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Listening to skilled algorithmic traders and interviewing them helps one know about their challenges, success, and the correct practices that are needed to succeed in the world of algorithmic trading as it is priceless. These traders elaborate their life stories, self-taught lessons, and even the tips they have for beginner traders. Here is the summarization of all themes discussed in the interviews. Starting Off and the Education Most of the proficient algorithmic traders come from industries such as computing, mathematics, and even related fields such as computer science or finance. Such individuals share many important aspects of their lives, such…
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The development of 5G technology is going to change different sectors globally – and high-frequency trading (HFT) is no different. HFT depends on performing trade orders almost instantaneously with other trades, which are executed throughout markets in order to earn a profit from the difference in prices. These systems depend on reliable data transmission to get information at the speed it is required, which is what makes HFT reliant on 5G technology. What is 5G? Compared to those that came before it, 5G indeed promises far better perks for its users, including faster data retrieval, weaker lag (or latency), and…
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The combination of behavioral finance and machine learning is capable of producing great insights in the financial markets, due to their respective focuses: finance tackles the psychology surrounding the investment decisions of people while ML allows for the analysis of large data sets to identify patterns that might be skipping traditional statistical analyses. This intersection is particularly notable when considering the construction of models and strategies to predict events deemed as anomalies for human biases against markets behaviors. Understanding Investor Psychology in Finance Behavioral finance shifts the burden of rationality from economic agents to the systems of rules under which…
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Event driven trading strategies are based on events or corporate actions that have a strong impact on prices of assets. These specific events can vary from earnings reports, mergers and acquisitions (M&A), economic data to even regulatory information. Such strategies make use of how poorly these events have been timed and display inadequate decision making. These opportunities are used to gain profits from the initial inefficiencies caused by the event. This case study looks into the process of earning announcements and their trading strategy at the same time. Understanding the Strategy: Earnings Announcement Trading Earning reports give core information on…
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The emergence of algorithmic trading has transformed the world of finance, allowing for the implementation of quicker and more effective trading methods. On the flip side, accompanying this transformation is the dire need to ensure compliance with all financial laws and regulations so as to prevents costly legal, financial, or reputational liability. Firms and traders utilize a compliance checklist to address the legal risk posed by algorithmic trading so that their business can run efficiently. This is how you can build your algorithmic trading compliance checklist. Compliance with the Rules and Regulations a. Analysis of Applicable Rules and Regulations Cross…
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Traders can benefit greatly from alternative data from social media, satellite images, or web traffic when trading in financial markets. This non-traditional data source provides a vast plethora of information, however its inclusion in trading strategies does bring about a few challenges. Here are some of the primary challenges related to alternative data trading. Quality and Reliability of Data a. Noise and Inconsistency Challenge: Data from unconventional sources is prone to inconsistency which leads to differing formats and overall quality. Consideration: Data cleaning would need to be employed by the traders, which can include preprocessing techniques. b. Historical Data Scarcity…
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Machine learning (ML) models are used heavily for trading now as they enable traders to take decisions by analyzing available datasets. However, these models have their shortcomings when deployed in live trading and thus require several factors to be taken into account. This article will discuss the challenges and steps involved when deploying ML models within trading systems. Model Development and Training a. Data Collection and Preprocessing Data Sources: Gather data from all possible avenues which include volumes, historical prices, news/newscasters, social media, etc. Data Cleansing: The gathered data should be cleansed of all types of errors, missing values, or…
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High-Frequency Trading (HFT) is now commonplace in the financial market, executing high volumes of transactions in record time through the use of technology. With the advent of new technologies, however, significant modifications to HFT are expected to follow. In this article, innovations like technology, laws, and market operation are discussed in more detail concerning the future of HFT. First, let us have a look at technology. HFT Strategies in Quantitative Trading In quantum trading, algorithms will be employed by traders to construct and implement various set of organized plans in order to seize trading opportunities that are available for only…
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Investors these days want their investments to have a sustainable focus which is where the ESG (Environmental, Social and Governance) criteria come in. By understanding and integrating the ESG criteria, investors can use non-measurable factors alongside standard financial ratios to minimize risk when investing over a long period of time. This article explains the hows of quantitative investment decisions while keeping ESG into account. What Are The ESG Factors? A company’s sustainability and ethics can be assessed based on ESG practices that a firm has adopted: Environmental (E): This involves a company’s carbon footprints, energy consumption, managing resources, and the…
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Technical indicators are essential in algorithmic trading for determining market patterns and making trading choices. Most traders seem to base their trades on established indicators like Moving Averaging Convergence Divergence and Relative Strength Indicators, however developing custom technical indicators can give traders an extraordinary advantage. In this post, the steps to create custom technical indicators will be discussed as well as their contributions to a trader’s strategy. Introduction to Technical Indicators Calculating numbers are derived from historical price data, volume data, and open interest data and are referred to as technical indicators. These indicators assist marketers by telling them whether…