[R-SIG-Finance] statistical features of equity time series

Alex Grund st.helldiver at googlemail.com
Sun Oct 28 15:24:49 CET 2012

Hi Matthew,

2012/10/28 Matthew Gilbert <matthew.douglas.gilbert at gmail.com>:
> The books "Analysis of Financial Time Series" by Ruey Tsay and "Statistics
> of Financial Markets" by Franke, Hardle and Hafner are both good references.

Thank your for this hints!

> But ultimately if the end goal is to test a trading strategy why simulate
> your own data? It seems like a lot of work and the end result would be to
> generate a profitable strategy on fictitious data?

No, the goal should NOT be to have a trading strategy. The goal is to
find some rational bahaviors.
For example: Given special characteristics of prcing data, is it
rational to invest 300000 $ directly or to invest 100000 $ at each
month's first trading day for three month. What will the result likely
be in 12 months?
Is it rational to take some profits?

That is not the same as a strategy "buy if MA crosses price" or
something like that. It is rather an market condition independent
bahavior. If one cannot "predict" the market, is it possible to reduce
risk or gain extra returns if one does other things like buy and hold,
but not with any information influence, only by bhavioral patterns.

That's why I called it "bahavior" rather than "strategy".

Why not on live data?
I could run simulations on 500 stocks (e.g. from SP500). But to
eliminate survivorship bias etc. and to run much more tests (1000s to
10000s) it sounds more suitable to run against artificial market data.
Maybe special characteristics are revealed which gives an insight to
"black swans" which are not obvious from real data.


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