Dynamic Portfolio Strategies: Quantitative Methods and Empirical
Rules for Incomplete Information investigates optimal investment
problems for stochastic financial market models. It is addressed to
academics and students who are interested in the mathematics of
finance, stochastic processes, and optimal control, and also to
practitioners in risk management and quantitative analysis who are
interested in new strategies and methods of stochastic
analysis.
While there are many works devoted to the solution of optimal
investment problems for various models, the focus of this book is
on analytical strategies based on "technical analysis" which are
model-free. The technical analysis of these strategies has a number
of characteristics. Two of the more important characteristics are:
(1) they require only historical data, and (2) typically they are
more widely used by traders than analysis based on stochastic
models. Hence it is the objective of this book to reduce the gap
between model-free strategies and strategies that are "optimal" for
stochastic models. We hope that researchers, students and
practitioners will be interested in some of the new empirically
based methods of "technical analysis" strategies suggested in this
book and evaluated via stochastic market models.
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