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Relevant bibliographies by topics / Portfolio management Brownian motion processes

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Academic literature on the topic 'Portfolio management Brownian motion processes'

Author: Grafiati

Published: 4 June 2021

Last updated: 3 February 2022

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Journal articles on the topic "Portfolio management Brownian motion processes"

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KEEL, SIMON, FLORIAN HERZOG, HANS P. GEERING, and LORENZ M. SCHUMANN. "OPTIMAL PORTFOLIO CONSTRUCTION UNDER PARTIAL INFORMATION FOR A BALANCED FUND." International Journal of Theoretical and Applied Finance 10, no. 06 (2007): 1015–42. http://dx.doi.org/10.1142/s0219024907004536.

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The model parameters in optimal asset allocation problems are often assumed to be deterministic. This is not a realistic assumption since most parameters are not known exactly and therefore have to be estimated. We consider investment opportunities which are modeled as local geometric Brownian motions whose drift terms may be stochastic and not necessarily measurable. The drift terms of the risky assets are assumed to be affine functions of some arbitrary factors. These factors themselves may be stochastic processes. They are modeled to have a mean-reverting behavior. We consider two types of

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HURD, T. R. "CREDIT RISK MODELING USING TIME-CHANGED BROWNIAN MOTION." International Journal of Theoretical and Applied Finance 12, no. 08 (2009): 1213–30. http://dx.doi.org/10.1142/s0219024909005646.

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Motivated by the interplay between structural and reduced form credit models, we propose to model the firm value process as a time-changed Brownian motion that may include jumps and stochastic volatility effects, and to study the first passage problem for such processes. We are lead to consider modifying the standard first passage problem for stochastic processes to capitalize on this time change structure and find that the distribution functions of such "first passage times of the second kind" are efficiently computable in a wide range of useful examples. Thus this new notion of first passage

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Zhao, Lin. "Portfolio Selection with Jumps under Regime Switching." International Journal of Stochastic Analysis 2010 (July 28, 2010): 1–22. http://dx.doi.org/10.1155/2010/697257.

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We investigate a continuous-time version of the mean-variance portfolio selection model with jumps under regime switching. The portfolio selection is proposed and analyzed for a market consisting of one bank account and multiple stocks. The random regime switching is assumed to be independent of the underlying Brownian motion and jump processes. A Markov chain modulated diffusion formulation is employed to model the problem.

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Browne, Sid, and Ward Whitt. "Portfolio choice and the Bayesian Kelly criterion." Advances in Applied Probability 28, no. 04 (1996): 1145–76. http://dx.doi.org/10.1017/s0001867800027592.

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We derive optimal gambling and investment policies for cases in which the underlying stochastic process has parameter values that are unobserved random variables. For the objective of maximizing logarithmic utility when the underlying stochastic process is a simple random walk in a random environment, we show that a state-dependent control is optimal, which is a generalization of the celebrated Kelly strategy: the optimal strategy is to bet a fraction of current wealth equal to a linear function of the posterior mean increment. To approximate more general stochastic processes, we consider a co

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Browne, Sid, and Ward Whitt. "Portfolio choice and the Bayesian Kelly criterion." Advances in Applied Probability 28, no. 4 (1996): 1145–76. http://dx.doi.org/10.2307/1428168.

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We derive optimal gambling and investment policies for cases in which the underlying stochastic process has parameter values that are unobserved random variables. For the objective of maximizing logarithmic utility when the underlying stochastic process is a simple random walk in a random environment, we show that a state-dependent control is optimal, which is a generalization of the celebrated Kelly strategy: the optimal strategy is to bet a fraction of current wealth equal to a linear function of the posterior mean increment. To approximate more general stochastic processes, we consider a co

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BENTH, FRED ESPEN, KENNETH HVISTENDAHL KARLSEN, and KRISTIN REIKVAM. "A NOTE ON PORTFOLIO MANAGEMENT UNDER NON-GAUSSIAN LOGRETURNS." International Journal of Theoretical and Applied Finance 04, no. 05 (2001): 711–31. http://dx.doi.org/10.1142/s0219024901001206.

