A research-grade framework for forecasting tokenomic gene evolution across market cycles. Analyzes historical gene frequencies, models behavioral drift, and predicts future gene expression using interpretable trend and moving-average forecasting. Designed for tokenomics research, risk analysis, and evolutionary cryptoeconomics.
data-science time-series forecasting research-tool python-cli cryptoeconomics trend-analysis blockchain-analytics behavioral-economics tokenomics decentralized-finance risk-modeling smart-contract-analysis onchain-analysis market-cycles gene-drift defi-research tokenomic-genes economic-evolution tokenomics-research
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Updated
Nov 30, 2025 - Python