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Books on the topic 'Automated trading systems'

Author: Grafiati

Published: 4 June 2021

Last updated: 15 June 2025

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1

1965-, Tsudikman Vadim, ed. Automated option trading: Create, optimize, and test automated trading systems. FT Press, 2012.

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2

Young, Andrew R. Expert advisor programming: Creating automated trading systems in MQL for MetaTrader 4. Edgehill Pub., 2010.

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3

Building automated trading systems: With an introduction to Visual C++.NET 2005. Academic Press, 2007.

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4

Stock Exchange of Singapore Dealing and Automated Quotation System. Trading bye-laws on SESDAQ securities, SESDAQ listing requirements, central depository procedures, central depository regulations. SESDAQ, 1988.

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5

Office, General Accounting. Automated Export System: Prospects for improving data collection and enforcement are uncertain : report to the Chairman, Committee on the Judiciary, U.S. Senate. The Office, 1997.

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6

Tsudikman, Vadim, and Sergey Izraylevich. Automated Option Trading: Create, Optimize, and Test Automated Trading Systems. Financial Times/Prentice Hall, 2012.

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7

O'Garro, Jamal Sinclair. Learn Algorithmic Trading with Python: Build Automated Electronic Trading Systems Using Python. Apress L. P., 2022.

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8

POLLY, Lina. Day Trading and Options Trading : 10 Day Trading Strategies for Beginners : Options Trading Strategies - a Guide for Beginners : How Automated Trading Systems: Day Trading Rules. Independently Published, 2020.

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9

Vliet, Benjamin Van. Building Automated Trading Systems: With an Introduction to Visual C++. NET 2005. Elsevier Science & Technology Books, 2007.

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10

Young, Andrew R. Expert Advisor Programming for MetaTrader 4: Creating automated trading systems in the MQL4 language. Edgehill Publishing, 2015.

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11

Young, Andrew R. Expert Advisor Programming for MetaTrader 5: Creating automated trading systems in the MQL5 language. Brand: Edgehill Publishing, 2013.

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12

Young, Andrew R. Expert Advisor Programming for MetaTrader 5: Creating automated trading systems in the MQL5 language. Edgehill Publishing, 2018.

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13

New York Stock Exchange: Capability of automated systems to identify program trading : report to the Chairman, Committee on Agriculture, Nutrition, and Forestry, U.S. Senate. The Office, 1991.

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14

New York Stock Exchange: Capability of automated systems to identify program trading : report to the Chairman, Committee on Agriculture, Nutrition, and Forestry, U.S. Senate. The Office, 1991.

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15

Bensdorp, Laurens. Automated Stock Trading Systems: A Systematic Approach for Traders to Make Money in Bull, Bear and Sideways Markets. Lioncrest Publishing, 2020.

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16

Vassiliadis, Vassilios, and Georgios Dounias. Algorithmic Trading based on Biologically Inspired Algorithms. Edited by Shu-Heng Chen, Mak Kaboudan, and Ye-Rong Du. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199844371.013.11.

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The chapter discusses algorithmic trading, which refers to any automated process, consisting of a number of interconnected components, whose main aim is to perform financial transactions of any kind. Its chief advantage lies in the fact that human intervention is minimized to an acceptable extent. This is quite desirable because nowadays numerous factors affect financial decisions. Financial managers are able to deal with a limited amount of information. There are many ways to implement algorithmic trading systems. This chapter aims to highlight the efficiency of biologically inspired methodologies when incorporated in such systems. Biologically inspired intelligence comprises a range of algorithms whose common philosophy is based on the behavior of real-world, natural systems and networks. What is more, the performance of the applied nature-inspired intelligence (NII) methodologies is compared to traditional benchmark approaches such as the random portfolio construction.

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17

Chen, Shu-Heng, Mak Kaboudan, and Ye-Rong Du. Computational Economics in the Era of Natural Computationalism. Edited by Shu-Heng Chen, Mak Kaboudan, and Ye-Rong Du. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199844371.013.1.

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After a brief review of natural computationalism, this introductory chapter presents a new skeleton of computational economics and finance (CEF) along with an overview of the handbook. It begins with a conventional pursuit focusing on the algorithmic or numerical aspect of CEF such as computational efforts devoted to rational expectations, (dynamic) general equilibrium, and volatility. It then moves toward an automata- or organism-based perspective of CEF, involving nature-inspired intelligence, algorithmic trading, automated markets, network- and agent-based computing, and neural computing. As an alternative way to introduce this novel skeleton, the chapter starts with a view of computation or computing, addressing what computational economics intends to compute and what kinds of economics make computation so hard, and then it turns to a view of computing systems in which the Walrasian kind of computational economics is replaced by the Wolframian kind due to computational irreducibility.

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18

United States. Congress. Senate. Committee on Banking, Housing, and Urban Affairs. The role of regulation in shaping equity market structure and electronic trading: Hearing before the Committee on Banking, Housing, and Urban Affairs, United States Senate, One Hundred Thirteenth Congress, second session, on examining the influence of regulation on the growth of market structure, the systems and operation of market participants and the development of business practices related to high-frequency trading, electronic markets and automated trading, July 8, 2014. 2015.

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19

Sr, David J. Lyder. Automatic Alpha: How to Build a Winning FOREX Trading System. iExpertAdvisor, 2005.

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20

Logan, Steve. Cryptocurrency Passive Income: How to Create Automated Online Trading System and Start Online Trading Business with Bitcoin and Other Cryptocurrencies. Cryptotrader Step-By-step. Independently Published, 2018.

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