Reference Data Tables › Portfolio Data Reference Tables
Portfolio Data Reference Tables
Portfolio data reference tables provide the historical return and risk figures that portfolio construction models require. Building a mean-variance optimized portfolio requires expected return assumptions, and the most common starting point is the long-run historical return for each asset class. These tables collect those series along with correlation data that shows how different asset classes have moved together over time.
Direct Answer
Portfolio reference tables provide the historical data used to build and evaluate asset allocation strategies. Long-run returns for stocks, bonds, cash, real estate, and commodities show what each asset class has delivered over different economic environments. Correlation data shows how much diversification benefit different combinations actually provide. Both are inputs to any rigorous portfolio construction process.
Common questions
What is a correlation matrix and how is it used in portfolio construction?
A correlation matrix shows the pairwise correlation coefficients between different asset classes or securities, ranging from -1 (perfect negative correlation, moves in opposite directions) to +1 (perfect positive correlation, moves together). A correlation near zero means the two assets move independently. In portfolio construction, combining assets with low or negative correlations reduces overall portfolio volatility without necessarily reducing expected return, which is the quantitative basis for diversification.
How reliable are historical return assumptions for future portfolio projections?
Historical returns are the standard starting point but are not a reliable forecast. The 20th-century US equity return was exceptionally high by global historical standards, partly due to economic and geopolitical factors that cannot be assumed to repeat. Valuation-adjusted return estimates (which lower expected returns when starting valuations are high) have historically been more accurate over 10-year horizons. Using a range of return scenarios rather than a single-point historical average produces more realistic portfolio projections.
Every guide in this section
5 guides in this section.
All guides
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Asset Allocation Models Reference
Compare classic asset allocation frameworks including 60/40, all-weather, and lifecycle glide paths with historical risk and return data.
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Factor Investing Premiums Reference
Historical premium data for major equity risk factors including value, size, momentum, quality, and low volatility from Fama-French and AQR research.
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Monte Carlo Retirement Simulation Inputs Reference
Reference table of standard inputs used in Monte Carlo retirement simulations including return assumptions, volatility, and inflation rates by asset class.
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Portfolio Rebalancing Frequency Reference
Compare rebalancing strategies by frequency, drift thresholds, and historical impact on risk-adjusted returns.
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Safe Withdrawal Rate Research Reference
Summary table of major safe withdrawal rate studies including the 4% rule and subsequent research showing updated SWR ranges by time horizon.