Back to Community
Are US Value Factors Dead?

Behavioural interpretation for existence of the value factor: investors extrapolate past growth rates too far into the future.
The market slowly realises that growth rates for values stocks are higher than initially expected.

The notebook explores three most popular factor investing approaches based on the following price multiples:
- Book value
- Free cash flow
- Dividends

Sector-neutral value factors are constructed by ranking stocks from US investment universe by value measures in descending order. We go long top 30 names and short bottom 30 names.The stocks are equally weighted and rebalanced monthly. The investment universe is updated yearly and new sets of stocks are allocated to long and short baskets.

The notebook concludes that the value factor does not exhibit consistent performance in US equity market and might indicate market efficiency with regards to the factor.
Although investing in value factor does not provide attractive returns, it must be considered for inclusion in multi-factor portfolios that are subject to future research.

It can be easily seen from the chart below that value factors do not exhibit consistent returns.
It is also important to take a closer look on the performance of the dividend-to-price factor during the years following financial crisis of 2007-2008. The substantial performance improvement during this period can indicate that the ability of the firm to pay dividend following the crisis are seen by the market as an indicator of healthy stream of company's earnings. However, the factor ignores alternative forms of payouts like share buybacks that can significantly impact factor performance.

Loading notebook preview...
Notebook previews are currently unavailable.
1 response

Hey Julij,

This analysis is great and we'd like to encourage more hypothesis testing like this. A lot of this analysis could be done directly on the factors using our factor analysis library tool, AlphaLens. You can even copy paste the factors out of the pipeline API in the backtester.

Doing the analysis this way also enables you to do more granular analysis and test hypotheses more rigorously. One caveat is that due to current memory constraints on the research environment you need to run your factors in 6mos batches and stitch the results together. We're working to fix this issue.


The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by Quantopian. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Employee Retirement Income Security Act of 1974, as amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein. If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances. All investments involve risk, including loss of principal. Quantopian makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances.