Is a probabilistic modeling really useful in financial engineering?
A-t-on vraiment besoin d'un modèle probabiliste en ingénierie financière ?
Abstract
A new standpoint on financial time series, without the use of any mathematical model and of probabilistic tools, yields not only a rigorous approach of trends and volatility, but also efficient calculations which were already successfully applied in automatic control and in signal processing. It is based on a theorem due to P. Cartier and Y. Perrin, which was published in 1995. The above results are employed for sketching a dynamical portfolio and strategy management, without any global optimization technique. Numerous computer simulations are presented.
Domains
Quantitative Finance [q-fin] Computational Finance [q-fin.CP] Quantitative Finance [q-fin] Portfolio Management [q-fin.PM] Computer Science [cs] Computational Engineering, Finance, and Science [cs.CE] Computer Science [cs] Automatic Control Engineering Computer Science [cs] Signal and Image Processing Engineering Sciences [physics] Signal and Image processing Mathematics [math] Logic [math.LO] Mathematics [math] Statistics [math.ST] Statistics [stat] Statistics Theory [stat.TH] Statistics [stat] Methodology [stat.ME]
Origin : Files produced by the author(s)
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