[R-SIG-Finance] Sullivan, Timmerman and White 1999: TA rules, and R
radek.maciaszek at gmail.com
Tue Nov 20 15:48:23 CET 2012
Apologies for necromancing such an old topic but I was wondering if this
work has been added in the end to the TTR (or perhaps some other package)? I
am facing a similar issue and would like to calculate when the volume is
(pivoting) breaking the channel.
> OK, so Josh actually reviewed the paper rather than relying on hazy
> recollection (my bad).
> Based on this, you'd apply the relevant indicators for MA periods,
> DonchianChannel, or OBV, es needed. Channel Break-outs are also often
> called pivots. We have some code for this, and will endeavor to
> document it and get it into TTR.
> After any indicators are applied, as required, you'll then generate
> signals as I described in my prior email.
> - Brian
> On 03/29/2011 01:24 AM, Joshua Ulrich wrote:
>> 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.
>> Joshua Ulrich | FOSS Trading: www.fosstrading.com
>> On Mon, Mar 28, 2011 at 4:33 PM, Worik<
> > wrote:
>>> [Apologies if I have sent this multiple times. I have been struggling
>>> SMTP sewrvers and I have not seen my message appear on the list]
>>> 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
>>> 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
>>> would save me a pile of work.
>>> It would be nice to just grab some rules from the TTR package, but
>>> 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
>>> direction than slogging through the English text and trying to match
>>> with the TTR docs I would be grateful
>>> PS Here is an example of their text. Not that it is bad, just quite a
>>> of work....
>>> A. Filter Rules
>>> Filter rules are used in Alexander (1961) to assess the efficiency of
>>> 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
>>> 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
>>> 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
>>> position. Likewise, a subsequent low is the lowest closing price
>>> while holding a particular short position. Alternatively, a low (high)
>>> defined as the most recent closing price that is less (greater) than the
>>> previous closing prices. Next, we will expand the universe of filter
>>> allowing a neutral position to be imposed. This is accomplished by
>>> 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
>>> the previous low. Following BLL, we also consider holding a given long
>>> short position for a prespecified number of days, c, effectively
>>> other signals generated during that time.
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