Quantitative analysis (finance) | Solutional Webdesign Antwerpen

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Quantitative analysis in finance, often referred to as ‘quant’, is a field that applies mathematical and statistical methods to financial and risk management. Its roots date back to 1900 and its development has been influenced by prominent figures such as Louis Bachelier, Harry Markowitz, Edward Thorp, and Robert Merton. Professionals in this field, known as quantitative analysts or ‘quants’, typically have backgrounds in disciplines such as financial mathematics, physics, or engineering. Quants utilize models and techniques like Black-Scholes or the HJM Framework for pricing derivatives and securities, as well as utilizing data science and machine learning^[1] for portfolio analysis and risk modeling. The application of quantitative analysis can be seen in various areas such as investment management, derivative structuring, and risk management. This field has evolved over time, adapting to changes in financial markets and regulations and incorporating new methodologies and technologies.

Terms definitions

1. ↑ machine learning. Machine learning, a term coined by Arthur Samuel in 1959, is a field of study that originated from the pursuit of artificial intelligence. It employs techniques that allow computers to improve their performance over time through experience. This learning process often mimics the human cognitive process. Machine learning applies to various areas such as natural language processing, computer vision, and speech recognition. It also finds use in practical sectors like agriculture, medicine, and business for predictive analytics. Theoretical frameworks such as the Probably Approximately Correct learning and concepts like data mining and mathematical optimization form the foundation of machine learning. Specialized techniques include supervised and unsupervised learning, reinforcement learning, and dimensionality reduction, among others.

Quantitative analysis (finance) (Wikipedia)

Quantitative analysis is the use of mathematical and statistical methods in finance and investment management. Those working in the field are quantitative analysts (quants). Quants tend to specialize in specific areas which may include derivative structuring or pricing, risk management, investment management and other related finance occupations. The occupation is similar to those in industrial mathematics in other industries. The process usually consists of searching vast databases for patterns, such as correlations among liquid assets or price-movement patterns (trend following or mean reversion).

Although the original quantitative analysts were "sell side quants" from market maker firms, concerned with derivatives pricing and risk management, the meaning of the term has expanded over time to include those individuals involved in almost any application of mathematical finance, including the buy side. Applied quantitative analysis is commonly associated with quantitative investment management which includes a variety of methods such as statistical arbitrage, algorithmic trading and electronic trading.

Some of the larger investment managers using quantitative analysis include Renaissance Technologies, D. E. Shaw & Co., and AQR Capital Management.

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