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We calculate numerically the optimal allocation and consumption strategies for Merton's optimal portfolio management problem when the risky asset is modelled by a geometric normal inverse Gaussian Lévy process. We compare the computed strategies to the ones given by the standard asset model of geometric Brownian motion. To have realistic parameters in our studies, we choose Norsk Hydro quoted on the New York Stock Exchange as the risky asset. We find that an investor believing in the normal inverse Gaussian model puts a greater fraction of wealth into the risky asset. We also investigate the l

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Landriault, David, Bin Li, and Hongzhong Zhang. "On the Frequency of Drawdowns for Brownian Motion Processes." Journal of Applied Probability 52, no. 01 (2015): 191–208. http://dx.doi.org/10.1017/s0021900200012286.

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Drawdowns measuring the decline in value from the historical running maxima over a given period of time are considered as extremal events from the standpoint of risk management. To date, research on the topic has mainly focused on the side of severity by studying the first drawdown over a certain prespecified size. In this paper we extend the discussion by investigating the frequency of drawdowns and some of their inherent characteristics. We consider two types of drawdown time sequences depending on whether a historical running maximum is reset or not. For each type we study the frequency rat

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Landriault, David, Bin Li, and Hongzhong Zhang. "On the Frequency of Drawdowns for Brownian Motion Processes." Journal of Applied Probability 52, no. 1 (2015): 191–208. http://dx.doi.org/10.1239/jap/1429282615.

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Drawdowns measuring the decline in value from the historical running maxima over a given period of time are considered as extremal events from the standpoint of risk management. To date, research on the topic has mainly focused on the side of severity by studying the first drawdown over a certain prespecified size. In this paper we extend the discussion by investigating the frequency of drawdowns and some of their inherent characteristics. We consider two types of drawdown time sequences depending on whether a historical running maximum is reset or not. For each type we study the frequency rat

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Magin, Richard L., and Ervin K. Lenzi. "Slices of the Anomalous Phase Cube Depict Regions of Sub- and Super-Diffusion in the Fractional Diffusion Equation." Mathematics 9, no. 13 (2021): 1481. http://dx.doi.org/10.3390/math9131481.

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Fractional-order time and space derivatives are one way to augment the classical diffusion equation so that it accounts for the non-Gaussian processes often observed in heterogeneous materials. Two-dimensional phase diagrams—plots whose axes represent the fractional derivative order—typically display: (i) points corresponding to distinct diffusion propagators (Gaussian, Cauchy), (ii) lines along which specific stochastic models apply (Lévy process, subordinated Brownian motion), and (iii) regions of super- and sub-diffusion where the mean squared displacement grows faster or slower than a line

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Chang, Hao, Kai Chang, and Ji-mei Lu. "Portfolio Selection with Liability and Affine Interest Rate in the HARA Utility Framework." Abstract and Applied Analysis 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/312640.

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This paper studied an asset and liability management problem with stochastic interest rate, where interest rate is assumed to be governed by an affine interest rate model, while liability process is driven by the drifted Brownian motion. The investors wish to look for an optimal investment strategy to maximize the expected utility of the terminal surplus under hyperbolic absolute risk aversion (HARA) utility function, which consists of power utility, exponential utility, and logarithm utility as special cases. By applying dynamic programming principle and Legendre transform, the explicit solut

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Dissertations / Theses on the topic "Portfolio management Brownian motion processes"

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Nouri, Suhila Lynn. "Expected maximum drawdowns under constant and stochastic volatility." Link to electronic thesis, 2006. http://www.wpi.edu/Pubs/ETD/Available/etd-050406-151319/.

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Walljee, Raabia. "The Levy-LIBOR model with default risk." Thesis, Stellenbosch : Stellenbosch University, 2015. http://hdl.handle.net/10019.1/96957.

