Download or read book Application of Stochastic Optimal Control to Financial Market Debt Crises written by Jerome L. Stein and published by . This book was released on 2009 with total page 29 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Stochastic Optimal Control and the U S Financial Debt Crisis written by Jerome L. Stein and published by Springer Science & Business Media. This book was released on 2012-03-30 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic Optimal Control (SOC)—a mathematical theory concerned with minimizing a cost (or maximizing a payout) pertaining to a controlled dynamic process under uncertainty—has proven incredibly helpful to understanding and predicting debt crises and evaluating proposed financial regulation and risk management. Stochastic Optimal Control and the U.S. Financial Debt Crisis analyzes SOC in relation to the 2008 U.S. financial crisis, and offers a detailed framework depicting why such a methodology is best suited for reducing financial risk and addressing key regulatory issues. Topics discussed include the inadequacies of the current approaches underlying financial regulations, the use of SOC to explain debt crises and superiority over existing approaches to regulation, and the domestic and international applications of SOC to financial crises. Principles in this book will appeal to economists, mathematicians, and researchers interested in the U.S. financial debt crisis and optimal risk management.
Download or read book Applicaton of Stochastic Optimal Control to Financial Market Debt Crises written by Jerome L. Stein and published by . This book was released on 2013 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: This interdisciplinary paper explains how mathematical techniques of stochastic optimal control can be applied to the recent subprime mortgage crisis. Why did the financial markets fail to anticipate the recent debt crisis, despite the large literature in mathematical finance concerning optimal portfolio allocation and stopping rules? The uncertainty concerns the capital gain, the return on capital and the interest rate. An optimal debt ratio is derived where the drift is probabilistic but subject to economic constraints. The crises occurred because the market neglected to consider pertinent economic constraints in the dynamic stochastic optimization. The first constraint is that the firm should not be viewed in isolation. The optimizer should be the entire industry. The second economic constraint concerns the modeling of the drift of the price of the asset. The vulnerability of the borrowing firm to shocks from the capital gain, the return to capital or the interest rate, does not depend upon the actual debt/net worth per se. Instead it increases in proportion to the difference between the Actual and Optimal debt ratio, called the excess debt. A general measure of excess debt is derived and I show that it is an early warning signal of the recent crisis.
Download or read book Stochastic Optimal Control International Finance and Debt Crises written by Jerome L. Stein and published by Oxford University Press, USA. This book was released on 2006-04-06 with total page 305 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the interaction between equilibrium real exchange rates, optimal external debt, endogenous optimal growth and current account balances, in a world of uncertainty. The theoretical parts result from interdisciplinary research between economics and applied mathematics. From the economic theory and the mathematics of stochastic optimal control the author derives benchmarks for the optimal debt and equilibrium real exchange rate in an environment where both thereturn on capital and the real rate of interest are stochastic variables. The theoretically derived equilibrium real exchange rate - the "natural real exchange rate" NATREX - is where the real exchange rate is heading. These benchmarks are applied to answer the following questions.* What is a theoretically based empirical measure of a "misaligned" exchange rate that increases the probability of a significant depreciation or a currency crisis?* What is a theoretically based empirical measure of an "excess" debt that increases the probability of or a debt crisis?* What is the interaction between an excess debt and a misaligned exchange rate?The theory is applied to evaluate the Euro exchange rate, the exchange rates of the transition economies, the sustainability of U.S. current account deficits, and derives warning signals of the Asian crises and debt crises in emerging markets.
Download or read book Applications of Stochastic Optimal Control to Economics and Finance written by Salvatore Federico and published by . This book was released on 2020-06-23 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a world dominated by uncertainty, modeling and understanding the optimal behavior of agents is of the utmost importance. Many problems in economics, finance, and actuarial science naturally require decision makers to undertake choices in stochastic environments. Examples include optimal individual consumption and retirement choices, optimal management of portfolios and risk, hedging, optimal timing issues in pricing American options, and investment decisions. Stochastic control theory provides the methods and results to tackle all such problems. This book is a collection of the papers published in the Special Issue "Applications of Stochastic Optimal Control to Economics and Finance", which appeared in the open access journal Risks in 2019. It contains seven peer-reviewed papers dealing with stochastic control models motivated by important questions in economics and finance. Each model is rigorously mathematically funded and treated, and the numerical methods are employed to derive the optimal solution. The topics of the book's chapters range from optimal public debt management to optimal reinsurance, real options in energy markets, and optimal portfolio choice in partial and complete information settings. From a mathematical point of view, techniques and arguments of dynamic programming theory, filtering theory, optimal stopping, one-dimensional diffusions and multi-dimensional jump processes are used.
Download or read book Stochastic Optimal Control Modeling of Debt Crises written by and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Stochastic Optimal Control Modeling of Debt Crises written by Jerome L. Stein and published by . This book was released on 2003 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Stochastic Optimal Control International Finance and Debt Crises written by Jerome L. Stein and published by OUP Oxford. This book was released on 2006-04-06 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the interaction between equilibrium real exchange rates, optimal external debt, endogenous optimal growth and current account balances, in a world of uncertainty. The theoretical parts result from interdisciplinary research between economics and applied mathematics. From the economic theory and the mathematics of stochastic optimal control the author derives benchmarks for the optimal debt and equilibrium real exchange rate in an environment where both the return on capital and the real rate of interest are stochastic variables. The theoretically derived equilibrium real exchange rate - the "natural real exchange rate" NATREX - is where the real exchange rate is heading. These benchmarks are applied to answer the following questions. * What is a theoretically based empirical measure of a "misaligned" exchange rate that increases the probability of a significant depreciation or a currency crisis? * What is a theoretically based empirical measure of an "excess" debt that increases the probability of or a debt crisis? * What is the interaction between an excess debt and a misaligned exchange rate? The theory is applied to evaluate the Euro exchange rate, the exchange rates of the transition economies, the sustainability of U.S. current account deficits, and derives warning signals of the Asian crises and debt crises in emerging markets.
