The group of the Brazilian scientists published the research devoted to creation of the tool for a prediction of behavior of the assets bargaining in stock market. In work the detailed description of a method and method of calculations for similar forecasts is submitted. We present to yours the most interesting moments of this document.
Earlier we published in our blog first partresearches of sociology of financial algorithms executed by professor of the Higher school of social sciences of Edinburgh of Donald Mackenzie. Today we present to yours continuation of this interesting work — in the second part it is about different types of HFT requests, dark-pools and the connected ekologiya of the financial markets.
Presently technologies and special trade algorithms exert on the situation developing in stock markets, the increasing impact. With growth of automation change also social the relation between bidders.
Research of professor of the Higher school of social sciences of Edinburgh Donald Mackenzie is devoted to the analysis of a subject of sociology of financial algorithms. We represent you the most interesting thoughts of this work — in the first part it is about premises of emergence of HFT trading and classification of schemes of its application.
Note: The material given below belongs to the category of "large-scale holiday reading" — it needs to be considered, selecting time for its studying.
Stock market — a high-tech industry. In our blog we already wrote about transfer protocols of financial data, algorithms of detection of insider trade, development of financial software and methods of acceleration of transactions. All this variety of technologies and tools is built around a server core of the exchanges — many HFT traders use services of a collocation and place servers with the trade applications as it is possible closer to the exchange trade engine.
Today we will talk about data-centers of different platforms and we will show how they look.
Stock market — large-scale and difficult knowledge domain. Different technologies of exchange trade actively develop in the last a couple of decades. To understand the structure of stock market, the laws and the principles working at it and also used by different players technologies — it is absolutely difficult.
In our today's material — a selection from 40 books and educational which will help to be prepared better for the beginning of work in stock market and to writing of mechanical trade systems.
How insiders at the exchange specifically behave? Whether their transactions depend on a post in the company (the general or finance director) whether the behavior of insiders changes eventually (whether crisis of 2008 influenced him, for example)?
The group of researchers of institute of technology of Georgia conducted research on the basis of the transactions given about 12 million made by 370 thousand insiders during the period from 1986 to 2012. Identification of patterns of behavior of players in stock market by means of which regulators could find and stop illegal insider trade was the purpose of this work. We present to yours highlights of this document.
In our blog we often write about technologies of trading, high-frequency trade and creation of robots for commission of operations at the exchange. However many traders still use special trade terminals by means of which it is possible to monitor stock quotations for work and to make purchase or sale of securities and other financial instruments, besides it is possible to create trade robots and not from scratch, and by means of specialized platforms.
Today we will talk about the existing tendencies in the field of development of interfaces of such applications — both mobile, and desktop.
Many trading platforms for high-frequency trading often work at the equipment with high-performance network adapters. However minus of such systems is rather high and unpredictable delay — as a result many traders turned the view of hybrid architecture with hardware acceleration.
Experts of the Algo-Logic Systems Inc company. John Lokvud (Jowhn W. Lockwood), to Advayt Gupta (Adwait Gupte) and Nishit Mehta (Nishit Mehta) published work in which told about how FPGA are used in online trading for reduction of transfer lags of data. We present to yours highlights of this publication.
In this article we will consider methods of application of machine learning in the field of high-frequency trading (HFT) and the analysis of microstructural data. Machine learning is the remarkable section of information science using models and methods from statistics, algorithm theories, computational complexity theories, artificial intelligence, the theory of management and huge number of other disciplines. The main object of research of machine learning are the effective algorithms allowing to create good predictive models on the basis of big data sets – for this reason it so well is suitable for a solution of problems of high-frequency trading: conclusions of transactions and calculation of an indicator "alpha".