introduction
Ted Theodore first wrote about value and momentum stocks in 1984.But almost 40 years later, there continues to be no real consensus amongst investors and academics about what drives each strategy.
This is just not for a scarcity of research. Thousands of papers have examined equity aspects across markets and asset classes, and a few have analyzed strategies dating back greater than 200 years.
Part of the issue is that while performance drivers have been identified, they should not widely accepted by practitioners. This is comprehensible. If it is obvious what drives a technique’s returns, fund managers might be out of a job if the environment becomes unfavorable to their investment style. They are higher off remaining vague about performance drivers in public, as this helps them maintain their assets under management (AUM).
A second problem is that the drivers of performance are never entirely clear. Finance is just not a precise science with immutable, gravity-like laws. Markets are always changing and historical performance and trends should not perfectly replicable. So relating to drivers of performance, finance professionals must live with relatively low standards of proof.
Our framework for determining a performance driver consists of 4 criteria:
- It needs to be based on a solid economic foundation.
- On average it should work, but not at all times.
- It needs to be feasible.
- It should delay when tested across different time periods, markets and asset classes.
So what’s the important thing performance driver of the worth factor? What evidence do we’ve got to support this conclusion?
What determines the worth factor?
The value factor generates positive returns when low cost stocks outperform expensive ones. So when does this occur?
Cheap firms are frequently troubled firms. Otherwise they would not be trading at low valuations. Their problems could also be temporal or structural: an over-leveraged balance sheet or belonging to an industry in decline, for instance. In any case, investors will find these stocks uncomfortable since the news and broker rankings surrounding them will are inclined to be bearish.
This implies that investors are most willing to purchase questionable firms once they have more confidence within the economy and the stock market. When the economy is heading toward a recession, investors are inclined to favor firms with quality or growth characteristics. In other words, risk appetite is a very powerful performance driver of the worth factor.
There are many variables that may be used to measure risk appetite. We will deal with three: equity market volatility, equity market skewness, and the yield curve.
The value factor and the realized volatility of the stock market
We created a worth factor from the most cost effective and costliest 10% of stocks within the U.S. stock market, measured by price-to-book ratios using data from the Kenneth R. French Data LibraryWe then calculated the Z-score of stock market volatility based on a three-month lookback.
Most of the positive returns of the worth factor from 1926 to 2020 may be attributed to decreasing volatility. However, this relationship is just not perfect: Between 1931 and 1943, the worth factor’s returns declined when volatility increased. From then on, nevertheless, returns have been consistently negative when volatility was on the rise.
The value factor and the realized volatility of the stock markets within the USA
These results provide some support for the notion that risk appetite is the major driver of the worth factor’s performance: equity market volatility tends to rise when economic volatility increases, which generally happens when the economy worsens. During such periods, investors prefer lower-risk assets and subsequently are inclined to avoid low cost stocks.
The value factor and the skewness of the stock market
Next, we analyzed the returns of the worth aspects within the context of stock market skewness, which we calculated looking back 12 months. Stock market skewness is a more abstract measure, however it simply implies that investors could also be more cautious after a stock market crash.
With its long uptrends and few but steep downturns, the U.S. stock market is more negatively skewed than positively skewed over time. Almost all the positive returns from the worth factor occur in periods of positive skew, when there have been no recent severe downturns. Investors feel secure and are more willing to bet on troubled firms.
The value factor and the stock market skew within the USA
The value factor and the yield curve
We calculated the yield curve because the difference between the rates of interest on 10-year and 2-year US Treasury bonds. A downward sloping yield curve is related to slowing economic growth and an inverted yield curve is interpreted as a number one indicator of a recession. Unfortunately, the info only goes back to 1976, which limits the scope of our evaluation.
We calculated the slope of the yield curve with a Z-score, using a three-month lookback. We found that just about all the positive returns from the worth factor occurred when the yield curve was upward sloping or when economic conditions were more favorable.
Value Factor and the Yield Curve within the USA
Combination of key metrics for factor risk management
Based on these insights, investors might think about using these metrics to time the worth factor. We recommend approaching this from a risk relatively than a return perspective. That is, we recommend specializing in avoiding significant price declines when the market environment is more negative for owning low cost stocks.
Our multidimensional risk management framework assigned the worth factor only when a mixture of equity market volatility, market skewness and yield curve was favorable. Specifically, we modeled three scenarios where one, two or three signals are required for an element project. Without the required signals, interest-free money was held as a substitute.
Given the constraints of our yield curve data, three positive signals representing a market environment with declining market volatility, positive market skewness, and an upward sloping yield curve have only been possible since 1976.
Our results are quite typical for multimetric frameworks: the more filters, the more consistent the returns, however the lower the factor loading.
Requiring a minimum of one positive signal resulted in returns comparable to the buy-and-hold value factor. However, with two and even three signals, returns were way more consistent and drawdowns were significantly smaller. Total returns were lower than the worth factor resulting from high money allocations and limited yield curve data.
Multimetric risk management framework for the worth factor
We also evaluated the performance of the Value factor on negative signals. This may very well be used to potentially short the factor by buying expensive stocks and selling low cost stocks.
Requesting a single signal resulted in performance consistent with the buy-and-hold value factor, while requesting two or three signals resulted in consistent losses, suggesting a market environment of accelerating volatility, negative market skewness, and a downward sloping yield curve.
Multimetric Risk Management Framework for the Value Factor: Short Signals
All in all, this evaluation is much from perfect. We haven’t thoroughly tested the framework for robustness. We could use price-to-earnings ratios as a substitute of price-to-book ratios for stock selection, change the lookback periods, include transaction costs, apply the framework to international markets and other asset classes, and so forth.
But we used common risk measures and publicly available data, made few assumptions, and applied our method to greater than 90 years of economic history, which provides some reason to imagine that these results matter.
An obviously false assumption is that we apply trading signals on a same-day basis. This is unimaginable to implement because changes in variables and stock markets occur concurrently.
Same-day trading vs. next-day trading: CAGRs, 1926–2020
To make the signals more realistic, we analyzed what would occur if the trades were executed the subsequent day. This resulted in a big reduction in CAGRs for the frameworks that required one or two positive signals, but not for those with three positive signals.
Further considerations
Understanding what influences value factor performance is immensely helpful, but implementing a framework around those aspects is difficult. On average, it can work, but not consistently.
And the more filters there are around investors’ risk sentiment metrics, the lower the actual allocation to the factor and the more often money is held. Investors do not like being out of the market, especially when the worth factor is performing well.
While it’s great to know learn how to improve your probabilities of winning by buying low cost stocks, it doesn’t make value investing any easier.
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Photo credit: ©Getty Images / Monticello
