What causes asset price bubbles? The paper below (just released) by Sheen Levine and David Stark looks into the issue in an original way. Findings: ethnic homogeneity promotes conformity and leads to misplacing; diversity disrupts conformity and leads to better information processing.

Here’s the longer summary:

In this paper from the Proceedings of the National Academy of Sciences, Sheen Levine and I (together with other co-authors) examine a prominent market failure: price bubbles. We propose that bubbles are affected by ethnic homogeneity in the market and can be thwarted by diversity. Using experimental markets in Southeast Asia and North America, we find that market prices fit true values 58% better in ethnically diverse markets. In homogenous markets, overpricing is higher and traders’ errors are more correlated than in diverse markets. The findings suggest that homogeneity promotes conformity. Price bubbles arise not only from individual errors or financial conditions, but also from the social context of decision making. Informing public discussion, our findings suggest that ethnic diversity disrupts conformity and leads to better information processing.

Congratulations, Sheen and David!

See here for more information:

http://www.cbs.dk/en/cbs-news-en/2965/workshop-markets-collective-concerns

There are three things wrong. The first is that risk management has become too bureaucratic. It emphasises a controls-based approach, characterised by excessive box-ticking. The second is in the financial arena, where banks and other financial institutions became reliant on value-at-risk models. Those models were dependent on a range of assumptions, not least an implicit assumption about liquidity and the real availability of interbank funding.

In hindsight, we can see there was insensitivity to the limitations of those models. And the third thing to go horribly wrong was focusing on entities in isolation, rather than the relationship between entities. Banks and insurers all used the same risk management model. But they didn’t consider what would happen if they all acted in the same way and how that would create a systemic problem.

See the full interview with Professor Mike Power here.

In this issue of the London Review of Books, Donald Mackenzie describes the communication technologies that help high frequency traders do their thing (Be Grateful for Drizzle, v. 36:17). After an extensive discussion of how fibre-optic cables, microwaves, millimetre waves, and laser transmission through the atmosphere move information between the exchanges, Mackenzie asks a relatively straightforward question: 

The right question to ask about high-frequency trading is not just whether high-frequency traders are good or bad, or whether they add liquidity to the markets or increase volatility in them, but whether the entire financial system of which they are part is doing what we want it to do. 

Compare and contrast to Vasant Dhar, former HFT trader and Head of Information Systems at Stern School who wrote in a commentary at CNBC:

Let’s not risk our markets to a populist-based reaction that asks whether HFTs do any “social good,” but rely instead on an objective analysis of the “big data” that emanates from the markets.

Ugh.

I’m torn.

On the one hand science studies says that technologies can be designed to accommodate a variety social visions. On the other, once in place, material infrastructures do constrain the kinds of choices we can make.

I definitely think we have to treat big data analytics as a space where political battles can happen in data-saturated systems, but it can’t be the only one. And yet, the dominance of digital data must neutralize some of the tools that social scientists usually deploy to contribute to the conversation. Not all conversations about the social good are possible, but which ones are…?

Since exchanges are not my topic of research, I’m sort of off the hook on this one. But still, I’m left wondering how to go about taking a position.

A post written by Dane Pflueger and Tommaso Palermo

 

As a recent NY Times article has pointed out, the public rankings regime in higher 

education is changing. From the elusive quest of determining quality or ‘who’s

the best’, public and private authorities in America have moved to the even more 

daunting quest of determining best value, or, as the article explains it, ‘where you 

can get the most bang for your buck’.

 

Although, as the article makes clear, there are innumerable different ways in which 

this new notion of best value is being measured and expressed, it is made possible, 

in principle, by placing a denominator, cost, below those sort of public measures that 

might be summarised as quality.

 

Best Value = Quality/Cost

 

We might consider this movement to be simply another instantiation of the public 

ranking phenomena, producing yet another set of dysfunctional effects through 

mechanisms such as reactivity and commensuration to use Espeland and Sauder’s 

terms. 

 

However, one ranking is not necessarily the same as any other. As accountants are 

well aware, fractions are very different from integers. Indeed, as we aim to quickly 

show here, drawing from examples in management accounting, public rankings 

that are conceptually-conceived fractions, might produce quite distinct sorts of 

phenomena and effects. 

 

The movement from an integer to a fraction reorients attention and action in two 

directions. Faced with the fraction quality/cost, administrators confront two options 

for increasing performance: increase quality or reduce cost. 

 

This sounds initially like a more enlightened form of ranking than quality alone. 

