Blog Posts

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) […]

Bayesian Efficiency, based in Bayesian probability theory, is used in financial modeling and decision-making. It involves updating the probability of a hypothesis as more evidence or information becomes available. In finance, this concept is applied to continuously refine trading strategies and risk assessments based on incoming data.   Key Takeaways – Bayesian Efficiency Bayesian Efficiency […]

Pareto Efficiency, a concept derived from economics, is used in financial decision-making. It refers to a state in which reallocating resources can’t make any individual better off without making someone else worse off. In a Pareto Efficient market, resources are allocated optimally. It reflects an equilibrium where no further gains can be achieved without incurring […]

Sector rotation is a strategy used in financial markets, where traders/investors allocate their investments across various economic sectors at different times, aligning with the business cycle. This approach is predicated on the observation that different sectors of the economy perform differently during various phases of the business cycle.   The Business Cycle and Sector Performance […]

Dynamic Asset Allocation (DAA) is a strategy that involves frequent adjustments to the mix of asset classes within an investment portfolio. This approach contrasts with static asset allocation, which maintains a fixed allocation of assets over time. The dynamic strategy is used to capitalize on market inefficiencies or economic changes, with the goal of optimizing […]