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Democratizing Wall Street: Inspired by 'Hoofy & Boo,' 'Seasonal Odds' Aims to Level the Playing Field

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Here's how a Harvard PhD Candidate and a Visiting Scholar at the Federal Reserve was inspired to work in financial education by watching animated cartoons.

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Most people at the US Federal Reserve would understandably be reluctant to admit that they first learned about financial markets from an animated talking bear.

Likely most did not. But I am the front end of a very different generation - late-twenty-somethings who first became aware of markets when the Internet was already in existence, and who underwent many of their early financial educational experiences online.

While many in the early 2000s wondered what would come of the kids who were spending countless hours in front of these new, interconnected computer screens, I am happy to report that my hours spent with two animated talking characters in particular - Hoofy and Boo - christened a journey into markets and finance that years later culminated in a PhD at Harvard and a Visiting Scholar position at the Federal Reserve. The New Media - and especially Hoofy and Boo - now have at least one coming-of-age success story - and without a doubt, hundreds more will emerge over the coming years as the teenagers who grew up with them leave university and enter the upper echelons of Wall Street.

Why would a PhD Candidate at Harvard and a Visiting Scholar at the Federal Reserve admit that he started his journey into financial education by watching animated cartoons? Because at a time when wealth is becoming increasingly stratified, information technology and New Media are one of the few prevailing counterforces. They are transforming financial education, increasing transparency around once-proprietary knowledge, and leveling the playing field in a domain of human activity where, as Gordon Gekko once put it, information is the most valuable commodity.

I am merely a case in point. I come from a middle-class family and went to public school all my life prior to studying political economy at Harvard. But my experiences with Hoofy and Boo - and the success I've been fortunate enough to enjoy in my educational and professional life (without having had the benefit of private tutors or the advantages of elite boarding schools) - is emblematic of what becomes possible when education is democratized by information technology.

As those adorable characters argued about finance in their timeless, ageless sessions, my generation gained an appealing window into forms of financial knowledge that many on Wall Street hoarded in order to earn their livelihoods.

Of course, Hoofy and Boo - and the immersive online education movements they represent - are only the most recent data points in the centuries-long growth curve of informational access. At one point, mere numeracy itself - the ability to understand basic arithmetic - separated those who were empowered to benefit from commerce from those who could not even verify whether they were being shortchanged. Around the time of the Renaissance, the development of a relatively standardized system of accounting ledgers empowered merchants to track an increasing array of private transactions, where once only kings and lords had the resources to accurately maintain such accounts. The development of relatively commoditized private lending and borrowing over the subsequent centuries (on terms more standardized than Shylock's "flesh bond" in The Merchant of Venice) enabled a robust commercial class to emerge from the financial grip of those same European monarchs, arguably precipitating many of the political revolutions that followed.

The founding of the Dutch East India Company in 1602 and the first stock exchanges that emerged in Holland and Britain over the course of that century provided ordinary laymen with the first-ever opportunity to participate in the risks and benefits of what were previously the exclusive profit domains of sovereign states, their kings, and treasuries, such as naval exploration, foreign trade, wars, and large-scale infrastructure projects. Similarly, the creation of early insurance and pension instruments in late 17th century Britain increased mass public accessibility to financial planning, and introduced the first-ever possibility that the lives of ordinary people and their families could be "hedged" against what Shakespeare called "the Slings and Arrows of outrageous Fortune" and the "whips and scorns of time."

In the 20th century, the rise of electronic trading, online brokerages, and ETFs enabled private middle class citizens - with no access to wealth managers or hedge funds - to gain types of market exposure and speeds of execution that were previously only imaginable to elite financial professionals meeting in glass-walled boardrooms overlooking Central Park.

Having been in many such boardrooms, I can confirm that this last step - where the ordinary citizens are freed from the professional merchant class, which itself was freed from the sovereign state - is perhaps the most disruptive transformation in financial markets that the world has ever known. Put another way, there is now less and less that the average private citizen investor structurally cannot do, once they learn how to do it, and whether or not they should. I recall a conversation I had with Chris Peacock, a senior editor at CNN, who described the feeling of almost 'subversive' empowerment he felt on behalf of Main Street when CNN first made electronic stock quotes available on the Web for free. Make no mistake, technological change is and always has been about subversion, disruption, creative distraction, and the empowerment of a new class of beneficiaries at the expense of an old guard.

Obviously this is alarming for existing financial power structures, and so it is in this respect that Gordon Gekko's mantra - information is the most valuable commodity - takes on special significance, with elite financial institutions, such as hedge funds, attempting to maintain as tight a grip as possible on the last informational totems of their exclusivity and power. Counterforces, such as Minyanville, the online edition of The Economist, StockTwits, and others - using all the most powerful new tools and innovations afforded by revolutions in information technology - are oppositely working to spread and disseminate this knowledge as widely and quickly as possible.

