Prediction Markets Round-Up

Prediction Markets are a tool for collecting group opinion using market principles. The price is usually based on a conversion of an opinion of the percent likely an event is to happen (i.e., the probability), for example there is a 40% change that Candidate X will win the election. The premise is that there is a lot of hidden information that can be sharable but there are not mechanisms to share it because information-holders either cannot or do not wish to share it (for example that a current work team project may not finish on time). Some research has found that prediction markets may beat polls or experts in terms of forecast accuracy [1].

Figure 1. Prediction Market Example

To aggregate hidden organizational opinion and expertise, Prediction Markets are in use at 100-200 large US organizations as of June 2014: Paypal, HP, BestBuy, Electronic Arts, Boeing, Amazon, Harvard, GM, Hallmark, P&G, Ford, Microsoft, Chevron, Lockheed Martin, CNN, Adobe, American Express, and Bosch. There are several enterprise Prediction Market vendors for enterprise idea management: Consensus Point, Inkling, Spigit/Crowdcast, Bright Idea, and Qmarkets. The main applications of Enterprise Prediction Markets are revenue forecasting, demand planning, and capital budgeting; innovation life cycle management (rate, filter, and prioritize ideas), and project management and risk management.

There are Enterprise Prediction Markets and also Consumer Prediction Markets for event prediction such as politics: election results; economics: box office receipts, product sales; and health: pandemic prediction. Some of the leading markets are Iowa Electronic Markets (and Iowa Electronic Health Markets), the Hollywood Stock Exchange (film box office, TV shows, celebrities), simExchange (gaming: video game consoles, video game launches), CROWDPARK (general), and LongBets (futurist). A new market, SciCast, has recently launched for detailed science and technology predictions.

Markets are typically real-money, reputation-based, or anonymous. In the wake of Intrade’s regulation-forced closure, Bitcoin Prediction Markets are enjoying a surge of trading activity; markets like Predictious, Fairlay, and Bitcoin Bull Bear.

More Information: Prediction Markets @ Singularity University

[1] Trepte, K. et al. Forecasting consumer products using prediction markets. MIT. 2009.

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.

Newtech: enterprise social networks

Like email, instant messaging, and wikis, the latest newtech spreading into businesses is social networks, essentially serving as a private internal version of Facebook and Twitter. Enterprise social networks are used for a number of purposes, first and foremost, status updates to work teams, but also for real-time messaging with colleagues including document transfer, broadcast announcements, and opinion capture via polls. There are several companies in the enterprise social software sector (Gartner chart). Among the most vibrant are Yammer and Chatter (affiliated with salesforce) each of which has over 100,000 corporate customers in a wide range of industries from finance to entertainment to professional sports; Jive is a third large company in the space. The standard pricing model appears to be freemium-based, free for light-users and $5/seat/month for power users. Enterprise social networks are typically externally-hosted.

Two of the key challenges that come to mind with enterprise social software are: consolidation with other internal communications platforms and data mining. As with enterprise instant messaging, archival and retrieval is important, both at the personal level (for productivity) and organization level (for information systems backup and compliance). There need to be effective ways to consolidate and mine multi-platform internal communications. Formalizing the explosion of casual interaction as it naturally occurs could be abstracted into value-added tools such as a codification of internal knowledge and expertise in the internal wiki for training purposes. It might also be possible to integrate communication flows unobtrusively and automatically into prediction markets or other sentiment analysis algorithms to capture opinion about key upcoming events like product launches and quarterly sales results.

Anticipative demand and consumer intent prediction

Social economic networks improve the value proposition for both individual and institutional consumers since products and services can be discovered and targeted with greater relevancy.

Rich attribute information posted publicly by social media users (individual and institutional) can be used by marketers and other interested parties (for example, potential employees) to infer the values, preferences, and interests of others. In response, hyper-personalized advertisements may be presented (Reference: Shih, The Facebook Era, 2009).

Hyper-targeted-marketing, recommendations, and authentic product endorsements from friends are some of the ways that social economic networks have improved commerce relevancy.

The next obvious step would be for vendors to predict demand before it occurs, responding to customer intention.

Intention prediction could be accomplished by merging aggregate Facebook or other social media ‘likes’ and comments from high-influence users into purchase intent well before sales transactions. An anticipative demand market could arise.

Traditional economics equations could be further transformed as vendors test large varieties of targeted offerings in cost-effective ways via the internet.

