Replicating a basket of Hedge Fund positions seems not to be an effective strategy, demonstrated by the lackluster performance of ALFA, GURU etc. copycat ETFs. An alternative strategy, premised on that insider information advantage can be reaped and converted to the alpha signal, are gaining more traction.
The rationale is simple, whether a company is running steadily healthy or in a deteriorating status, the one who knows the best is the CEO or likewise position holders – insiders. And for their own interest, they very likely will act upon the information they have to trade – sell if the company is in a downtrending tube; buy if sales are picking up far ahead of the outsides can feel any difference. Therefore, following the trading pattern of insiders is a good alpha-seeking strategy.
Thanks to the SEC regulation that significant position holders in the company are required to report their tradings in a form called 4s, allowing investors to act upon this informaiton., subsequently, indexers can systematically comb through this type of regulatory filings to pack in a list of companies on the buy/sell timing for the ETF to be formed.
KNOW and NFO are two representative funds of this kind, with $240 and $71 million AuMs as of May 2017 respectively.
The Direxion All Cap Insider Sentiment Shares ETF, KNOW, was issued in December 2011, tracks Sabrient Multi-Cap Insider/Analyst Quant-Weighted Index. it’s based on the available insider activity and analyst estimates and confirms the information to avoid behavioral pitfalls of the insiders and analysts.
Sabrient’s proprietary forensic accounting methodology will first remove those companeis with aggressive accounting practices, then a “defensive sentiment” overlay is used to identify stocks from the previous pool of strong insider/analyst stocks that have strong free cash flow yield, strong dividend yield, and have performed well in weak markets over the past 60 days. The index is rebalanced monthly; there are no sector concentration restrictions and no turnover limitations.
Even the broad concept of riding on insider trading is intuitive and seems straightforwad, there are lot of nuances and Sabrient did a great job to crack the codes to formulate a rigorous computation. For example, insiders often-times can be overoptimistic and habitually anchoring on their own comapanies’ stock for psychologicla reasons, so Sabrient devleoped a non-linear relevance scoring system to test logical combinations of all possibilities. Another example is some tradings are triggered not by their judgment but for liqudity needs. So Sabrient applied Open-market purchases analysis rather than blind utilization of Form 4s. what’s more, Sabrient regards Wall Street analysts as somewhat insiders too because these analysts breathe and live companies they analyze, thus grasped deep inside knowledge too.
Lastly, the weighting is quite innovative that they decided to “quant-weight” each of the 100 stocks that make it to the final portfolio. They weight each position in a piecewise exponential fashion so that the top 50 represent a range of 2.6% (for the highest ranked stock) to 0.96% for the 50th ranked stock; then flat-weight the bottom 50 stocks so that each represents 0.35% of the index. This captures the benefit of exponential weighting without under-representing the bottom stocks and ensures adequate diversification and liquidity.
NFO, The Guggenheim Insider Sentiment ETF, started much earlier in September 2006, but only accumulated $70 million assets so far. It tracks Nasdaq US Insider Sentiment Index. Looking into this index, the methodology is relatively more simplistic compared to Sabrient’s. It designed to provide exposure to U.S. companies within the Nasdaq US Large Mid Cap Index (which consists of approximately 900 stocks) which exhibit high degrees of corporate insider buying. The universe of securities is screened by a series of three factors—increase in average shares held by corporate insiders, and a combination of positive share price momentum and lower share price volatility. The 100 highest-ranking securities, subject to industry weight constraints, are selected for inclusion in the Index and an equal weighting methodology is applied.
Complexity doesn’t necessary equal or translate to performance, comparing these two funds with S&P 500 performance, we can see firstly, the insider sentiment trading strategy does work, both KNOW and NFO has outperformed the market over the years, secondly, NFL and KNOW are highly correlated, additional complexity imposed by KNOW seems not to be necessary, on the other hand, KNOW, being a more insider sentiment focused fund, it’s been attracting more investment as well as achieving better return than NFO.