: (Electronic Trading Systems: Saudi vs. Tokyo Financial Market)

2007 ◽  
Author(s):  
Mohammad Al-Suhaibani
Computation ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 77
Author(s):  
Oleksandr Terentiev ◽  
Tatyana Prosiankina-Zharova ◽  
Volodymyr Savastiyanov ◽  
Valerii Lakhno ◽  
Vira Kolmakova

The article describes the original information technology of the algorithmic trading, designed to solve the problem of forming the optimal portfolio of trade strategies. The methodology of robust optimization, using the Ledoit–Wolf shrinkage method for obtaining stable estimates of the covariance matrix of algorithmic strategies, was used for the formation of a portfolio of trade strategies. The corresponding software was implemented by SAS OPTMODEL Procedure. The paper deals with a portfolio of trade strategies built for highly-profitable, but also highly risky financial tools—cryptocurrencies. Available bitcoin assets were divided into a corresponding proportion for each of the recommended portfolio strategies, and during the selected period (one calendar month) were used for this research. The portfolio of trade strategies is rebuilt at the end of the period (every month) based on the results of trade during the period, in accordance with the conditions of risk minimizing or income maximizing. Trading strategies work in parallel, being in a state of waiting for a relevant trading signal. Strategies can be changed by moving the parameters in accordance with the current state of the financial market, removed if ineffective, and replaced where necessary. The efficiency of using a robust decision-making method in the context of uncertainty regarding cryptocurrency trading was confirmed by the results of real trading for the Bitcoin/Dollar pair. Implementation of the offered information technology in electronic trading systems will allow risk reduction as a result of making incorrect decisions or delays in making decisions in a systemic trading.


2021 ◽  
Vol 4 ◽  
Author(s):  
Daniel Libman ◽  
Simi Haber ◽  
Mary Schaps

Liquidity plays a vital role in the financial markets, affecting a myriad of factors including stock prices, returns, and risk. In the stock market, liquidity is usually measured through the order book, which captures the orders placed by traders to buy and sell stocks at different price points. The introduction of electronic trading systems in recent years made the deeper layers of the order book more accessible to traders and thus of greater interest to researchers. This paper examines the efficacy of leveraging the deeper layers of the order book when forecasting quoted depth—a measure of liquidity—on a per-minute basis. Using Deep Feed Forward Neural Networks, we show that the deeper layers do provide additional information compared to the upper layers alone.


2019 ◽  
Vol 17 (1) ◽  
pp. 80
Author(s):  
Leandro Maciel ◽  
Rosangela Ballini

<p>Stock exchange automation, characterized by the replacement of floor trading systems by electronic trading systems, is one of the main restructuring processes observed in global capital markets in recent decades. This paper investigates the effects of automation in the São Paulo Stock Exchange (B3), which adopted an electronic trading system in October 2005. Empirical analysis of the Bovespa index rejects the random walk hypothesis for the periods before and after B3 automation, and provides evidence of distinct volatility regimes. After automation, there is an increase in the linear dependence of IBovespa returns, suggesting a negative effect of automation on the Brazilian stock market’s efficiency. On the other hand, in the same period, there is evidence for a reduction in the long-term persistence of conditional volatility, in response to shocks to returns.</p>


Author(s):  
Amit Sinha ◽  
Eurico J. Ferreira ◽  
Ronald Green

The last few decades have witnessed the transformation of financial markets in the United States. Electronic trading markets have now surpassed floor-based trading systems in terms of both trading volume and importance. The growth in technology-driven markets has led universities to evaluate and establish financial trading rooms in their College or School of Business. In this paper we discuss the purpose of such a room, the need for one, and how such a room fits into the overall mission of ‘excellence in teaching’ of a general College or School of Business. We find that the two most important factors to consider for a successful trading room program are faculty and curriculum.


This article reviews the analysis of the activities of electronic trading systems in Uzbekistan. The analysis shows the rapid development of electronic commerce, there is an increase in the number of electronic platforms and systems, which leads to a steady increase in the number of transactions and the volume of turnover. In recent years, Uzbekistan has adopted a number of legislative and regulatory documents and measures aimed at the development of EC, which have brought tangible results and revitalization in the e-commerce market. Nowadays, a number of electronic platforms and systems act as an information intermediary in Uzbekistan. To maintain the National Register of Electronic Commerce Entities in Uzbekistan, a website, which gives entrepreneurs the opportunity to voluntarily and free of charge apply for entry into the register in electronic form was developed and launched. The measures taken in Uzbekistan (legislative and regulatory, infrastructural) allowed electronic commerce to develop rapidly, which formed the basis of a market mechanism in the virtual space


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