70,063 research outputs found
The virtues and vices of equilibrium and the future of financial economics
The use of equilibrium models in economics springs from the desire for
parsimonious models of economic phenomena that take human reasoning into
account. This approach has been the cornerstone of modern economic theory. We
explain why this is so, extolling the virtues of equilibrium theory; then we
present a critique and describe why this approach is inherently limited, and
why economics needs to move in new directions if it is to continue to make
progress. We stress that this shouldn't be a question of dogma, but should be
resolved empirically. There are situations where equilibrium models provide
useful predictions and there are situations where they can never provide useful
predictions. There are also many situations where the jury is still out, i.e.,
where so far they fail to provide a good description of the world, but where
proper extensions might change this. Our goal is to convince the skeptics that
equilibrium models can be useful, but also to make traditional economists more
aware of the limitations of equilibrium models. We sketch some alternative
approaches and discuss why they should play an important role in future
research in economics.Comment: 68 pages, one figur
Using Laboratory Experiments to Design Efficient Market Institutions: The case of wholesale electricity markets
This paper assesses the contribution of laboratory experiments to the economics of design applied to the electricity industry. The analysis is dedicated to wholesale markets, and reviews the results accumulated to date concerning both the general architecture of power markets and the very details of the market rules or institution, that is the auction rule. We argue that these experimental results contribute to a better understanding of the performances properties and implementation features of competitive market designs and that experimental economics has proven very useful to public authorities to inform the restructuring of electricity industry. It thus confirms the role of experimental economics as a complement to theoretical approaches in the design effort.Experimental economics; market design; design economics; electricity auction;
Computing large market equilibria using abstractions
Computing market equilibria is an important practical problem for market
design (e.g. fair division, item allocation). However, computing equilibria
requires large amounts of information (e.g. all valuations for all buyers for
all items) and compute power. We consider ameliorating these issues by applying
a method used for solving complex games: constructing a coarsened abstraction
of a given market, solving for the equilibrium in the abstraction, and lifting
the prices and allocations back to the original market. We show how to bound
important quantities such as regret, envy, Nash social welfare, Pareto
optimality, and maximin share when the abstracted prices and allocations are
used in place of the real equilibrium. We then study two abstraction methods of
interest for practitioners: 1) filling in unknown valuations using techniques
from matrix completion, 2) reducing the problem size by aggregating groups of
buyers/items into smaller numbers of representative buyers/items and solving
for equilibrium in this coarsened market. We find that in real data
allocations/prices that are relatively close to equilibria can be computed from
even very coarse abstractions
Cloud computing resource scheduling and a survey of its evolutionary approaches
A disruptive technology fundamentally transforming the way that computing services are delivered, cloud computing offers information and communication technology users a new dimension of convenience of resources, as services via the Internet. Because cloud provides a finite pool of virtualized on-demand resources, optimally scheduling them has become an essential and rewarding topic, where a trend of using Evolutionary Computation (EC) algorithms is emerging rapidly. Through analyzing the cloud computing architecture, this survey first presents taxonomy at two levels of scheduling cloud resources. It then paints a landscape of the scheduling problem and solutions. According to the taxonomy, a comprehensive survey of state-of-the-art approaches is presented systematically. Looking forward, challenges and potential future research directions are investigated and invited, including real-time scheduling, adaptive dynamic scheduling, large-scale scheduling, multiobjective scheduling, and distributed and parallel scheduling. At the dawn of Industry 4.0, cloud computing scheduling for cyber-physical integration with the presence of big data is also discussed. Research in this area is only in its infancy, but with the rapid fusion of information and data technology, more exciting and agenda-setting topics are likely to emerge on the horizon
An Investigation Report on Auction Mechanism Design
Auctions are markets with strict regulations governing the information
available to traders in the market and the possible actions they can take.
Since well designed auctions achieve desirable economic outcomes, they have
been widely used in solving real-world optimization problems, and in
structuring stock or futures exchanges. Auctions also provide a very valuable
testing-ground for economic theory, and they play an important role in
computer-based control systems.
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.
This report aims to survey the theoretical and empirical approaches to
designing auction mechanisms and trading strategies with more weights on
empirical ones, and build the foundation for further research in the field
Algorithmic Approaches to Game-theoretical Modeling and Simulation
This paper deals with a methodology of computer modeling and simulation of market competitive situations using game theory. The situations are thematically focused mostly to models of commodity markets but the applications of the methodology can be wider. This methodology covers the whole modeling work, including a primary specification of a problem, making an abstract model, making a simulation model, design of a state space of the problem and the simulator itself. As a whole, the methodology represents a complete framework for implementation of computer models of commodity markets suitable for their further analysis and prediction of their future evolution. The main contribution of the paper consists in the algorithmic implementation of computer processing of large strategic game.Market models, non-cooperative game theory, modeling and simulation, artificial intelligence
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