Review of Discrete and Continuous Processes inFinance: Theory and Applications
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"]