Blog Posts

Stochastic processes are mathematical models used to predict the probability of various outcomes over time, accounting for random variables and unknowns. In finance, they are used in forecasting market trends and asset prices, helping traders/investors to make informed decisions and manage risks effectively.   Key Takeaways – Stochastic Processes in Financial Markets Understanding Uncertainty: Stochastic […]

Modeling the term structure of interest rates and credit spreads is a fundamental task for risk managers and those who trade rate and fixed-income securities. Various models and methods have been developed to accurately capture and predict the behavior of interest rates and credit spreads over time. They help understand and predict various financial phenomena, […]

Order Flow Trading is an often overlooked trading strategy that focuses on the analysis of advertised and executed orders to identify potential trading opportunities. This method allows traders to gain a deeper insight into the market dynamics and capitalize on the imbalances between supply and demand. In this article, we’ll discuss the key concepts of […]

Extended Mathematical Programming (EMP) is a framework that allows for the formulation and solution of complex optimization problems by integrating various programming paradigms, such as quadratic, nonlinear, mixed integer, and stochastic programming. This method extends beyond traditional linear and nonlinear programming techniques, which allows for a more nuanced handling of real-world financial scenarios.   Key […]

Genetic algorithms (GAs) are adaptive heuristic search algorithms premised on the evolutionary ideas of natural selection and genetics. They represent an exploitation of a random search within a defined search space to solve optimization problems. In trading and investing, GAs have been used in portfolio optimization, trading rule creation, and market prediction models.   Key […]

Deterministic global optimization refers to a branch of mathematical optimization that doesn’t rely on probabilistic methods to find the global maximum or minimum of a given function. In the context of trading and investing, it involves applying rigorous mathematical techniques to optimize trading strategies, portfolio allocations, and trading models with the aim of achieving the […]

Principal Component Analysis (PCA) is a statistical method used to simplify the complexity in high-dimensional datasets by reducing the dimensionality. This technique transforms the original variables into a new set of variables – termed the principal components – which are uncorrelated and ordered in a way that the first few retain most of the variation […]

Stochastic programming is a framework for modeling optimization problems that involve unknowns. In the context of trading and investing, it’s used to make decisions under uncertain market conditions. The objective is to optimize the expected outcome considering the random variables that represent risks and opportunities in financial markets.   Key Takeaways – Stochastic Programming in […]

Mixed Integer Programming (MIP) is a specialized form of mathematical optimization. It’s used in solving problems that require decision-making in discrete steps, often under complex constraints and variables. In the context of trading and investing, MIP allows for the creation of models that can handle a range of trading/investment decisions, from portfolio optimization to order […]

Nonlinear programming (NLP) is a mathematical optimization technique for solving complex problems where the objective function or the constraints are nonlinear. In trading and investing, NLP is used in portfolio optimization, risk management, and identifying trading strategies that maximize returns or minimize risk.   Key Takeaways – Nonlinear Programming in Trading & Investing Better Optimization […]