Seth Goldstein

Self Operating Machines

The most exciting new Internet companies are focused on lead generation, behavioral targeting, co-registration paths (aka coreg) and domain name brokerage.

I seem to stumble every day across some new firm propping itself up on the shoulders of Google, Yahoo! or others to take advantage of a current wrinkle in an otherwise perfectly efficient landscape.  The fact is, however, that these wrinkles never seem to disappear.  These advertising mechanisms emerged alongside of the pure media companies, starting with Doubleclick back in 1996, and followed by other advertising networks such as Flycast, Overture and Advertising.com, each firm iterating on the prior model to gain some head room from the imminent internal advertising service offerings of the pure media companies.

Although these advertising technologies have focused on targeting the behavior of consumers, they have also tended to ignore the role of consumers in the production process of the media that they consume.  This is why these networks tend to dynamically balloon in terms of sales growth.  They capitalize on a behavioral blindspot, where the supply of inventory versus the demands of advertising value are disjointed.  As consumers become smart about these artificial mechanisms (banners, keywords, freeipods) their effectiveness drops and they look to get acquired by larger media entities.

The elusive goal of internet media (and the advertising that drives its value) has been to keep up with changing consumer preferences as the technologies of communication continue to evolve.  The adoption of a new means of using the Internet (whether it be ecommerce, webmail, search engines, or shortly blog readers) creates enormous economic value for the donors incredibly quickly. 

The latest shift in online consumption has been the institutionalization of amateur publishing tools.  The unique attribute of RSS is how simply it enables individual publishers of data to connect with individual subscribers to such data.  RSS tools like typepad, flickr, adsense and del.icio.us have made it easy for individuals to syndicate their preferences, memories and desires.  RSS tracking tools like feedburner make it easy for individuals to track who is paying attention.  At the site you are on, I am streaming my Flickr photos, am recommending books as an Amazon associate and am promoting a Google ad-sense ad.

Not unlike dial-up authentication protocols (remember the classic AOL logon "hand-shake"),  the interaction between RSS feeds and their readers is a structured negotiation:  do you, John Q. Public, agree to take the whole feed, nothing but the feed, until you delete it?  I do. Click.   

When you aggregate all of these individual reading and writing agents, it looks more like a landscape of cellular automata than a tradition publishing model.  This would seem to be the essence of social media (props to my wife and guide Tina Sharkey for coining this years ago and registering the domain) and social computing, two memes that seem to be growing in influence.  When individual decisions such as applying certain tags to pages or photos achieve a broad social consensus, then it as if these tags begin to self replicate which is the essence of automatic behavior.

There is a good word to describe this, which comes out of physics, namely Excitable Media.  as per Wikipedia:

Cellular automata provide a simple model to aid the understanding of excitable media. Each cell of the automaton is made to represent some section of the medium (for example, a patch of trees in a forest, or stress in heart tissue). Each cell can be in one of the three following states:

Quiescent or excitable — the cell is unexcited, and can be excited. In the forest fire example, this corresponds to the trees being unburnt.

Excited — the cell is excited. The trees are on fire.

Refractory — the cell has recently been excited and has not yet been through the refractory period. A patch of land where the trees have burnt and the vegetation has yet to regrow.

The concept of cellular automata is useful as a metaphor for next generation Internet content, which is similarly dynamic, member-generated, and excitable.  In the next post, I will focus on algorithms, as they transform the automatic social media into business rules and procedures. 

Last month I held a workshop with the elegant, imaginative programmer Steve Steinberg of GGH at Web 2.0.  The conference was at times a best-hits convention of the SF Internet scene circa 1999, but in other important ways a series of discussions about the evolution of the Web as a platform.  Instead of large sites connected by single links, as the web may have looked 10 years ago, now we have niche pages and targeted offers connected through elaborate search algorithms, RSS feeds, and affiliate marketing networks. 

The conversation with Steve started as follows:

It is easy to confuse the Internet as a medium of distribution with the Internet as a computational platform. Nowhere is this confusion more pronounced than in the use of the Internet by investors.

Usually, investors think of Yahoo! Finance or Ameritrade. No doubt the Internet has emerged as a useful source of information and a convenient brokerage interface, but do these uses qualify as platform applications?

Beneath the user functionality of the web hums a constant drone of data processing. This is the under-web of click-streams, item listings, user queries, and other flora and fauna of network behavior.  This is the web tone for investors: filled with important data insights usually lost in the noise of random traffic.

