TY - JOUR
T1 - Econophysics and fractional calculus
T2 - Einstein's evolution equation, the fractal market hypothesis, trend analysis and future price prediction
AU - Blackledge, Jonathan
AU - Kearney, Derek
AU - Lamphiere, Marc
AU - Rani, Raja
AU - Walsh, Paddy
N1 - Publisher Copyright:
© 2019 by the authors.
PY - 2019/11/1
Y1 - 2019/11/1
N2 - This paper examines a range of results that can be derived from Einstein's evolution equation focusing on the effect of introducing a Lévy distribution into the evolution equation. In this context, we examine the derivation (derived exclusively from the evolution equation) of the classical and fractional diffusion equations, the classical and generalised Kolmogorov-Feller equations, the evolution of self-affine stochastic fields through the fractional diffusion equation, the fractional Poisson equation (for the time independent case), and, a derivation of the Lyapunov exponent and volatility. In this way, we provide a collection of results (which includes the derivation of certain fractional partial differential equations) that are fundamental to the stochastic modelling associated with elastic scattering problems obtained under a unifying theme, i.e., Einstein's evolution equation. This includes an analysis of stochastic fields governed by a symmetric (zero-mean) Gaussian distribution, a Lévy distribution characterised by the Lévy index γ ∈ [0, 2] and the derivation of two impulse response functions for each case. The relationship between non-Gaussian distributions and fractional calculus is examined and applications to financial forecasting under the fractal market hypothesis considered, the reader being provided with example software functions (written in MATLAB) so that the results presented may be reproduced and/or further investigated.
AB - This paper examines a range of results that can be derived from Einstein's evolution equation focusing on the effect of introducing a Lévy distribution into the evolution equation. In this context, we examine the derivation (derived exclusively from the evolution equation) of the classical and fractional diffusion equations, the classical and generalised Kolmogorov-Feller equations, the evolution of self-affine stochastic fields through the fractional diffusion equation, the fractional Poisson equation (for the time independent case), and, a derivation of the Lyapunov exponent and volatility. In this way, we provide a collection of results (which includes the derivation of certain fractional partial differential equations) that are fundamental to the stochastic modelling associated with elastic scattering problems obtained under a unifying theme, i.e., Einstein's evolution equation. This includes an analysis of stochastic fields governed by a symmetric (zero-mean) Gaussian distribution, a Lévy distribution characterised by the Lévy index γ ∈ [0, 2] and the derivation of two impulse response functions for each case. The relationship between non-Gaussian distributions and fractional calculus is examined and applications to financial forecasting under the fractal market hypothesis considered, the reader being provided with example software functions (written in MATLAB) so that the results presented may be reproduced and/or further investigated.
KW - Diffusion equation
KW - Efficient market hypothesis
KW - Einstein's evolution equation
KW - Evolutionary computing
KW - Financial time series analysis
KW - Fractal market hypothesis
KW - Fractional diffusion equation
KW - Kolmogorov-Feller equation
KW - Random market hypothesis
KW - Self-affine stochastic fields
UR - http://www.scopus.com/inward/record.url?scp=85075375118&partnerID=8YFLogxK
U2 - 10.3390/math7111057
DO - 10.3390/math7111057
M3 - Article
SN - 2227-7390
VL - 7
JO - Mathematics
JF - Mathematics
IS - 11
M1 - 1057
ER -