Computers and Operations Research
Stabilization and destabilization of hybrid systems of stochastic differential equations
Automatica (Journal of IFAC)
International Journal of Business Information Systems
Trading a mean-reverting asset: Buy low and sell high
Automatica (Journal of IFAC)
A generalized multi-period mean-variance portfolio optimization with Markov switching parameters
Automatica (Journal of IFAC)
Incorporating the Markov chain concept into fuzzy stochastic prediction of stock indexes
Applied Soft Computing
Computers and Operations Research
Randomly switching systems: models, analysis, and applications
CCDC'09 Proceedings of the 21st annual international conference on Chinese Control and Decision Conference
Journal of Computational and Applied Mathematics
On Maximizing CRRA Utility in Regime Switching Markets with Random Endowment
SIAM Journal on Control and Optimization
A trend-following strategy: Conditions for optimality
Automatica (Journal of IFAC)
Computers & Mathematics with Applications
Trend Following Trading under a Regime Switching Model
SIAM Journal on Financial Mathematics
Numerical methods for controlled regime-switching diffusions and regime-switching jump diffusions
Automatica (Journal of IFAC)
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Trading in stock markets consists of three major steps: select a stock, purchase a number of shares, and eventually sell them to make a profit. The timing to buy and sell is extremely crucial. A selling rule can be specified by two preselected levels: a target price and a stop-loss limit. This paper is concerned with an optimal selling rule based on the model characterized by a number of geometric Brownian motions coupled by a finite-state Markov chain. Such a policy can be obtained by solving a set of two-point boundary value differential equations. Moreover, the corresponding expected target period and probability of making money and that of losing money are derived. Analytic solutions are obtained in one- and two-dimensional cases. Finally, a numerical example is considered to demonstrate the effectiveness of our method.