[R-SIG-Finance] Sullivan, Timmerman and White 1999: TA rules, and R
Joshua Ulrich
josh.m.ulrich at gmail.com
Tue Mar 29 08:24:11 CEST 2011
Hi Worik,
There are 5 types of rules: filter rules, moving averages, support and
resistance, channel break-outs, and on-balance volume averages. TTR
contains what you need for moving averages, channel break-outs
(DonchianChannel) and on-balance volume (OBV).
I coded filter rules in another language a few years ago, so I could
help you write them in R. I don't understand how the support and
resistance rules differ from the channel break-outs, but that could be
due to the time of day and my lack of sleep. Regardless, I doubt they
would be difficult to code.
Best,
--
Joshua Ulrich | FOSS Trading: www.fosstrading.com
On Mon, Mar 28, 2011 at 4:33 PM, Worik <worik.stanton at gmail.com> wrote:
> [Apologies if I have sent this multiple times. I have been struggling with
> SMTP sewrvers and I have not seen my message appear on the list]
>
> Friends
>
> I am trying to save myself some tedious work.
>
> I am processing a paper from "The Journal Of Finance * Vol. LIV, No. 5
> October 1999" by Sullivan, Timmerman and White. "Data-Snooping,
> Technical Trading Rule Performance, and the Bootstrap"
>
> I am aiming to reproduce their results using the same TA rules as they
> used.
>
> They describe the rules they use in English and I am in the process of
> trying to programme them into R. But if some one has already done this it
> would save me a pile of work.
>
> It would be nice to just grab some rules from the TTR package, but because
> of the way STW describe the rules it is quite a lot of work to calculate
> what parameters to use.
>
> So I am clutching at a straw here: If anybody could point me in a better
> direction than slogging through the English text and trying to match that
> with the TTR docs I would be grateful
>
> cheers
> Worik
>
> PS Here is an example of their text. Not that it is bad, just quite a bit
> of work....
>
> A. Filter Rules
> Filter rules are used in Alexander (1961) to assess the efficiency of stock
> price movements. Fama and Blume (1966) explain the standard filter rule:
> An x per cent filter is defined as follows: If the daily closing price of a
> particular security moves up at least x per cent, buy and hold the se-
> curity until its price moves down at least x per cent from a subsequent
> high, at which time simultaneously sell and go short. The short position
> is maintained until the daily closing price rises at least x per cent above
> a subsequent low at which time one covers and buys. Moves less than x
> per cent in either direction are ignored. (p. 227)
> The first item of consideration is how to define subsequent lows and highs.
> We will do this in two ways. As the above excerpt suggests, a subsequent
> high is the highest closing price achieved while holding a particular long
> position. Likewise, a subsequent low is the lowest closing price achieved
> while holding a particular short position. Alternatively, a low (high) can
> be
> defined as the most recent closing price that is less (greater) than the e
> previous closing prices. Next, we will expand the universe of filter rules
> by
> allowing a neutral position to be imposed. This is accomplished by liquidat-
> ing a long position when the price decreases y percent from the previous
> high, and covering a short position when the price increases y percent from
> the previous low. Following BLL, we also consider holding a given long or
> short position for a prespecified number of days, c, effectively ignoring
> all
> other signals generated during that time.
>
> --
> If we amplify everything, we hear nothing.
> --
>
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