THE COMPLETE MULTI-STRATEGY INVESTING COURSE (PORTFOLIO DIVERSIFYING) – AllQuant

COURSE OVERVIEW

This flagship program integrates four institutional-grade quantitative strategies—Risk Parity, Trend Following, Volatility Risk Premium, and Sector Rotation—into a unified portfolio management framework constructed entirely in Microsoft Excel. Participants build individual strategy models plus a master multi-strategy allocation engine that dynamically distributes capital, tracks performance, and executes rebalancing based on objective, data-driven rules. The curriculum translates hedge fund-level portfolio construction principles into a single, operable Excel ecosystem requiring approximately ten minutes of daily maintenance.

Core Value Proposition: Master capital allocation across uncorrelated strategies while constructing a live-deployable portfolio management system that automates weight optimization and rebalancing decisions.

LEARNING OBJECTIVES

Upon completion, participants will demonstrate competency in:

Modern Portfolio Theory Extension: Implementing advanced diversification beyond Markowitz mean-variance optimization

Four Quantitative Strategies: Risk parity, trend following, volatility risk premium, and sector rotation mechanics

Capital Allocation: Dynamic weighting based on risk contribution, performance momentum, and correlation stability

Performance Aggregation: Consolidating individual strategy returns into multi-strategy analytics

Rebalancing Logic: Trigger-based rebalancing rules versus calendar-based approaches

VBA Automation: Scripting data updates and weight optimization to minimize manual intervention

Multi-Strategy Dashboard: Real-time tracking of portfolio-level exposure, leverage, and strategy drift

Operational Discipline: Maintaining synchronized updates across five interconnected Excel files

COURSE CONTENT STRUCTURE

Total Duration: Approximately 24 hours across 21 sections

SECTION 1: INTRODUCTION TO PORTFOLIO CONSTRUCTION (30 minutes)

Limitations of single-strategy investing; diversification decay during crises

Multi-strategy architecture: combining negatively and weakly correlated strategies

Capital allocation philosophies: risk budget versus return contribution

SECTION 2: EXCEL CRASH COURSE (60 minutes)

Critical functions: VLOOKUP, INDEX/MATCH, array formulas, logical operators

VBA fundamentals: recording macros, editing code, triggering automation

Multi-file data linking: external cell references and dynamic range naming

Error handling across interconnected workbooks

SECTION 3: FINANCIAL MATHEMATICS (90 minutes)

Covariance matrix construction and rolling correlation estimation

Risk parity mathematics: equalizing marginal risk contributions

Leverage and margin modeling across strategies with different volatilities

Multi-strategy Sharpe ratio: portfolio-level risk-adjusted return aggregation

SECTIONS 4-7: RISK PARITY STRATEGY

Concept (60 min): All-weather portfolio theory, Bridgewater-inspired construction

Model Building (120 min): Calculating asset-class risk budgets, implementing inverse volatility weighting

Operations (30 min): Monthly rebalancing workflow, leverage adjustment protocols

SECTIONS 8-10: TREND-FOLLOWING STRATEGY

Concept (60 min): Time-series momentum, dual moving average crossovers

Model Building (120 min): Signal generation for equity universe, position sizing with volatility targeting

Operations (30 min): Daily signal monitoring, trade execution logic

SECTIONS 11-13: VOLATILITY RISK PREMIUM STRATEGY

Concept (60 min): Shorting VIX futures via ETFs, contango harvesting

Model Building (120 min): VIX percentile-based entries, risk caps, hedge ratio calculation

Operations (30 min): Monitoring term structure, crisis exit triggers

SECTIONS 14-16: SECTOR ROTATION STRATEGY

Concept (60 min): Momentum-based sector selection, risk-on/risk-off filtering

Model Building (120 min): XLY, XLU, XLF universe construction, relative strength ranking

Operations (30 min): Weekly ranking updates, turnover management

SECTION 17: MULTI-STRATEGY INTEGRATION (60 minutes)

Strategy correlation matrix: combining negatively correlated (trend + vol premium) and weakly correlated (risk parity + sector rotator) models

Capital allocation framework: static versus dynamic weighting

Performance attribution: isolating contribution from each strategy layer

SECTION 18: MULTI-STRATEGY IMPLEMENTATION IN EXCEL (180 minutes)

Building master portfolio file: linking four strategy workbooks

VBA automation: macro for simultaneous data refresh across all models

Weight optimization engine: Solver-based allocation with turnover constraints

Cash management: handling unsettled trades and margin requirements

SECTION 19: SETTING UP PERFORMANCE ANALYTICS (90 minutes)

Aggregating returns from four strategies into unified time series

Rolling performance tracking: 3-month, 6-month, 12-month attribution

Correlation monitoring: detecting strategy correlation breakdown

Drawdown analysis: strategy-level versus portfolio-level drawdown

SECTION 20: ADDING STRATEGIES TO PORTFOLIO (60 minutes)

Modular architecture: plugging in fifth strategy (e.g., carry, mean reversion)

Rebalancing frequency calibration: mixing daily, weekly, and monthly models

Tax implications: managing short-term gains from high-turnover strategies

SECTION 21: OPERATIONS (60 minutes)

