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Dr. Sarah Chen, Ph.D.

Senior Quantitative Strategist & Statistical Modeling Lead
Head of Mathematical Risk & Volatility Analytics

Ph.D. in Financial Mathematics and Senior Quantitative Strategist. Expert in stochastic volatility modeling, 14-period Wilder RSI smoothing, MVRV Z-Scores, and capital preservation mathematics.

Professional Credentials & Background
  • Ph.D. in Financial Mathematics & Applied Probability
  • Author of peer-reviewed papers on volatility clustering in digital assets
  • Architect of the BitcoinCrypto Dynamic Position Sizing Calculator
  • Lecturer on Quantitative Risk Management & On-Chain Valuation
Areas of Quantitative Research & Market Expertise
Stochastic Volatility & ATR Dynamic EnvelopesMVRV Z-Score & Realized Price Mathematical ModelingWilder's RSI & Moving Average Convergence DivergenceKelly Criterion & Fixed-Fractional Risk SizingBehavioral Finance & Harmonic Mean Dollar-Cost Averaging

About Dr. Sarah Chen, Ph.D.

Dr. Sarah Chen leads quantitative statistical modeling and risk architecture at BitcoinCrypto.tech. Holding a Ph.D. in Financial Mathematics and Applied Probability, Dr. Chen's academic and professional work centers on non-linear price distributions, stochastic calculus, and mathematical capital preservation strategies in highly volatile asset classes.

At BitcoinCrypto.tech, Dr. Chen oversees the statistical calibration of the 6-pillar confluence scoring model, Wilder's smoothed Relative Strength Index (RSI), Average True Range (ATR) dynamic volatility bands, and harmonic-mean dollar-cost averaging formulas.

Dr. Chen is a passionate advocate for financial literacy and mathematical risk management, emphasizing that long-term survival in digital asset markets depends strictly on position sizing formulas (such as the Kelly Criterion and maximum drawdown limits) rather than speculative intuition.

Published Research & Analysis

Peer-reviewed quantitative articles authored by Dr. Sarah Chen, Ph.D.

2 Papers
Quantitative Math• 15 min read•Aug 2026

Volatility Clustering and ATR Regimes: Designing Adaptive Stop-Loss and Target Frameworks

Mathematical modeling of volatility clustering, Average True Range (ATR) expansion, and dynamic trade management.

#Volatility#ATR#Risk Management
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Investment Strategies• 15 min read•Oct 2026

Bitcoin Dollar-Cost Averaging (DCA) Math: Dynamic Sentiment-Weighted Value Averaging vs Lump Sum Across 4-Year Halving Cycles

The definitive mathematical study comparing conventional DCA, lump-sum investing, and sentiment-weighted dynamic value averaging. Discover how scaling Bitcoin purchases using Fear & Greed Index regimes and on-chain MVRV Z-Scores enhances Sharpe ratios and suppresses portfolio drawdowns.

#Bitcoin DCA#Dollar Cost Averaging#Value Averaging
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