Бакалавриат
2019/2020
Теория финансов
Статус:
Курс по выбору (Программа двух дипломов по экономике НИУ ВШЭ и Лондонского университета)
Направление:
38.03.01. Экономика
Кто читает:
Международный институт экономики и финансов
Где читается:
Международный институт экономики и финансов
Когда читается:
3-й курс, 1, 2 модуль
Формат изучения:
без онлайн-курса
Язык:
английский
Кредиты:
4
Контактные часы:
64
Course Syllabus
Abstract
Prerequisites: microeconomics, basic calculus and probability theory, linear algebra The course consists of two parts: Part 1 is devoted to theoretical behavioral finance and Part 2 is devoted to microstructure of financial markets. Part 1 of the course examines asset pricing implications of several ``irrational’’ aspects of human behavior. According to the rational finance paradigm, it is true that some investors may be driven by psychological factors, emotions, limited attention, etc, however these features are not likely to affect aggregate quanties – asset prices, asset volatilies. Behavioral finance researchers disagree by showing, both theoretically and empirically, that accounting for various behavioral factors can help explaining empirical evidence that is hard to explain under the rational paradigm. In this part of the course, we will examine in detail several behavioral finance models that have helped to establish behavioral finance as an important branch within financial economics. Part 2 of the course is an introduction into some basic concepts and models of the microstructure theory of financial markets. Theoretical Market Microstructure is intended to develop economic models of financial markets within a “microscopic” approach when one explicitly takes into account a particular market design and types of agents involved in a trading process. One application of the Market Microstructure models is analysis of the impact of market organizational structure on various important market characteristics, such as price efficiency, transaction costs, liquidity, etc., and to construct quantitative indicators of market quality. Both Part 1 and Part 2 are based on original academic research papers on Behavioral Finance and Market Microstructure theory. The emphasis is on the finance models that are sufficiently simple and analytically tractable. The goal is to provide students with the tools and basic knowledge required to understand and analyze original academic papers.
Learning Objectives
- 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
Expected Learning Outcomes
- define the main concepts of behavioral finance and microstructure
- know the details of main models and methods used in these areas
Course Contents
- 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?
Assessment Elements
- home assignments in Part 1
- presentation of papers in class and class participation
- final exam
Interim Assessment
- 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
Bibliography
Recommended Core Bibliography
- 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
- The microstructure of financial markets, Jong de, F., Rindi, B., 2010
Recommended Additional Bibliography
- Richard K. Lyons. (2006). The Microstructure Approach to Exchange Rates. The MIT Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsrep&AN=edsrep.b.mtp.titles.026262205x