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Thesis (MSc)--Stellenbosch University, 2015<br>ENGLISH ABSTRACT : In recent years, the use of Lévy processes as a modelling tool has come to be viewed more favourably than the use of the classical Brownian motion setup. The reason for this is that these processes provide more flexibility and also capture more of the ’real world’ dynamics of the model. Hence the use of Lévy processes for financial modelling is a motivating factor behind this research presentation. As a starting point a framework for the LIBOR market model with dynamics driven by a Lévy process instead of the classical Brownian

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Kimura, Herbert. "A precificação de opções para processos de mistura de brownianos." Universidade de São Paulo, 1998. http://www.teses.usp.br/teses/disponiveis/45/45133/tde-14042015-235109/.

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O estudo apresenta um modelo de precificação de derivativos financeiros baseado em processos de mistura de movimentos brownianos. A partir de uma modelagem probabilística, são apresentados ajustes ao modelo tradicional de Black-Scholes-Merton para contemplar situações em que o retorno do ativo-objeto não segue uma distribuição normal. O trabalho discute ainda um mecanismo de estimação de parâmetros da mistura de normais. O resultado da pesquisa possibilita a análise de preço de opções em situações mais gerais.<br>The study presents a model for pricing financial derivatives based on a mixture o

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Deschatre, Thomas. "Dependence modeling between continuous time stochastic processes : an application to electricity markets modeling and risk management." Thesis, Paris Sciences et Lettres (ComUE), 2017. http://www.theses.fr/2017PSLED034/document.

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Cette thèse traite de problèmes de dépendance entre processus stochastiques en temps continu. Ces résultats sont appliqués à la modélisation et à la gestion des risques des marchés de l'électricité.Dans une première partie, de nouvelles copules sont établies pour modéliser la dépendance entre deux mouvements Browniens et contrôler la distribution de leur différence. On montre que la classe des copules admissibles pour les Browniens contient des copules asymétriques. Avec ces copules, la fonction de survie de la différence des deux Browniens est plus élevée dans sa partie positive qu'avec une d

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Bukhari, Abdulwahab Abdullatif. "Optimization of production allocation under price uncertainty : relating price model assumptions to decisions." Thesis, 2011. http://hdl.handle.net/2152/ETD-UT-2011-08-3780.

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Allocating production volumes across a portfolio of producing assets is a complex optimization problem. Each producing asset possesses different technical attributes (e.g. crude type), facility constraints, and costs. In addition, there are corporate objectives and constraints (e.g. contract delivery requirements). While complex, such a problem can be specified and solved using conventional deterministic optimization methods. However, there is often uncertainty in many of the inputs, and in these cases the appropriate approach is neither obvious nor straightforward. One of the major uncertaint

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Book chapters on the topic "Portfolio management Brownian motion processes"

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Ferreira, M. A. M., and José António Filipe. "Diffusion and Brownian Motion Processes in Modeling the Costs of Supporting Non-autonomous Pension Funds." In Contributions to Management Science. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-67020-7_5.

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Aïıt-Sahalia, Yacine, and Jean Jacod. "Is Brownian Motion Really Necessary?" In High-Frequency Financial Econometrics. Princeton University Press, 2014. http://dx.doi.org/10.23943/princeton/9780691161433.003.0013.

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The mathematical treatment of models relying on pure jump processes is quite different from the treatment of models where a Brownian motion is present. For instance, risk management procedures, derivative pricing and portfolio optimization are all significantly altered, so there is interest from the mathematical finance side in finding out which model is more likely to have generated the data. This chapter provides explicit testing procedures to decide whether the Brownian motion is necessary to model the observed path, or whether the process is entirely driven by its jumps. The structural assumption is the same as in the previous two chapters, with the underlying process X being a one-dimensional Itô semimartingale, since in the multi-dimensional case we can again perform the test on each component separately.

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Arutyunov, A. L. "Mathematical Methods and Models of Optimization and Control in the Formation of a Bonds Portfolio in the Derivatives Market." In Theory and Practice of Institutional Reforms in Russia: Collection of Scientific Works. Issue 49. CEMI Russian Academy of Sciences, 2020. http://dx.doi.org/10.33276/978-5-8211-0785-5-101-119.

