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Accurately pricing complex financial instruments is a cornerstone of modern finance, essential for trading, investment strategy, and risk management. For many advanced models, especially those involving three or more stochastic variables like fluctuating interest rates or volatility, closed-form analytical solutions are impractical or impossible to derive. This reality makes numerical methods, particularly Monte-Carlo simulations, the only viable alternative for obtaining a s

To optimize a Field-Programmable Gate Array (FPGA) design, an Agent requires a formal mathematical model—either empirical (based on measurements) or analytical (based on first principles)—to guide the optimization. This model must allow the Agent to infer optimal actions, such as minimizing memory block transfers between storage and the processing pipeline. The paper reviewed addresses this by proposing the authors' FPGA Empirical Roofline (FER) benchmarking tool as a modelin

Given their unique capabilities, what surprising and counter-intuitive realities have kept FPGAs from becoming a mainstream force in HPC?

Background: The "Research Review" series is a grouping of articles that review scientific publications on the topics of financial modeling, foundation mathematics, and parallel computing. It is meant to enrich the community with technical knowledge and provide clarity on topics that can create distrust in the markets Paper being review: Ana M. Monteiro, António A.F. Santos, Parallel computing in finance for estimating risk-neutral densities through option prices Journal of Pa

Time series analysis is a powerful tool in the world of finance and technology. It allows businesses to analyze data points collected or recorded at specific time intervals. In the fast-paced fintech industry, understanding trends and patterns in data can lead to better decision-making and improved financial products. This blog post will explore the significance of time series analysis in fintech applications, its methodologies, and real-world examples. What is Time Series An

Machine learning is transforming the financial sector. It is not just a buzzword; it is a powerful tool that can enhance decision-making, improve customer experiences, and streamline operations. As financial technologies evolve, understanding how to leverage machine learning becomes essential for businesses aiming to stay competitive. In this blog post, we will explore the various applications of machine learning in financial technologies. We will discuss its benefits, challe

In today's fast-paced world, financial solutions must adapt quickly to changing circumstances. Traditional methods often fall short in addressing the complexities of modern finance. This is where dynamic systems come into play. They offer innovative approaches that can transform how we manage and understand financial data. Dynamic systems are not just a trend; they represent a shift in how we think about finance. By leveraging technology and data analytics, these systems prov