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Automatic Control, IEEE Transactions on

Issue 3 • Date March 2004

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Displaying Results 1 - 22 of 22
  • Table of contents

    Publication Year: 2004 , Page(s): c1
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  • IEEE Transactions on Automatic Control publication information

    Publication Year: 2004 , Page(s): c2
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  • Guest Editorial Special Issue on Stochastic Control Methods in Financial Engineering

    Publication Year: 2004 , Page(s): 321 - 323
    Cited by:  Papers (3)
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  • Scanning the issue

    Publication Year: 2004 , Page(s): 324 - 325
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  • Optimal portfolio and consumption policies subject to Rishel's important jump events model: computational methods

    Publication Year: 2004 , Page(s): 326 - 337
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (760 KB) |  | HTML iconHTML  

    At important events or announcements, there can be large changes in the value of financial portfolios. Events and their corresponding jumps can occur at random or scheduled times. However, the amplitude of the response in either case can be unpredictable or random. While the volatility of portfolios is often modeled by continuous Brownian motion processes, discontinuous jump processes are more appropriate for modeling the response to important external events that significantly affect the prices of financial assets. Discontinuous jump processes are modeled by compound Poisson processes for random events or by quasi-deterministic jump processes for scheduled events. In both cases, the responses are randomly distributed and are modeled in a stochastic differential equation formulation. The objective is the maximal, expected total discounted utility of terminal wealth and instantaneous consumption. This paper was motivated by a paper by Rishel (1999) concerning portfolio optimization when prices are dependent on external events. However, the model has been significantly generalized for more realistic computational considerations with constraints and parameter values. The problem is illustrated for a canonical risk-adverse power utility model. However, the usual explicit canonical solution is not strictly valid. Fortunately, iterations about the canonical solution result in computationally feasible approximations. View full abstract»

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  • Estimating stochastic volatility via filtering for the micromovement of asset prices

    Publication Year: 2004 , Page(s): 338 - 348
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (544 KB) |  | HTML iconHTML  

    Under the general framework of a previous paper, a unified approach via filtering is developed to estimate stochastic volatility for micromovement models. The key feature of the models is that they can be transformed as filtering problems with counting process observations. In order to obtain trade-by-trade, real-time Bayes estimates of stochastic volatility, the Markov chain approximation method is applied to the filtering equation to construct a consistent recursive algorithm, which computes the joint posterior. To illustrate the approach, a recursive algorithm is constructed in detail for a jumping stochastic volatility micromovement model. Simulation results show that the Bayes estimates for stochastic volatilities capture the movement of volatility. Trade-by-trade stochastic volatility estimates for a Microsoft transaction data set are obtained and they provide strong affirmative evidence that volatility changes even more dramatically at trade-by-trade level. View full abstract»

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  • Markowitz's mean-variance portfolio selection with regime switching: from discrete-time models to their continuous-time limits

    Publication Year: 2004 , Page(s): 349 - 360
    Cited by:  Papers (58)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (336 KB) |  | HTML iconHTML  

    We study a discrete-time version of Markowitz's mean-variance portfolio selection problem where the market parameters depend on the market mode (regime) that jumps among a finite number of states. The random regime switching is delineated by a finite-state Markov chain, based on which a discrete-time Markov modulated portfolio selection model is presented. Such models either arise from multiperiod portfolio selections or result from numerical solution of continuous-time problems. The natural connections between discrete-time models and their continuous-time counterpart are revealed. Since the Markov chain frequently has a large state space, to reduce the complexity, an aggregated process with smaller state-space is introduced and the underlying portfolio selection is formulated as a two-time-scale problem. We prove that the process of interest yields a switching diffusion limit using weak convergence methods. Next, based on the optimal control of the limit process obtained from our recent work, we devise portfolio selection strategies for the original problem and demonstrate their asymptotic optimality. View full abstract»

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  • Modeling of the defaultable term structure: conditionally Markov approach

    Publication Year: 2004 , Page(s): 361 - 373
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (336 KB)  

    This paper provides a detailed technical description of the Bielecki and Rutkowski approach to the Heath-Jarrow-Morton type modeling of defaultable term structure of interest rates with multiple ratings. Special emphasis is put on the arbitrage-free feature of the model, as well as on the explicit construction of the conditionally Markov process of credit migrations. View full abstract»

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  • Valuation of American options via basis functions

    Publication Year: 2004 , Page(s): 374 - 385
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (384 KB) |  | HTML iconHTML  

    After a brief review of recent developments in the pricing and hedging of American options, this paper modifies the basis function approach to adaptive control and neuro-dynamic programming, and applies it to develop: 1) nonparametric pricing formulas for actively traded American options and 2) simulation-based optimization strategies for complex over-the-counter options, whose optimal stopping problems are prohibitively difficult to solve numerically by standard backward induction algorithms because of the curse of dimensionality. An important issue in this approach is the choice of basis functions, for which some guidelines and their underlying theory are provided. View full abstract»

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  • Pathwise optimality for benchmark tracking

    Publication Year: 2004 , Page(s): 386 - 395
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (272 KB) |  | HTML iconHTML  

    We consider the problem of investing in a portfolio in order to track or "beat" a given benchmark. We study this problem from the point of view of almost sure/pathwise optimality. We first obtain a control that is optimal in the mean and this control is then shown to be also pathwise optimal. The standard Merton model leads to lognormality of the value process so that it does not possess the required ergodic properties. We obtain ergodicity by transforming the process so that it remains bounded thereby using a method that can be related to a random time change. We furthermore describe a general approach to solve the Hamilton-Jacobi-Bellman equation corresponding to the given problem setup. View full abstract»

