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The Omniscient, yet Lazy, Investor

The Omniscient, yet Lazy, Investor ArXiv ID: 2510.24467 “View on arXiv” Authors: Stanisław M. S. Halkiewicz Abstract We formalize the paradox of an omniscient yet lazy investor - a perfectly informed agent who trades infrequently due to execution or computational frictions. Starting from a deterministic geometric construction, we derive a closed-form expected profit function linking trading frequency, execution cost, and path roughness. We prove existence and uniqueness of the optimal trading frequency and show that this optimum can be interpreted through the fractal dimension of the price path. A stochastic extension under fractional Brownian motion provides analytical expressions for the optimal interval and comparative statics with respect to the Hurst exponent. Empirical illustrations on equity data confirm the theoretical scaling behavior. ...

October 28, 2025 · 2 min · Research Team

Optimizing Broker Performance Evaluation through Intraday Modeling of Execution Cost

Optimizing Broker Performance Evaluation through Intraday Modeling of Execution Cost ArXiv ID: 2405.18936 “View on arXiv” Authors: Unknown Abstract Minimizing execution costs for large orders is a fundamental challenge in finance. Firms often depend on brokers to manage their trades due to limited internal resources for optimizing trading strategies. This paper presents a methodology for evaluating the effectiveness of broker execution algorithms using trading data. We focus on two primary cost components: a linear cost that quantifies short-term execution quality and a quadratic cost associated with the price impact of trades. Using a model with transient price impact, we derive analytical formulas for estimating these costs. Furthermore, we enhance estimation accuracy by introducing novel methods such as weighting price changes based on their expected impact content. Our results demonstrate substantial improvements in estimating both linear and impact costs, providing a robust and efficient framework for selecting the most cost-effective brokers. ...

May 29, 2024 · 2 min · Research Team