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QuantConnect is an open-source, cloud-based algorithmic trading platform for equities, FX, futures, options, derivatives and cryptocurrencies.QuantConnect serves over 100,000 quants from over 170 countries, with customers including hedge funds and brokerages, as well as individuals such as engineers, mathematicians, scientists, quants, students, traders, and programmers.
Algorithmic trading is a method of executing orders using automated pre-programmed trading instructions accounting for variables such as time, price, and volume. [1] This type of trading attempts to leverage the speed and computational resources of computers relative to human traders.
Around 2005, copy trading and mirror trading emerged as forms of automated algorithmic trading. These systems allowed traders to share their trading histories and strategies, which other traders could replicate in their accounts. One of the first companies to offer an auto-trading platform was Tradency in 2005 with its "Mirror Trader" software.
The effects of algorithmic and high-frequency trading are the subject of ongoing research. High frequency trading causes regulatory concerns as a contributor to market fragility. [ 56 ] Regulators claim these practices contributed to volatility in the May 6, 2010, Flash Crash [ 62 ] and find that risk controls are much less stringent for faster ...
Download as PDF; Printable version; In other projects Wikidata item; ... Pages in category "Algorithmic trading" The following 13 pages are in this category, out of ...
Cloud bursting is an application deployment model in which an application runs in a private cloud or data center and "bursts" to a public cloud when the demand for computing capacity increases. A primary advantage of cloud bursting and a hybrid cloud model is that an organization pays for extra compute resources only when they are needed. [ 68 ]
The history of computational thinking as a concept dates back at least to the 1950s but most ideas are much older. [6] [3] Computational thinking involves ideas like abstraction, data representation, and logically organizing data, which are also prevalent in other kinds of thinking, such as scientific thinking, engineering thinking, systems thinking, design thinking, model-based thinking, and ...
Algorithmic information theory was founded by Ray Solomonoff, [7] who published the basic ideas on which the field is based as part of his invention of algorithmic probability—a way to overcome serious problems associated with the application of Bayes' rules in statistics.