arXiv subjects

Valerii Salov

Publications and source records attributed to Valerii Salov.

7 recordsLinked to original sources

arXiv2017

Trading Strategies with Position Limits

Whether you trade futures for yourself or a hedge fund, your strategy is counted. Long and short position limits make the number of unique strategies finite. Formulas of the numbers of strategies, transactions, do nothing actions are derived. A discrete distribution of actions, corresponding probability mass, cumulative distribution and characteristic functions, moments, extreme values are presented. Strategies time slice distributions are determined. Vector properties of trading strategies are studied. Algebraic not associative, commutative, initial magmas with invertible elements control trading positions and strategies. Maximum profit strategies, MPS, and optimal trading elements can define trading patterns. Dynkin introduced the term interpreted in English as "Markov time" in 1963. Neftci applied it for the formalization of Technical Analysis in 1991.

q-fin.GN↗

arXiv2017

The Wandering of Corn

Time and Sales of corn futures traded electronically on the CME Group Globex are studied. Theories of continuous prices turn upside down reality of intra-day trading. Prices and their increments are discrete and obey lattice probability distributions. A function for systematic evolution of futures trading volume is proposed. Dependence between sample skewness and kurtosis of waiting times does not support hypothesis of Weibull distribution. Kumaraswamy distribution is more suitable for waiting times. Relationships between trading volume and maximum profit strategies are presented. Frequencies of absolute b-increments are approximated by a Hurwitz Zeta distribution. Relative b-increments are non-Gaussian too. Dependence between b- and a-increments allows to interpret the sample variances of b-increments as a stochastic process. Mean sample variance of b-increments vs. a-increments is presented. The L1 distance and Log-likelihood statistics for independence between a- and b-increments are controversial. Corn price jumps remind of chain branching reactions. Bi-logarithmic plots of the empirical frequencies of extreme b-increments vs. ranks are presented. Corresponding distributions resemble snakes forked tongues. The maximum profit strategy is discussed as a measure of non-equilibrium.

q-fin.GN↗

arXiv2015

The Role of Time in Making Risky Decisions and the Function of Choice

The prospects of Kahneman and Tversky, Mega Million and Powerball lotteries, St. Petersburg paradox, premature profits and growing losses criticized by Livermore are reviewed under an angle of view comparing mathematical expectations with awards received. Original prospects have been formulated as a one time opportunity. An award value depends on the number of times the game is played. The random sample mean is discussed as a universal award. The role of time in making a risky decision is important as long as the frequency of games and playing time affect their number. A function of choice mapping properties of two-point random variables to fractions of respondents choosing them is proposed.

q-fin.GN↗

arXiv2014

"The Gibbon of Math History". Who Invented the St. Petersburg Paradox? Khinchin's resolution

A sentence from Carl Boyer's A History of Mathematics can be interpreted so that the full brothers Nicolaus II (02/06/1695 - 07/31/1726) and Daniel Bernoulli (02/08/1700 - 03/17/1782) are the authors of the St. Petersburg paradox. The paradox was formulated by their cousin Nicolaus I Bernoulli (10/21/1687 - 11/29/1759). The author did not find evidences that Nicolaus II and Daniel Bernoulli discussed the paradox. The key articles on the topic and its history from Karl Menger and Paul Samuelson, and recent papers presenting the time resolution miss Alexandr Khinchin's resolution of the paradox in his paper "On Petersburg game." Matematicheskii sbornik, Volume 32, No 2, 1925, pp. 330 - 341. The C++ program khinchin.cpp simulates conditions of two Khinchin's theorems and confirms his results providing concrete empirical dependencies of the frequencies corresponding to geometric and arithmetic mean payments on the number of Petersburg games.

math.HO↗

arXiv2013

Optimal Trading Strategies as Measures of Market Disequilibrium

For classification of the high frequency trading quantities, waiting times, price increments within and between sessions are referred to as the a-, b-, and c-increments. Statistics of the a-b-c-increments are computed for the Time & Sales records posted by the Chicago Mercantile Exchange Group for the futures traded on Globex. The Weibull, Kumaraswamy, Riemann and Hurwitz Zeta, parabolic, Zipf-Mandelbrot distributions are tested for the a- and b-increments. A discrete version of the Fisher-Tippett distribution is suggested for approximating the extreme b-increments. Kolmogorov and Uspenskii classification of stochastic, typical, and chaotic random sequences is reviewed with regard to the futures price limits. Non-parametric L1 and log-likelihood tests are applied to check dependencies between the a- and b-increments. The maximum profit strategies and optimal trading elements are suggested as measures of frequency and magnitude of the market offers and disequilibrium. Empirical cumulative distribution functions of optimal profits are reported. A few classical papers are reviewed with more details in order to trace the origin and foundation of modern finance.

q-fin.GN↗

arXiv2012

Inevitable Dottie Number. Iterals of cosine and sine

The unique real root of cos(x) = x, recently referred to as the Dottie number, is expressed as an iteral of cosine. Using the derivatives of iterals, it is shown why this number is achieved starting from any real number, when the iterates of cosine successfully approach infinity, and how this affects the Maclaurin series of the iterals. Properties of the iterals of cosine and sine and their derivatives are considered. A C++ template for iteral is applied for computation of Julia sets.

math.HO↗

arXiv2012

Notation for Iteration of Functions, Iteral

A new mathematical notation is proposed for the iteration of functions. It facilitates the application of the iteration of functions in mathematical and logical expressions, definitions of sets, and formulations of algorithms. Illustrations of the notation include definitions of constant points, periodic points, a filled-in Julia set, the Mandelbrot set, iterations of a logistic map, the double-approximating procedure for solving the Lorenz equations, a description of a financial time series, and reordering nonnegative integers useful for the investigation of the Collatz's (3x+1)/2 convergence problem. The terms iteral and iteral of function are suggested to name the new denomination.

math.DS↗