scholarly journals Chain: A Dynamic Double Auction Framework for Matching Patient Agents

2007 ◽  
Vol 30 ◽  
pp. 133-179 ◽  
Author(s):  
J. L. Bredin ◽  
D. C. Parkes ◽  
Q. Duong
Keyword(s):  
General Framework ◽  
Allocative Efficiency ◽  
Double Auction ◽  
Matching Method ◽  
Learning Agents ◽  
Double Auctions ◽  
Single Period ◽  
Zero Intelligence ◽  
Multiple Buyers ◽  
Arrival Intensity

In this paper we present and evaluate a general framework for the design of truthful auctions for matching agents in a dynamic, two-sided market. A single commodity, such as a resource or a task, is bought and sold by multiple buyers and sellers that arrive and depart over time. Our algorithm, Chain, provides the first framework that allows a truthful dynamic double auction (DA) to be constructed from a truthful, single-period (i.e. static) double-auction rule. The pricing and matching method of the Chain construction is unique amongst dynamic-auction rules that adopt the same building block. We examine experimentally the allocative efficiency of Chain when instantiated on various single-period rules, including the canonical McAfee double-auction rule. For a baseline we also consider non-truthful double auctions populated with ``zero-intelligence plus"-style learning agents. Chain-based auctions perform well in comparison with other schemes, especially as arrival intensity falls and agent valuations become more volatile.

Fuzzy logic-based bidding strategies in dynamic double auctions

Kybernetes ◽  
2019 ◽  
Vol 48 (3) ◽  
pp. 612-635
Author(s):  
Baki Unal ◽  
Çagdas Hakan Aladag
Keyword(s):  
Fuzzy Logic ◽  
Bidding Strategy ◽  
Double Auction ◽  
Auction Markets ◽  
Content Type ◽  
Bidding Strategies ◽  
Double Auctions ◽  
Inference Systems ◽  
Zero Intelligence ◽  
Logic Inference

Purpose Double auctions are widely used market mechanisms on the world. Communication technologies such as internet increased importance of this market institution. The purpose of this study is to develop novel bidding strategies for dynamic double auction markets, explain price formation through interactions of buyers and sellers in decentralized fashion and compare macro market outputs of different micro bidding strategies. Design/methodology/approach In this study, two novel bidding strategies based on fuzzy logic are presented. Also, four new bidding strategies based on price targeting are introduced for the aim of comparison. The proposed bidding strategies are based on agent-based computational economics approach. The authors performed multi-agent simulations of double auction market for each suggested bidding strategy. For the aim of comparison, the zero intelligence strategy is also used in the simulation study. Various market outputs are obtained from these simulations. These outputs are market efficiencies, price means, price standard deviations, profits of sellers and buyers, transaction quantities, profit dispersions and Smith’s alpha statistics. All outputs are also compared to each other using t-tests and kernel density plots. Findings The results show that fuzzy logic-based bidding strategies are superior to price targeting strategies and the zero intelligence strategy. The authors also find that only small number of inputs such as the best bid, the best ask, reference price and trader valuations are sufficient to take right action and to attain higher efficiency in a fuzzy logic-based bidding strategy. Originality/value This paper presents novel bidding strategies for dynamic double auction markets. New bidding strategies based on fuzzy logic inference systems are developed, and their superior performances are shown. These strategies can be easily used in market-based control and automated bidding systems.

scholarly journals Bidding in Smart Grid PDAs: Theory, Analysis and Strategy

2020 ◽  
Vol 34 (02) ◽  
pp. 1974-1981
Author(s):  
Susobhan Ghosh ◽  
Sujit Gujar ◽  
Praveen Paruchuri ◽  
Easwar Subramanian ◽  
Sanjay Bhat
Keyword(s):  
Smart Grids ◽  
Complete Information ◽  
Equilibrium Analysis ◽  
Equilibrium Strategy ◽  
Double Auction ◽  
Single Shot ◽  
Wholesale Market ◽  
Bidding Strategies ◽  
Double Auctions ◽  
Best Response

Periodic Double Auctions (PDAs) are commonly used in the real world for trading, e.g. in stock markets to determine stock opening prices, and energy markets to trade energy in order to balance net demand in smart grids, involving trillions of dollars in the process. A bidder, participating in such PDAs, has to plan for bids in the current auction as well as for the future auctions, which highlights the necessity of good bidding strategies. In this paper, we perform an equilibrium analysis of single unit single-shot double auctions with a certain clearing price and payment rule, which we refer to as ACPR, and find it intractable to analyze as number of participating agents increase. We further derive the best response for a bidder with complete information in a single-shot double auction with ACPR. Leveraging the theory developed for single-shot double auction and taking the PowerTAC wholesale market PDA as our testbed, we proceed by modeling the PDA of PowerTAC as an MDP. We propose a novel bidding strategy, namely MDPLCPBS. We empirically show that MDPLCPBS follows the equilibrium strategy for double auctions that we previously analyze. In addition, we benchmark our strategy against the baseline and the state-of-the-art bidding strategies for the PowerTAC wholesale market PDAs, and show that MDPLCPBS outperforms most of them consistently.

