Shall We Play a Market Timing Game? (2018)

Post by legolas2412 » Mon, Mar 23, 2020, 6:32 AM UTC

qihqi wrote: post #43

c06n wrote: post #8

Generally, in markets that were part bearish (like the 80s), I made very good returns, between 10 % and 30 % above the index. As a very simple rule, after 2 days of a falling index, sell for exactly 1 day. This works mainly because there are enough consecutive 3 days of a falling index. However, if the market trend is overwhelmingly bullish, that does not work anymore, because there are not enough triplets of falling…

You can beat falling markets by not buying anything. I don't get why is beating the market a goal, isn't making money the goal? I am much happier making 20% while market is up 30%, than losing 5% when the market loses 20%.

That is literally beating the market. It includes downturns.

Post by rmrfstar » Mon, Mar 23, 2020, 8:55 PM UTC

Majromax wrote: post #20

> Update: Added a Monte Carlo mode which lets you play with data that is randomly generated from the daily returns of the S&P500. The probability of a daily return being picked is the same probability/frequency that it occurred in the last 68 years. This mode is rigged. Any proposal for market timing requires correlated returns. "Technical" traders infer short-term trends form patterns like the shave-and-a-haircut an…

Actually, this is not correct.

Any proposal for market timing requires an observable x[t] that is correlated to R[t+d] for d>0. The returns may themselves lack any auto-correlation.

If market returns are auto-correlated in some way, then x[t] could be a function of R[s] for sIn the context of this game, x[t] would be some information about the internal state of the RNG at time t.

Re: Shall We Play a Market Timing Game? (2018)

Re: Shall We Play a Market Timing Game? (2018)