Blog Posts

Fixed-Income Attribution is a process used to analyze the performance of a fixed-income portfolio relative to a benchmark. This technique decomposes the returns from a bond portfolio into different sources to understand what factors contributed to its performance. It’s a tool for portfolio managers, analysts, and traders/investors to assess the effectiveness of trading and investment […]

The Universal Portfolio Algorithm is a strategy in quantitative finance developed by information theorist Thomas Cover. It’s based on the concept of universal schemes in information theory and portfolio selection. This algorithm aims to achieve long-term growth of capital by effectively distributing investments across a variety of assets in a way that does not rely […]

We look at the differences in various types of performance ratios: Sharpe Ratio Sortino Ratio Treynor Ratio Information Ratio Omega Ratio Bias Ratio We’ll also look at the concepts of Active Return and Active Risk.   Key Takeaways: Performance Ratios – Sharpe vs. Sortino vs. Treynor vs. Information vs. Bias Sharpe Ratio: Measures the excess […]

In the context of finance, the term “high-dimensional” refers to the characteristic of problems or models that involve a large number of variables or factors. Financial markets are complex systems influenced by many elements and variables influencing them. Many things are dependent on lots of other things. Moreover, we have known unknowns (things we know […]

Malliavin calculus, named after the mathematician Paul Malliavin, represents an advanced branch of mathematical finance that extends the traditional scope of stochastic analysis. This calculus introduces a framework for assessing the smoothness of functionals of stochastic processes. This is particularly beneficial in the context of differentiation of random variables. Its applications in finance are used […]

The Hamilton-Jacobi-Bellman (HJB) equation is used in dynamic programming and control theory. It’s heavily used in the context of optimal control and decision-making under uncertainty. This equation provides a framework for solving continuous-time, stochastic control problems by establishing a necessary condition for optimality. In simple terms, the HJB equation is a mathematical formula used to […]

Gradient-based methods are a category of optimization techniques used in quantitative finance. They use the concept of a gradient, which is a vector indicating the direction of the steepest ascent of a function. These methods are particularly effective in scenarios involving continuous and differentiable objective functions.   Key Takeaways – Gradient-Based Methods in Quantitative Finance […]

In quantitative finance, heuristic and metaheuristic algorithms help in solving complex problems where traditional optimization methods may not be efficient or might fail to provide satisfactory solutions. These methods are especially useful in scenarios involving large-scale portfolio optimization, algorithmic trading strategies, and objectives characterized by complexity, non-linearity, and multimodality. They’re often borrowed from events we […]

The Zillow Zestimate and other Automated Valuation Models (AVMs) like it are designed to provide an estimate of a property’s market value using algorithmic modeling. These models typically rely on a combination of publicly available data, historical transaction data, and various computational techniques. They involve statistical analysis (like regressions) and often basic machine learning algorithms. […]

Non-parametric models in finance are valuable for their flexibility and adaptability to various types of financial data. They’re particularly useful in scenarios where the underlying data doesn’t conform to standard distributional assumptions (e.g., normal distribution). We’ll cover many examples of non-parametric mathematical models in finance.   Key Takeaways – Non-Parametric Models in Finance & Trading […]