Risk diversification is one of the dominant concerns for portfolio managers. Various portfolio constructions have been proposed to minimize the risk of the portfolio under some constrains including expected returns. We propose a portfolio construction method that incorporates the complex valued principal component analysis into the risk diversification portfolio construction. The proposed method is verified to outperform the conventional risk parity and risk diversification portfolio constructions.

Financial time series have been investigated to follow fat-tailed distributions. Further, an empirical probability distribution sometimes shows cut-off shapes on its tails. To describe this stylized fact, we incorporate the cut-off effect in superstatistics. Then we confirm that the presented stochastic model is capable of describing the statistical properties of real financial time series. In addition, we present an option pricing formula with respect to superstatistics.

In this paper various eccentric hole dynamics are presented in defect turbulence of the one-dimensional complex Ginzburg-Landau equation. Each hole shows coherent particlelike motion with nonconstant velocity. On the other hand, successive hole velocities without discriminating each hole exhibit anomalous intermittent motions being subject to multi-time-scale non-Gaussian statistics. An alternate non-Markov stochastic differential equation is proposed, by which all these observed statistical properties can be described successfully.

This paper presents a fractional generalized Cauchy process (FGCP) with an additive and a multiplicative Gaussian white noise for describing subordinated anomalous fluctuations. The FGCP displays intermittent dynamics during random time durations, whose analytical representation is given by the Itô stochastic integral. The associated probability density function is given by the Tsallis q-Gaussian distribution at the stationary state. The method of fractional Feynman-Kac formula shows that weak ergodicity breaking of the FGCP depends on the existence of the subordinator and/or the divergence of variance.

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