Market-Capitalization-Weighted Indexing * Approach: Weights securities based on their market capitalization (Price \(\times\) Shares Outstanding). * Pros: Theoretical efficiency (CAPM), self-rebalancing, high liquidity, low turnover. * Cons: Overweights overvalued stocks and underweights undervalued stocks; concentration risk in largest names/sectors.
Factor-Based Strategies (Smart Beta) * Approach: Selects and weights securities based on specific drivers of return (factors) rather than market cap. * Goal: Improve risk-adjusted returns or achieve specific outcomes (e.g., lower volatility, higher yield). * Common Factors: * Value: Low P/E, low P/B, high dividend yield. * Size: Small-cap stocks (historically outperform large-cap). * Momentum: Stocks with strong recent price performance. * Quality: High profitability, low debt, stable earnings. * Volatility: Low volatility stocks (defensive). * Yield: High dividend yield. * Types of Strategies: * Return-Oriented: Dividend yield, Momentum, Fundamental weighting (weights based on metrics like sales, cash flow, dividends to avoid price bias). * Risk-Oriented: Volatility weighting (inverse volatility), Minimum Variance (optimization to minimize portfolio volatility). * Diversification-Oriented: Equally weighted (\(1/n\)), Maximum diversification (ratio of weighted average volatilities to portfolio volatility).
Pooled Investments * Mutual Funds: * Structure: Open-end funds; transact at Net Asset Value (NAV) at end of day. * Pros: Convenience, lower initial investment limits. * Cons: Potential tax inefficiency (capital gains distributions due to redemptions), accumulation of cash drag. * Exchange-Traded Funds (ETFs): * Structure: Trade intraday on exchanges; creation/redemption process with Authorized Participants (APs). * Pros: Intraday liquidity, tax efficiency (in-kind creation/redemption avoids triggering capital gains), can be shorted or leveraged. * Cons: Trading costs (bid-ask spread, commissions), prices can deviate from NAV (premiums/discounts).
Derivatives-Based Approaches * Futures: * Use: Gain market exposure quickly (equitizing cash), adjust beta, tactical asset allocation. * Pros: High liquidity, low transaction costs, leverage (small margin requirement). * Cons: Finite life (must roll contracts), Basis Risk (futures price may not perfectly track spot price), no voting rights/dividends (though price reflects expected dividends). * Swaps (Equity Total Return Swaps): * Use: Customized exposure (e.g., specific sector or foreign index). * Pros: Customization, no need to trade underlying stocks. * Cons: Counterparty credit risk, lack of liquidity (OTC), potentially higher fees.
Separately Managed Accounts (SMAs) * Use: Direct ownership of individual securities for large investors. * Pros: Customization (ESG screens, tax harvesting), control. * Cons: High minimum investment, operational complexity (trading, compliance, corporate actions). * Process: Uses Program Trading (buying/selling a basket of stocks simultaneously) to execute lists.
1. Full Replication * Method: Hold all securities in the index in exact weights. * Pros: Lowest tracking error (theoretically zero before costs), simple to understand. * Cons: High transaction costs (especially for indexes with thousands of illiquid stocks), frequent rebalancing required. * Best For: Indexes with liquid constituents and moderate number of names (e.g., S&P 500).
2. Stratified Sampling * Method: Divide index into “strata” (cells) based on characteristics (e.g., Sector, Country, Market Cap, P/E) and select a subset of representative stocks for each cell. * Pros: Lower trading costs than replication. * Cons: Higher tracking error than replication; relies on manager skill to select representative stocks. * Best For: Large indexes with illiquid tails (e.g., MSCI ACWI), or smaller AUM portfolios.
3. Optimization * Method: Use multifactor risk models and mean-variance optimization to select a subset of securities that minimizes predicted tracking error. * Pros: Explicitly accounts for covariances; minimizes tracking error for a given number of holdings. * Cons: “Black box” nature; relies on historical data (risk of overfitting/instability); requires sophisticated software; optimization inputs (covariances) change over time. * Best For: Complex situations with specific constraints (e.g., ESG limits, tax constraints).
Note: Tracking error vs. Number of stocks held typically follows a U-shaped curve: * Too few stocks = High tracking error (sampling risk). * Too many stocks (illiquid tail) = High tracking error (transaction costs).
Tracking Error (TE) * Definition: Standard deviation of the difference between portfolio return (\(R_p\)) and benchmark return (\(R_b\)). * Formula: \(TE = \text{StDev}(R_p - R_b)\)
Causes of Tracking Error: 1. Fees and Expenses: Management fees, custodial fees, audit fees reduce returns relative to the frictionless benchmark. 2. Transaction Costs: Brokerage commissions, bid-ask spreads, market impact. 3. Cash Drag: Indexes assume 0% cash; portfolios hold cash for liquidity/dividends. Cash creates a drag in rising markets. 4. Sampling/Optimization: Holding a subset of stocks creates deviation. 5. Intraday Trading: Benchmark assumes closing prices; manager executes over the day (timing differences).
Methods to Control TE: 1. Equitization: Use futures to gain market exposure on cash balances (minimizes cash drag). 2. Dividend Reinvestment: Reinvest dividends promptly or use accrued dividend futures. 3. Program Trading: Execute baskets at Market-On-Close (MOC) to match benchmark pricing. 4. Securities Lending: Lend portfolio stocks to short-sellers to earn fee income (offsets management fees/costs).
Attribution Analysis * Used to identify sources of return (and TE) relative to the benchmark. * Sector Attribution Example: * Allocation Effect: Did we overweight a performing sector? * Selection Effect: Did we pick the best stocks within the sector? (Less relevant for full replication, critical for sampling/factor strategies). * Formula: \(R_{portfolio} - R_{benchmark} = \sum (w_{p,i} \times R_{i}) - \sum (w_{b,i} \times R_{i})\)
Securities Lending * Mechanism: Fund lends stocks to borrowers (short sellers); borrower posts collateral (usually >100% value). * Return: Lender earns a fee (rebate rate spread) + reinvestment income on cash collateral. * Risk: * Counterparty Risk: Borrower defaults and collateral is insufficient. * Collateral Reinvestment Risk: Loss on the investment of cash collateral (e.g., buying risky bonds with collateral cash).
Investor Activism * Index managers are “permanent owners” (cannot sell if stock stays in index). * Engagement: Voting proxies, engaging with management on ESG, governance, and strategy. * Goal: Improve long-term corporate performance to lift the index return.