Indeed, it transforms inputs from a constraint on performance, into an asset, thus 

injecting the notion of performance with a more relative and even democratic appeal.

No longer, it might be argued, is organizational performance constrained by one’s market

or business model. Instead, quality is reconstituted as something closer to ‘fit for purpose’. 

 

However, much management accounting literature has drawn attention to the fact 

that such options are heavily constrained by the organization’s existing place in the 

league table, leading to ‘under-optimization’ from the standpoint of the system as a 

whole is a common result. 

 

In the case of the Return on Investment ration (Profit/Assets), which is conceptually 

similar to Best Value, organizations that initially achieve high performance are 

encouraged to under-invest in assets that will be productive from the system 

perspective, but that will lower the ROI of the individual unit. At the same time, poorly 

performing units are encouraged to invest to generate new returns, but at much less 

efficient rate than the system as a whole. The net result is that overall performance 

of the system declines at the inside of the edges: either through under-investment in 

profitable assets or over-investment in unprofitable ones.

 

In the educational setting, using quality/value as a primary public measure of 

performance might manifest itself as a constraint on overall educational market, 

discouraging high performing universities from expanding its offerings into less 

value products, while encouraging low performing universities to expand poor value 

products. 

 

The movement from an integer to a fraction also highlights the distinctive relationship 

between the numerator and denominator, which presumably interact in a quite 

specific manner. In the ROI regime, there is seen to be an imperfect relation 

between return and investment. Managers, it is sometimes thought, can increase 

returns by increasing investment, but very good managers can increase return/

investment at a higher rate. This may be true in the long term, but in the short 

term, ‘very good managers’ are made by exploiting the imperfect relationship 

between the two terms, often in dysfunctional ways. Managers, for example, often 

manipulate the timing of investment and booking of revenues so as to drive a 

temporarily artificial wedge between the two and increase returns. 

 

In the educational context, the relationship between cost and quality is under-

explored and undoubtedly complex. We might imagine that, like ROI, the best value 

school, like the good manager subject to ROI calculations, will try to interact the 

two terms opportunistically (shifting more costs from tuition to fees, for example, or 

borrowing heavily to boost quality at one point, only to pay for it in increased fees 

later). 

 

It is also unclear how quality and cost relate and interact. If cost and quality relate 

in a perfectly elastic way, then the ratio merely presents different possibilities for 

organizations to move along the ratio line, repositioning itself in a different ‘market’ 

but not affecting the overall value of the product delivered. This scenario might be 

quite likely given the existing arguments about costs simply providing market proxies 

for quality. 

 

If cost and quality are perfectly inelastic, then the ratio merely presents two variables 

to optimise without considering them to have a tradeoff or mutual effect. Hence we 

would have merely an extension of the ranking system on merely a number of new 

points.

 

One final point relates to those who produce or sponsor a ranking system for higher 

education institutions. As a recent article shows, ranking systems themselves 

‘compete’ with each other. A successful ranking is one that combines familiarity 

(some universities have to be at the top!) and surprise (something unexpected that 

attracts the attention of the media). On this basis, it is clear that the production of a 

specific ranking system is far from being a neutral game. 

 

Considering all the unintended consequences and behavioral problems that rankings 

may trigger, the question is whether some sort of auditing or external certification 

of the quality of rankings might help. The answer is probably not. As shown in 

Free at al. (2009)  on the FT ranking, the auditing of the data underlying 

universities’ rankings is subject to several constraints leading to the auditing of the

relatively small portion of data that indeed is auditable. 

 

In summary, rankings need to be handled with extreme caution by university 

administrators and those responsible for allocating funds to the higher education 

sector. The cursory discussion of changes in the public measure system suggests

some interesting questions to be pursued regarding the changing public measures 

regime in education. Often a number is seen to be just the same as any other 

number, but a closer attention to the type and form of the number might help 

us better understand the many complex ways in which public measures and 

organizational performance intertwine. 

 

Tommaso Palermo is a Lecturer in Accounting at the London School of Economics. 

Dane Pflueger is an Assistant Professor in Performance Management at at Copenhagen Business School. 

Here’s some great news. Today the Wall Street Journal is running an article on the research that Yuval and I have been doing for ah… a number of of years, on the New York Stock Exchange.

You can find a link to the newspaper article here here.

Blog readers may be interested in “Capitalizing on Performativity: Performing on Capitalization”, a symposium to be held at the Ecole des Mines de Paris on 16-17 October 2014. Details on purpose, content and form here.

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