Learning and Expectations in Macroeconomics

Learning and Expectations in Macroeconomics

Author: George W. Evans

Publisher: Princeton University Press

Published: 2012-01-06

Total Pages: 440

ISBN-13: 1400824265

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A crucial challenge for economists is figuring out how people interpret the world and form expectations that will likely influence their economic activity. Inflation, asset prices, exchange rates, investment, and consumption are just some of the economic variables that are largely explained by expectations. Here George Evans and Seppo Honkapohja bring new explanatory power to a variety of expectation formation models by focusing on the learning factor. Whereas the rational expectations paradigm offers the prevailing method to determining expectations, it assumes very theoretical knowledge on the part of economic actors. Evans and Honkapohja contribute to a growing body of research positing that households and firms learn by making forecasts using observed data, updating their forecast rules over time in response to errors. This book is the first systematic development of the new statistical learning approach. Depending on the particular economic structure, the economy may converge to a standard rational-expectations or a "rational bubble" solution, or exhibit persistent learning dynamics. The learning approach also provides tools to assess the importance of new models with expectational indeterminacy, in which expectations are an independent cause of macroeconomic fluctuations. Moreover, learning dynamics provide a theory for the evolution of expectations and selection between alternative equilibria, with implications for business cycles, asset price volatility, and policy. This book provides an authoritative treatment of this emerging field, developing the analytical techniques in detail and using them to synthesize and extend existing research.


The Legacy of Herbert Simon in Economic Analysis

The Legacy of Herbert Simon in Economic Analysis

Author: Peter E. Earl

Publisher: Edward Elgar Publishing

Published: 2001

Total Pages: 600

ISBN-13:

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Herbert A. Simon has been a leading contributor to cognitive psychology, computer science, public administration, philosophy and statistics, and is the winner of the 1978 Nobel Memorial Prize in economics. As this collection demonstrates, his impact on economics has been felt in areas as diverse as the theory of the firm and economic organization, consumer behaviour, law and economics, and environmental economics. Central to his work is the notion of bounded rationality - the mismatch between human decision-making capacities and the scale of the decision problems that people face, which results in satisficing rather than optimizing behaviour - and his belief that economic research should start from the study of actual behaviour rather than being based on convenient but unrealistic assumptions. Peter Earl's choice of articles shows both the kind of economics that emerges when Simon's philosophy is followed comprehensively, and what happens when neo-classical economists partially adopt his ideas.


Algorithmic and High-Frequency Trading

Algorithmic and High-Frequency Trading

Author: Álvaro Cartea

Publisher: Cambridge University Press

Published: 2015-08-06

Total Pages: 360

ISBN-13: 1316453650

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The design of trading algorithms requires sophisticated mathematical models backed up by reliable data. In this textbook, the authors develop models for algorithmic trading in contexts such as executing large orders, market making, targeting VWAP and other schedules, trading pairs or collection of assets, and executing in dark pools. These models are grounded on how the exchanges work, whether the algorithm is trading with better informed traders (adverse selection), and the type of information available to market participants at both ultra-high and low frequency. Algorithmic and High-Frequency Trading is the first book that combines sophisticated mathematical modelling, empirical facts and financial economics, taking the reader from basic ideas to cutting-edge research and practice. If you need to understand how modern electronic markets operate, what information provides a trading edge, and how other market participants may affect the profitability of the algorithms, then this is the book for you.


A Practical Guide to Forecasting Financial Market Volatility

A Practical Guide to Forecasting Financial Market Volatility

Author: Ser-Huang Poon

Publisher: John Wiley & Sons

Published: 2005-08-19

Total Pages: 236

ISBN-13: 0470856157

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Financial market volatility forecasting is one of today's most important areas of expertise for professionals and academics in investment, option pricing, and financial market regulation. While many books address financial market modelling, no single book is devoted primarily to the exploration of volatility forecasting and the practical use of forecasting models. A Practical Guide to Forecasting Financial Market Volatility provides practical guidance on this vital topic through an in-depth examination of a range of popular forecasting models. Details are provided on proven techniques for building volatility models, with guide-lines for actually using them in forecasting applications.


Implied Volatility Functions

Implied Volatility Functions

Author: Bernard Dumas

Publisher:

Published: 1996

Total Pages: 34

ISBN-13:

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Abstract: Black and Scholes (1973) implied volatilities tend to be systematically related to the option's exercise price and time to expiration. Derman and Kani (1994), Dupire (1994), and Rubinstein (1994) attribute this behavior to the fact that the Black-Scholes constant volatility assumption is violated in practice. These authors hypothesize that the volatility of the underlying asset's return is a deterministic function of the asset price and time and develop the deterministic volatility function (DVF) option valuation model, which has the potential of fitting the observed cross-section of option prices exactly. Using a sample of S & P 500 index options during the period June 1988 through December 1993, we evaluate the economic significance of the implied deterministic volatility function by examining the predictive and hedging performance of the DV option valuation model. We find that its performance is worse than that of an ad hoc Black-Scholes model with variable implied volatilities.