Optimization of Trading Physics Models of Markets

We describe an end-to-end real-time S&P futures trading system. Inner-shell stochastic nonlinear dynamic models are developed, and Canonical Momenta Indicators (CMI) are derived from a fitted Lagrangian used by outer-shell trading models dependent on these indicators. Recursive and adaptive optimization using Adaptive Simulated Annealing (ASA) is used for fitting parameters shared across these shells of dynamic and trading models

Forecasting COVID-19 with Importance-Sampling and Path-Integrals

Background Forecasting nonlinear stochastic systems most often is quite difficult without giving in to temptations to simply simplify models for the sake of permitting simple computations Objective Here two basic algorithms Adaptive Simulated Annealing ASA and path-integral codes PATHINT PATHTREE and their quantum generalizations qPATHINT qPATHTREE are suggested as being useful to fit COVID-19 data and to help predict spread or control of this pandemic Multiple variables are considered e g potentially including ethnicity population density obesity deprivation pollution race environmental temperature Method ASA and PATHINT PATHTREE have been demonstrated as being effective to forecast properties in three disparate disciplines in neuroscience financial markets and combat analysis Results Not only can selected systems in these three disciplines be aptly modeled but results of detailed calculations have led to new results and insights not previously obtaine

Le trading algorithmique

The algorithmic trading comes from digitalisation of the processing of trading assets on financial markets. Since 1980 the computerization of the stock market offers real time processing of financial information. This technological revolution has offered processes and mathematic methods to identify best return on transactions. Current research relates to autonomous transaction systems programmed in certain periods and some algorithms. This offers return opportunities where traders can not intervene. There are about thirty algorithms to assist the traders, the best known are the VWAP, the TWAP, TVOL. The algorithms offer the latest strategies and decision-making are the subject of much research. These advances in modeling decision-making autonomous agent can envisage a rich future for these technologies, the players already in use for more than 30% of their trading.marché électronique;algorithme de trading;agent autonome;VWAP;TVOL;Arbitrage:marché financier; passage d'ordre automatisés

Hybrid Classical-Quantum Computing: Applications to Statistical Mechanics of Neocortical Interactions

Several commerical quantum computers are now available that offer Hybrid Classical-Quantum computing Application is made to a classical-quantum model of human neocortex Statistical Mechanics of Neocortical Interactions SMNI which has had its applications published in many papers since 1981 However this project only uses Classical super- computers Since 2015 PATHINT has been used as a numerical algorithm for folding path-integrals Applications in several systems in several disciplines has generalized been from 1 dimension to N dimensions and from classical to quantum systems qPATHINT Papers have applied qPATHINT to neocortical interactions and financial options The classical space described by SMNI applies nonlinear nonequilibrium multivariate statistical mechanics to synaptic neuronal interactions while the quantum space described by qPATHINT applies synaptic contributions from Ca2 waves generated by astrocytes at tripartite neuron-astrocyte-neuron site

СВЕРТКА РЕГУЛЯРНЫХ МАТРИЧНЫХ СТРУКТУР ЗАКАЗНЫХ СБИС МЕТОДОМ МОДЕЛИРОВАНИЯ ОТЖИГА

Рассматривается задача топологической оптимизации программируемых логических матрицметодом свертки. Предлагаются алгоритмы многократной и простой сверток регулярных струк-тур СБИС на основе моделирования отжига, позволяющие находить оптимальное или близкое к нему решение задачи свертки. Приводятся результаты исследования предложенных алгоритмов свертки