Tag: Probability Theory

  • Antifragility


    Nassim Nicholas Taleb’s antifragility describes systems that gain from stress, differentiating from mere resilience. This principle, applicable from biological to economic systems, underscores growth and adaptation amidst volatility and unpredictability.

  • Ergodicity


    Originating in thermodynamics, the concept of ergodicity posits that systems, over extended periods, equally traverse every possible state. Beyond its foundational role in physics, ergodicity impacts disciplines from mathematics to economics, shaping understanding of prolonged system dynamics.

  • Sensitivity Analysis

    Sensitivity Analysis

    Sensitivity Analysis quantifies the impact of variable changes on a specific outcome within a model. Employed across various disciplines, it aids in risk assessment, model validation, and decision-making, offering metrics to represent sensitivity.

  • Monte Carlo Simulation

    Monte Carlo Simulation

    Utilizing statistical sampling, Monte Carlo Simulation offers insights into risk and uncertainty within predictive models. By generating a spectrum of outcomes from random inputs, it finds applications in fields like finance and engineering. Its precision is contingent on the accuracy of the underlying model and inputs.

  • Fat Tail Events

    Fat Tail Events

    Fat Tail Events denote uncommon, large deviations from averages, often linked with significant financial shifts. These are characterized by a greater likelihood of extreme occurrences than typical predictions suggest. Their profound impact, as witnessed in events like the 2008 financial crisis, underscores the importance of understanding and managing such phenomena.

  • Expected Value

    Expected Value

    Expected value, a cornerstone of statistics and probability, indicates the average outcome of repeated events. Despite its ubiquity in fields such as economics and decision-making, it doesn’t predict individual outcomes and can be skewed by outliers. Its broad applications necessitate considering ethical implications due to potential unequal impacts.

  • Null Hypothesis

    Null Hypothesis

    In statistical hypothesis testing, the null hypothesis asserts a lack of effect and serves as a baseline for evaluation. Specific tests are employed to assess evidence, leading to either the rejection or the failure to reject this initial assumption. This methodology is pivotal in both scientific inquiry and rational decision-making.