Geodesic
Analysis of financial time series with binary $n$-grams frequency dictionaries
Žurnal Sibirskogo federalʹnogo universiteta. Matematika i fizika, Tome 7 (2014) no. 1, pp. 112-123.

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The paper presents a novel approach to statistical analysis of financial time series. The approach is based on $n$-grams frequency dictionaries derived from the quantized market data. Such dictionaries are studied by evaluating their information capacity using relative entropy. A specific quantization of (originally continuous) financial data is considered: so called binary quantization. Possible applications of the proposed technique include market event study with the $n$-grams of higher information value. The finite length of the input data presents certain computational and theoretical challenges discussed in the paper. also, some other versions of a quantization are discussed.
Keywords: order, entropy, mutual entropy, indicator, trend. 
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Michael G. Sadovsky; Igor Borovikov. Analysis of financial time series with binary $n$-grams frequency dictionaries. Žurnal Sibirskogo federalʹnogo universiteta. Matematika i fizika, Tome 7 (2014) no. 1, pp. 112-123. http://geodesic.mathdoc.fr/item/JSFU_2014_7_1_a11/

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