Download or read book A Stochastic Optimal Control Formulation of the Consumption debt Decision written by and published by Bib. Orton IICA / CATIE. This book was released on with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Stochastic Control written by Chris Myers and published by BoD – Books on Demand. This book was released on 2010-08-17 with total page 663 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty presents significant challenges in the reasoning about and controlling of complex dynamical systems. To address this challenge, numerous researchers are developing improved methods for stochastic analysis. This book presents a diverse collection of some of the latest research in this important area. In particular, this book gives an overview of some of the theoretical methods and tools for stochastic analysis, and it presents the applications of these methods to problems in systems theory, science, and economics.
Download or read book Stochastic Optimal Control International Finance Debt written by and published by . This book was released on 2002 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Continuous time Stochastic Control and Optimization with Financial Applications written by Huyên Pham and published by Springer Science & Business Media. This book was released on 2009-05-28 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic optimization problems arise in decision-making problems under uncertainty, and find various applications in economics and finance. On the other hand, problems in finance have recently led to new developments in the theory of stochastic control. This volume provides a systematic treatment of stochastic optimization problems applied to finance by presenting the different existing methods: dynamic programming, viscosity solutions, backward stochastic differential equations, and martingale duality methods. The theory is discussed in the context of recent developments in this field, with complete and detailed proofs, and is illustrated by means of concrete examples from the world of finance: portfolio allocation, option hedging, real options, optimal investment, etc. This book is directed towards graduate students and researchers in mathematical finance, and will also benefit applied mathematicians interested in financial applications and practitioners wishing to know more about the use of stochastic optimization methods in finance.
Download or read book A Tale of Two Debt Crises written by Jerome L. Stein and published by . This book was released on 2008 with total page 23 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Debt Risk and Liquidity in Futures Markets written by Barry Goss and published by Routledge. This book was released on 2007-09-17 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: The issues of developing country debt crises, increased volatility and risk, and the determination of market liquidity are high on the agendas of policy makers, market participants and researchers in the area of financial markets. These issues are also of major importance to regulators and exchange officials. This book contains a collection of eigh
Download or read book Mathematics of Finance written by George Yin and published by American Mathematical Soc.. This book was released on 2004 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contains papers based on talks given at the first AMS-IMS-SIAM Joint Summer Research Conference on Mathematics of Finance held at Snowbird. This book includes such topics as modeling, estimation, optimization, control, and risk assessment and management. It is suitable for students interested in mathematical finance.
Download or read book Optimal Stochastic Control Stochastic Target Problems and Backward SDE written by Nizar Touzi and published by Springer Science & Business Media. This book was released on 2012-09-27 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book collects some recent developments in stochastic control theory with applications to financial mathematics. We first address standard stochastic control problems from the viewpoint of the recently developed weak dynamic programming principle. A special emphasis is put on the regularity issues and, in particular, on the behavior of the value function near the boundary. We then provide a quick review of the main tools from viscosity solutions which allow to overcome all regularity problems. We next address the class of stochastic target problems which extends in a nontrivial way the standard stochastic control problems. Here the theory of viscosity solutions plays a crucial role in the derivation of the dynamic programming equation as the infinitesimal counterpart of the corresponding geometric dynamic programming equation. The various developments of this theory have been stimulated by applications in finance and by relevant connections with geometric flows. Namely, the second order extension was motivated by illiquidity modeling, and the controlled loss version was introduced following the problem of quantile hedging. The third part specializes to an overview of Backward stochastic differential equations, and their extensions to the quadratic case.
Download or read book Decision Making under Uncertainty in Financial Markets written by Jonas Ekblom and published by Linköping University Electronic Press. This book was released on 2018-09-13 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis addresses the topic of decision making under uncertainty, with particular focus on financial markets. The aim of this research is to support improved decisions in practice, and related to this, to advance our understanding of financial markets. Stochastic optimization provides the tools to determine optimal decisions in uncertain environments, and the optimality conditions of these models produce insights into how financial markets work. To be more concrete, a great deal of financial theory is based on optimality conditions derived from stochastic optimization models. Therefore, an important part of the development of financial theory is to study stochastic optimization models that step-by-step better capture the essence of reality. This is the motivation behind the focus of this thesis, which is to study methods that in relation to prevailing models that underlie financial theory allow additional real-world complexities to be properly modeled. The overall purpose of this thesis is to develop and evaluate stochastic optimization models that support improved decisions under uncertainty on financial markets. The research into stochastic optimization in financial literature has traditionally focused on problem formulations that allow closed-form or `exact' numerical solutions; typically through the application of dynamic programming or optimal control. The focus in this thesis is on two other optimization methods, namely stochastic programming and approximate dynamic programming, which open up opportunities to study new classes of financial problems. More specifically, these optimization methods allow additional and important aspects of many real-world problems to be captured. This thesis contributes with several insights that are relevant for both financial and stochastic optimization literature. First, we show that the modeling of several real-world aspects traditionally not considered in the literature are important components in a model which supports corporate hedging decisions. Specifically, we document the importance of modeling term premia, a rich asset universe and transaction costs. Secondly, we provide two methodological contributions to the stochastic programming literature by: (i) highlighting the challenges of realizing improved decisions through more stages in stochastic programming models; and (ii) developing an importance sampling method that can be used to produce high solution quality with few scenarios. Finally, we design an approximate dynamic programming model that gives close to optimal solutions to the classic, and thus far unsolved, portfolio choice problem with constant relative risk aversion preferences and transaction costs, given many risky assets and a large number of time periods.
