The size factor is one in all the stock risk aspects that exist a long-term bonus is granted. However, recently some researchers have expressed doubts about its usefulness based on a comparison of its performance with other known aspects. For example, Ron Alquist, Ronen Israel, and Tobias Moskowitz in addition to Noah Beck, Jason Hsu, Vitali Kalesnik and Helge Kostka have argued that there’s neither strong empirical evidence nor solid theoretical support for a everlasting size premium.
However, there are the reason why most investors should query the relevance of those conclusions.
Statistical analyzes of Joel L. Horowitz, Tim Loughran and NE Savin show that the standalone outperformance of small-cap stocks over large-cap stocks is weak and may even disappear when exposure to the market factor is taken under consideration. In particular, expanding the set of independent variables to incorporate the lagged market return along with the concurrent market return ends in an insignificant size premium.
Although this result’s of marginal statistical interest, it has little to no practical implications for investors. In fact, the lagged market factor is a synthetic construct that investors cannot hold of their portfolios and subsequently has only hypothetical statistical applications. Therefore, measuring the alpha of such a non-investable factor doesn’t make economic sense.
For us, the more essential query is: Does the dimensions factor add value to an investor’s portfolio?
Factor performance must be assessed from a portfolio perspective
The easiest solution to determine whether an element adds value to a portfolio is to match the Sharpe ratio of the portfolio with and without the factor. The higher the Sharpe ratio, the upper the risk-adjusted return of the general portfolio. A stand-alone factor premium cannot answer this query since it doesn’t keep in mind the danger properties of the aspects, namely the correlations between the factor into account and the opposite aspects within the portfolio.
Additionally, measuring exposure to the market factor alone doesn’t provide a whole picture of how that factor affects the portfolio since it ignores correlations with other aspects. Adding the lagged values ​​of the market factor into the regression doesn’t solve this problem and likewise assumes that an investor’s alternative is proscribed to only holding the market or holding the market and size.
To properly analyze the dimensions factor, we must evaluate its utility inside a spread of economically relevant aspects. Considering the dimensions factor alongside economically meaningless or redundant aspects hardly provides any statistical or economic insights. Therefore, to find out whether size adds value and improves a portfolio’s Sharpe ratio, we want to include exposure to all of those other aspects into our evaluation.
In Work previously published in Beta scientific researchers Mikheil Esakia, Felix Goltz, Ben Luyten and Marcel Sibbe conducted several tests to find out whether the dimensions factor actually improves a multi-factor investor’s Sharpe ratio. The results presented within the table below illustrate that that is clearly the case are consistent with findings from other researchers. The chart shows the factor weights that maximize the Sharpe Ratio of an investor, who can select from an element menu with the widely used market, size, value, momentum, low risk, high return, and low investment aspects in each academic and practical terms Research.
This is a straightforward solution to assess the influence of an element on the risk-return characteristics of a portfolio. Any deviation from these weights would lower the Sharpe ratio. The size factor received a weight of greater than 9% within the portfolio, which is larger than that of value (2.9%) and shut to those of momentum (11.4%) and low risk (11.7%).
Weights within the mean-variance optimal portfolio, July 1963 to December 2018
In the identical study, researchers also reported that the standalone size factor produced the bottom return amongst menu aspects over the evaluation period. For momentum and low risk, the common individual premiums were about 3 times higher. However, the weights of the momentum and low-risk aspects within the optimal portfolio usually are not much higher than those of the dimensions factor.
What explains these results? Ultimately, optimal factor weights rely on greater than just returns. They also depend on risk characteristics, particularly factor volatilities and the correlations of every factor with aspects apart from the market factor. Considering these risk characteristics is especially useful because we are able to measure them with an affordable level of confidence. while expected returns are notoriously difficult to estimate.
The positive weight of the dimensions think about the optimal portfolio shows that the inclusion of the dimensions factor improves the risk-return profile of a multi-factor portfolio. The size factor specifically contributes to the Sharpe ratio since it has a very low correlation with other traditional aspects and is subsequently an efficient diversifier of the portfolio. In fact, its diversification advantages are so great that even with almost no premium, the dimensions factor would still be a helpful addition to a multi-factor portfolio.
While the dimensions factor doesn’t produce outstanding returns, it’s a helpful addition to a portfolio
When a portfolio’s exposure to aspects apart from the market factor is taken under consideration, the addition of the dimensions factor significantly improves the risk-return characteristics of the portfolio. Size is a powerful diversifier over other traditional aspects and subsequently increases the worth of a multi-factor portfolio. Analysis that doesn’t keep in mind the danger of momentum, profitability and other aspects is of little use to investors.
Finally, there’s a size effect. Claims on the contrary contradict the varied academic asset price models that show that the dimensions factor adds more explanatory power to the cross-section of returns. By incorporating aspects apart from the market, these models provide meaningful conclusions for investors and reinforce the essential contribution of size to portfolio diversification and risk control.
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Photo credit: ©Getty Images /Liudmila Chernetska
