Sunday, February 26, 2012

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,, 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.

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