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  • Mean-variance hedging and stochastic control: beyond the Brownian setting

    Publication Year: 2004 , Page(s): 396 - 408
    Cited by:  Papers (11)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (336 KB) |  | HTML iconHTML  

    We show for continuous semimartingales in a general filtration how the mean-variance hedging problem can be treated as a linear-quadratic stochastic control problem. The adjoint equations lead to backward stochastic differential equations for the three coefficients of the quadratic value process, and we give necessary and sufficient conditions for the solvability of these generalized stochastic Riccati equations. Motivated from mathematical finance, this paper takes a first step toward linear-quadratic stochastic control in more general than Brownian settings. View full abstract»

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  • Stochastic target hitting time and the problem of early retirement

    Publication Year: 2004 , Page(s): 409 - 419
    Cited by:  Papers (12)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (360 KB) |  | HTML iconHTML  

    We consider a problem of optimal control of a "retirement investment fund" over a finite time horizon with a target hitting time criteria. That is, we wish to decide, at each stage, what percentage of the current retirement fund to allocate into the limited number of investment options so that a decision maker can maximize the probability that his or her wealth exceeds a target x prior to his or her retirement. We use Markov decision processes with probability criteria to model this problem and give an example based on data from certain options available in an Australian retirement fund. View full abstract»

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  • Risk-sensitive ICAPM with application to fixed-income management

    Publication Year: 2004 , Page(s): 420 - 432
    Cited by:  Papers (14)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (328 KB) |  | HTML iconHTML  

    This paper presents an application of risk-sensitive control theory in financial decision making. A variation of Merton's continuous-time intertemporal capital asset pricing model is developed where the infinite horizon objective is to maximize the portfolio's risk adjusted growth rate. The resulting model is tractable and thus provides economic insight about optimal trading strategies as well as the fact that the strategy of 100% cash is not necessarily the least risky one. For fixed-income applications we utilize the concept of rolling-horizon bonds, which are stochastic process models of certain mutual funds of zero coupon bonds. We show by numerical example that the optimal proportion of one's wealth to hold in an asset is given by a simple affine function of economic factors such as interest rates of various maturities. View full abstract»

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  • Remarks on the pricing of contingent claims under constraints

    Publication Year: 2004 , Page(s): 433 - 441
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (240 KB) |  | HTML iconHTML  

    The study of the pricing of contingent claims under constraints leads, in the case of stocks obeying lognormal distributions, to an interesting analytical result. Namely, the price satisfies the Black Scholes equation with a different initial condition. We give a mostly analytical treatment of this result, using the probabilistic interpretation of the Cauchy problem, with nonsmooth initial conditions. View full abstract»

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  • Portfolio optimization with Markov-modulated stock prices and interest rates

    Publication Year: 2004 , Page(s): 442 - 447
    Cited by:  Papers (24)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (248 KB) |  | HTML iconHTML  

    A financial market with one bond and one stock is considered where the risk free interest rate, the appreciation rate of the stock and the volatility of the stock depend on an external finite state Markov chain. We investigate the problem of maximizing the expected utility from terminal wealth and solve it by stochastic control methods for different utility functions. Due to explicit solutions it is possible to compare the value function of the problem to one where we have constant (average) market data. The case of benchmark optimization is also considered. View full abstract»

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  • Risk control over bankruptcy in dynamic portfolio selection: a generalized mean-variance formulation

    Publication Year: 2004 , Page(s): 447 - 457
    Cited by:  Papers (27)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (464 KB)  

    For an investor to claim his wealth resulted from his multiperiod portfolio policy, he has to sustain a possibility of bankruptcy before reaching the end of an investment horizon. Risk control over bankruptcy is thus an indispensable ingredient of optimal dynamic portfolio selection. We propose in this note a generalized mean-variance model via which an optimal investment policy can be generated to help investors not only achieve an optimal return in the sense of a mean-variance tradeoff, but also have a good risk control over bankruptcy. One key difficulty in solving the proposed generalized mean-variance model is the nonseparability in the associated stochastic control problem in the sense of dynamic programming. A solution scheme using embedding is developed in this note to overcome this difficulty and to obtain an analytical optimal portfolio policy. View full abstract»

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  • Risk-sensitive portfolio optimization with completely and partially observed factors

    Publication Year: 2004 , Page(s): 457 - 464
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (392 KB) |  | HTML iconHTML  

    In this note, optimal portfolio maximizing the long run risk-sensitized growth rate of the capital process in the case when the dynamics of the asset prices depend on some economical factors, which are completely or partially observed, using a discounted cost approach is shown. View full abstract»

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  • System Identification: Linear vs. Nonlinear

    Publication Year: 2004 , Page(s): 465
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  • Quality without Compromise [advertisement]

    Publication Year: 2004 , Page(s): 467
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  • IEEE Member Digital Library [advertisement]

    Publication Year: 2004 , Page(s): 468
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  • IEEE Control Systems Society Information

    Publication Year: 2004 , Page(s): c3
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  • Blank page [back cover]

    Publication Year: 2004 , Page(s): c4
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Aims & Scope

In the IEEE Transactions on Automatic Control, the IEEE Control Systems Society publishes high-quality papers on the theory, design, and applications of control engineering.  Two types of contributions are regularly considered

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
P. J. Antsaklis
Dept. Electrical Engineering
University of Notre Dame