Verified Double Sided Auctions for Financial Markets

Double sided auctions are widely used in financial markets to match demand and supply. Prior works on double sided auctions have focused primarily on single quantity trade requests. We extend various notions of double sided auctions to incorporate multiple quantity trade requests and provide fully formalized matching algorithms for double sided auctions with their correctness proofs. We establish new uniqueness theorems that enable automatic detection of violations in an exchange program by comparing its output with that of a verified program. All proofs are formalized in the Coq proof assistant without adding any axiom to the system. We extract verified OCaml and Haskell programs that can be used by the exchanges and the regulators of the financial markets. We demonstrate the practical applicability of our work by running the verified program on real market data from an exchange to automatically check for violations in the exchange algorithm

The Design and Regulation of Exchanges: A Formal Approach

We use formal methods to specify, design, and monitor continuous double auctions, which are widely used to match buyers and sellers at exchanges of foreign currencies, stocks, and commodities. We identify three natural properties of such auctions and formally prove that these properties completely determine the input-output relationship. We then formally verify that a natural algorithm satisfies these properties. All definitions, theorems, and proofs are formalized in an interactive theorem prover. We extract a verified program of our algorithm to build an automated checker that is guaranteed to detect errors in the trade logs of exchanges if they generate transactions that violate any of the natural properties

An Integrated Framework for Modelling and Control of eP2P Interactions based on Model Predictive Control

The energy paradigm is undergoing substantial changes in recent years. In terms of production, it is observable how distributed generation, with an ever-increasing contribution from renewable sources, is displacing large concentrated generation plants. But the fundamental change is not so much about energy supply as about diluting the historical roles of producers and consumers to give way to the concept of prosumers. That is, instead of just being energy consumers, households and industries also become producers. In principle, the purpose of this production, which is inherently distributed, is self-consumption. However, when there is a surplus of production, prosumers can choose between storing the excess, if they have an energy storage system, or sell the unused fraction of energy. An obvious type of prosumers are those industries that have renewable generation facilities and which, as a consequence of their production process, generate by-products that can be used for cogeneration. In this case an obvious problem for the company is to select at all times the power sources that minimize the cost of production, which is known as Optimal Power Dispatch (OPD). If, in addition, the energy consumption time profile of the manufacturing process (per unit of raw material introduced) is known, it is also possible to make an optimal production schedule to minimize energy cost, which is called Optimal Power Scheduling (OPS). Chapter 3 presents an Economic Model Predictive Controller (EMPC) that simultaneously performs OPD and OPS using an olive mill as an example. The emergence of the role of energy prosumers makes it necessary to extend, improve or replace the traditional mechanisms of energy exchange. This thesis includes novel approaches for modelling the behaviour of prosumers. It also proposes new structures to facilitate energy trading, always from the perspective of the peerification of the energy paradigm. Thus, another line of research studies the establishment of peer-to-peer (P2P) markets for the exchange of energy between heterogeneous prosumers (homes, vehicles, intelligent buildings, etc.). The efficiency of markets based on both discrete double auctions (DDAs) and continuous double auctions (CDAs) is compared. An Energy Management System (EMS) is also introduced including market agent software that allows the necessary tasks for participation in the auctions to be carried out automatically (determination of private valuation, role selection and price adaptation). Chapter 4, Chapter 5 and Chapter 6 present some examples of such exchange markets stablished between different types of prosumers: i) energy market for electric vehicles that coincide parked in a large workplace, ii) power market for households within the same neighbourhood and iii) integrated energy and power markets for heterogeneous energy entities. The evolution of aforementioned mechanisms and the appearance of new market models must be accompanied by the development of control techniques that optimise and automate all the processes related to energy saving and trading, by a group of increasingly heterogeneous prosumers. This thesis deals with how different variants of predictive controllers can contribute to this last aspect. For industries with cogeneration capacity, the EMPC contributes to the optimal scheduling of production to maximise the return from energy reuse, either through self-consumption or through the trading of surpluses. The use of stochastic predictive control is proposed in order to maximise the expected return on the participation of prosumers, whatever their type, in continuous markets where the price of energy may undergo stochastic variations.El paradigma energético está experimentando cambios sustanciales en los últimos años. En cuanto a la producción, se observa cómo la generación distribuida, con un aporte cada vez mayor de fuentes renovables, está desplazando a las grandes plantas de generación concentrada. Pero el cambio fundamental no consiste tanto en el suministro de energía como en la dilución de la clasificación tradicional entre productores y consumidores para dar paso al concepto de prosumidores. Es decir, en lugar de ser simplemente consumidores de energía, los hogares y las industrias también se convierten en productores. En principio, el objetivo de esta producción, que es intrínsecamente distribuida, es el autoconsumo. Sin embargo, cuando hay un excedente de producción, los prosumidores pueden elegir entre almacenar el excedente, si tienen un sistema de almacenamiento de energía, o vender la fracción no utilizada de la energía. Un tipo obvio de prosumidores son aquellas industrias que cuentan con instalaciones de generación renovable y que, como consecuencia de su proceso de producción, generan subproductos que pueden ser utilizados para la cogeneración. En este caso, un problema obvio para la empresa es seleccionar en todo momento las fuentes de energía que minimizan el coste de producción, lo que se conoce como Optimal Power Dispatch (OPD). Si, además, se conoce el perfil temporal de consumo de energía asociado al proceso de fabricación (por unidad de materia prima introducida), también es posible realizar un programa de producción óptimo para minimizar el coste de la energía, lo cual se denomina Optimal Power Scheduling (OPS). El capítulo 3 presenta un Controlador Predictivo Económico basado en Modelo (EMPC) que realiza simultáneamente OPD y OPS utilizando como caso de estudio una almazara olivarera. La aparición de la figura de los prosumidores energéticos hace necesario ampliar, mejorar o sustituir los mecanismos tradicionales de intercambio energético. Esta tesis incluye enfoques novedosos para modelar el comportamiento de los prosumidores. También propone nuevas estructuras para facilitar el comercio de energía, siempre desde la perspectiva de la peerificación del paradigma energético. Así, otra línea de investigación estudia el establecimiento de mercados peer-to-peer (P2P) para el intercambio de energía entre prosumidores heterogéneos (viviendas, vehículos, edificios inteligentes, etc.). Se compara la eficiencia de los mercados basados tanto en subastas dobles discretas (Discrete Double Auction - DDA) como en subastas dobles continuas (Continuous Double Auctions - CDA). También se introduce un Sistema de Gestión Energética (Energy Management System - EMS) que incluye un software de agente de mercado que permite que las tareas necesarias para la participación en las subastas (determinación de la valoración privada, selección de roles y adaptación de precios) se lleven a cabo automáticamente. Los capítulos 4, 5 y 6 presentan algunos ejemplos de estos mercados de intercambio establecidos entre diferentes tipos de prosumidores: i) mercado de energía para vehículos eléctricos que coinciden aparcados en un gran lugar de trabajo, ii) mercado de energía para hogares dentro de un mismo barrio y iii) mercados integrados de energía y electricidad para entidades energéticas heterogéneas. La evolución de los mecanismos mencionados y la aparición de nuevos modelos de mercado deben ir acompañados del desarrollo de técnicas de control que optimicen y automaticen todos los procesos relacionados con el ahorro y la comercialización de la energía, por parte de un conjunto de prosumidores cada vez más heterogéneos. Esta tesis trata de cómo las diferentes variantes de los controladores predictivos pueden contribuir a este último aspecto. Para las industrias con capacidad de cogeneración, el EMPC contribuye a la programación óptima de la producción para maximizar el rendimiento de la reutilización de la energía, ya sea a través del autoconsumo o de la comercialización de excedentes. Por otro lado, se propone el uso del control predictivo estocástico para maximizar el rendimiento esperado de la participación de los prosumidores, cualquiera que sea su tipo, en mercados P2P donde el precio de la energía está sujeto a incertidumbres

