Scoring Methodology
To navigate the high-volume landscape of quantitative finance, thequant.space utilizes a dual-axis scoring framework. This system decomposes complex ArXiv research into two primary dimensions: Theoretical Complexity and Empirical Rigor.
The Classification Framework
1. Math Complexity
This metric quantifies the “theoretical overhead” required to parse the paper. We analyze the density of mathematical notation and the sophistication of the underlying machinery.
- High Score (7–10): Heavy reliance on Stochastic Calculus, Partial Differential Equations (PDEs), bespoke optimization proofs, or advanced topology.
- Low Score (1–3): Primarily descriptive statistics, high-level conceptual frameworks, or basic linear algebra.
2. Empirical Rigor
This metric assesses the “path to implementation.” We look for signals that the strategy has been stress-tested against the realities of the market.
- High Score (7–10): Extensive backtesting on high-fidelity data (Tick-level, WRDS, Bloomberg), clear mention of transaction costs, and rigorous out-of-sample validation.
- Low Score (1–3): Use of “toy” datasets, synthetic data, or purely logical derivations without historical verification.
Penalty flags
Practitioners trust a backtest only as far as its execution assumptions go, so every empirical paper page carries four flags above the summary:
| Flag | Values | What it means |
|---|---|---|
| Transaction costs | Modeled · Partial · Not modeled | Modeled: an explicit cost model (commission, spread or slippage in bps, or a market-impact model) is applied to the reported results. Partial: costs are only discussed, tested in a sensitivity or break-even table, or a fee is charged without spread or slippage for a high-turnover strategy. |
| Out-of-sample | Hold-out · Walk-forward · Cross-validation · None | How the reported results were validated on data the model never saw. |
| Data | L2 order book · Tick · Intraday bars · Daily · Weekly / monthly · Synthetic only | The finest resolution of market data used in the evaluation. |
| Code | available · not found | The authors’ own public repository, checked to be live (papers with code). |
The cap. Empirical Rigor is capped at 6.0 when a paper reports trading or execution results without explicitly modelling transaction costs, or reports trading, execution or forecasting results without any out-of-sample test. The page then shows the capped score, the score before the cap, and the reason. The cap never applies to theory, surveys, pricing or calibration papers, or to descriptive empirical studies.
How the flags are set. A structured-decision model reads the paper’s data, method, results and conclusion sections and answers each question with a calibrated probability. When it isn’t sure, a second model is asked. A flag the models still aren’t confident about is shown as Unclear, and an unclear flag never triggers the cap. The setup was chosen on a hand-checked set of 40 papers, where it capped no paper wrongly. Flags are automated, so if one is wrong, say so in the comments on the paper’s page.
Strategic Quadrants
By plotting these scores, we categorize research into four distinct strategic “vibes.” This allows you to filter papers based on your current objective—whether it’s deep R&D or immediate alpha generation.
| Quadrant | Designation | Strategic Utility |
|---|---|---|
| High Math + High Rigor | Holy Grail | Institutional-grade research. Validated theory ready for sophisticated production environments. |
| High Math + Low Rigor | Lab Rats | The “Research Frontier.” Highly innovative math that lacks empirical testing—high potential for “hidden” alpha. |
| Low Math + High Rigor | Street Traders | Applied Alpha. Robust, data-driven strategies that prioritize execution and simplicity over theoretical flair. |
| Low Math + Low Rigor | Philosophers | Market Meta-Analysis. Conceptual frameworks and “think pieces” that shape broad market perspectives. |
Current Library Distribution
| Quadrant | Papers | Share |
|---|---|---|
| Holy Grail | 2,357 | 43% |
| Lab Rats | 1,811 | 33% |
| Street Traders | 901 | 16% |
| Philosophers | 476 | 9% |
The Strategic Map
Each dot is one paper. Scores come in half-point steps, so dots are spread slightly within their cell; hover shows the exact score and how many papers share it. Click a dot to open the paper.
Pro-Tip: Identifying “Alpha Clusters” Watch for clusters in the Lab Rats quadrant. These represent theoretical breakthroughs that have not yet been commoditized by the broader market. Bridging the gap from Lab Rat to Street Trader is where individual quants find their edge.
Disclaimer: Scoring is performed via automated semantic analysis. If you believe a paper has been misclassified, please open an issue.