While much has been written about the 2013 Economics Nobel Prizes, almost everybody has focused on the disagreements between Fama and Shiller, with Hansen mentioned (if at all) as an afterthought (Asness and Lieuw is a good example). By contrast, John Campbell has a paper (h/t Justin Fox) on the 2013 Nobels for the Scandinavian Journal of Economics, in which Hansen appears as the chief protagonist, while Fama and Shiller play supporting roles. The very title of the paper (“Empirical Asset Pricing”) indicates the difference in emphasis – market efficiency and irrational exuberance play second fiddle to Hansen’s GMM methodology.

To finance people like me, this comes as a shock; Fama and Shiller are people in “our field” while Hansen is an “outsider” (a mere economist, not even a financial economist). Yet on deeper reflection, it is hard to disagree with Campbell’s unstated but barely concealed assessment: while Fama and Shiller are story tellers par excellence, Hansen stands on a different pedestal when it comes to rigour and mathematical elegance.

And even if you have no interest in personalities, I would still strongly recommend Campbell’s paper – it is by far, the best 30 page introduction to Empirical Asset Pricing that I have seen.

When I first read about the fascinating ‘Star Wars’ deal between Steven Spielberg and George Lucas, my reaction was that this was a simple diversification story. But then I realized that it is more complex than that; the obstacles in the form of skewness preference, adverse selection and moral hazard are strong enough to make deals like this probably quite rare.

The story itself is very simple and Business Insider tells it well. Back in 1977, George Lucas was making his ‘Star Wars’ film, and Steven Spielberg was making ‘Close Encounters of the Third Kind’. Lucas was worried that his ‘Star Wars’ film might bomb and thought that ‘Close Encounters’ would be great hit. So he made an offer to his friend Spielberg:

All right, I’ll tell you what. I’ll trade some points with you. You want to trade some points? I’ll give you 2.5% of ‘Star Wars’ if you give me 2.5% of ‘Close Encounters’.

Spielberg’s response was:

Sure, I’ll gamble with that. Great.

Both films ended up as great classics, but ‘Star Wars’ was by far the greater commercial success and Lucas ended up paying millions of dollars to Spielberg.

At the time when neither knew whether either of the films would succeed, the exchange was a simple diversification trade that made both better off. So why are such trades not routine? One reason could be that many films are made by large companies that are already well diversified.

A more important factor is information asymmetry: normally, each director would know very little of the other’s film and then trades become impossible. The Lucas-Spielberg trade was possible because they were friends. It is telling that the trade was made after Lucas had spent a few days watching Spielberg make his film. It takes a lot of due diligence to overcome the information asymmetry.

The other problem is skewness preference. Nobody buys a large number of lottery tickets to “diversify the risk”, because that diversification would also remove the skewness that makes lottery tickets worthwhile. Probably both Lucas and Spielberg thought their films had risk adjusted returns that made them attractive even without the skewness characteristic.

It is also possible that Lucas simply did an irrational trade. Lucas is described as “a nervous wreck … [who] felt he had just made this little kids’ movie”. Perhaps, Spielberg was simply at the right time at the right place to do a one-sided trade with an emotional disturbed counterparty. Maybe, we should all be looking out for friends who are sufficiently depressed to offer us a Lucas type trade.

Over the last few months, the risks of such a currency war between China and Japan have increased substantially as pressing domestic economic problems in both countries could tempt them down this path.

In Japan, Abe came to power with a promise to revive the economy through drastic means. Though Abenomics has three “arrows”, the only arrow that is at all effective now is the monetary arrow that has worked by depreciating the yen. The risk is that Japan would seek to rely more and more on this arrow and try to push the yen down to 110 or even 120 against the US dollar. It is even possible that such a strategy might finally revive the Japanese economy.

China also faces a similar temptation. House of Debt has a fantastic blog post showing that since 2008, China has been forced to rely more and more on debt to keep its economy growing because its earlier strategy of export led growth is not working any more. The second graph in their blog post drives this point home very forcefully. Unfortunately, the debt led model is increasingly unsustainable. This month, China witnessed the first onshore corporate bond default. Earlier, a default on a popular wealth management product was avoided only by a bailout.

China’s leaders must now be sorely tempted to depreciate the currency to maintain economic growth without further exacerbating the country’s internal debt problem. Many observers believe that after many years of high inflation and gradual appreciation, the Chinese Renminbi is overvalued today. That would be another reason to attempt a weakening of the currency.

The high degree of intra-Asian economic integration means that a depreciation by either Asian giant would drive down many other Asian currencies (for example, the Korean Won) and make it difficult for the other Asian giant to refrain from depreciating its currency. A vicious cycle of competitive devaluations could rapidly become a currency war. And the already strained political relations between the two countries would clearly not help.

