Blog Posts

Affine Term Structure Models (ATSMs) are a class of models used in finance to describe the evolution of interest rates or the term structure of interest rates. These models are characterized by the fact that the yield of a bond at any given time can be expressed as an affine (i.e., linear) function of factors […]

Fast Fourier Transform (FFT) pricing is a computational technique in financial quantitative analysis. It’s used primarily for the pricing of options and other financial derivatives. FFT transforms complex pricing models into a more manageable form to perform efficient calculations and analysis.   Key Takeaways – Fast Fourier Transform Pricing Computation Efficiency Fast Fourier Transform (FFT) […]

Rough volatility models emerged from empirical observations that the volatility of financial markets does not behave smoothly. Instead, it displays “roughness,” and needed better quantitative models to represent it accurately.   Key Takeaways – Rough Volatility & Bergomi Model Non-Smooth Volatility – Rough volatility models, including the Bergomi model, capture the observed rough, non-smooth nature […]

There are many games that share similarities to trading. In fact, some of them you can also make money from. Here we’ll take a look at the games most similar to trading.   Key Takeaways – Games Most Similar to Trading We look at the games most similar to trading. These game concepts, when applied […]

Hidden Markov Models (HMMs) are statistical models that represent systems with hidden states. These models are useful in fields like speech recognition, bioinformatics, and financial analysis. They capture the idea that the observed outputs of a system are the result of states that are not directly visible or “hidden.”   Key Takeaways – Hidden Markov […]

Hidden variables in finance refer to elements that aren’t directly observable or quantifiable but significantly influence financial markets and investment outcomes. These variables often exist beneath the surface of standard financial analyses, impacting asset performance, market movements, and risk assessments.   Key Takeaways – Hidden Variables in Finance Hidden variables in finance, like central bank […]

Quantization in finance refers to a mathematical technique used to reduce the number of continuous state variables into a finite state space. This process simplifies complex financial models while attempting to retain their essential characteristics and predictive power. The main idea is to represent a range of values with a single representative value, effectively discretizing […]

Inflation-linked bonds (ILBs) – also commonly called inflation-indexed bonds, inflation-protected bonds, or linkers – are a type of fixed income security where the principal is indexed to the rate of inflation or deflation. The concept of the inflation-linked bond is not new. People want to own securities that give them a steady stream of income, […]

Multi-Objective Optimization (MOO) refers to mathematical processes designed to optimize multiple conflicting objectives simultaneously. Unlike single-objective optimization, which focuses on one goal, MOO addresses scenarios where trade-offs between two or more objectives must be made. This complexity is common in fields like engineering, finance, economics, policymaking, and logistics.   Key Takeaways – Multi-Objective Optimization Balanced […]

Multiple-Criteria Decision Analysis (MCDA) is a decision-making process involving multiple, often conflicting criteria. It’s used in fields where decisions can’t be made based purely on a single criterion, like in economics, finance, policymaking, and management.   Key Takeaways – Multiple-Criteria Decision Analysis (MCDA) Holistic Evaluation MCDA facilitates decision-making by evaluating options against multiple (often conflicting) […]