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Hi Mark,
You are magnanimous and indomitable. You are like my big brother, so
is Steve. You both have superegos and it is unfortunate that you
both could not reconcile your differences yet. I am the loser and I
suspect so are others. You must measure what you might gain by what
you might lose...
rgds, Pal
--- In amibroker@xxxxxxxxxxxxxxx, "quanttrader714"
<quanttrader714@xxxx> wrote:
> It's late and I've had too much scotch, so one very quick example
> which I'll explain the basics of but would like to have someone else
> please take a stab at interpreting.
>
> To recap the Robustness Criteria, Condensed Version 1-5:
>
> 1. Test on small, mid & large cap stocks in bull, bear & sideways
> markets.
> 2. Evaluate performance on top 20% most actively traded small, mid &
> large cap stocks.
> 3. Graph and evaluate system performance consistency (%profit/trade
> and % profit/bar) on select stocks.
> 4. Perform simulation to estimate probability of profit in 10 trades
> (for select stocks).
> 5. Perform simulation to estimate future drawdown (for select
stocks).
>
> For this example I picked a stock, any stock. I think everyone gets
> what I mean by criteria 1 and 2 (whether they agree or not), correct
> me if I'm wrong. I've posted the output of criteria 3-5 in the
> example folder in the photos section. Criterion 3 output is photos
1
> and 2, criterion 4 output is photos 3 and 4, and criterion 5 output
is
> photos 5 and 6. I think the criterion 3 graphs are self
explanatory.
> On criterion 4, forget how it's calculated for now. It estimates
the
> probability of profit (and how much) at the end of 10 trades. Unit
of
> measure is % of starting equity. Looking at the histogram, the
> highest bin (the mode of the distribution) is 19.16 -- 29.63 which
> means approx 15.5% of the time (y axis) the profit at the end of 10
> trades fell in this bin, between 19.16% and 29.63% of initial
equity.
> The cumulative distribution graph is the histogram in cumulative
> form and shows the likelihood that a result falls below the value on
> the x axis. For example, 20% of the simulations (of the sum of 10
> trades) lost money so you can *estimate* there's an 80% chance
you'll
> be profitable after 10 trades with this. Same unit of measure for
max
> dd and those graphs are read the same way. P.S. Each simulation was
> 1000 runs, so the graphs of criterion 3 show one actual pass through
> the data by AB, while the others depict the collective results of
1000
> simulated runs (and include my adjustment factor).
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