In my case, the counterforce prevailed, and while not coming from an elite commercial class, I was empowered by information (yes, by animated talking bears, as well as the many other information technology-enabled resources I would later use over the course of my studies) to the point where I could come to deeply understand that sector of society and how it functioned.

It is for this reason that I feel it is only appropriate and fair that the emerging contribution to this long-run historical democratization of financial markets and information made by myself and my colleagues from Harvard and MIT - a statistical computing engine that makes the now-famous big data statistical analysis capabilities of a few elite hedge funds accessible to ordinary people - is debuted in its retail form on the very site where I was first inspired and introduced to financial markets.

Throughout Minyanville, you will now see a "Trading Calendar" - the simplest and most accessible embodiment of our large-scale statistical computing capabilities. For more than 7,000 US equities, it answers the most basic question in financial markets, "Is now a good time to buy this stock?", by dynamically computing and updating the historical performance of the stock surrounding the current period of the trading year. Like sports networks tabulating batting averages and player lineups to predict the outcomes of games, hedge funds use such tools to help them determine statistical probabilities surrounding the risk and profitability of the trades they are considering. This allows them to attempt to only hold positions during statistically favorable periods, and to discover and capitalize on pricing anomalies that until now were invisible to retail investors. For example, Wal-Mart Store, Inc. (NYSE:WMT) has for the last four decades experienced seasonal pricing anomalies (perhaps corresponding to the highly seasonal nature of their own retail sales) that are well known in the hedge fund world: While the stock is positive less than half of the time in September, it has, over the last 35 years, rallied 73% of the time in March, returning an average of 4.56% -- more than half of a year's return for some asset managers for a month's worth of risk exposure.

Such pricing anomalies are not idiosyncratic to Wal-Mart. Apple Inc. (NASDAQ:AAPL), also a retail-cycle-oriented company, has been positive only 40% of the time in September over the last three decades while rallying 68% of the time in October, returning an average of 5.27%. It is the well-documented, persistent seasonal and cyclical price anomalies such as these that led the Wall Street Journal to alert its readers, back in 2010, that, "There's ample evidence that the stock market's performance is tied to the time of year and even the days of a month. Seasonal patterns persist not just in the US, but in other countries as well. If you recognize these patterns, you can increase the odds of matching or even outperforming the market with considerably less risk."

Of course, true to the exclusive form of much of Wall Street, the Wall Street Journal tantalized its readers with this declaration without providing them with any further information on which seasons or cycles could actually lead ordinary retail investors (who presumably do not have their own high-grade statistical computing platforms) to "[outperform] the market with considerably less risk." For reference, here is the information that the Wall Street Journal did not provide: Over the last two decades, the best month for the S&P 500 (INDEXSP:.INX) has been December, during which it has rallied 75% of the time (15 out of the last 20 years) and in which it has averaged a return of 1.44%. The worst month for the S&P 500 historically has been July, in which it has only been positive 45% of the time over the last 20 years, averaging a return of only 0.34%.

As alluded to in the Wal-Mart and Apple examples, even more extreme pricing anomalies abound at the stock-specific level. For example, McDonald's Corporation (NYSE:MCD), a quintessential blue chip, has rallied more than 80% of the time in November over the last 33 years, gaining an average 3.53% in that month alone. In Las Vegas, the "house" is more than satisfied with 55%+ odds. But even the most statistically prudent casino actuaries seem like wild gamblers compared to the hedge funds that have pricing anomaly knowledge of three-decade persistent 80%+ odds in a blue chip stock.

It is precisely knowledge and information such as this, enabled by high-grade statistical computing, that gives financial professionals on Wall Street such an edge over retail investors. In the spirit of prying away one last informational advantage that elite financial institutions have kept for themselves, we are distributing these statistical computing tools across Minyanville, for Hoofy, Boo, and their hundreds of thousands of friends to use.

Thank you Hoofy and Boo! Keep education fun and information accessible. Greater wealth, prosperity, and fairness will always and inevitability follow, as it has from the time of the Renaissance right up to today.

Daniel J. Nadler is a PhD Candidate at Harvard University and a Visiting Scholar at the United States Federal Reserve. His writings have been featured in the Wall Street Journal and Bloomberg. His forthcoming book, The Global Debt Crisis, is being published by the Brookings Institution in 2013. In 2012 Daniel was profiled on CNN's What's Next, a program featuring "forward-looking thinkers in the fields of tech, science and social change who will help shape our collective future." Daniel is a co-founder of Kensho Technologies, one of the first cloud-based statistical computing and risk analysis platforms in the finance industry. Kensho is the maker of Seasonal Odds and the Trading Calendar technology used on Minyanville.
No positions in stocks mentioned.
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