VOLATILITY TRADING (PORTFOLIO HEDGE) VIA QUANTITATIVE MODELING IN EXCEL – AllQuant
COURSE OVERVIEW
This program institutionalizes volatility risk premium capture strategies—practiced by hedge funds—into a deployable Excel-based system. The curriculum focuses on constructing systematic trades that generate returns during calm markets while providing portfolio hedge characteristics during crisis periods. Participants build a complete volatility trading model without programming, chart reading, or continuous news monitoring.
Core Value Proposition: Acquire a defensive quantitative strategy requiring five minutes of daily operation, grounded in observable market phenomena rather than forecasting.
LEARNING OBJECTIVES
Upon completion, participants will demonstrate competency in:
Volatility Risk Premium Mechanics: Capturing the spread between implied and realized volatility through ETF-based instruments
Quantitative Investing Protocols: Distinguishing systematic volatility strategies from directional equity approaches
Excel Implementation: VLOOKUP, INDEX/MATCH, array formulas, and conditional logic for signal generation
Risk Analytics: Computing volatility-adjusted returns, Sharpe ratio, drawdown metrics, and tail risk measures
Transaction Cost Integration: Modeling slippage and commissions specific to volatility products
Leverage Application: Understanding margin requirements for amplified volatility exposure
Performance Tracking: Building dashboards for real-time hedge effectiveness monitoring
Multi-Strategy Context: Positioning volatility trading within broader portfolio allocation frameworks
COURSE CONTENT STRUCTURE
Total Duration: Approximately 5 hours across 6 sections
SECTION 1: INTRODUCTION (15 minutes)
Volatility as an asset class: VIX futures, volatility ETFs, and options-based replication
Strategy role: income generation versus crisis alpha
Course roadmap and performance expectations
SECTION 2: CONCEPT OF VOLATILITY RISK PREMIUM (75 minutes)
Empirical evidence: persistent spread between implied and realized volatility
Structural drivers: investor preference for crash protection, behavioral biases
Instrument selection: VXX, SVXY, UVXY criteria and contango/backwardation dynamics
Strategy weaknesses: volatility regime shifts, central bank interventions, ETF decay mechanics
Hedge characteristics: correlation breakdown during equity market stress
SECTION 3: EXCEL CRASH COURSE (45 minutes)
Critical functions: VLOOKUP, INDEX/MATCH, logical operators, statistical arrays
Time series data alignment for volatility term structures
Dynamic charting for VIX futures curve visualization
Error checking protocols for model audit trails
SECTION 4: FINANCIAL MATHEMATICS (60 minutes)
Log returns for high-volatility instruments
Rolling volatility estimation for position sizing
Sharpe ratio calculation with zero or negative risk-free rate handling
Contango cost quantification and drag attribution
Leverage ratio mathematics and margin call risk modeling
SECTION 5: BUILDING THE VOLATILITY RISK PREMIUM MODEL (120 minutes)
Yahoo Finance data retrieval for VIX futures and ETF prices
Signal construction: rolling volatility percentile thresholds
Entry/exit logic: VIX level-based scaling and term structure filters
Transaction cost integration: ETF expense ratios and bid-ask spreads
Backtesting engine: simulating short-volatility strategies with risk caps
Hedging overlay: sizing volatility long positions against equity portfolio beta
SECTION 6: VOLATILITY RISK PREMIUM OPERATIONS (45 minutes)
Daily workflow: data update, signal verification, order sizing (5-minute protocol)
Risk monitoring: vega exposure, contango drag, margin utilization
Performance logging: separating premium capture from hedge payoffs
Crisis protocol: when and how to exit short-volatility positions
Dashboard creation: extracting key metrics for decision support
DELIVERABLES & RESOURCES
Fully Completed Model File: Live-ready Excel workbook with volatility term structure analytics, signal generation, and hedging calculators
Guided Build Templates: Step-by-step worksheets for progressive model construction
Practice Exercises: Financial mathematics problem sets with detailed solutions focusing on volatility scaling
Bulk Data Tool: VBA-enabled Excel file for automated Yahoo Finance VIX and ETF data retrieval
Performance Analytics Worksheet: Pre-built metrics calculator for Sharpe ratio, Sortino ratio, and contango-adjusted returns
Decision Dashboard: Interactive summary interface for signal extraction and hedge ratio determination
TARGET AUDIENCE PROFILE
Portfolio managers seeking systematic hedging tools without options trading complexity
Investment advisors constructing resilient multi-asset portfolios for high-net-worth clients
Sophisticated self-directed investors managing ₹50+ lakh equity portfolios requiring crash protection
Risk officers at family offices evaluating non-correlated return streams
Quantitative analysts building strategy diversification within hedge fund structures
Individuals seeking speculative high-return strategies (focus is defensive)
Traders lacking understanding of contango/backwardation mechanics (will incur predictable losses)
Participants without intermediate Excel proficiency (model debugging will be problematic)
Investors unable to maintain discipline during volatility spikes (strategy requires consistent execution)
PREREQUISITES & TECHNICAL REQUIREMENTS
Foundational derivatives knowledge: futures, options basics, settlement mechanics
Statistics: percentile ranks, standard deviation, correlation
Understanding of portfolio beta and hedging concepts
Microsoft Excel 2016 or later with VBA macros enabled
Stable internet connection for daily data retrieval
No prior VBA or Python knowledge required
Software Provision: All analysis uses free resources; no mandatory data vendor subscriptions
INSTRUCTOR BIOGRAPHIES
ENG GUAN – CO-FOUNDER & LEAD INSTRUCTOR
Quantitative investment practitioner with 15+ years spanning sovereign wealth funds, investment banks, proprietary trading desks, and multi-strategy hedge funds. Most recent role: key Portfolio Manager at a Singapore-based multi-strategy hedge fund, managing cross-asset systematic strategies with direct P&L responsibility. Holds MSc in Financial Engineering specializing in derivatives pricing and optimal execution algorithms.
