SearcharxivSearch

arXiv subjects

Igor Nesiolovskiy

Publications and source records attributed to Igor Nesiolovskiy.

3 recordsLinked to original sources

Stock exchange shares ranking and binary-ternary compressive coding

This paper proposes a method for ranking the investment attractiveness of exchange-traded stocks where investment risk is not related to the volatility indicator but instead is related to the indicator of compression of the time series of price changes. The article describes in detail the ranking algorithm, provides an example of ranking the shares of all companies included in the Dow Jones stock index. The paper additionally compares the results of ranking these stocks by volatility and compression and also shows the strengths of the second indicator, which is formed using the method of binary-ternary compression of historical financial data.

q-fin.ST

Multiplication method for factoring natural numbers

We offer multiplication method for factoring big natural numbers which extends the group of the Fermat's and Lehman's factorization algorithms and has run-time complexity $O(n^{1/3})$. This paper is argued the finiteness of proposed algorithm depending on the value of the factorizable number n. We provide here comparative tests results of related algorithms on a large amount of computational checks. We describe identified advantages of the proposed algorithm over others. The possibilities of algorithm optimization for reducing the complexity of factorization are also shown here.

cs.DS

BIN@ERN: Binary-Ternary Compressing Data Coding

This paper describes a new method of data encoding which may be used in various modern digital, computer and telecommunication systems and devices. The method permits the compression of data for storage or transmission, allowing the exact original data to be reconstructed without any loss of content. The method is characterized by the simplicity of implementation, as well as high speed and compression ratio. The method is based on a unique scheme of binary-ternary prefix-free encoding of characters of the original data. This scheme does not require the transmission of the code tables from encoder to decoder; allows for the linear presentation of the code lists; permits the usage of computable indexes of the prefix codes in a linear list for decoding; makes it possible to estimate the compression ratio prior to encoding; makes the usage of multiplication and division operations, as well as operations with the floating point unnecessary; proves to be effective for static as well as adaptive coding; applicable to character sets of any size; allows for repeated compression to improve the ratio.

cs.IT