Market Microstructure
- Teacher(s): R.Mihet
- Course given in: English
- ECTS Credits: 3 credits
- Schedule: Autumn Semester 2022-2023, 2.0h. course + 1.0h exercices (weekly average)
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Related programmes:
Master of Science (MSc) in Finance, Orientation Corporate Finance
Master of Science (MSc) in Finance : Financial Entrepreneurship and Data Science
Master of Science (MSc) in Finance, Orientation Asset and Risk Management -
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ObjectivesCourse objective: Information is at the heart of the economy today. Despite this, there is still a lively debate over whether markets aggregate the dispersed information of agents in the economy or whether they are at the mercy of herd behavior and fads and in the hands of short-term speculators and insiders. The debate has old roots and goes back at least to the exchange between Hayek and Lange in the 1930s about the economic viability of socialism. While Lange (1936, 1937) argued that socialism was viable because a competitive allocation can be replicated by a central planner, Hayek contended that the superiority of markets was to be found in their ability to aggregate the dispersed information of agents in the economy (Hayek, 1945). In contrast to Hayek, Keynes in his General Theory pioneered the view of the stock market as a beauty contest where investors try to guess average opinion, instead of fundamentals, and end up chasing the crowd (Keynes, 1936). The central issue is whether we can trust markets to aggregate information in a world where information is dispersed. Does the stock market reflect the underlying fundamentals of the traded firms? Or, to put the question in more concrete terms, does the price in the futures market for gas aggregate the relevant information of producers and speculators? In this course we will analyze in depth the information aggregation properties of markets and the impact of specific trading arrangements (the market microstructure) on the information aggregation process and the quality or performance of the market. We will explore some of the latest research questions and theories designed to address those questions. We will use information frictions and information choice as a way to reconcile standard theory with puzzling facts. At the same time as we explore theory, we will be building up the tools of Bayesian updating and Bayesian forecasting, powerful tools to address many questions that arise in the business world as well.
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