Crowdsourced stock market trading

Stock market trading has become a dirty word, or if not that, at least uninteresting. Wall Street excesses and the 2008 crash have led to little recent opportunity for financial return (non-existent interest rates for saving, and flat stock markets for equities (the S&P 500 return in 2011 was 0% (S&P 1257 at 12/31/10, 1258 at 12/31/11). Gold has been one of the only asset classes to realize real return (142% five-year return, $632 as of 12/28/06, $1531 as of 12/29/11). The particular subjective day trader gave way to faceless high-frequency computer algorithms as one of the only means of squeezing profits out of the stock market.

One thing that could turn this around, and have the dual benefit of bringing more transparency to markets and market practices is crowdsourcing. The enormous amounts of clean, freely available, computable, straightforward-to-understand data without privacy issues are ideal for crowdsourced manipulation.

Earlier attempts at applying crowdsourcing to stock market trading (for example, Yahoo Prediction Markets with leaderboard-style tracking of traders’ mock portfolios) fell by the wayside with the 2008 crash, but the concept could be reincarnated. There are several obvious ways to deploy crowdsourcing in stock market trading startups:

1. First would be a direct implementation of crowdsourcing as from the Wikinomics, fold.it, eteRNA model: making usable web-based datasets available to the wisdom-of-crowds to apply diverse ideas from different disciplines, often resulting in better results than those produced by the ‘experts’ in any field. Leaderboards, competition, leveling-up, forums, badges, and other gamefication techniques would be expected.
2. Second would be a platform where real-life traders can open source their trades, either before or after execution. Interested traders would grant open access to their trade logs, inviting crowd review to find winning trades, strategies, and traders, and conduct meta-analyses like what strategies work well in a high-volatility environment, a down economy, etc.
3. Third would be prediction markets 2.0, a more social gamefication implementation of prediction markets for stock trading, sales forecasting, movie hit projections, elections, and flu outbreaks through platforms like Iowa Electronic Markets, Intrade, etc.

Design and the disruptive startup: dynamic pivoting

In the mashup world of life, business, and web 2.0, spurred on by the Apple-ification of the world (iLife - as a concept not a product), one new idea is applying design to business models, and really by extension, applying design to everything.

Unfortunately, this does not mean as one might think, applying aesthetic principles, conceptually and literally, to business, business models, or any life context, adding beauty to function, and thereby function to function, and questioning the right proportionality of form and function.

Rather, at present applying design to business models means more basically, using design tools and design thinking in a business context, specifically, in the conduct of an iterative prototyping process with users.

In business 1.0, an entrepreneur would dream up an idea and write a business plan. In business 2.0, the claim is that entrepreneurs should interview dozens of potential customers to pivot through value propositions for ideas that solve the biggest customer pain points. Customer acquisition is tantamount, in a 'get, keep, grow' cycle. Elliptical tools like the business model canvas are proposed as support for this iterative prototyping process.

Long-tail economics extended to physical objects

Chris Anderson, editor of WIRED magazine, gave an excellent talk on August 5, 2010 at the PARC Forum. He explained how the long-tail economic models which have driven digital content (allowing consumers to access books, music, and movies in the 80% of the market that is not blockbusters) are now starting to appear in the world of physical goods.

The process of realizing long-tail economics in any sector is that of going one-to-many; democratizing the tools of creation, then the tools of production, and finally the tools of distribution. This is what happened with internet content such as publishing, where it is now easy for anyone to create, produce, and distribute content with blogs, twitter feeds, YouTube, etc. This has also happened with other digital content and some physical goods that are ordered and distributed via internet models (e.g.; Amazon, Zappos, etc.).

The new industrial revolution, argues Anderson, is in opensource hardware factories. The supply chain has now opened up to the digital and the small. The ability to make and distribute anything massively decentralizes traditional manufacturing and could completely reorganize industrial economies…atoms are the new bits. Matthew Sobol’s holons (communities of local resilience and sustainability) are in the works. Goods can be self-designed or crafted from available digital designs (e.g.; communities like ShapeWays and Ponoko), and then printed locally on the MakerBot or ordered from Alibaba or other global manufacturies. Opensource manufacturing is starting to have an impact on industries like auto design and construction (e.g.; Local Motors), drones (e.g.; DIY Drones), and general hardware design (empowered by the Beagle Board and Arduino).