The long-tail of supply and demand could meet in millions of micro-markets, possibly even at the level of individual pricing and individual offerings. Smaller lot sizes means higher margin. There are numerous entrepreneurial opportunities in facilitating product and service generation, production, and distribution at the level of n=1.

Social currency unlocks value for individuals and organizations

Social currency, shared information which encourages further social encounters, is transacted through social economic networks.

From an economic perspective, the role of social economic networks is to unlock and monetize hidden value. This value is mainly in the form of information asymmetry as buyers and sellers hold information that is useful to each other. Both buyer and seller realize greater utility than if the social economic network did not exist.

Social economic networks are impacting both individuals and organizations at the global and local level. Transactions may be between anonymous parties or parties who know each other. For example, in the Groupon / Peixe Urbano group-purchasing model, individuals pre-commit to a purchase to obtain a discount if a minimum number of people participate.

With social economic networks, organizations can unlock intellectual capital (social business intelligence) in ways that were not possible before with tools such as prediction markets (a mechanism for collecting and aggregating opinion using market principles). The concepts are attractive on a global level and can be implemented on a local level with the democratizing power of the internet.

Social economic networks could likely grow in the next several years, particularly in the type of assets created, and in the venues and models for their exchange.

The real-time economy

The encephalization of the earth (the coming together of human minds in a variety of higher resolution formats) is picking up speed. More and more people have a pass to join the information highway – Honest Signals points out that ten years ago, less than half the world’s population had made a phone call, but today, 70% of the world’s population has access to a phone for calls and texting.

Numerous collective intelligence tools have been emerging to uplevel and structure the context and quality of human interaction. The Wikipedia is the quintessential collective intelligence tool, as are wikis generally, social networks, buzzing and tweeting status updates, collaboration websites, question networks, social purchasing networks, and prediction markets.

The real-time economy
The pulse of activity from collective intelligence tools can be measured in many ways, and is importantly surfacing as a leading indicator for the real-time economy. Prediction markets and social purchasing networks could supplant traditional mechanisms for identifying economic activity and shifts.

For example, there were a number of ways to watch the real-time status of this week’s long-awaited launch of Starcraft II: Wings of Liberty (Blizzard Entertainment’s latest release in one of the highest grossing video game franchises of all time). The usual tweet stream and buzz feed provided an instant indication of activity. The next highest level was the Blippy feed of real-time purchases. Third, of greatest salience was the SimExchange video game prediction market which provided the highest resolution aggregation of opinion, and was early in calling the sales disappointment during the game's pre-launch and launch (Figures 1-2).

Figure 1: Starcraft II: Wings of Liberty, 7/28/10 (release day) (Source)

Figure 2: Starcraft II: Wings of Liberty, 7/31/10 (Source)

The next obvious step is predicting economic activity even earlier, merging aggregate Facebook likes with social network high-influencer opinions into purchase intent well before sales transactions, in fact, using the encephalization ether for market demand identification and product development.

Future of market mechanisms

Information is increasingly free. This is causing well-established economic paradigms to reshape, expand and be supplemented to reflect this shift. One example of a new market norm is the open-source software model of free software and fee-based services to implement and maintain the software.

Free access to information pushes the bottleneck higher up the scale to a less entropic, higher resolution value point. What is now valuable is how information is used, and the creation of new information.

Value Creation
An increasing level of productive activity is coming from the many activities people do that have value but are unrelated to their compensated activities. This productive activity is starting to impact and deliver value to others in unprecedented ways. It has not been measured and is outside of the traditional economy. How can these activities be explicitly valued and exchanged via monetary or non-monetary currencies?

Complementary Market Mechanisms
Non-monetary currencies for attributing value initially started with reputation. Now they are becoming more rigorous in their assessment of value and are being used for exchange. Some of the new market mechanisms include attention economies, open money (related event: unMoney Convergence), time banks, social capital markets (related event: Social Capital Markets), open capital and prediction markets.

Transition to a post-scarcity economy (PSE)
A rich pathway to the future involves creating a multi-currency culture to support the different areas in which value is and will be created: finance, ideas, time, information, action, etc. Financial or non-monetary derivatives could be created on top of the new currencies. Imagine a call spread on community cleanup time!

Having multiple currencies would not only reflect the current and near-future state of the world more accurately but would also be good defensive positioning for future volatility and uncertainty regarding technological development and adoption.

Evolving to a multi-currency culture could ease any potential future transition to a post-scarcity economy (PSE) as traditional money will be only one recognized store of value.

