Paper: arXiv 2604.01431

Authors: Hardhik Mohanty, Bhaskar Krishnamachari

Abstract

Daily probability changes in Kalshi macro prediction markets forecast cryptocurrency realized volatility through two distinct channels. The monetary policy channel, measured by Fed rate repricing on KXFED contracts, predicts Bitcoin volatility in sample with t = 3.63 and p < 0.001 but exhibits regime dependence tied to the 2024-2025 rate-cutting cycle. The recession risk signal from KXRECSSNBER proves more stable out of sample, delivering an MSFE ratio of 0.979 with Clark-West p = 0.020. The inflation channel, measured by CPI repricing on KXCPI contracts, predicts altcoin volatility for Ethereum, Solana, Cardano, and Chainlink with t-statistics ranging from -2.1 to -3.4 and out-of-sample gains for Ethereum at MSFE = 0.959 with p = 0.010 and Solana at p = 0.048. Both the Bitcoin–Fed-dovish and Chainlink–CPI specifications survive Benjamini-Hochberg correction at q = 0.05. Orthogonalization and baseline comparisons against Fed Funds futures, Treasury yields, and the Deribit implied volatility index confirm that these signals carry information not embedded in conventional financial instruments. The sample covers ten Kalshi event series and six cryptocurrency assets over January 2023 to March 2026.

Complexity vs Empirical Score

  • Math Complexity: 4.5/10
  • Empirical Rigor: 8.5/10
  • Quadrant: Street Traders — practical and empirical, lighter on theory

Why this score: The paper presents a highly empirical and novel investigation into using prediction market probabilities (Kalshi) to forecast cryptocurrency volatility. It employs rigorous out-of-sample statistical testing (Clark-West, Benjamini-Hochberg) and benchmark comparisons, though the underlying mathematical framework relies on linear regression and time-series econometrics rather than heavy mathematical proofs.

Research Flowchart

  flowchart TD
    A["Research Goal: Evaluate if Kalshi Prediction Markets<br>Forecast Crypto Volatility"] --> B["Data Inputs (Jan 2023–Mar 2026):<br>10 Kalshi Macro Series & 6 Crypto Assets"]
    B --> C["Methodology: Time Series Regressions,<br>Orthogonalization & Out-of-Sample MSFE"]
    C --> D["Multiple Testing Correction:<br>Benjamini-Hochberg (q = 0.05)"]
    D --> E["Findings: Monetary/Recession Signals<br>Predict Bitcoin Volatility"]
    D --> F["Findings: Inflation Signals (KXCPI)<br>Predict Altcoin Volatility"]

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0 of 37 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.