Sean Wang Email & Phone Number

New York, Ny, Us

Global, Remote First, Us

Develop systematic and standardized analytics solutions with reference data aggregating data across crypto exchange/OTC liquidity providers and blockchains, including constructing factors, estimating implied volatility surfaces, extracting data metrics from blockchains, DeFi protocols and stablecoins offering staking/lending/pooling/farming, and establishing risk metrics for crypto referenced ETPs (exchange traded products) and structured products.

Fort Lee, New Jersey, Us

Devised systematic tools to empower the institutional-grade digital asset trade execution providing cross-exchange liquidity, crypto market neutral strategies relative to fiat currencies, as well as portfolio and risk management. Designed 3 trading strategies: Arbitrage utilizing negative cycle detection; Liquidity capturing spreads and volatility skews; Momentum based on volatility break-out, particularly in providing the downside hedge. Created basis/spread trading signals using Python for co integrated crypto assets. Developed risk models to set risk limits, reduce portfolio concentration risk through systematic exposure sizing, and alarm liquidity risk across digital assets, exchanges, markets, and funding constraint.

New York, Ny, Us

Led a global team of 8 developers to develop market risk models (VaR/Stressed VaR/IRC/CRM/IDL/DRC) that calculate potential daily losses, regulatory capital and RWA, compliant with Basel 2.5/3 and FRTB transition, and to design scenarios used by ICAAP (e.g. BAU stress testing for risk limit setting) and regulatory regimes, such as CCAR stress testing. Addressed Model Validation and Internal Audit effective challenges, and remediated regulatory matters. Coordinated with risk managers, desk strategists, stress testing team, Finance, and Risk IT, and reported to stakeholders and the senior management.Created new methodologies to enhance risk and regulatory capital measurement, e.g. calibrating CDS spreads implied factor loadings used by asymptotic multi-risk-factor models to simulate correlated credit rating migration and defaults, adding equity exposures by assigning equity ratings from CDS spreads with equity volatilities, estimating granular transition probability matrices and correlated recovery rates to distinguish credit cohorts with different ratings, industries, and regions, and developing a unified IDL model reducing production cycle by weeks that utilizes importance sampling to simulate PnLs conditional on the default of large counterparties.More than doubled the granularity of instantaneous market shocks, strengthened the coherence across risk factors of all asset classes, and improved the consistency among risk identification, scenario narratives, and stress scenarios to enhance stress testing utilizing PCA to find patterns, as well as regression, regularization, and independent/dependent/expansion reduced form approaches to make predictions. Contributed to credit limits and ICAAP economic capital measurement in simulating interest rates and other risk factors to produce derivatives’ future positive exposures for EAD estimation with PFE add-on, as well as CVA given the probability and severity of a counterparty default as implied by its credit spreads.

New York, Ny, Us

Developed intra-day statistical arbitrage models, such as multifactor expected alpha models, to generate trading signals used for optimal portfolio construction, while monitoring portfolio risks. Constructed excess return influencing factors to make predictions utilizing econometrics, time series analysis, data analytics, regression/data classification/decision trees, as well as by identifying patterns in market and analysts data through PCA and cluster analysis. Backtested the efficacy of fundamental, idiosyncratic, macro and statistical factors, such as company sizes and financial strengths, price momentum and reversal, volatility of returns, economic indices, and analyst skills associated with their revisions on earnings, recommendations or target prices. Measured portfolio risks, set risk limits, and monitored portfolio exposures. Expanded the usage of effective alpha models to trade in Asia-Pacific markets.

New York, Ny, Us

Created path-dependent tactical asset allocation models among stocks, bonds, and hedge funds based on equity risk premium, yield curve movements, CDS spreads, and bond spreads, as well as multifactor hedge fund ranking models utilizing the measurement of asymmetric risk-adjusted rate of returns under up and down markets, and dynamic beta sensitivities to markets. Co-wrote regular reviews of multi-asset exposures (covering equities, credits, interest rates, fixed income securities, currencies, commodities, and derivatives) through investment in various hedge fund strategies (e.g., discretionary, arbitrage, event-driven, CTA/managed futures, and global macro) informing decision-making.