are random trading strategies more successful than technical ones?

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Re: Are random trading strategies more successful than technical ones?

#41

Post by anthony_r »

Win % is a really useless metric in this business, try computing win % for something like long vol strategies (for example things like what Taleb did back in the day), it might come out to 5% or lower and still make money. And because every trade has a counterparty there's plenty of strategies that win 95% or more of the time but eventually lead to ruin. Returns pretty much never have a symmetric distribution.

Computing win % is akin to measuring software quality in terms of number of lines of code - only someone who has no first-hand experience would ever attempt to do that.

Re: Are random trading strategies more successful than technical ones?

#42

Post by veeenu »

rubyn00bie wrote: post #17

Prices are pretty well modeled using Brownian motion. Most economists should know this while almost no one in the normal population will be aware of it. Sometimes people are just lucky, but overall the more trades you make the more you'll converge on the average return rate. I would also like to note, that predicting price is different from predicting an overall increase in the value of the underlying security. https…

The assumptions underlying Brownian motion of prices have been disputed for quite a while now: the normality hypothesis can be rejected on most if not all historical financial returns series, as it turns out that most returns are actually fat tailed processes with very significant (and variable over time) correlations between distinct assets, which makes research around portfolio theory even harder to conduct.

Re: Are random trading strategies more successful than technical ones?

#43

Post by OnlineGladiator »

veeenu wrote: post #28
cschmidt wrote: post #6

This reminds me a bit of a classic paper called "1/N". It compared a portfolio of putting equal money into each security, vs a bunch of fancier approaches. The 1/N almost always won. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=911512

This is widely known among practitioners, but there is a caveat -- a 1/N portfolio bears a much higher risk than, say, a cap-weighted portfolio or a risk-parity asset allocation. A 1/N portfolio receives an equal contribution in terms of volatility from each asset, meaning that very risky assets significantly increase the portfolio's volatility, while not necessarily contributing proportionally better returns, due to…

> This way, 1/N ends up performing very poorly on a risk-adjusted basis while undoubtedly at the same time outperforming any other kind of allocation on the basis of return alone.

I fear I'm misunderstanding you. Are you saying despite having higher returns, the higher risk makes this strategy worse? That really feels like handwaving to me, since the only thing I care about is ROI. I understand nonlinearity and how it could tank your investment, but if it doesn't and you make more money then you're criticizing something that never happened. The higher risk is already baked into the ROI, because it includes the times that failed. The point is, in aggregate, you make more money - and most of the time that is the only thing I care about when investing.

Or am I misunderstanding you?

Re: Are random trading strategies more successful than technical ones?

#44

Post by gitfan86 »

rubyn00bie wrote: post #17

Prices are pretty well modeled using Brownian motion. Most economists should know this while almost no one in the normal population will be aware of it. Sometimes people are just lucky, but overall the more trades you make the more you'll converge on the average return rate. I would also like to note, that predicting price is different from predicting an overall increase in the value of the underlying security. https…

As someone who has beat the market over a 17 year period, I attribute it to having made very few trades AND being lucky.

There are a lot of ways that a company can go under. All it takes is one mistake or one black swan event and what would have been an amazing investment 99.9999% of the time goes to zero.

Re: Are random trading strategies more successful than technical ones?

#45

Post by initplus »

awb wrote: post #37
stouset wrote: post #22

Earlier quoted context omitted.

Further, every time you trade, the overwhelming likelihood is that the counterparty to that trade is a financial professional with dramatically more access to company-specific research and information than you. This imbalance is minimized when you trade infrequently and maximized when you trade frequently.

I don’t think that’s quite right. Otherwise, you could just follow the opposite of your unprofessional trade strategy as a cheap proxy for a professional trading strategy. I think the market is dominated by front-running trades and randomness.

This reasoning doesn't work because the market isn't a sequence of discrete binary choices. If the "opposite" of a bad strategy was a good one anyone could have great returns by designing some obviously terrible money losing strategy then doing the "opposite".

Re: Are random trading strategies more successful than technical ones?

#46

Post by samvega_ »

veeenu wrote: post #42
rubyn00bie wrote: post #17

Prices are pretty well modeled using Brownian motion. Most economists should know this while almost no one in the normal population will be aware of it. Sometimes people are just lucky, but overall the more trades you make the more you'll converge on the average return rate. I would also like to note, that predicting price is different from predicting an overall increase in the value of the underlying security. https…

The assumptions underlying Brownian motion of prices have been disputed for quite a while now: the normality hypothesis can be rejected on most if not all historical financial returns series, as it turns out that most returns are actually fat tailed processes with very significant (and variable over time) correlations between distinct assets, which makes research around portfolio theory even harder to conduct.

Which assets are that?

Re: Are random trading strategies more successful than technical ones?

#47

Post by civilized »

awb wrote: post #37
stouset wrote: post #22

Earlier quoted context omitted.

Further, every time you trade, the overwhelming likelihood is that the counterparty to that trade is a financial professional with dramatically more access to company-specific research and information than you. This imbalance is minimized when you trade infrequently and maximized when you trade frequently.

I don’t think that’s quite right. Otherwise, you could just follow the opposite of your unprofessional trade strategy as a cheap proxy for a professional trading strategy. I think the market is dominated by front-running trades and randomness.

Front-runners still have to run in front of something, though. And it's probably not going to be the purchases of some little retail investor.

Re: Are random trading strategies more successful than technical ones?

#50

Post by Behemoth66 »

OnlineGladiator wrote: post #43
veeenu wrote: post #28

Earlier quoted context omitted.

This is widely known among practitioners, but there is a caveat -- a 1/N portfolio bears a much higher risk than, say, a cap-weighted portfolio or a risk-parity asset allocation. A 1/N portfolio receives an equal contribution in terms of volatility from each asset, meaning that very risky assets significantly increase the portfolio's volatility, while not necessarily contributing proportionally better returns, due to…

> This way, 1/N ends up performing very poorly on a risk-adjusted basis while undoubtedly at the same time outperforming any other kind of allocation on the basis of return alone. I fear I'm misunderstanding you. Are you saying despite having higher returns, the higher risk makes this strategy worse? That really feels like handwaving to me, since the only thing I care about is ROI. I understand nonlinearity and how i…

I believe OP is saying that due to the increase in risk and volatility there is a greater chance of the trader to emotionally manage their money as it peaks and falls.

And obviously there’s mathematical measurements where one tries to get the highest return per unit of risk. It’s possible that these returns might be higher but fall under the curve.

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