risk management
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Supervised machine learning – Decision trees
Quantitative developers are pivotal in leveraging data to make informed investment decisions. Among the array of analytical tools available, decision trees are a powerful, interpretable, and versatile method for solving financial problems. Their ability to model decisions based on structured…
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Macroeconomic decision-making
Macroeconomic events are pivotal in influencing market dynamics. Understanding and responding to these events can make the difference between profit and loss for investment professionals. Python, with its extensive ecosystem and user-friendly capabilities, has become a go-to tool for quantitative…
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Price modelling – Itô’s Lemma – Geometric Brownian Motion
Quantitative analysts constantly seek robust methods to model and predict asset price movements. One such powerful tool is Itô’s Lemma, a cornerstone of stochastic calculus. By leveraging this mathematical framework alongside Python, quants can enhance their analytical toolkit, making strides in…
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Portfolio optimisation – Linear algebra
Making investment decisions based on intuition or limited data can often lead to suboptimal outcomes. Quantitative analysis revolutionises how investors and portfolio managers approach asset allocation, enabling precise, data-backed strategies that optimise returns while controlling risks. One example of this…
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Market structure – Fractal microstructures
In financial markets, the ability to accurately and timely identify turning points in floating assets such as stocks, commodities, or forex pairs can spell the difference between profit and loss. Fractal analysis, a technical approach focusing on repetitive patterns and…
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Supervised machine learning – Gaussian Naïve Bayes
In quantitative finance, having access to precise data analytics and advanced predictive models is key. With its versatile ecosystem, Python has emerged as an indispensable tool for quantitative developers seeking to optimise investment strategies and forecast market movements. One such…