Pedagogical Edge: Direct hedge fund implementation experience ensures instruction reflects operational realities: transaction cost management, leverage constraints, and institutional risk mandates. Sovereign wealth fund background provides long-horizon capital preservation principles.
PATRICK LING – CO-FOUNDER & SENIOR INSTRUCTOR
15+ years of comprehensive investment industry experience across private banking (UBS), investment banking (Goldman Sachs), and hedge fund portfolio management. As a key Portfolio Manager at the same Singapore-based multi-strategy hedge fund, he co-managed systematic equity strategies and developed proprietary risk analytics. Holds MSc in Wealth Management, integrating quantitative techniques with high-net-worth client portfolio construction.
Pedagogical Edge: Private banking experience translates quantitative concepts into executable processes for non-institutional investors. Hedge fund tenure provides insight into multi-strategy portfolio integration and factor diversification—critical context for preventing over-reliance on volatility trading as single alpha source.
Joint Credibility: Both instructors maintain parallel practitioner careers, ensuring curriculum evolves with current industry standards.
METHODOLOGICAL APPROACH
The course employs a "build-operate-improve" framework. Participants construct a baseline short-volatility model, operate it through historical regimes (including 2008 and 2020), then iteratively add hedging overlays and leverage controls. Each module includes validation checkpoints where learners test their model against known crisis outcomes before advancing.
Instruction explicitly addresses why volatility risk premium exists (behavioral risk aversion, regulatory constraints) and when it collapses (volatility-of-volatility spikes, liquidity crises). This prevents blind implementation and cultivates adaptive execution essential for strategy survival.
Time Commitment: While video instruction totals 5 hours, practical implementation requires an estimated additional 3-5 hours of independent model building and parameter calibration. Five-minute daily operation assumes stable model and reliable data feeds.
STRATEGY SCOPE & LIMITATIONS
Geographic Application: Explicit model calibrated for U.S. volatility products (VIX futures curve, ETFs: VXX, SVXY, UVXY) to ensure data availability. Mathematical architecture is transferable to India VIX futures or other volatility indices where liquid ETFs exist.
Asset Class Constraints: Focuses exclusively on volatility ETF trading; does not teach direct options trading, variance swaps, or VIX futures rolling. Participants gain indirect volatility exposure through ETF structures, avoiding complex derivatives mechanics but incurring contango decay.
Performance Expectations: Designed for portfolio hedging first, income generation second. Participants should expect negative correlation of -0.6 to -0.8 with equity portfolios during crises, with modest positive returns (3-6% annually) during calm periods. The strategy is not engineered for standalone high returns; it functions as a diversifying satellite allocation.
Risk Warnings: Short-volatility positions carry theoretical unlimited loss potential. The model incorporates risk caps and position limits, but participants must maintain strict discipline during volatility spikes exceeding 40 VIX.
BOTTOM-LINE ASSESSMENT
This program provides precise, practitioner-validated volatility trading infrastructure without requiring derivatives expertise or programming capability. The instructors' hedge fund tenure ensures the model addresses real-world frictions: contango drag, ETF liquidity gaps, and margin volatility.
Critical Caveat: Volatility risk premium strategies experienced severe drawdowns in 2018 (Volmageddon) and 2020 (COVID spike). The model's risk controls mitigate but do not eliminate these outcomes. Participants must allocate no more than 5-10% of total portfolio to this strategy and maintain psychological preparedness for rapid losses.
For the target audience—equity portfolio managers seeking non-correlated hedges—this represents a professionally rigorous, operationally viable tool that translates institutional-grade risk management into Excel-based execution. The primary value lies not in exceptional returns but in predictable portfolio insurance characteristics during equity market dislocations.
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