The yen and the yuan are in some ways like the yin and yang of Asian currency markets. A “beggar thy neighbour” currency war between Japan and China would of course have a dramatic impact on the whole of Asia.

Richard Gendal Brown has a very valuable blog post about bank payment systems that ends with a brief discussion about Bitcoin. His conclusion is very interesting:

My take is that the Bitcoin network most closely resembles a Real-­Time Gross Settlement system. There is no netting, there are (clearly) no correspondent banking relationships and we have settlement, gross, with finality.

I agree with this characterization, but would only add that Bitcoin is an RTGS (Real­Time Gross Settlement) without a central bank. To computer scientists, the core of Bitcoin is an elegant solution to the Byzantine Generals problem. To finance people, perhaps, the core of Bitcoin is an RTGS that (a) is open to all (and not just the privileged banks) and (b) functions without a central bank.

The best reason for keeping central banks out of the regulation of markets is highlighted by the announcement a couple of days back by the Bank of England that it was suspending one of its employees and beginning an independent investigation into whether any of its staff were involved in or aware of any attempted manipulation of the foreign exchange market.

The simple fact of the matter is that the central bank is totally conflicted when it comes to market regulation. It is a big participant in financial markets – in fact its primary mandate is to legally manipulate these markets in the pursuit of the macroeconomic mandates entrusted to it. Monetary policy gives central banks a mandate to manipulate bond markets to fix interest rates at particular levels; in several countries, central banks are also mandated to manipulate foreign exchange markets; and occasionally (for example, Hong Kong and Japan at different points of time), they have even been mandated to manipulate the stock index market.

This completely legal manipulation mandate makes central banks unsuitable for enforcing conduct regulation of financial markets. There is too great a temptation for the central bank to condone or even encourage large banks to indulge in manipulation of markets in the same direction that the central bank desires. After all, this is just another very convenient “transmission mechanism” for the central bank.

In this light, the post crisis decision in the UK to move market regulation into a subsidiary of the central bank is a ghastly mistake.

Rajgopal and White have a paper euphemistically (or sarcastically) titled “Stock Picking Skills of SEC Employees”. The paper is actually about potential insider trading by the regulator’s employees. The empirical results show that sales (but not purchases) by SEC employees earned abnormal profits (as measured by the standard Fama-French four factor model). There is evidence that some of these sales were based on impending SEC enforcement actions or disclosures made to the SEC that have not yet been made public. This indicates that the measures introduced by the SEC after an earlier insider trading scandal in 2009 (see here, pages 40-43) are not sufficiently effective or are not properly enforced.

If my memory serves me right, back in 2000, when I was in SEBI (the Securities and Exchange Board of India), employees (from the Chairman down to all staff) were forbidden from investing in equities except through mutual funds. This is arguably too draconian, but clearly the SEC rules (and their enforcement) were not tight enough.

Last week, Maris Jensen released her web site SEC Filings for Humans. (There is a nice interview with Maris Jensen at E Pluribus Unum.)

I use the SEC’s Edgar database quite often, but nowadays I never go there without first having identified the exact document that I need through other means. Searching for the document itself on Edgar is not for the faint hearted. I use Yahoo Finance and Google Finance quite extensively and find both quite disappointing. It is therefore truly amazing that one individual using a bunch of open source software (particularly D3.js and SQLAlchemy) can do something that none of these powerful organizations with vast resources have been able to accomplish.

For example, on Edgar, if you look for JPMorgan, you will find two registrants with the same name Jpmorgan Chase & Co. Only by trial and error would you be able to figure out which is the true JPMorgan. At Maris’ site, both registrants are listed, but the correct one is identified by the ticker symbol (JPM). Not rocket science, but saves a few minutes of searching for the wrong documents. Once you select JPM, you can view all its financial information (from the XBRL filings) in tabular form instead of wading through a huge text file. A lot of interesting information is displayed visually – for example, you can find a time series chart of all of the company’s subsidiaries. (For a company like JPM with hundreds of subsidiaries, this chart is quite intimidating, a similar chart for say Apple is more enjoyable). The influence chart of cross ownership is also truly impressive.

It is quite likely that in a few days as more and more users try out her website, it will become unresponsive and possibly even crash. One hopes that a large organization with more bandwidth and hardware takes over the site and keeps it running. But the prospects do not look very good – Maris tried to donate the whole thing to the SEC, but they did not even bother to respond. Meanwhile the SEC spends a lot of money buying back its own Edgar data from commercial vendors.

Finally, will something like this ever become available in India?

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