Tracing of stock market long term trend by information efficiency measures

Neurocomputing

Volumn 109, Issue , 2013, Pages 105-113

  Sakalauskas, Virgilijus ^a   Kriksciuniene, Dalia ^a  

^a VILNIUS UNIVERSITY   (Lithuania)

Author keywords

Emerging stock market; Hurst exponent; Information efficiency; Neural network; Shannon entropy

Indexed keywords

EXPERIMENTAL RESEARCH; FINANCIAL TIME SERIES; HURST EXPONENTS; INFORMATION EFFICIENCY; NEURAL NETWORK MODEL; RADIAL BASIS FUNCTION NEURAL NETWORKS; SHANNON ENTROPY; STOCK MARKET;

BEHAVIORAL RESEARCH; EFFICIENCY; FINANCE; FINANCIAL DATA PROCESSING; NEURAL NETWORKS; SENSITIVITY ANALYSIS; SOFT COMPUTING;

COMMERCE;

ANALYTIC METHOD; ANALYTICAL PARAMETERS; ARTICLE; ARTIFICIAL NEURAL NETWORK; CALIBRATION; COMPUTER MODEL; DATA ANALYSIS; ECONOMIC ASPECT; ESTONIA; FINANCIAL MANAGEMENT; HURST EXPONENT; INFORMATION PROCESSING; LATVIA; LITHUANIA; MATHEMATICAL COMPUTING; MATHEMATICAL VARIABLE; NEUROANATOMICAL TRACT TRACING; PRIORITY JOURNAL; PROCESS MODEL; SENSITIVITY ANALYSIS; SHANNON ENTROPY; STOCK MARKET; STOCK MARKET INDEX; TIME SERIES ANALYSIS; TREND STUDY;

EID: 84875915037     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2012.02.044     Document Type: Article

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