European Parliament Library

Identifying Stock Market Bubbles, Modeling Illiquidity Premium and Bid-Ask Prices of Financial Securities, by Azar Karimov

Label
Identifying Stock Market Bubbles, Modeling Illiquidity Premium and Bid-Ask Prices of Financial Securities, by Azar Karimov
Language
eng
Bibliography note
Includes bibliographical references at the end of each chapters
resource.imageBitDepth
0
Literary Form
non fiction
Main title
Identifying Stock Market Bubbles
Medium
electronic resource
Nature of contents
dictionaries
Responsibility statement
by Azar Karimov
Series statement
Contributions to Management Science,, 1431-1941
Sub title
Modeling Illiquidity Premium and Bid-Ask Prices of Financial Securities
Summary
This book introduces readers to a new approach to identifying stock market bubbles by using the illiquidity premium, a parameter derived by employing conic finance theory. Further, it shows how to develop the closed form formulas of the bid and ask prices of European options by using Black-Scholes and Kou models. By using the derived formulas and sliding windows technique, the book explains how to numerically calculate illiquidity premiums. The methods introduced here will enable readers interested in risk management, portfolio optimization and hedging in real-time to identify when asset prices are in a bubble state and when that bubble bursts. Moreover, the techniques discussed will allow them to accurately recognize periods of exuberance and panic, and to measure how different strategies work during these phases with respect to calmer periods of market behavior. A brief history of financial bubbles and an outlook on future developments serve to round out the coverage
Table Of Contents
Introduction -- Review on Research Conducted -- Theory of Conic Finance -- Stock Prices Follow a Brownian Motion -- Stock Prices Follow a Double Exponential Jump-Diffusion Model -- Numerical Implementation and Parameter Estimation Under Kou Model -- Illiquidity Premium and Connection with Financial Bubbles -- Conclusion and Future Outlook.
Classification
Content
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