The traditional financial theory attributes security returns to market- or factor-based risk, with no role ascribed to other influences. In this research, the authors argue for including investor demand as an additional variable in explaining returns. Can changes in investor demand generate systematic changes in security returns?
The empirical evidence demonstrates that returns to the low-beta anomaly are well explained by exposure to other common factors, and it has only justified investment when low-beta stocks were in the value regime, after periods of strong market and small-cap stock performance, and when they excluded high-beta stocks that had low short interest.
Doug Pugliese, the head of our 1042 QRP business, was recently invited on the ScuttleButt Podcast to discuss the ESOP landscape and the costs and benefits of 1042 QRP transactions. (article on the topic is here).
By using a novel measure of investor attention, generated from InvestingChannel’s clickstream data on online financial news consumption, we can identify broad groups of stocks which are less efficiently priced and therefore where anomalies such as Value and Momentum are likely to produce greater cross sectional differentiation in returns. We also apply these groupings to proprietary ExtractAlpha stock selection signals.
Running regressions on past returns is a great tool for academic researchers who understand this approach's nuance, assumptions, pitfalls, and limitations. However, when factor regressions become part of a sales effort and/or are put in the hands of investors/advisors/DIYers, "the tool can quickly turn you into a fool."
The empirical research demonstrates that, on average, investing in previous winners and short selling previous losers offers highly significant returns that other common risk factors cannot explain. However, momentum also displays huge tail risk, as there are short but persistent periods of highly negative returns. Crashes occur particularly in reversals from bear markets when the momentum portfolio displays a negative market beta and momentum volatility is high.
This study explores the degree to which fund concentration (high tracking error) affects the magnitude of excess returns and whether or not the likelihood of outperformance or underperformance are distributed similarly.
Academic research has demonstrated that the higher risk associated with less sustainable firms should be compensated by higher returns. It also has shown that more sustainable firms have less investment risk.
Standardized Performance Factor Performance Factor Exposures Factor Premiums Factor Attribution Factor Data Downloads
Although the most efficient way to implement a value strategy may need to be clarified, it is clear that value has withstood the test of time and that some implementations are superior to others. The evidence suggests that P/B is not an efficient metric as a standalone criteria. Instead, value strategies that use P/B should include at least a measure of profitability while managing sector - and security-level diversification.
Researchers have raised questions and led to research into how many factors are needed, the replicability of originally reported results, and the decay of factor performance over time.
The “Intangible Value Factor” (IHML) can play an additive role in factor portfolios alongside the established market, size, value, quality, and momentum factors. This Six-Factor Model avoids the problematic “anti-innovation” bias of traditional factor portfolios and can be easily implemented using ETFs.
The article aims to explore the possibility that changes in fundamentals play a role in the attenuation of stock market anomalies, offering an alternative explanation to the prevailing arbitrage-based explanation
There are several significant, well-documented benefits of index funds. In addition to outperforming a large majority of actively managed funds, they tend to have low fees, low turnover (resulting in low trading costs and high tax efficiency), broad diversification, high liquidity, and near-zero tracking error (generally assumed to mean that they incur negligible trading costs).
Summary: no difference in average returns between large-cap and small-cap portfolios. There you have it. The small-cap sacred cow has been slaughtered.
This paper finds that the level of industry classification plays a significant role in the performance of industry momentum strategies.
Standardized Performance Factor Performance Factor Exposures Factor Premiums Factor Attribution Factor Data Download
While most sin stocks in the IC method were also identified as sin in the TA method, there were 57 firm-year cases where a company showed up as sin only in the IC method—these were false positive sin stocks as identified in the IC method.
Not accounting for intangibles affects not just value metrics but other measures (such as profitability) that often scale by book value or total assets, both of which are affected by intangibles—and investors recognize at least some of their value.
We recently hosted our 6th Annual Democratize Quant Conference. This post is a recap of what we heard and some resources we can make available to the public.
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