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The domain of high-frequency trading (HFT) is enjoying an upward trend through the past 2 decades. With the aid of a supercomputer to execute hundreds of orders within a second, HFT has the possibility of exploiting minute fluctuations in prices. An organization that has the requisite algorithms and relevant infrastructure might be in a position […]
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In the investment world, the approach of portfolio diversification is one of the most preferred scenarios where risk is mitigated by distributing the investments in different assets or asset classes. In essence, the its focus reduces the core concentration towards any single asset type, industry, or geographical scope in exchange for a balance of risk […]
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Trend lines are a popular technical analysis concept among algorithmic traders, allowing them to focus on a specific price point, buy or sell, within a certain price range, for their desired security or asset. This level can serve as a basis for trading decisions or stop orders. As a trader, it is also beneficial to […]
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In algorithmic trading strategies and using models, the most important is how quality and how clean or how free from errors, is the data. Data, models, and analysis can be greatly affected by data inaccuracies, inconsistencies, and irrelevant information. Proper data processing can minimize the problem by making sure that financial data is clean and […]
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Algorithmic transactions are on the rise globally and its increasing popularity can be attributed to several aspects such as simplicity and a wide range of libraries that Python boasts. These libraries come in handy for back testing, analysis, risk management as well as model building which assists traders and developers in creating effective and robust […]
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In the machine-learning industry, predictive models were often created, particularly for trading purposes, across pioneer domains in this upper technological world. It is a widely known fact that Machine learning models can evaluate and understand elation large amounts of data to extract various non-obvious relationships within it. In addition to price movements of stocks, Machine […]
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Risk management is a major necessity for every algorithmic trading system. Algorithms are created to execute orders as quickly as possible but given the unpredictable nature of volatility, liquidity or just the entire market in general, they are not risk-free. Risk management helps adhere to these risks as it enables the trader to get higher […]
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Efficiency metrics help to measure the degree of success or the failure of any algorithmic trading strategy. This study outlines how algorithmic traders and investors measure performance in terms of returns, risks, and efficiencies, among other value points that assist them in understanding when to adjust their strategies to better meet differing financial objectives. These […]
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Backtesting is a key procedure in algorithmic (algo) trading which relies on historical data to assess the effectiveness of a particular trading strategy. It enables traders to put a strategy to the test ,perfect it and verify its usefulness without putting any capital at risk. In a way, backtesting allows traders to imagine how their […]
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Heffernan’s approach, momentum trading, involves riding on the coat-tails of existing trends, which in effect captures more return as the market is already moving in the direction of the position. During a strong market, an investor can simply buy any security and, due to momentum getting pushed in the direction of the traction of the […]