Recent Advances in Financial Engineering 2014

Recent Advances in Financial Engineering 2014

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Since 2004, the Tokyo Metropolitan University (TMU) has been conducting workshops that serve as a forum for academic researchers and practitioners to exchange ideas and developments in different fields of finance. This book is based on papers presented at the 2014 workshop held in Tokyo, on 6a€“7 November, 2014. The chapters address state-of-the-art techniques in mathematical finance and financial engineering. The authors share ideas and information on new methods and up-to-date results of their research in these fields. This book is a must-read for researchers, practitioners, and graduate students in the fields of mathematical finance, quantitative finance and financial engineering. Contents: Moment Properties of Probability Distributions Used in Stochastic Financial Models (J Stoyanov)An Equilibrium Approach to Indifference Pricing with Model Uncertainty (M H A Davis and D Yoshikawa)Volume Imbalance and Market Making (A Cartea, R. Donnelly and S Jaimungal)Optimal Short-Covering with Regime Switching (T K. Chung)Effects of Reversibility on Investment Timing and Quantity Under Asymmetric Information (X Cui and T. Shibata)Quadratic Gaussian Joint Pricing Model for Stocks and Bonds: Theory and Empirical Analysis (K Kikuchi)Option Pricing with Ambiguous Correlation and Fast Mean-reverting Volatilities (M H Leung and H Y Wong)Callable Stock Loans (C C Siu, S C P Yam and W Zhou)Cash Management and Control Band Policies for Spectrally One-sided LAcvy Processes (K Yamazaki)A Second-order Monotone Modification of the Sharpe Ratio (M Zhitlukhin) Readership: Graduate students, researchers and practitioners of financial engineering and mathematical finance. Key Features:Contains cutting-edge research in financial engineeringServes as a bridge between academic researchers and practitionersKeywords:Financial Engineering;Mathematical Finance;Money a Banking;Risk Management;Real Option;Corporate Finance;Computational Financeon the Kalman filter to estimate the latent state variable XI. We instead apply the unscented Kalman filter developed by [9] to actual financial market data. The first step of ... We calculate the prediction of X, using a€œsigma points.a€ For k = 1, ..., S, anbsp;...

Title:Recent Advances in Financial Engineering 2014
Author: Masaaki Kijima, Yukio Muromachi, Takashi Shibata
Publisher:World Scientific - 2016-02-29

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