Multifractal diffusion entropy analysis: Optimal bin width of probability histograms

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F14%3A00221493" target="_blank" >RIV/68407700:21340/14:00221493 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.sciencedirect.com/science/article/pii/S0378437114005755" target="_blank" >http://www.sciencedirect.com/science/article/pii/S0378437114005755</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.physa.2014.07.008" target="_blank" >10.1016/j.physa.2014.07.008</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Multifractal diffusion entropy analysis: Optimal bin width of probability histograms

Popis výsledku v původním jazyce

In the framework of Multifractal Diffusion Entropy Analysis we propose a method for choosing an optimal bin-width in histograms generated from underlying probability distributions of interest. The method presented uses techniques of Rényi?s entropy and the mean squared error analysis to discuss the conditions under which the error in the multifractal spectrum estimation is minimal. We illustrate the utility of our approach by focusing on a scaling behavior of financial time series. In particular, we analyze the S&P500 stock index as sampled at a daily rate in the time period 1950?2013. In order to demonstrate a strength of the method proposed we compare the multifractal ?-spectrum for various bin-widths and show the robustness of the method, especiallyfor large values of q. For such values, other methods in use, e.g., those based on moment estimation, tend to fail for heavy-tailed data or data with long correlations. Connection between the ?-spectrum and Rényi?s q parameter is also di

Název v anglickém jazyce

Multifractal diffusion entropy analysis: Optimal bin width of probability histograms

Popis výsledku anglicky

In the framework of Multifractal Diffusion Entropy Analysis we propose a method for choosing an optimal bin-width in histograms generated from underlying probability distributions of interest. The method presented uses techniques of Rényi?s entropy and the mean squared error analysis to discuss the conditions under which the error in the multifractal spectrum estimation is minimal. We illustrate the utility of our approach by focusing on a scaling behavior of financial time series. In particular, we analyze the S&P500 stock index as sampled at a daily rate in the time period 1950?2013. In order to demonstrate a strength of the method proposed we compare the multifractal ?-spectrum for various bin-widths and show the robustness of the method, especiallyfor large values of q. For such values, other methods in use, e.g., those based on moment estimation, tend to fail for heavy-tailed data or data with long correlations. Connection between the ?-spectrum and Rényi?s q parameter is also di

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

BE - Teoretická fyzika

OECD FORD obor

—

Projekt

<a href="/cs/project/GCP402%2F12%2FJ077" target="_blank" >GCP402/12/J077: Aplikace zobecněné statistiky v teorii kritických jevů a ve finančních trzích</a><br>

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Physica A: Statistical Mechanics and Its Applications

ISSN

0378-4371

e-ISSN

—

Svazek periodika

413

Číslo periodika v rámci svazku

—

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

21

Strana od-do

438-458

Kód UT WoS článku

000340977700047

EID výsledku v databázi Scopus

—