The present work discuss the continuous double auction mechanisms and the order book models. After a brief introduction to selected models, a general model of the the continuous double auction from the thesis title is described. Further, a structure of british market data is given as well as an approach to them. Based on these data the validity of Smith Farmer's model and Cont Stoikov's model is tested in the context of general model by linear regression. Finally, based on the previous results, the own order book model is suggested and its validity tested.

Financial markets use complex computer trading systems whose failures can cause serious economic damage, making reliability a major concern. Automated random testing has been shown to be useful in finding defects in these systems, but its inherent test oracle problem (automatic generation of the expected system output) is a drawback that has typically prevented its application on a larger scale. Two main tasks have been carried out in this thesis as a solution to the test oracle problem. First, an independent model of a real trading system based on constraint programming, a method for solving combinatorial problems, has been created. Then, the model has been integrated as a true test oracle in automated random tests. The test oracle maintains the expected state of an order book throughout a sequence of random trade order actions, and provides the expected output of every auction triggered in the order book by generating a corresponding constraint program that is solved with the aid of a constraint programming system. Constraint programming has allowed the development of an inexpensive, yet reliable test oracle. In 500 random test cases, the test oracle has detected two system failures. These failures correspond to defects that had been present for several years without being discovered neither by less complete oracles nor by the application of more systematic testing approaches. The main contributions of this thesis are: (1) empirical evidence of both the suitability of applying constraint programming to solve the test oracle problem and the effectiveness of true test oracles in random testing, and (2) a first attempt, as far as the author is aware, to model a non-theoretical continuous double auction using constraint programming. / Winner of the Swedish AI Society's prize for the best AI Master's Thesis 2010.

Submitted by Fernando Reis de Odriozola (odriozola.fernando@gmail.com) on 2015-09-21T04:39:27Z No. of bitstreams: 1 Dissertação - Fernando R Odriozola.pdf: 881210 bytes, checksum: 13c5e46a6da326c976883920a7af7eb6 (MD5) / Approved for entry into archive by Renata de Souza Nascimento (renata.souza@fgv.br) on 2015-09-21T23:06:54Z (GMT) No. of bitstreams: 1 Dissertação - Fernando R Odriozola.pdf: 881210 bytes, checksum: 13c5e46a6da326c976883920a7af7eb6 (MD5) / Made available in DSpace on 2015-09-22T13:32:47Z (GMT). No. of bitstreams: 1 Dissertação - Fernando R Odriozola.pdf: 881210 bytes, checksum: 13c5e46a6da326c976883920a7af7eb6 (MD5) Previous issue date: 2015-08-24 / For complex systems, traditional analytical-approach with differential equations sometimes results in intractable solutions. An alternative approach could be through Agents-Based Models as a complementary tool witch systems can be modeled from their constituent parts and interactions. Financial Markets are good examples of complex system and thus Agent-Based Models would be a correct approach. This paper implements an Artificial Financial Market composed by market makers, information broadcasters and a set of heterogeneous agents who trade assets through a Continuous Double Auction mechanism. Several aspects of the simulation were investigated to consolidate their understanding and thus contribute to the design of models, where we can highlight, among others: distinctions between Discrete and Continuous Double Auction; implications of Market Maker spread settings; Budget Constraints effects on agents and Analysis of pricing formation in offer submissions. Thinking about the adherence of the model to the Brazilian market reality, a method named Inverse Simulation is used to calibrate the input parameters in a way that the output matches historical market price series. / Na modelagem de sistemas complexos, abordagens analíticas tradicionais com equações diferenciais muitas vezes resultam em soluções intratáveis. Para contornar este problema, Modelos Baseados em Agentes surgem como uma ferramenta complementar, onde o sistema é modelado a partir de suas entidades constituintes e interações. Mercados Financeiros são exemplos de sistemas complexos, e como tais, o uso de modelos baseados em agentes é aplicável. Este trabalho implementa um Mercado Financeiro Artificial composto por formadores de mercado, difusores de informações e um conjunto de agentes heterogêneos que negociam um ativo através de um mecanismo de Leilão Duplo Contínuo. Diversos aspectos da simulação são investigados para consolidar sua compreensão e assim contribuir com a concepção de modelos, onde podemos destacar entre outros: Diferenças do Leilão Duplo Contínuo contra o Discreto; Implicações da variação do spread praticado pelo Formador de Mercado; Efeito de Restrições Orçamentárias sobre os agentes e Análise da formação de preços na emissão de ofertas. Pensando na aderência do modelo com a realidade do mercado brasileiro, uma técnica auxiliar chamada Simulação Inversa, é utilizada para calibrar os parâmetros de entrada, de forma que trajetórias de preços simulados resultantes sejam próximas à séries de preços históricos observadas no mercado.

「預測市場」以未來事件為交易標的，透過網路平台彙整即時資訊，運用價格來判斷未來事件的發展，此研究方法同時具有「適當獎懲」與「連續修正」兩項特性。 本研究以文獻分析途徑探究預測市場在不同交易機制下的運作方式與市場價格決定過程，並據此分析不同交易機制之間的差異與影響預測市場運作的因素；除此之外，本研究另以個案研究途徑來探討「連續雙向拍賣」與「市場計分法則」兩個交易機制在價格準確度、市場流動性、價格炒作、參與誘因與莊家風險之間的差異。 本研究發現：若交易機制是連續雙向拍賣，則「0-100型」合約價格的預測準確度較高；若交易機制是市場計分法則，則「落點預測型」合約價格的預測準確度較高。連續雙向拍賣機制具有市場流動性不足的問題；市場計分法則機制面臨莊家風險的危機且不適用於市場競爭度高的環境；而上述兩種交易機制皆會出現價格炒作的現象。 / “Prediction market” is a research method based on immediate information collecting and organizing on the internet platform. With future events as the object of transaction, variations of the price of each transaction thus immediately provide the prediction of the development of future events. Therefore, this method has two properties including “appropriate incentives” and “continuous correction”. In this study, document analysis is first conducted to review the operation modes of different trading mechanisms for prediction markets and the process of price making. Accordingly, differences between trading mechanisms and the factors that affect the operation of prediction market will also be analyzed. Furthermore, comparisons of the price accuracy, market liquidity, price speculation, incentives and maker risks between "continuous double auction" and "market scoring rule" are discussed in case study. The findings of this study: if the trading mechanism is “continuous double auction”, the price accuracy of “winner-take-all” contract is higher; if the trading mechanism is “market scoring rules”, the price accuracy of “index” contract is higher. There exists insufficient market liquidity in “continuous double auction;” while in “market scoring rule,” there exists maker risks and it is hard to be applied in highly competitive market. The phenomenon of price speculation exits in both trading mechanisms.