A widespread misconception about major market declines is that they are only caused by recessions, pandemics or other singular events, but that’s not the case. Market downturns over a 12-month period—particularly large market downturns—are best explained by valuation factors.
Valuation factors are a big deal. When the market is highly priced, the probability of decline caused by lofty valuations is dramatically increased, whereas the likelihood of a large decline is extremely low when valuations are cheap. As a portfolio’s time horizon is extended, valuation becomes increasingly crucial.
The longer a portfolio investment time horizon, the more heavily weighted an algorithm should be towards valuation factors, and the more patient investors can be regarding performance. Conversely, the shorter the time horizon, the less weight the algorithm should have in valuation factors because they are the most predictive factors of long-term return.
One of the most compelling analytical techniques used to measure valuation is normalization, an attempt to “normalize” financial data, whether for an individual company or the entire equities market.
On a micro or individual company level, normalization helps smooth out the anomalies of a company’s financial statements by adjusting or discounting non-recurring expenses or revenues. Financial statements often contain expenses that do not reflect a company’s normal business operations and may distort earnings. Normalization reduces the impact of these aberrations.
On a macro level—valuing a market—one of the most widely recognized normalization techniques was developed by Yale University professor Robert Schiller. He created the cyclically adjusted price to earnings ratio (CAPE), which calculates the market’s average earnings for the previous ten years and compares that data to the current price.
Dr Schiller is broadly hailed for his contributions to market valuation. And while I believe his approach is valid from an academic standpoint, when it comes to making money in a capitalist environment, what transpired a decade ago has little or nothing to do with what’s happening in the market today, not to mention what may occur in the future.
We use normalization but with a different timeline calculation—an analysis of four years back and one year projected forward—to give us five years of normalized earnings. We believe this technique is more accurate for macro or total market analysis.
Source: Normalized Earnings – Overview, How To Estimates, Examples (corporatefinanceinstitute.com)
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