Calculating Profits and Losses for Algorithmic Trading Strategies: A Short Guide
Calculating Profits and Losses for Algorithmic Trading Strategies: A Short Guide ArXiv ID: 2411.14068 “View on arXiv” Authors: Unknown Abstract We present a series of equations that track the total realized and unrealized profits and losses at any time, incorporating the spread. The resulting formalism is ideally suited to evaluate the performance of trading model algorithms. Keywords: realized profit/loss, unrealized profit/loss, spread, trading algorithms, performance evaluation, Trading Strategies Complexity vs Empirical Score Math Complexity: 3.5/10 Empirical Rigor: 2.0/10 Quadrant: Philosophers Why: The paper presents a series of algebraic equations to formalize profit and loss calculations, which is moderately math-intensive but lacks the deep stochastic calculus or advanced statistics often seen in quant finance research. Empirically, it is a theoretical guide with illustrative examples but no backtested performance, real-world datasets, or implementation code. flowchart TD A["Research Goal: Develop<br>algorithms to track<br>realized & unrealized PnL"] --> B["Key Methodology: Mathematical Formalism"] B --> C["Data/Inputs: Trades, Prices, Spread"] C --> D["Computational Process:<br>Equations for PnL Calculation"] D --> E["Key Findings: Robust<br>Performance Evaluation"]