Quantitative Research: Market Inefficiencies & Risk Modeling in Prediction Markets
Estimated duration
~3d
Deadline
Not specified
Location
📍 Remote only
PRICING
USD
DESCRIPTION
We are seeking a highly skilled Quantitative Researcher or Financial Mathematician to conduct a rigorous analysis of the mathematical and statistical viability of systematic trading on decentralized prediction markets (such as Polymarket and Kalshi).
IMPORTANT: This is a pure financial modeling, market microstructure, and statistical validation mandate. You are NOT expected to write production code, build execution bots, or test software architecture. The underlying codebase will be handled independently; your sole focus is the quantitative theory, mathematical proofs, and risk frameworks.
Core Areas of Focus:
- Market Microstructure & Behavioral Alpha: Analyze prediction market order books to determine how a retail-dominated user base and emotional trading behavior create predictable price dislocations, volatility spikes, and mean-reverting tendencies. 2.Mathematical Contract Modeling: Formulate rigorous frameworks for true probability extraction ("de-vigging" algorithms) and capital allocation models (e.g., adapted Kelly Criterion variants) for both binary and complex multi-outcome categorical markets.
- Fee Drag & Friction Analysis: Evaluate how exchange transaction fees—specifically dynamic fee structures tied to contract uncertainty/entropy—impact the mathematical edge of aggressive trading (taker) versus passive liquidity provision (maker).
- Oracle & Settlement Risk Quantification: Model the structural risks associated with decentralized resolution. Quantify the potential for governance manipulation, voter collusion, and settlement delays (such as UMA Optimistic Oracle disputes), and formulate a dynamic risk premium equation to account for these variables.
DEFINITION OF DONE
The task will be considered complete when the researcher delivers a comprehensive, academically rigorous Research Brief and Mathematical Specification. The delivery must include:
- A detailed written analysis of the identified market inefficiencies and behavioral skews.
- Formal LaTeX equations defining the probability extraction algorithms, optimal capital sizing (Kelly variant), and fee-drag boundaries.
- A completed theoretical framework/equation for the Oracle Risk Premium variable.
- A clean decision matrix mapping out the exact mathematical thresholds under which a market becomes statistically viable or systemically toxic.
REQUIRED EVIDENCE
EVIDENCE DETAILS
Please upload the final research paper and mathematical specification as a single, beautifully formatted PDF or Markdown document containing all required LaTeX equations and analysis.
REQUIREMENTS
- •
Advanced background in Quantitative Finance, Financial Mathematics, Statistics, or Actuarial Science.
- •
Deep understanding of market microstructure, order book dynamics, and liquidity modeling.
- •
Familiarity with prediction markets or binary options structures.
- •
Ability to formulate clean, production-ready mathematical specifications using LaTeX.
- •
Strong statistical backtesting capabilities (theoretical layout and data analysis).
SKILLS NEEDED
REQUIRED LINKS
COMMENTS
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PRICING
USD
FINDER'S FEE
$4
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