Theory of Finance
- Identifying the scientific nature of the problems in the professional field
- Working with information: to find, evaluate and use information from various sources, necessary to solve scientific and professional problems (including those on the basis of a systematic approach)
- Learning how to work in a team
- Intelligently build communication based on the goals and situation of communication
- Based on the description of economic processes and phenomena, build theoretical and econometric models, analyzing and meaningfully interpreting the results obtained
- Use the basic modeling approaches in microstructure, particularly the information based models
- Be able to read and understand original research papers on the subject.
- Distinguish between rational and behavioral paradigms
- Distinguish between risk and uncertainty
- Analyze the effect of ambiguity aversion on asset pricing
- Use pioneering models examining limited arbitrage
- Identify main types of real world constraints preventing “ideal” arbitrage strategies from theoretical models
- Introduction to behavioral financeThere are two main paradigms in financial economics: rational and behavioral. For a long time, the rational paradigm was the dominant one. It was justifed by the natural selection hypothesis: irrational people cannot survive in the market for a long time because they are gradually outsmarted by rational investors. We will discuss some key ideas of the rational finance (e.g., efficient market hypothesis), study some simple rational asset pricing models, and talk about ``puzzles’’ – features of the real data that rational models have not been able to explain. We will then review key ideas of behavioral finance, and how they helped to build models with realistic empirical predictions
- Ambiguity aversionRational finance theories assume that an investor, when faced with an uncertainty about stock return, forms a certain belief about the stock distribution. Classical Elsberg’s paradox reveals that real peoples’ choice can be inconsistent with this assumption. In situations when people do not know the distribution of a random quantity, they may act as if they are averse to the ambiguity created by this lack of knowledgere. We will examine how standard portfolio choice and asset pricing models can be extended to account for ambiguity aversion, and how it affects the predictions.
- Limits to arbitrageThe above-mentioned natural selection hypothesis posits that rational investors – arbitrageurs – are always able to outsmart irrational investors drive them out of the financial market by making them quickly lose their wealth. While theoretically appealing, this argument may not fully describe the actual behavior of arbitrageurs given various real-world constraints. In other words, there are limits to arbitrage - it may not be possible to arbitrage away price anomalies. As a result, markets can remain inefficient, and irrational investors can survive. We will study several highly-influential papers in which these ideas are formalized. The reason why these papers are influential is because of their ability to explain what happened during several major financial crises in the US and other countries
- Review1.Basic facts and terminology on financial market structure. Auction, dealers’ and hybrid markets, order-driven and quote-driven, call and continuous markets. High-frequency (HFT) and algoritmic trading. Liquidity; bid-ask spread and its components; price impact and its components; cost of trading and transaction cost (t-cost). Notion of informational efficiency. 2. General approaches to modelling trading strategies and prices. Price taking and Rational expectations. Information and pricing; Rational Expectations Equilibrium (REE). Models of strategic trading. 3. Dynamic strategies. Dynamic trading strategies, modelling in discrete and continuous time. Liquidity and algorithmic trading. Optimal execution. "Predatory trading" and "front running". 4. Applied topics: Liquidity provision, HFT and algorithmic trading. a. High-frequency and algorithmic trading and liquidity issues. b. Quality of markets and informed liquidity provision. Problems of assessing the quality of markets and liquidity provision. Optimization of limited information resources (limited attention).
- Price taking, Rational Expectations, and Strategic trading modelsCompare different trading strategies, pricing rules and types of equilibrium described by all three classes of models.
- Dynamic trading strategiesCompare the cases of strategic trading based on single and multiple signals (static and dynamic private information structure), and trading not based on information (optimal execution). What makes “predatory trading” possible? What are the shortcomings of Brunnermeier and Pedersen (2005) model?
- Applied topicsWhat are the different aspects of liquidity discussed in the first two empirical papers? Describe and explain the economic content of the “invariants” considered in the third paper. What do the existing theoretical models say about order cancellation and its impact on the market quality?
- home assignments in Part 1
- presentation of papers in class and class participation
- final exam
- Interim assessment (2 module)0.6 * final exam + 0.15 * home assignments in Part 1 + 0.25 * presentation of papers in class and class participation
- The microstructure of financial markets, Jong de F., Rindi B., 2010
- Shleifer, A. (2000). Inefficient Markets: An Introduction to Behavioral Finance. Oxford University Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.b.oxp.obooks.9780198292272