Recovering the Probability Density Function of Asset Prices Using GARCH as Diffusion Approximations
Title | Recovering the Probability Density Function of Asset Prices Using GARCH as Diffusion Approximations PDF eBook |
Author | Fabio Fornari |
Publisher | |
Pages | 52 |
Release | 2001 |
Genre | Investment analysis |
ISBN |
Economic Foundation of Asset Price Processes
Title | Economic Foundation of Asset Price Processes PDF eBook |
Author | Erik Paul Lüders |
Publisher | Springer Science & Business Media |
Pages | 127 |
Release | 2012-12-06 |
Genre | Business & Economics |
ISBN | 379082660X |
In this book the relation between the characteristics of investors' preferences and expectations and equilibrium asset price processes are analysed. It is shown that declining elasticity of the pricing kernel can lead to positive serial correlation of short term asset returns and negative serial correlation of long term returns. Analytical asset price processes are also derived. In contrast to the widely used "empirical" time-series models these processes do not lack a sound economic foundation. Moreover, in contrast to the popular Ornstein Uhlenbeck process and the Constant Elasticity of Variance model the proposed stochastic processes are consistent with a classical representative investor economy.
Asset Price Dynamics, Volatility, and Prediction
Title | Asset Price Dynamics, Volatility, and Prediction PDF eBook |
Author | Stephen J. Taylor |
Publisher | Princeton University Press |
Pages | 544 |
Release | 2011-02-11 |
Genre | Business & Economics |
ISBN | 1400839254 |
This book shows how current and recent market prices convey information about the probability distributions that govern future prices. Moving beyond purely theoretical models, Stephen Taylor applies methods supported by empirical research of equity and foreign exchange markets to show how daily and more frequent asset prices, and the prices of option contracts, can be used to construct and assess predictions about future prices, their volatility, and their probability distributions. Stephen Taylor provides a comprehensive introduction to the dynamic behavior of asset prices, relying on finance theory and statistical evidence. He uses stochastic processes to define mathematical models for price dynamics, but with less mathematics than in alternative texts. The key topics covered include random walk tests, trading rules, ARCH models, stochastic volatility models, high-frequency datasets, and the information that option prices imply about volatility and distributions. Asset Price Dynamics, Volatility, and Prediction is ideal for students of economics, finance, and mathematics who are studying financial econometrics, and will enable researchers to identify and apply appropriate models and methods. It will likewise be a valuable resource for quantitative analysts, fund managers, risk managers, and investors who seek realistic expectations about future asset prices and the risks to which they are exposed.
Handbook of Financial Econometrics
Title | Handbook of Financial Econometrics PDF eBook |
Author | Yacine Ait-Sahalia |
Publisher | Elsevier |
Pages | 809 |
Release | 2009-10-19 |
Genre | Business & Economics |
ISBN | 0080929842 |
This collection of original articles—8 years in the making—shines a bright light on recent advances in financial econometrics. From a survey of mathematical and statistical tools for understanding nonlinear Markov processes to an exploration of the time-series evolution of the risk-return tradeoff for stock market investment, noted scholars Yacine Aït-Sahalia and Lars Peter Hansen benchmark the current state of knowledge while contributors build a framework for its growth. Whether in the presence of statistical uncertainty or the proven advantages and limitations of value at risk models, readers will discover that they can set few constraints on the value of this long-awaited volume. Presents a broad survey of current research—from local characterizations of the Markov process dynamics to financial market trading activity Contributors include Nobel Laureate Robert Engle and leading econometricians Offers a clarity of method and explanation unavailable in other financial econometrics collections
Stochastic Volatility in Financial Markets
Title | Stochastic Volatility in Financial Markets PDF eBook |
Author | Antonio Mele |
Publisher | Springer Science & Business Media |
Pages | 156 |
Release | 2012-12-06 |
Genre | Business & Economics |
ISBN | 1461545331 |
Stochastic Volatility in Financial Markets presents advanced topics in financial econometrics and theoretical finance, and is divided into three main parts. The first part aims at documenting an empirical regularity of financial price changes: the occurrence of sudden and persistent changes of financial markets volatility. This phenomenon, technically termed `stochastic volatility', or `conditional heteroskedasticity', has been well known for at least 20 years; in this part, further, useful theoretical properties of conditionally heteroskedastic models are uncovered. The second part goes beyond the statistical aspects of stochastic volatility models: it constructs and uses new fully articulated, theoretically-sounded financial asset pricing models that allow for the presence of conditional heteroskedasticity. The third part shows how the inclusion of the statistical aspects of stochastic volatility in a rigorous economic scheme can be faced from an empirical standpoint.
Journal of Empirical Finance
Title | Journal of Empirical Finance PDF eBook |
Author | |
Publisher | |
Pages | 1350 |
Release | 2000 |
Genre | Econometrics |
ISBN |
Integrated Supply Chain Planning in Chemical Industry
Title | Integrated Supply Chain Planning in Chemical Industry PDF eBook |
Author | Thomas Kirschstein |
Publisher | Springer |
Pages | 263 |
Release | 2015-01-07 |
Genre | Business & Economics |
ISBN | 3658084332 |
Thomas Kirschstein provides an overview on methods and approaches for planning and optimizing large-scale chemical production networks. The focus is on an integrated modelling of chemical production processes, logistical processes as well as environmental effects. Therefore, a hybrid simulation framework is designed taking into account time series models for modelling chemical production processes, linear optimization models for describing logistical processes as well as stochastic processes for modelling environmental effects.