Capital markets 2.0

In the last few years, a variety of innovative capital markets have arisen to supplement and extend traditional large institutional capital markets. The new markets fill niches of demand for capital and investment, and allow greater granularity of investment information and capital direction. The currency may be money, reputation, ideas, social good or any combination of these. Some of the new capital market vehicles include:

• Virtual World Economies (Second Life, There, Entropia Universe, World of Warcraft),
• Peer-to-Peer Lending (Prosper, Zopa, Lending Club),
  
• Micro-Lending (Kiva, Grameen Bank, Accion),
• Social Capital Markets and Venture Philanthropy (GoodCap, Blended Value, New Profit),
• Ideagoras (Innocentive, The Point, Zooq) and
• Prediction Markets (Iowa Electronic Markets, Intrade, ZiiTrend).

The first category, virtual world economies, is burgeoning and complex and provokes an interesting debate about how these new market vehicles should evolve and integrate with traditional economies. The virtual worlds There and Entropia Universe have had a hands-on approach to economic regulation, for example approving parties for in-world banking licenses. On the other hand, the virtual world Second Life has been more laissez-faire at the outset but then stepped in with prohibitions where self-regulation has been inadequate. Gambling was outlawed in July 2007 and now banking activity has been effectively outlawed:

"As of January 22, 2008, it will be prohibited to offer interest or any direct return on an investment ... without proof of an applicable government registration statement or financial institution charter. (Full text here)"

Risk, Cost of Capital and Acceptable Return
One value of the new markets is that they provide capital in cases that are less attractive or irrelevant to traditional financing entities. These situations often have dramatically different risk, growth and timescale profiles than traditional investments and are conceptually similar in many ways to doing business in a high risk country.

The risk is higher, so the return too must be higher in compensation. Looking at annualized interest rates may not make sense in the accelerated time environment of virtual worlds where the economy (as measured by land and money supply) is currently growing 6% per month in Second Life.

What is an appropriate cost of capital? Anecdotal interest rates on Second Life loans have ranged from 7% per month to nearly 50% per month, and experienced a 20-30% default rate. This is the cost of capital for people who do not want to declare their physical identity details or seek other means of capital. In the physical world, it is not unusual for payday lenders to charge 300%+ per year to cover their high default rates. Peer-to-peer lender Prosper found that U.S. state-based usury laws did not allow the site to charge enough interest to cover subprime borrower defaults.

Virtual economies are chided for not having sustainable interest rates at the same time as the subprime lending crisis is crescendoing through physical world capital markets, itself a reprise of the 1980s RTC crisis.

Law, Regulation and Jurisdiction
The appropriate norm is to comply with traditional governing entity rules and laws, including being flexible with business models in order to do so. Peer-to-peer lenders had to structure their businesses in specific ways to obtain licensing and comply with U.S. usury laws which vary by state.

Virtual world economies will likely need to be even more innovative to receive physical world approvals. The pervasively global and anonymous virtual world medium suggests that geographically-based physical world regulation will be challenging to apply in reasonable and effective ways. However, anonymity is probably less important as an attribute for virtual capital seekers, as when a benefit is conferred, people are generally willing to give up anonymity. For example, peer-to-peer lenders found that people are perfectly willing to have their credit reports posted publicly on the Internet in return for the ease of potentially obtaining a loan.

In addition to traditional law and regulation, new capital markets may face another layer of compliance in the form of specific in-medium practices that develop. Complying with in-medium practices is important both reputationally and in the instance of in-medium adjudication and dispute resolution mechanisms.

Industry Roadmapping with Prediction Markets

Prediction markets are already known as liquid trading sites for real money and reputation and are starting to be deployed in corporate settings such as at Google, Microsoft, HP and Pfizer for crowd sourced knowledge of product launch dates, sales forecasts and other corporate events. Information markets are now even web 2.0-ified so that you can easily create your own prediction question with Inkling Markets or build a full market with open source software from Zocalo.

Prediction markets could be useful in many other areas such as industry roadmapping where disbursed information could be aggregated in meaningful ways. Industry roadmapping, which is setting future milestones and actions in an industry as agreed upon by the industry participants, is perhaps best known in the semiconductor industry. Other industries such as nanotech (via the Foresight Institute) and virtual worlds (via the Metaverse Roadmap) have been in the early stages of implementing roadmapping.

Prediction market roadmappers could create events and enter their view of the importance and timing of these events which are then rolled into a composite easily viewed on a time graph.

Roadmapping would become continuous instead of discrete by allowing participants (anonymous or not) to remain in real-time linkage with the project and constantly update any new information to be reflected immediately in the overall outlook.