@TDAM_Canada
TD Asset Management Inc. (TDAM) unveiled its 2024 long-term capital markets assumptions for stocks, bonds and alternative investments in a recent paper.
The firm uses these assumptions to make decisions about the optimization of strategic asset allocation and the design of multi-asset, balanced or target date funds.
TDAM's asset class assumptions are long-term in nature, reflecting average annual expectations over horizons of 7 to 10 years. The methodology assumes that historical relationships are fairly constant and that most asset classes will trend according to structural macro-economic factors over time. This allows strategic asset mix decisions to rely on mid-term and long-term trends rather than on attempts to time the business cycle.
TDAM's asset class assumptions fall under three categories: returns, risk and correlation.
- Expected returns for each asset class
TDAM uses a forward-looking building block approach to set asset class return assumptions. This methodology builds on the Grinold and Kroner forecasting approach. The return assumptions encapsulate four financial and economic parameters: expected real Gross Domestic Product growth, expected inflation, yield and an idiosyncratic component, which is asset-specific. Different asset classes incorporate different financial and economic parameters into their return expectations.
- Expected risk - setting standard deviation of asset class returns
The TDAM approach uses historical returns dating back to December 31, 1998 for each asset class to set expected standard deviations. For most asset classes, prevailing benchmarks are sourced. Volatility metrics for illiquid assets can be artificially low due to the smoothing effect of appraisal-based returns coupled with infrequent trading. This can underestimate the level of asset class risk if not accounted for. To de-smooth the return time series for illiquid assets, the Fisher-Geltner-Webb methodology is applied.
- Expected correlation across asset class returns
Correlation for public assets is calculated from historical returns of respective market indices for each asset class from December 31, 1998 to September 30, 2023. In order to capture different market regimes, correlation with commodities is derived from series going back further, depending on the data availability. Correlations with private assets are derived from series as far back as the firm could source. To correct for appraisal biases within real estate and infrastructure in the correlation matrix, TDAM uses de-smoothed returns to calculate the correlation where alternative assets are involved.
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