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An order matching system or simply matching system is an electronic system that matches buy and sell orders for a stock market, commodity market or other financial exchanges. The order matching system is the core of all electronic exchanges and are used to execute orders from participants in the exchange.
A central limit order book (CLOB) [1] is a trading method used by most exchanges globally using the order book and a matching engine to execute limit orders.It is a transparent system that matches customer orders (e.g. bids and offers) on a 'price time priority' basis.
An order book is the list of orders (manual or electronic) that a trading venue (in particular stock exchanges) uses to record the interest of buyers and sellers in a particular financial instrument. A matching engine uses the book to determine which orders can be fully or partially executed.
Kleinberg, J., and Tardos, E. (2005) Algorithm Design, Chapter 1, pp 1–12. See companion website for the Text Archived 2011-05-14 at the Wayback Machine. Knuth, D. E. (1996). Stable Marriage and Its Relation to Other Combinatorial Problems: An Introduction to the Mathematical Analysis of Algorithms. CRM Proceedings and Lecture Notes.
Trie data structures are commonly used in predictive text or autocomplete dictionaries, and approximate matching algorithms. [11] Tries enable faster searches, occupy less space, especially when the set contains large number of short strings, thus used in spell checking, hyphenation applications and longest prefix match algorithms.
This is opposed to pattern matching algorithms, which look for exact matches in the input with pre-existing patterns. A common example of a pattern-matching algorithm is regular expression matching, which looks for patterns of a given sort in textual data and is included in the search capabilities of many text editors and word processors.
Gestalt pattern matching, [1] also Ratcliff/Obershelp pattern recognition, [2] is a string-matching algorithm for determining the similarity of two strings. It was developed in 1983 by John W. Ratcliff and John A. Obershelp and published in the Dr. Dobb's Journal in July 1988.
The algorithm will determine, for any instance of the problem, whether a stable matching exists, and if so, will find such a matching. Irving's algorithm has O(n 2) complexity, provided suitable data structures are used to implement the necessary manipulation of the preference lists and identification of rotations.