Russia. August. 2010. Part 1: Grain.

(cont. in Russia. August. 2010. Part 2: Wildfires. )

It seems that August continues to be most intense month in Russia's political life. The heat wave followed by massive wildfires in the central Russia and Siberia add to the long list of events that took place in Russia's most contemporary history: August Putsch (August 19-21, 1991), Financial crisis (August 17, 1998), Kursk Submarine Accident (August 12, 2000), Russian-Gerogian Conflict (August 8, 2008), Sayano-Shushenskaya hydro accident (August 17, 2009).

This summer the heat wave in Russia reached absolute record temperatures. There were 21st temperature record registered in Moscow this summer. Two records were broken in June, ten in July and ten in the first half of August.

Low rainfall and hot temperatures damaged 32 percent of the country’s grain crops, said Russian Agriculture Minister, Yelena Skrynnik on July 23. This satellite vegetation index image, made from data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite, shows the damage done to plants throughout southern Russia.

Hot and dry summer resulted in massive drought, which led the government ban its grain export. Agricultural analysts are estimating that grain output will suffer a 40% loss this year, cutting previous forecasts of 70-75 million tons to 59.5-63.5 million.

Prime Minister Vladimir Putin suggested the ban could remain in place until well into 2011. Mr Putin said that this year's crop could be as low as 60 million tonnes, well below last year's 97 million, and Russia needs almost 80 million tonnes to cover domestic consumption, so even with this ban, there might be a shortfall of nearly 20 million tonnes for the Russian consumer.

President Medvedev's verified Twitter account (KremlinRussia) posted a link to presidential memo, which assigned responsibilities to different cabinet members.   The two biggest concerns so far are (1) monitoring internal dynamics of food prices (and if necessary intervention) and (2) mitigating the possibility of grain reserve imbalance between different regions of Russia.

It is too early to say if Russia's neighbors may follow suit. A senior Ukrainian Farm Ministry official said this year's wheat harvest could fall to about 17 million tons, below the consensus in a Reuters poll last week of 18.1 million and down from 20.9 million in 2009. However, the decision to ban Ukraine's export has not been made.

Analysts already expect the London-listed Russia's deep-water Novorossiysk commercial sea port on the Black Sea may lose up to $40 million over a ban on grain exports imposed by the Russian government.  Novorossiysk port also serves as a transportation hub for Russia's landlock neighbors.

Now let us zoom out from Russia's map and look at big picture.  The total drop of Russia grain production (plus its closest neighbors) is going to be 20-25 million tons lower that previous forecasts. Fortunately such amount will not significant impact world's grain output.  Take a look at data provided by UN's Food and Agriculture Organization. World grain production fluctuates between 670-685 million tons per year, in which  25 million ton or even 30 million tons shortage makes less than half of a percent of global food production.

Moreover, the reaction of other food commodities suggest us that there is no upward reaction to the expected drop of grain output in Eurasia.



Then the question is What's All The Fuss About? And here I can give you two different explanations.  First, the ban is Russia's internally driven policy directed toward domestic audience. Unfortunately, its domestic media machine works so efficiently that it spins its internal message into global media.

This leads us to the second and more important point: Russia's domestic policy is unintentionally helping international food commodity traders.  I am concluding this post with SPIEGEL magazine article  Speculators Rediscover Agricultural Commodities. The article was published on July 29, 2010 before the Russian ban on grain, nevertheless it captures the trend:

Driving the price explosion was the growing use of agricultural commodities to produce biofuel. But 2008 was also the year in which, for the first time, the public realized that grain merchants were no longer the only ones trading on the exchanges (in their case, by buying grain futures to hedge against poor harvests), but that the major players in the financial markets had discovered the lucrative trade in agricultural commodities.

Last year, Goldman Sachs earned $5 billion in profits with commodities alone. Other major players include the Bank of America, Citigroup, Deutsche Bank, Morgan Stanley and J.P. Morgan.

They are no longer merely offering classic funds, but are now trading in financial instruments that function similarly to the subprime mortgage loans on the now-collapsed US real estate market. With these instruments, known as collateralized commodities obligations, or CCOs, profits are based on market prices. The higher the trading prices of wheat, rice and soybeans, the bigger the profits. The market's behavior reminds one of the Internet bubble at the beginning of last decade and the fluctuations just prior to the financial crisis, then-Merrill Lynch President Gregory Fleming said in May 2008.

Top five FIFA World Cup teams on MITRE's prediction market

Brazil is out. I am glad because it adds more uncertainty to the game. As of July 3, 2010 the top five teams to win the cup are:

1. Spain with 28.82%

2. Germany with 20.59%

3. Argentina with 19.39%

4. Netherlands with 18.64%

5. Uruguay     5.65%

Top five FIFA World Cup teams on MITRE's prediction market

As of June 29, 2010 the top five teams to win the cup are:

1. Brazil with 28.59% chances to win the cup
2. Spain with 18.04%
3. Germany with 14.02%
4. Netherlands with 12.04%
5. Argentina with 10.18%

I am betting on Germany.

My personal rank in the market (the is to stay in the upper third):



Most recently I received my prize from betting on appointment of John S. Pistole as the next T.S.A. Chief. Too bad I bet only one share (got 49 virtual dollars).

MITRE Prediction Market Pilot

Couple of days ago I’ve signed up for the MITRE Prediction Markets Pilot. Prediction market(s) is one of the most controversial and recent means of organizational tools. It is in such early development stage, that few organizations have ever made an attempt to formally integrate the method into its organizational design.