The challenge is how to interpret the Internet platform for financial gain. In so far as there is no “Bloomberg” for analyzing Internet and other electronic transaction patterns, investors today are faced with myriad tools, techniques and sources of information that require significant manual effort to correlate.

The typical search box is a limited tool for investors, since understanding what metrics one is looking for is almost as important as the metrics themselves. Most publicly-traded companies (for instance the majority of those in health care, technology, retail and financial services) serve different customers differently and so understanding such companies require monitors across the full length of the supply and demand chain.

We proceeded to lay out a number of examples of how the Web could be searched, scraped, bot-ted, mined, and grokked for unique information on publicly traded equities.  We touched on the dangerous temptation to trust data simply because it’s data (when in fact as we all know data carries with it many of the same assumptions and biases of anecdotal water cooler observations).  We also focused on the gray area separating legitimate data discovery from the act of stumbling across (or better yet, browsing into) material non public information in an otherwise public network such as the Web.

The combination of insider information restrictions and Regulation Fair Disclosure has become the impetus for equity research to continually reinvent itself.  As the SEC has written in the case of Reg FD:

"Whenever an issuer, or any person acting on its behalf, discloses any material nonpublic information regarding that issuer or its securities to [certain enumerated persons], the issuer shall make public disclosure of that information… simultaneously, in the case of an intentional disclosure; and… promptly, in the case of a non-intentional disclosure."

The Emergence of a Packet Switched Research Model?

Insofar as such information is disclosed by a person (ie the CFO) to another person (ie an analyst at a Brokerage or at a fund) then the steps required are simple enough:  issue a press release immediately to everybody via the web.  It is decidedly more complex when such information is disclosed in bits and pieces, asynchronously through a “network of experts” composed of employees and consultants inside and outside of the company in question, issued to a buzzing audience of analysts and portfolio managers pushing and prodding at various aspects of the company’s performance.  If the CFO’s wink to the Sell Side analyst at the 17^th hole was the equivalent of dedicated circuit switch, then the current instance of buy-side analyst communities polling networks of industry and sell-side experts suggests the emergence of a packet switched research model.

Perhaps the full obsolescence of Reg FD as we know it emerges when research shifts its register from people to data entirely—when companies become fully transparent (cf. Bill Gross’s latest invention Snap), or else their transparency is enabled by others (cf. Majestic Research’s analysis of Ebay as well as other examples of Internet-based economic research).  At such moment, the entire notion of a privileged perspective dissolves—there is no longer an edge in trying to "game" the quarter– and the investor is forced to develop a new strategy for evaluating the equity. 

Otherwise, the index funds may integrate the public data themselves and force a number of highly paid fund managers to leave for the summer house in January.

We live in an equity culture. Perhaps it is because of the the legacy of the 401k, or the cultural influence of Peter Lynch, Warren Buffett the media focus on hi-growth technology enterprises like Microsoft, Intel, Ebay and Google. In any case, the gross majority of adults in this country own stocks of one kind or another, through a variety of brokerage, retirement and college savings accounts. The most convenient mechanism for investing in the stock market remains mutual funds, which typically charge a fee based on assets under management (AUM).

Despite a stellar 2003 where most mutual fund performance mimicked those of the broader indices, retail investors have come to question the credibility of some of the largest mutual fund complexes. This has come in the wake of Spitzer lawsuits against market timing and directed brokerage arrangements as well as the lingering effects of the bursting of the technology bubble in late 2000. Certain funds such as Fidelity and T Rowe Price seem to have managed to keep their reputations in tact, others such as Janus and Strong are working hard to rebuild their brand equity.

In the face of legislation, lawsuits and media criticism, mutual funds have become significantly more cautious. They can’t afford to become associated with any more scandals or be on the wrong side of any potential legislation. Mutual funds continue to lose their most successful fund managers and research analysts to unregulated hedge funds where such managers and analysts can make far more money with far less scrutiny. As if the brain drain wasn’t bad enough, mutual funds can no longer (by virtue of their huge asset bases) command proprietary information from companies since Regulation FD mandates that all investors receive material information concurrently.