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The article presents a set of methods and models of the mathematical foundations of management based on the basic concepts of functional analysis and generalized functions, as well as martingale methods in boundary crossing problems by Brownian motion, aimed at studying and studying optimization processes in managing the effectiveness of the stock and bond portfolio on the valuable market securities (derivatives).

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Özel, Gamze. "Stochastic Processes for the Risk Management." In Risk and Contingency Management. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-3932-2.ch010.

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The financial markets use stochastic models to represent the seemingly random behavior of assets such as stocks, commodities, relative currency prices such as the price of one currency compared to that of another, such as the price of US Dollar compared to that of the Euro, and interest rates. These models are then used by quantitative analysts to value options on stock prices, bond prices, and on interest rates. This chapter gives an overview of the stochastic models and methods used in financial risk management. Given the random nature of future events on financial markets, the field of stochastic processes obviously plays an important role in quantitative risk management. Random walk, Brownian motion and geometric Brownian motion processes in risk management are explained. Simulations of these processes are provided with some software codes.

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Özel, Gamze. "Stochastic Processes for the Risk Management." In Handbook of Research on Behavioral Finance and Investment Strategies. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-7484-4.ch011.

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The financial markets use stochastic models to represent the seemingly random behavior of assets such as stocks, commodities, relative currency prices such as the price of one currency compared to that of another, such as the price of US Dollar compared to that of the Euro, and interest rates. These models are then used by quantitative analysts to value options on stock prices, bond prices, and on interest rates. This chapter gives an overview of the stochastic models and methods used in financial risk management. Given the random nature of future events on financial markets, the field of stochastic processes obviously plays an important role in quantitative risk management. Random walk, Brownian motion and geometric Brownian motion processes in risk management are explained. Simulations of these processes are provided with some software codes.

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Nagarsheth, Shaival Hemant, and Shambhu Nath Sharma. "Statistics of an Appealing Class of Random Processes." In Advances in Data Mining and Database Management. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-4706-9.ch010.

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The white noise process, the Ornstein-Uhlenbeck process, and coloured noise process are salient noise processes to model the effect of random perturbations. In this chapter, the statistical properties, the master's equations for the Brownian noise process, coloured noise process, and the OU process are summarized. The results associated with the white noise process would be derived as the special cases of the Brownian and the OU noise processes. This chapter also formalizes stochastic differential rules for the Brownian motion and the OU process-driven vector stochastic differential systems in detail. Moreover, the master equations, especially for the coloured noise-driven stochastic differential system as well as the OU noise process-driven, are recast in the operator form involving the drift and modified diffusion operators involving an additional correction term to the standard diffusion operator. The results summarized in this chapter will be useful for modelling a random walk in stochastic systems.

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Guhathakurta, Kousik, Sharad Nath Bhattacharya, Santo Banerjee, and Basabi Bhattacharya. "Nonlinear Correlation of Stock and Commodity Indices in Emerging and Developed Market." In Chaos and Complexity Theory for Management. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-2509-9.ch004.

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The interrelationship between stock and commodity markets has been an issue of interest for both the academia and practitioners in the field of investment and wealth management. Traditionally, commodity has been a popular avenue for diversification in a mixed portfolio. However, this works well as long as there is little or no correlation between the two markets. This chapter presents an empirical investigation of the daily movement of stock and commodity index of two different countries to throw some light on the interrelationship between stock and commodity market. The uniqueness of this study lies in the choice of markets as also the methodology. The authors have chosen a developed market, viz., the US market, and an emerging market, viz., the Indian market. This study uses the major stock and commodity indices respectively for both countries for a period of three years. For analysis the authors have used the tools from nonlinear dynamics like recurrence analysis, power spectrum analysis, and delay based cross-correlation function. The investigation revealed that the dynamics of the time path of daily movement of Indian stock and commodity exchanges are much similar in nature while those of the US market are quite different. This chapter also models the respective time series using Geometric Brownian Motion and finds that the Indian data set performed much better than the US ones. This has a strong impact on strategy for designing mixed portfolios in Indian market.

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