[R-SIG-Finance] Processing time of backtests on a single computer

[Joshua Ulrich]

On Thu, Apr 7, 2016 at 8:10 AM, Jersey Fanatic <jerseyfanatic1 at gmail.com> wrote:
> 10 years of daily data makes about 2500 data points. So extrapolating from
> that to 58000 data points (assuming the relation is linear), it should take

Number of data points is not necessarily a good estimator for run time
even if the strategies are the same.  What matters more is the number
of timestamps/observations that must be evaluated.  That includes
signals, moving orders, processing fills, etc.

> about 12.2 secs for a single run with my dataset. For 144 runs (total
> number of parameter combinations), it should take about 30 mins. However, I

Again, the relationship is not linear.  Different parameter
combinations will produce differing amounts of signals, order
movement, fills, etc.

For example, I ran parameter optimization on ~3 years of 5-second
data.  Some parameter combinations took 1-2 minutes, some took >20
minutes.

> ran apply.paramset() this morning (without trailing stops), it took 4.5
> hours. And the code is the one that I sent earlier with Trailing stop rules
> enabled=FALSE'd.
>
> Did you run the macd demo code with single core? If you did some parallel
> processing, did you use doSNOW package or something else? Maybe that is the
> reason, I am not sure.
>
> Would deleting trailing stop rules speed things up, instead of defining
> them but setting enabled=FALSE?
>
> 2016-04-07 0:34 GMT+03:00 Brian G. Peterson <brian at braverock.com>:
>
>> On Wed, 2016-04-06 at 23:58 +0300, Jersey Fanatic wrote:
>> > I will try running the same code without trailing stops and see what
>> > effect
>> > it has on the processing time. I will report back as soon as it is
>> > finished.
>>
>> Running the macd demo code over 10 years of daily data on my machine (no
>> trailing stops) takes 0.5262365 secs for a single run.
>>
>>
>>
>
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Joshua Ulrich  |  about.me/joshuaulrich
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