One would expect that mutual funds would take this opportunity to reinvent themselves and distinguish their products through innovative research strategies. Ironically, however, mutual funds seem less willing to try new forms of research than ever. Structurally, there has been a virtual, self-imposed ban on soft dollars within the mutual fund industry. Mutual funds suggest that they will pay for independent research through their management fees, but in reality they would prefer to pay directly through trades to the proprietary desk of the research provider. The only problem is that most of the emerging value-added independent research providers produce innovative research as opposed to provide trade execution. The firms that the mutual funds are comfortable trading with (and thereby willing to purchase research from) remain the same large sell side institutions that have been replacing their equity analysts with in-house proprietary traders, who actually compete with the mutual funds themselves.

Against the backdrop of these challenges, hedge funds continue to acquire assets, track records and brains. In the last few weeks alone, I have heard of one fund that has just passed $1b in assets from only $100m about a year ago; another fund that has gone from $600m to north of $2b in 12 months; and a new hedge fund that just launched with north of $3b. There seems to be no shortage of institutional capital available to the best or most promising hedge fund managers. Risk management technologies and portfolio reporting platforms provide a level of comfort and transparency that has created enormous liquidity among funds of funds acting as intermediaries between single manager hedge funds and family offices, pension funds and endowments. Hedge funds would seem to be happy to ignore the average retail investor and focus exclusively, in perpetuity on institutional investors.

But then I heard something that surprised me. One hedge fund manager that I have enormous respect for shared the basic fact that he rarely makes money on the short side but maintains a hedged strategy because of the 2 & 20 fee structure that he is able to charge. His argument is that he could make less than 1% of AUM with a long only strategy and as much as 5x that with the same long book with a few short positions (even if they aren’t what’s contributing to the performance of the fund).

The second incident that caught my attention was the open rumor that a very large, very sophisticated, and very secretive hedge fund had tried to acquire the assets of a well-known mutual fund complex that had run across difficult times.

The third point in this nexus is the fact that Bill Miller, the legendary manager of Legg Mason’s mutual funds and certain portfolio managers at Fidelity have begun to utilize short positions as well as their long positions in a modified mutual fund meets hedge fund strategy.

And so when I synthesized these trends in my mind, I realized that it is inevitable for the line between hedge funds and mutual funds to become more and more vague. It is only a matter of time before the best mutual funds begin offering premium hedge fund-like strategies (with higher fees) for their top retail customers. At the same time, as certain of the savviest and most institutionalized hedge funds grow beyond their somewhat narrow professional investor base, they will likely acquire and/or merge with existing mutual fund franchises in order to acquire retail investment assets. One thing that has always plagued hedge funds has been the lack of long term equity value. You are only as good as your last year, as it were. With a mutual fund apparatus (and the long term brand equity value it might bring), perhaps hedge funds could establish equity above and beyond the presence of their founders.

As I look out over the next few years, here are some of the consequences that seem to be natural outcomes of these developments:

• Everybody (individuals and institutions) will be able to have their money managed by top hedge fund managers.

• As hedge funds, new long/short mutual fund strategies, and internal funds within banks start functioning more and more as a single asset class, the costs for investors will find a standard rate (2% of AUM and 20% of upside)
• Investors that are not willing to pay the market rate for sophisticated money management, but who do not want to actively manage their own portfolios, will likely simply opt for index funds which may replace traditional single manager mutual funds as the mass consumer investment instrument of choice.

• Funds with north of $1b will be forced to trade in the same crowded names because the number of equities of adequate liquidity is not growing nearly as fast as the funds are (ie hedge fund strategies will proliferate faster than the number of unique, tradable equity ideas available)

• The best opportunities for investment performance will reside in smaller, undiscovered hedge funds that have yet to break $100m in AUM and remain below the radar of fund of fund promoters. Same phenomena as signing Maroon5 when it was playing lounges in LA or Pedro Martinez when he was throwing coconuts in the Dominican Republic. Only these smaller funds will have the flexibility to move in and out of positions in smaller cap names and truly outperform the indices.

• The next generation of the sell-side will take its cues from the current experiments of independent research firms and direct access electronic trading platforms. The most successful sell-side firms will marry outsourced data acquisition and information analysis with electronic trading to become underlying, enabling operating systems for the buy-side to collaborate with and compete against itself.

• As trade execution and traditional equity analysis become commodities given away for free, the value of proprietary trading strategies and exclusive data will rapidly increase.

• The next generation of great Wall Street franchises will be created by software developers and information brokers rather than by equity analysts and sales traders.