Where are the FANGs?

Investors may find it hard to believe that there can be a systematic process, a machine, with a scoring system that anticipated the future on January 2022 at the market peak and decided to underweight the FANGs so much that not even one featured in the top 10 list. There are many ways to explain this and the simplest way to explain it is as follows.?

Figure 1: E&R U.S. 100 vs. S&P 100 Top 10

Modern finance is built on a scoring system. It was in 1968 that Ray Ball and Philip Brown considered the content of accounting information, the flow of information, the relevance of information, its predictive powers, and its continuity and time dependence. Since then the stock market believes in the power of fundamental information. Though there were other research papers, which confronted the idea of a fundamental world, like Rolf Banz (1978), who said that Size could be a proxy, it did not make a dent in mass perception regarding fundamental information. Fundamental data give humans a sense of explainability and hence majority will continue to rely on fundamental scoring of some kind, be it the Nobel Prize-winning work of Fama and French or the Investment rules of Graham and Dodd, even if the framework does not work and it is an ineffective tool to beat the market. Robert Shiller illustrated the unexplained fluctuations in 1981 and there is a ton of literature on both sides of the relevant and irrelevant information debate.

For us at AlphaBlock, fundamental, technical, quantitative, sentimental, crowd or other data, follow two statistical laws. Either that data (causal explanation) is persisting like a positive fat tail (black swan negative tail), which keeps growing (decaying), despite everything, a gravity-defying (induced) trend, like the Bitcoin price reaching the sky (or collapsing), or the same data point is changing a trend, an inflection, a turnaround, a reversal, stopping just before it reaches the moon, or stopping just when it is all hopeless and there is no end in sight. Our scoring process studies these two laws of persistence and reversion and based on them, our machines score and weight components of a portfolio, index, and basket. We add the element of time to these laws i.e. how long something that is persisting or reversing is continuing to do so. Our methodology is all Science, no fiction, available on Github.

And somehow, because the world is lost in translation, deciphering the ever-changing landscape of information while we teach our machines to embrace uncertainty, and look at information as a chaotic mechanism, a model of life, a quantum function, we become the agnostics. We of course have the company of our friends from the S&P, who also don’t read the newspaper to score. They rank everything on Size, the bigger the better. This makes our life a lot easier, all we need to do is to take the top 100 large-cap companies and tell the machine to do the rest. The machine cleans the data, indexes it, ranks it, allocates probabilities, and builds the portfolio, unique to a starting point. The machine follows the rules of anti-concentration. S&P loves concentration and we hate concentration so much that we have biased our machines against unwarranted concentration risk. And this is what our machines did on Jan 2022, underweighted all the FANGs before the F and N vanished from the top 10 list of S&P 100.

Figure 2: E&R U.S. 100 vs. S&P 100

Figure 3: E&R U.S. 100 performance metrics

Our Exceptional & Rich U.S. 100 Index delivered a whopping 6% this year above the S&P 100. And it did a lot more than underweight the FANGs, it also underweighted Tesla, delivered excess returns at 2.5% less annualized volatility than the S&P 100 at under 6% tracking error and Active Share more than 60%.

We license these Indexes wrapped in Electronic Investment Funds, which do not charge any management fees, are delivered by our advisory partners, without advisory fees, only pay - for - alpha after 12 months. Money saved is money earned and risk reduced is loss mitigated.

If you are an asset owner, Investment advisor or asset manager interested in knowing more about our Exceptional and Rich Indexes and our Electronic Investment Funds (EIFs), drop us an email at [email protected]

AlphaBlock Team

Bibliography

1] Ball. R, Brown. P, "An Empirical Evaluation of Accounting Income Numbers", Journal of Accounting Research, 1968

[2] Banz. R, "The relationship between return and market value of common stocks, Journal of Financial Economics, 1978

3] Pal. M, "The Size Proxy", SSRN, 2016