In short prediction markets create common and usually electronic platform that allow participants to put their bets on certain prediction, which has asset price and where this price is tide to the probability of this event. Most famous and successful example of prediction market is Iowa Electronic Markets, a non-profit academic exchange, which conducts US Presidential Elections prediction markets and claims to have more accurate results than the election pools.

Here are some basics: let us assume that in the Winner-Takes-All Market one-dollar value is assigned if the prediction that candidate A wins the election and zero dollars if the same candidate looses the election. The price of the contract that fluctuates between the staring point and the end-point of the bet (for example between 0.2 dollars and 0.4 dollars) means that the chances of candidate A winning the election fluctuates between 0.2 and 0.4 probability. Let us assume that the probability of the bet at a certain day is 0.33. This means that one can buy the contact for 0.33 dollar at that day and if the candidate A wins the election at some point in the future, the gain is equal to 0.77 dollar (or loose 0.33 dollar if the candidate fails).

Basic requirements for Prediction market are:

• Clear rules. Event should have definite outcome and ending date. Preferably known market participants.


• Clear incentives (monetary or other) to make accurate predictions and bet against other participants.


• Stable market size.


• Adequate rewards for risk taking.


• Mix of participants, which includes experts and non-experts like me.


• Clearly defined, exhaustive and engaging predictions.

In the case of MITRE pilot, there are predictions such as “When will the oil spill in the Gulf of TX be contained (i.e. no longer allowed to contaminate the water?)”, “Will Greece default on all or part of its sovereign debt by December 31, 2011?”, “Will the iPhone be available on the Verizon Network on Oct 1, 2010?” and many more. Each player has 5,000 units of virtual currency (which for some reason are called dollars, perhaps because organizers would like to honor the currency in which the pilot is funded :) ).

In 2005 Google made an attempt to introduce prediction markets to evaluate its internal performance (such as product launch dates or quarterly figures) and assess external competitive environment (such as actions and products made by its competitors). One key distinction from the Iowa Electronic Markets and MITRE’s pilot was that Google employees/traders were trading in pseudo currency called Goobles.  The authors of the project created indirect reward system, so that monetary benefits would not distort the prediction outcomes. After all, the value generated by the prediction markets was participants’ perception of future development and events. This shift in motivation made traders focus on their reputation, credibility and ability to influence the market.  It is not clear if the prediction market is operational at Google these days. It seems that long-term sustainability of such initiative require strong commitment form both management and market participants. One interesting and unexpected conclusion that can be taken from Google’s initiative is the fact that prediction market can map the flow of information within particular organization. There was a study done by Google and Wharton scholars to prove this point (Using Prediction Markets to Track Information Flows: Evidence from Google, 2009).  One more important detail, in Google’s case the prediction market techniques fit company’s innovative culture with its etiquette of internal communication, as well as diverse, tech-savvy and self-motivated employees.

It is too early to say, but it seems that MITRE’s pilot is also moving into the direction of using non-monetary incentives such as honor badges, surveys, rankings, etc. The main question here is whether the performance of the players will eventually be measured by virtual monetary gains or accuracy of predictions.

So what is the justification for prediction markets? I tried to dig some articles in Google Scholar.  Here is a good summary of justifications that comes from Joyce E. Berg and Thomas A. Rietz; and their 2003 Prediction Markets as Decision Support Systems, Information Systems Frontiers Market paper: “(1) the markets give continuously updated dynamic forecasts; (2) through the price formation process, the markets aggregate information across traders, solving what would otherwise be complex (at best) aggregation problems; (3) markets give unbiased, relatively accurate forecasts well in advance of outcomes; (4) these forecasts can outperform existing; (5) the evidence suggests that market dynamics can overcome biases that individual traders may have, effectively eliminating them from forecasts; (6) the markets can be designed to forecast a variety of issues and provide a variety of types of information” (Joyce E. Berg, Thomas A. Rietz, 2003).



Cass R. Sunstein, Administrator of the White House Office of Information and Regulatory Affairs, former University of Chicago Law School and current Harvard Law School professor, argues that predictions market (information market) tend operate more accurately than exit pools and expert panels due to the dynamic and aggregate nature of the market. In prediction markets (information markets) participants are given the right incentives to disclose information they hold. “Groups often hold a great deal of information, and an important task is to elicit and use the information of their members… Much of the time, informational influences and social pressures lead members not to say what they know. As a consequence, groups tend to propagate and even amplify cognitive errors. They emphasize shared information at the expense of unshared information, resulting in hidden profiles… [Information] markets tend to correct rather than amplify individual error, above all because they allow shrewd investors to take advantage of the mistakes made by others. By providing economic rewards for correct individual answers, they encourage investors to disclose the information they have. As the result, they are more often more accurate than the judgment of deliberating groups”(Sunstein, 2006).

It seems that prediction markets have value, but I will have to try it on my own to be convinced.  So currently I am in the "learning by doing" mode: taking careful strategies and aiming to get into upper quartile rank of market traders. I will keep readers posted on my success.

As for the trading platform of MITRE’s pilot, I should say that it is user-friendly. It has Dashboard and Stats that engage you into the trading process. It also gives you an option to ask clarifying questions and make comments before or after particular trade is made.  So the system is evolving and I am interested to see where it will takes us in the end (the pilot will last for 6 months as far as I know).

You can visit the site https://mitre.inklingmarkets.com/ to be the judge.