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High Frequency Trading (HFT) requires a very sophisticated and advanced infrastructure to bear the high speed and competition that comes with trading in the current market setting. In contrast to previous technologies, which were more focused on the transaction itself, HFT aims for maximal efficiency and information retrieval; trades are executed in milliseconds or even […]
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Portfolio management, or asset allocation, embodies an optimization problem: either maximize returns at a given risk point or minimize risk at a specific target return. For this group, the task of optimizing a portfolio is based on mathematical modeling and statistical methods for the relative allocation of assets. In this article, we will discuss a […]
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Technical indicators sometimes make this improbable trading mechanism a bit easier, these mechanisms help the traders to identify the direction, strength, volatility, and possible reversal level in the price action. They also enable the algorithm to use precise information leading to more successful trades. From the Top 8 algorithmic trading technical indicators goes. 1. Moving […]
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Feature engineering is an often overlooked but key aspect of creating quantitative models. It’s especially the case, when dealing with algorithmic trading, and finance overall. It is the process of deriving information features from the initial raw data which would make predictive models better. In trading, strong feature engineering is needed to learn the relations […]
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In Python, building a trading bot is very much a decent and well organized introductory step into algorithmic trading. A trading bot refers to a great set of rules that allows for automated trading to be well invoked, and as such absent owners of the warrants will not be obligated to oversee such strategies. Due […]
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MetaTrader is an immensely utilized platform in the trading world. It is predominantly famous for trading forex, commodities and other assets. MetaTrader has various features and tools that can be of great use to beginners as well as to professional algorithm traders who wish to create, test and implement automated trading strategies. Thanks to its […]
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Algorithmic trading has been on a new path since the introduction of deep learning into the picture. A deeper perspective of the situation can be provided by deep learning algorithms that rely on patterns in big data that are not always obvious and therefore can lead to nuanced approaches and more complex trading methods, in […]
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Stop-loss and take-profit are two very valuable additions to risk management that can greatly improve the effectiveness of an automated trading approach. When these levels are set, the traders can restrict their possible losses and secure their gains. This in turn leads to lower emotional trading and a more systematic approach to trading. When adding […]
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The Sharpe Ratio is perhaps the most popular definition used among money managers to gauge the satisfaction of risk. It was developed by an economist and a Nobel prize winner, William F. Sharpe. The Sharpe Ratio allows to determine what level of returns an investment provides for the risk taken. In the case of trading […]
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It is quite important to follow certain best practices when creating a backtesting environment for the purposes of obtaining useful and realistic results. Here are some best practices that you may find useful: 1. Select Historical Data with High Quality The reliability of backtest also depends a lot on its data. Use high history data […]