Blog Posts

Variational Bayesian methods, within the context of probability theory in finance and markets, offer a framework for dealing with uncertainty and making predictions. These methods belong to the family of Bayesian inference techniques, which update the probabilities of hypotheses as more evidence becomes available. Variational Bayesian methods specifically use optimization techniques to approximate complex posterior […]

Network theory and percolation models offer a lens through which we can understand various phenomena in finance and trading. These concepts, derived from mathematics and physics, provide quantitative frameworks for the interconnectedness and vulnerabilities within financial markets. Below, we look into the key concepts, applications, and how traders can leverage network theory and percolation in […]

Random Matrix Theory (RMT) is a statistical framework used to analyze the properties of matrices with random elements. In finance and trading, RMT is useful for analyzing the structure of correlations among assets in large portfolios, which can help with understanding why assets move the way they do, risk management, and portfolio optimization.   Key […]

Heavy-tailed distributions (or fat-tailed distributions) are used in financial modeling as these probability distributions better capture the behavior of financial data. The occurrence of extreme events such as market drops or booms are more common than would be predicted by normal (Gaussian) distributions. These distributions have “heavy tails” – i.e., a higher likelihood of extreme […]

Fractals and scale invariance are two interrelated concepts in mathematics and physics that also have applications in finance, markets, and trading. These concepts provide a framework for understanding the behavior observed in financial markets and for developing trading strategies that can adapt to the nature of market data.   Key Takeaways – Fractals in Finance, […]

Poisson Processes are a fundamental concept in stochastic processes, which are widely used in finance, markets, and trading to model random events that occur independently of each other within a fixed period of time. These events are characterized by some level of unpredictability (and sometimes rarity), such as defaults on loans, arrivals of orders in […]

Renewal theory is a branch of probability theory that deals with the times at which events recur. It’s based on the study of stochastic processes and has found applications across various fields, including finance, economics, and trading. In the context of finance and trading, renewal theory can offer frameworks for decision-making under uncertainty, especially in […]

Filtering theory is rooted in statistical and probabilistic methodologies and used in understanding and analyzing the dynamic, uncertain situations and environments in finance, markets, and trading. At its core, filtering theory is concerned with the problem of estimating the state of a dynamical system from noisy observations (i.e., separating signal from noise). It’s used in […]

Large Deviation Theory (LDT) is a branch of probability theory that studies the asymptotic behavior of remote tails of sequences of probability distributions. It’s useful in quantifying the probabilities of rare events in systems with many degrees of freedom, such as financial markets and trading activities. In finance, these “rare events” can include extreme market […]

Measure theory is a branch of mathematics that studies ways of generalizing the notion of integration, length, area, and volume. It’s used in probability theory, and by extension, it is fundamentally important in the fields of finance and trading, which is essentially an applied probability exercise. In these areas, measure theory underpins the mathematical models […]