Automated Auction Mechanism Design with Competing Markets

Resource allocation is a major issue in multiple areas of computer science. Despite the wide range of resource types across these areas, for example real commodities in e-commerce and computing resources in distributed computing, auctions are commonly used in solving the optimization problems involved in these areas, since well designed auctions achieve desirable economic outcomes. Auctions are markets with strict regulations governing the information available to traders in the market and the possible actions they can take. Auction mechanism design aims to manipulate the rules of an auction in order to achieve specific goals. Economists traditionally use mathematical methods, mainly game theory, to analyze auctions and design new auction forms. However, due to the high complexity of auctions, the mathematical models are typically simplified to obtain results, and this makes it difficult to apply results derived from such models to market environments in the real world. As a result, researchers are turning to empirical approaches. Following this line of work, we present what we call a grey-box approach to automated auction mechanism design using reinforcement learning and evolutionary computation methods. We first describe a new strategic game, called \cat, which were designed to run multiple markets that compete to attract traders and make profit. The CAT game enables us to address the imbalance between prior work in this field that studied auctions in an isolated environment and the actual competitive situation that markets face. We then define a novel, parameterized framework for auction mechanisms, and present a classification of auction rules with each as a building block fitting into the framework. Finally we evaluate the viability of building blocks, and acquire auction mechanisms by combining viable blocks through iterations of CAT games. We carried out experiments to examine the effectiveness of the grey-box approach. The best mechanisms we learnt were able to outperform the standard mechanisms against which learning took place and carefully hand-coded mechanisms which won tournaments based on the CAT game. These best mechanisms were also able to outperform mechanisms from the literature even when the evaluation did not take place in the context of CAT games. These results suggest that the grey-box approach can generate robust double auction mechanisms and, as a consequence, is an effective approach to automated mechanism design. The contributions of this work are two-fold. First, the grey-box approach helps to design better auction mechanisms which can play a central role in solutions to resource allocation problems in various application domains of computer science. Second, the parameterized view and the reinforcement learning-based search method can be used in other strategic, competitive situations where decision making processes are complex and difficult to design and evaluate manually

Maximizing matching in double-sided auctions

In this paper, we introduce a novel, non-recursive, maximal matching algorithm for double auctions, which aims to maximize the amount of commodities to be traded. It differs from the usual equilibrium matching, which clears a market at the equilibrium price. We compare the two algorithms through experimental analyses, showing that the maximal matching algorithm is favored in scenarios where trading volume is a priority and that it may possibly improve allocative efficiency over equilibrium matching as well. A parameterized algorithm that incorporates both maximal matching and equilibrium matching as special cases is also presented to allow flexible control on how much to trade in a double auction.Comment: 16 pages, 4 figures, full-length version of an extended abstract published at the AAMAS 2013 conferenc