CPL(ID:6867/cpl007)Chart-Pattern Languagefor Chart-Pattern Language used to describe trends in share prices from the direction and movement of stock Related languages
References: Search: The ACM Digital Library The Guide Feedback Report a problem Satisfaction survey Charting patterns on price history Full text Pdf (299 KB) Source ACM SIGPLAN Notices archive Volume 36 , Issue 10 (October 2001) table of contents Session: Session 4 table of contents Pages: 134 - 145 Year of Publication: 2001 ISBN:1-58113-415-0 Also published in ... Authors Saswat Anand National Univ. of Singapore Wei-Ngan Chin National Univ. of Singapore Siau-Cheng Khoo National Univ. of Singapore Publisher ACM Press New York, NY, USA Additional Information: abstract references index terms collaborative colleagues Tools and Actions: Discussions Find similar Articles Review this Article Save this Article to a Binder Display in BibTex Format DOI Bookmark: 10.1145/507635.507653 ABSTRACT It is an established notion among financial analysts that price moves in patterns and these patterns can be used to forecast future price. As the definitions of these patterns are often subjective, every analyst has a need to define and search meaningful patterns from historical time series quickly and efficiently. However, such discovery process can be extremely laborious and technically challenging in the absence of a high-level pattern definition language. In this paper, we propose a chart-pattern language (CPL for short) to facilitate pattern discovery process. Our language enables financial analysts to (1) define patterns with subjective criteria, through introduction of fuzzy constraints, and (2) incrementally compose complex patterns from simpler patterns. We demonstrate through an array of examples how real life patterns can be expressed in CPL. In short, CPL provides a high-level platform upon which analysts can define and search patterns easily and without any programming expertise. CPL is a domain-specific language embedded in Haskell. We show how various features of a functional language, such as pattern matching, higher-order functions, lazy evaluation, facilitate pattern definitions and implementation. Furthermore Haskell's type system frees the Programmers from annotating the programs with types. DOI Extract: RELATED WORK RELATED WORK CPL is a programming language for specifying geometrical patterns in time-series databases. In CPL, patterns are speci ed using syntactic constraints (in terms of primitive patterns) and semantic constraints (in terms of a set of constraints). On its own, syntactic pattern speci cation and its recognition techniques have been studied extensively in [9]. Here, patterns are described using some primitive patterns, and the recognition techniques translates the entire pattern into a string of tokens (primitive curves) for matching. The syntactic constraint of CPL is related to the Shape Description Language (SDL) proposed by Agrawal et al. [2]. In SDL, patterns are described in term of primitives like up, down, stable, etc., each of which are one time-unit long. Patterns can then be composed from these primitives in the form of regular expressions. SDL does not handle overlay patterns. Furthermore, it su ers from the following limitations: Firstly, SDL takes a microscopic approach in de ning patterns. As such, it is diÆcult to express in SDL the global features of a pattern using these primitives, which are local in nature. For example, a triangle pattern is formed by a pair of support and resistance line, ignoring the small uctuations within those line. De ning triangle using above microscopic primitives can become a complex task. Secondly, CPL has a strong support for creating indicators and using them in pattern de nitions. An Indicator is actually a new time series (eg. moving average) created out of raw a time series like closing prices. So it is very useful to be able to de ne patterns not only on the raw time series, but a new transformed series created out of it. SDL does not have such a facility. The semantic constraints of CPL are inspired by the landmark model proposed by Perng et al. for similarity-based pattern matching [17]. Brie y, this model is built from study of human visual system, which nds that much of the visual data perceived by human being is redundant; some dominant points on the shape contour are rich in information content, and are suÆcient to characterize a shape [6, 11]. Consequently, we de ne landmarks in a pattern to be those points having important shape attributes; i.e., those that form the joints of the skeleton of a pattern. By providing constraint on the landmarks, patterns can be de ned from a macroscopic level, ignoring unnecessary details. Our choice of pattern-composition operations allows us to support interval-based temporal reasoning of price history. These operations are closely related to those de ned in Allen's algebra for modeling times and events [3]. Allen's algebra (as well as its associated operators) has been used widely in developing query languages for temporal databases, such as TQUEL [20], TSQL [16], etc. However, these languages mainly translate Allen's operations into point-based temporal query; they do not make full use of interval-related temporal properties in their implementation. On the other hand, CPL as presented so far only supports two of the Allen's operators; we are currently extending CPL to fully support Allen's operators. Lastly, we have modeled technical indicators as functions, similar to Behaviors in Fran [8] and Observables in the work on Financial contract [18]. Since technical indicators operate on history data of a security, which can be viewed as a list of data, it is possible to model indicators as operations over in nite streams, as in Lustre [10]. However, the treatment of patterns as illustrated in this paper shows that we usually work on a nite period of time, and many operations |such as accessing a pattern's landmark | do not access history data in chronological order. in SIGPLAN Notices 36(10) October 2001 including Proceedings of the Sixth ACM SIGPLAN International Conference on Functional Programming. Florence 2001 view details in SIGPLAN Notices 36(10) October 2001 including Proceedings of the Sixth ACM SIGPLAN International Conference on Functional Programming. Florence 2001 view details |