It is likely that long-tail economics can be applied to many other areas. Medicine is the next obvious example, where health care, health maintenance, drug development, and disease treatment are already starting to shift into n=1 or n=small group tiers of greater customization and ideally, lower cost as more precision is obtained in the measuring and understanding of disease and wellness.

Economics taboo in life sciences

It is considered impolite at best to ask life sciences companies about their cost structure and pricing strategies. Life sciences executives can often appear naive, incognizant and uncaring about the basic economics of their industry. They appear to exclusively and superficially target profit maximization and wholly propriety IP development and protection; ironic given the greater goals of healthcare. Life sciences as an industry seems to be at least twenty years behind the high tech industries such as computing and communications in terms of understanding and delivering economic value to a wide audience of end consumers, and in terms of openness and collaboration.

Fixed and variable costs, pricing strategies and quantitative aspects of customer demand are much more known and openly shared and discussed by companies in the high tech industries. That critical piece of entrepreneurialism, understanding the specific economic value of a product or service to the end consumer is absent in life sciences. The problem of course is the “third party pays” dynamic in life sciences where a third party, insurers, pays for services consumed by patients. If patients knew, or perhaps were even paying, prices, their behavior would likely be much more rational, and so too would health services offering have to be much more rational. Price is not discussed and is rarely even available at the doctor’s office.

Future of entrepreneurialism

The traditional definition of entrepreneurship is expanding to include more creative ways of approaching business, applying business disciplines to social problems and establishing a wider range of success metrics. Four key trends are coming together to facilitate this new era of entrepreneurship: a shift in social consciousness, the democratization of capital, innovative responses to traditional financial systems and the low cost of starting a startup in the globalized world.

Shift in social consciousness
There is a great attitude shift underway towards sustainability and social responsibility. Al Gore, Paul Hawken and others have helped to put global warming, carbon neutrality, poverty and equity firmly on the international agenda. Part of the new social consciousness is also about effectiveness and accountability. Cycling the bottom of the pyramid out of poverty requires getting target populations actively involved. Loans are better than aid.

Democratization of capital
The ability to have more granular attribute knowledge about all economic transactions has triggered the demand to direct capital and consumption based on these affinity attributes. People are willing to pay on average 5-10% more for their attribute choices, for fair-trade, organic and local items, for hybrid cars and for blended value or double/triple bottom line financial returns.

Innovations to the traditional financial system
The shortcomings of traditional financial systems, their hierarchical nature, the lack of universal access and cyclic failures like the current mortgage crisis are triggering innovative solutions such as…

• Microfinance and P2P finance (for example, Kiva is currently active in 40 countries and lending about $750,000 per week)
• Socially Responsible Investing and social capital markets including social venture capital as offered by GoodCap
• Timebanks, gift economies and other non-monetary currency solutions
• Alternative payment mechanisms like developing country cell phone networks as money transfer systems

Low cost of starting a startup in the globalized world
The increasingly low cost of starting a startup makes a whole new tier of businesses possible: the LAMP software bundle provides free technology infrastructure, APIs replace business development and blogs and community interaction replace marketing (social networks become an overlay, a property of every website) and virtual world interactions replace face-to-face meetings.

Angel investors drive innovation

The Center for Venture Research at the University of New Hampshire reported that in 2007, angels invested almost as much as venture capitalists in startup companies, $26.0 billion vs. $29.4 billion. Focused on seed and startup stage financings, angels invested in far more firms, 57,120 vs. 3,813 for venture capitalists. Angel investment growth was flat in 2007 vs. 2006 while venture capital investment grew 11%. San Francisco Bay Area angel investors comprised 10% of total angel investment activity. As with venture capital, the top four categories of angel investment in order were software, healthcare, biotech and energy.

Angel investing was once a solitary activity driven by personal networks, the practice has been formalizing in the last several years and there are now over 150 angel investor groups in the U.S. and Canada. The groups typically meet monthly where 3-6 pre-screened companies present to members. Angel investors are not disengaged retirees, 80% continue to be actively involved in the business world. Cleantech and even social venture capital are starting to be interest areas for angel investors.

Angel investors are a critical component of the entrepreneurial ecosystem and should be encouraged and sponsored by communities trying to establish a more innovative environment. For startups, angels can be an important resource for funding, feedback, contacts and exposure. The contribution and impact of angel investors can be expected to grow.