Review of Discrete and Continuous Processes inFinance: Theory and Applications

ArXiv ID: ssrn-1373102 “View on arXiv”

Authors: Unknown

Abstract

We review the main processes used to model financial variables. We emphasize the parallel between discrete-time processes, mainly used by econometricians for ri

Keywords: Financial Modeling, Stochastic Processes, Time Series Econometrics, Discrete-time Processes, Econometrics

Complexity vs Empirical Score

• Math Complexity: 8.5/10
• Empirical Rigor: 3.0/10
• Quadrant: Lab Rats
• Why: The paper is dense with advanced mathematics like stochastic calculus, PDEs, and detailed derivations of processes (e.g., Ornstein-Uhlenbeck, fractional Brownian motion). However, it lacks backtesting, code examples beyond mention, or empirical datasets, focusing instead on theoretical review and intuition.

  flowchart TD
    A["Research Goal:\nReview & Compare Discrete vs. Continuous\nFinancial Processes"] --> B{"Methodology"}
    B --> C["Literature Review"]
    B --> D["Theoretical Analysis"]
    
    C --> E["Data/Inputs:\nEconometric Theory\nFinancial Models\nStochastic Processes"]
    D --> E
    
    E --> F["Computational Process:\nParallel Comparison of\nDiscrete-time vs. Continuous-time\nModeling Frameworks"]
    
    F --> G["Key Findings:\n1. Discrete-time: Preferred for Econometrics\n2. Continuous-time: Preferred for Derivatives\n3. Bridging the gap improves forecasting"]