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You searched for +publisher:"University of Michigan" +contributor:("Sinha, Arunesh"). Showing records 1 – 2 of 2 total matches.

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1. Brinkman, Erik. Understanding Financial Market Behavior through Empirical Game-Theoretic Analysis.

Degree: PhD, Computer Science & Engineering, 2018, University of Michigan

Financial market activity is increasingly controlled by algorithms, interacting through electronic markets. Unprecedented information response times, autonomous operation, use of machine learning and other adaptive techniques, and ability to proliferate novel strategies at scale are all reasons to question whether algorithmic trading may produce dynamic behavior qualitatively different from what arises in trading under direct human control. Given the high level of competition between trading firms and the significant financial incentives to trading, it is desirable to understand the effect incentives have on the behavior of agents in financial markets. One natural way to analyze this effect is through the economic concept of a Nash equilibrium, a behavior profile of every agent such that no individual stands to gain by doing something different. Some of the incentives traders face arise from the complexities of modern market structure. Recent studies have turned to agent-based modeling as a way to capture behavioral response to this structure. Agent-based modeling is a simulation paradigm that allows studying the interaction of agents in a simulated environment, and it has been used to model various aspects of financial market structure. This thesis builds on recent agent-based models of financial markets by imposing agent rationality and studying the models in equilibrium. I use empirical game-theoretic analysis, a methodology for computing approximately rational behavior in agent-based models, to investigate three important aspects of market structure. First, I evaluate the impact of strategic bid shading on agent welfare. Bid shading is when agents demand better prices, lower if they are buying or higher if they are selling, and is typically associated with lower social welfare. My results indicate that in many market environments, strategic bid shading actually improves social welfare, even with some of the complexities of financial markets. Next, I investigate the optimal clearing interval for a proposed market mechanism, the frequent call market. There is significant evidence to support the idea that traders will benefit from trading in a frequent call market over standard continuous double auction markets. My results confirm this statement for a wide variety of market settings, but I also find a few circumstances, particularly when large informational advantages exist, or when markets are thin, that call markets consistently hurt welfare, independent of frequency. I conclude with an investigation on the effect of trend following on market stability. Here I find that the presence of trend followers alters a market’s response to shock. In the absence of trend followers, shocks are small but have a long recovery. When trend followers are present, they alter background trader behavior resulting in more severe shocks that recover much more quickly. I also develop a novel method to efficiently evaluate the effect of shock anticipation on equilibrium. While anticipation of shocks does make markets more stable,… Advisors/Committee Members: Wellman, Michael P (committee member), Rajan, Uday (committee member), Abernethy, Jacob (committee member), Page, Scott E (committee member), Sinha, Arunesh (committee member).

Subjects/Keywords: empirical game-theoretic analysis; financial markets; Computer Science; Engineering

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Brinkman, E. (2018). Understanding Financial Market Behavior through Empirical Game-Theoretic Analysis. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/144031

Chicago Manual of Style (16th Edition):

Brinkman, Erik. “Understanding Financial Market Behavior through Empirical Game-Theoretic Analysis.” 2018. Doctoral Dissertation, University of Michigan. Accessed February 28, 2021. http://hdl.handle.net/2027.42/144031.

MLA Handbook (7th Edition):

Brinkman, Erik. “Understanding Financial Market Behavior through Empirical Game-Theoretic Analysis.” 2018. Web. 28 Feb 2021.

Vancouver:

Brinkman E. Understanding Financial Market Behavior through Empirical Game-Theoretic Analysis. [Internet] [Doctoral dissertation]. University of Michigan; 2018. [cited 2021 Feb 28]. Available from: http://hdl.handle.net/2027.42/144031.

Council of Science Editors:

Brinkman E. Understanding Financial Market Behavior through Empirical Game-Theoretic Analysis. [Doctoral Dissertation]. University of Michigan; 2018. Available from: http://hdl.handle.net/2027.42/144031


University of Michigan

2. Zhang, Qi. Making and Keeping Probabilistic Commitments for Trustworthy Multiagent Coordination.

Degree: PhD, Computer Science & Engineering, 2020, University of Michigan

In a large number of real world domains, such as the control of autonomous vehicles, team sports, medical diagnosis and treatment, and many others, multiple autonomous agents need to take actions based on local observations, and are interdependent in the sense that they rely on each other to accomplish tasks. Thus, achieving desired outcomes in these domains requires interagent coordination. The form of coordination this thesis focuses on is commitments, where an agent, referred to as the commitment provider, specifies guarantees about its behavior to another, referred to as the commitment recipient, so that the recipient can plan and execute accordingly without taking into account the details of the provider's behavior. This thesis grounds the concept of commitments into decision-theoretic settings where the provider's guarantees might have to be probabilistic when its actions have stochastic outcomes and it expects to reduce its uncertainty about the environment during execution. More concretely, this thesis presents a set of contributions that address three core issues for commitment-based coordination: probabilistic commitment adherence, interpretation, and formulation. The first contribution is a principled semantics for the provider to exercise maximal autonomy that responds to evolving knowledge about the environment without violating its probabilistic commitment, along with a family of algorithms for the provider to construct policies that provably respect the semantics and make explicit tradeoffs between computation cost and plan quality. The second contribution consists of theoretical analyses and empirical studies that improve our understanding of the recipient's interpretation of the partial information specified in a probabilistic commitment; the thesis shows that it is inherently easier for the recipient to robustly model a probabilistic commitment where the provider promises to enable preconditions that the recipient requires than where the provider instead promises to avoid changing already-enabled preconditions. The third contribution focuses on the problem of formulating probabilistic commitments for the fully cooperative provider and recipient; the thesis proves structural properties of the agents' values as functions of the parameters of the commitment specification that can be exploited to achieve orders of magnitude less computation for 1) formulating optimal commitments in a centralized manner, and 2) formulating (approximately) optimal queries that induce (approximately) optimal commitments for the decentralized setting in which information relevant to optimization is distributed among the agents. Advisors/Committee Members: Baveja, Satinder Singh (committee member), Durfee, Edmund H (committee member), Lewis, Richard L (committee member), Sinha, Arunesh (committee member).

Subjects/Keywords: Multiagent Coordination; Sequential Decision Making; Commitment; Markov Decision Process; Computer Science; Engineering

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Zhang, Q. (2020). Making and Keeping Probabilistic Commitments for Trustworthy Multiagent Coordination. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/162948

Chicago Manual of Style (16th Edition):

Zhang, Qi. “Making and Keeping Probabilistic Commitments for Trustworthy Multiagent Coordination.” 2020. Doctoral Dissertation, University of Michigan. Accessed February 28, 2021. http://hdl.handle.net/2027.42/162948.

MLA Handbook (7th Edition):

Zhang, Qi. “Making and Keeping Probabilistic Commitments for Trustworthy Multiagent Coordination.” 2020. Web. 28 Feb 2021.

Vancouver:

Zhang Q. Making and Keeping Probabilistic Commitments for Trustworthy Multiagent Coordination. [Internet] [Doctoral dissertation]. University of Michigan; 2020. [cited 2021 Feb 28]. Available from: http://hdl.handle.net/2027.42/162948.

Council of Science Editors:

Zhang Q. Making and Keeping Probabilistic Commitments for Trustworthy Multiagent Coordination. [Doctoral Dissertation]. University of Michigan; 2020. Available from: http://hdl.handle.net/2027.42/162948

.