scholarly journals A cloud priority-based dynamic online double auction mechanism (PB-DODAM)

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
S. M. Reza Dibaj ◽  
Ali Miri ◽  
SeyedAkbar Mostafavi
Keyword(s):  
Resource Allocation ◽  
Service Providers ◽  
Supply And Demand ◽  
Cloud Service ◽  
Time Constraints ◽  
Double Auction ◽  
Auction Mechanism ◽  
Double Auctions ◽  
Auction Models ◽  
Scheduling Mechanisms

AbstractDouble auctions are considered to be effective price-scheduling mechanisms to resolve cloud resource allocation and service pricing problems. Most of the classical double auction models use price-based mechanisms in which determination of the winner is based on the prices offered by the agents in the market. In cloud ecosystems, the services offered by cloud service providers are inherently time-constrained and if they are not sold, the allocated resources for the unsold services are wasted. Furthermore, cloud service users have time constraints to complete their tasks, otherwise, they would not need to request these services. These features, perishability and time-criticality, have not received much attention in most classical double auction models. In this paper, we propose a cloud priority-based dynamic online double auction mechanism (PB-DODAM), which is aligned with the dynamic nature of cloud supply and demand and the agents’ time constraints. In PB-DODAM, a heuristic algorithm which prioritizes the agents’ asks and bids based on their overall condition and time constraints for resource allocation and price-scheduling mechanisms is proposed. The proposed mechanism drastically increases resource allocation and traders’ profits in both low-risk and high-risk market conditions by raising the matching rate. Moreover, the proposed mechanism calculates the precise defer time to wait for any urgent or high-priority request without sacrificing the achieved performance in resource allocation and traders’ profits. Based on experimental results in different scenarios, the proposed mechanism outperforms the classical price-based online double auctions in terms of resource allocation efficiency and traders’ profits while fulfilling the double auction’s truthfulness pillar.

scholarly journals Efficient Allocations in Double Auction Markets

2021 ◽  
Author(s):  
Teemu Pennanen
Keyword(s):  
Pareto Frontier ◽  
Invisible Hand ◽  
Double Auction ◽  
Descriptive Model ◽  
Auction Markets ◽  
Double Auctions ◽  
Limit Orders ◽  
Finite Set ◽  
Classical Models ◽  
Efficient Allocations

This paper proposes a simple descriptive model of discrete-time double auction markets for divisible assets. As in the classical models of exchange economies, we consider a finite set of agents described by their initial endowments and preferences. Instead of the classical Walrasian-type market models, however, we assume that all trades take place in a centralized double auction where the agents communicate through sealed limit orders for buying and selling. We find that, under nonstrategic bidding, double auction clears with zero trades precisely when the agents’ current holdings are on the Pareto frontier. More interestingly, the double auctions implement Adam Smith’s “invisible hand” in the sense that, when starting from disequilibrium, repeated double auctions lead to a sequence of allocations that converges to individually rational Pareto allocations.

TRADING RESTRICTIONS, PRICE DYNAMICS AND ALLOCATIVE EFFICIENCY IN DOUBLE AUCTION MARKETS: ANALYSIS BASED ON AGENT-BASED MODELING AND SIMULATIONS

2003 ◽  
Vol 06 (03) ◽  
pp. 283-302 ◽  
Author(s):  
SHU-HENG CHEN ◽  
CHUNG-CHING TAI
Keyword(s):  
Experimental Economics ◽  
Human Subjects ◽  
Allocative Efficiency ◽  
Agent Based Modeling ◽  
Double Auction ◽  
Price Dynamics ◽  
Modeling And Simulations ◽  
Agent Based ◽  
Auction Market ◽  
Trading Restrictions

In this paper we conduct two experiments within an agent-based double auction market. These two experiments allow us to see the effect of learning and smartness on price dynamics and allocative efficiency. Our results are largely consistent with the stylized facts observed in experimental economics with human subjects. From the amelioration of price deviation and allocative efficiency, the effect of learning is vividly seen. However, smartness does not enhance market performance. In fact, the experiment with smarter agents (agents without a quote limit) results in a less stable price dynamics and lower allocative efficiency.

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