Blog Posts

Autocorrelation is the degree of similarity between a given time series and a lagged version of itself. In other words, it quantifies how similar a time series – e.g., interest rates, stock prices – is to itself at different points in time. A high autocorrelation means that the time series is highly similar to itself […]

In finance, Master Equations are a set of mathematical tools used to model and understand various financial processes. They mostly involve stochastic elements. These equations are used in quantitative finance for modeling the dynamics of financial markets and instruments.  They form the backbone of many advanced financial models, including those used for option pricing, risk […]

Spline models can be used in finance for modeling and interpolating financial data, which often exhibits non-linear patterns. These models are frequently applied in yield curve modeling, option pricing, and risk management.   Splines in Simple Terms A spline is a type of mathematical function used to create smooth curves. Imagine you have a series […]

Currency overlay is an investment strategy employed by institutional investors to protect their portfolios from currency fluctuations. The currency overlay manager first identifies the currency risk exposure of the portfolio, and then enters into currency hedging transactions to offset that risk. Currency overlay can be used to hedge both: currency risk arising from investments denominated […]

For traders, investors, and market participants, an understanding of various probabilistic, statistical, and analytical techniques is important for making good decisions when the future is unknown. Markets are heavily an applied probability exercise.  Each of these techniques and methods offers unique modeling capabilities and enables finance professionals to tackle specific and complex challenges – assessing […]

Bayesian analysis in finance, trading, and investing is a framework that incorporates probabilistic modeling and decision-making under uncertainty. This approach is based on Bayesian inference, where prior beliefs are updated with new information to form posterior beliefs.   Key Takeaways – Bayesian Methods in Finance Bayesian methods in finance offer a probabilistic framework for incorporating […]

Agent-Based Modeling (ABM) is a very important aspect of financial market analysis and prediction, but is one of the least talked about. It operates under a different paradigm compared to traditional economic and financial models, which often rely on equilibrium theories (e.g., value investing, discounted cash flow) and aggregate market behaviors. In ABM, the market […]

When constructing a portfolio with nominal bonds and inflation-linked bonds, several considerations come into play, particularly concerning the different characteristics and environmental biases of these two types of bonds. We’ll cover these matters in this article.   Key Takeaways – Inflation-Linked Bonds vs. Nominal Bonds Risk and Inflation Protection: Inflation-linked bonds offer some protection against […]

Stochastic Optimal Control represents a mathematical framework used to determine optimal decision-making strategies in situations where outcomes are: partly random, and partly under the control of a decision-maker (e.g., trading, investing, financial decision-making) This concept is rooted in the theory of stochastic processes and optimal control theory. Stochastic Process A stochastic process is a mathematical […]

When comparing Python and C++ for financial algorithms, particularly in quantitative finance and economics, it’s important to consider several factors, including: performance ease of use library support, and the specific requirements of the task at hand We’ll go through each category by category.   Key Takeaways – Python vs. C++ for Financial Algorithms Performance: C++ […]