Daily workflow: 10-minute protocol for updating all models and master portfolio

Signal reconciliation: resolving conflicts between strategy recommendations

Rebalancing execution: generating trade list across strategies

Stress-testing: simulating 2008 and 2020 scenarios on multi-strategy portfolio

DELIVERABLES & RESOURCES

Fully Completed Multi-Strategy Model File: Master Excel workbook integrated with four individual strategy files

All Four Individual Strategy Models: Complete risk parity, trend following, volatility premium, and sector rotation workbooks

VBA Automation Scripts: Pre-written macros for bulk data updates and weight optimization

Guided Build Templates: Section-by-section worksheets with partial completion scaffolding

Practice Exercises: Multi-strategy capital allocation problem sets with solution keys

Performance Analytics Worksheet: Portfolio-level metrics calculator with strategy attribution

Decision Dashboard: Multi-strategy summary interface showing weights, signals, and drift alerts

TARGET AUDIENCE PROFILE

Optimal Fit:

Portfolio managers at family offices and hedge funds constructing diversified strategy allocations

Investment advisors managing ₹1+ crore client portfolios requiring institutional-grade risk management

Sophisticated self-directed investors seeking to combine multiple uncorrelated quantitative strategies

Quantitative analysts building strategy suites for asset management firms

Proprietary traders transitioning from single-strategy to multi-strategy architectures

Suboptimal Fit:

Individuals seeking quick stock picking tips or discretionary forecasting services

Participants unable to commit to daily 10-minute update discipline across multiple files

Investors without intermediate Excel proficiency (model debugging complexity is high)

Traders requiring real-time intraday signals (strategies operate on daily/weekly frequencies)

PREREQUISITES & TECHNICAL REQUIREMENTS

Intellectual Prerequisites:

Advanced portfolio theory: understanding of correlation, covariance, volatility targeting

Multi-strategy intuition: recognizing interaction effects between quantitative models

Derivatives basics: futures, options mechanics (for volatility strategy)

Statistics: rolling correlations, percentile ranks, regression basics

Technical Prerequisites:

Microsoft Excel 2016 or later with VBA macros enabled

Intermediate Excel: pivot tables, array formulas, dynamic named ranges

Stable internet connection for daily data retrieval across multiple instruments

Ability to manage five interconnected Excel files

Software Provision: All analysis uses free resources; no data vendor subscriptions required

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, institutional risk mandates. Sovereign wealth fund background provides long-horizon capital preservation principles essential for multi-strategy longevity.

PATRICK LING – CO-FOUNDER & SENIOR INSTRUCTOR

15+ years 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 any single alpha source.

Joint Credibility: Both instructors maintain parallel practitioner careers, ensuring curriculum evolves with current industry standards rather than academic abstraction.

METHODOLOGICAL APPROACH

The course employs a "build-operate-improve" framework applied across four strategies, culminating in integration. Participants first construct each strategy independently, validate against historical crises, then combine into unified portfolio. Each module includes failure-mode analysis: what happens when risk parity fails (inflation), trend following fails (whipsaw), volatility premium fails (vol spike), and how multi-strategy allocation mitigates these simultaneous breakdowns.

Instruction emphasizes portfolio construction mathematics over individual strategy optimization, teaching participants to think in terms of risk budget allocation rather than return maximization.

Time Commitment: Video instruction totals 24 hours; independent model building requires estimated additional 12-16 hours. Ten-minute daily operation assumes fully constructed, stable ecosystem.

STRATEGY SCOPE & LIMITATIONS

Geographic Application: Explicit models calibrated for U.S. markets (S&P 500, VIX futures, sector SPDRs) to ensure data availability. Mathematical architecture is transferable to Indian markets (Nifty, India VIX, sector indices) where liquid instruments exist.

Capacity Constraints: Four-strategy portfolio requires minimum capital of ₹50 lakh for effective implementation across products with position size constraints. Below this threshold, transaction costs and ETF expense ratios erode edge.

Performance Expectations: Multi-strategy portfolio targets portfolio-level Sharpe ratio of 1.0-1.2 through diversification, not individual strategy excellence. Expect drawdown reduction of 40-50% versus Nifty 50 during crises (2008, 2020 backtests show -25% vs -60%), with annual returns of 10-12% during normal regimes.

Key Limitation: Multi-strategy portfolios still exhibit correlation breakdown during extreme liquidity crises (March 2020). All four strategies can lose money simultaneously for 2-4 weeks; risk management cannot eliminate this entirely.

BOTTOM-LINE ASSESSMENT

This program delivers institutional-grade multi-strategy portfolio construction in Excel, covering the complete workflow from individual strategy development to dynamic capital allocation. The instructors' practitioner credentials provide rare authenticity in teaching strategy interaction effects and correlation instability—concepts typically reserved for institutional training.

Critical Success Factor: This is not a stock picking course. Value derives from learning how to combine mediocrely profitable, uncorrelated strategies into a resilient portfolio whose whole is greater than sum of parts. Participants seeking single-strategy mastery should enroll in individual courses first.

For portfolio managers at single-strategy funds or HNW investors managing diversified accounts, this represents the most complete Excel-based implementation of hedge fund portfolio construction principles available without programming requirements. The primary risk is implementation complexity: maintaining five synchronized files requires organizational discipline that many individual investors lack.

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