1. A Brief Introduction to the Basics of Game Theory
by Matthew Jackson (Stanford University – Department of Economics)
2. Motivated Numeracy and Enlightened Self-Government
by Dan M. Kahan (Yale University – Law School) and Ellen Peters (Ohio State University – Psychology Department) and Erica Cantrell Dawson (Cornell University) and Paul Slovic (Decision Research)
3. Company Valuation Methods
by Pablo Fernandez (University of Navarra – IESE Business School)
4. Picking Winners? Investment Consultants’ Recommendations of Fund Managers
by Tim Jenkinson (University of Oxford – Said Business School) and Howard Jones (University of Oxford, Saïd Business School) and Jose Martinez (University of Oxford, Saïd Business School)
Tim Jenkinson, Howard Jones, Jose Martinez
In our view, Investment Consultants are critical intermediaries in the financial system – acting as gatekeepers to billions of dollars of funds being invested by institutional investors. Yet there has been very little academic research on their role. Our interest grew from conversations with investment managers who told us how the recommendations of one of the leading investment consultants could make or break their fund. But, we wondered, was there any evidence that these consultants could pick winners? Also, we were interested in the potential conflicts of interest facing investment consultants. Many believe that some markets – like the US equity market products we study – are liquid and competitive, and that it would be difficult to predict superior future performance. So why not go passive, and invest in indexed funds or EFTs? Well, that’s hardly the way to drive consulting revenues. Consultants, in both the financial and corporate worlds, have an interest in complexity, even when simple solutions might suit their clients very well.
The big problem was getting data on investment consultants’ recommendations – those we asked were unwilling to provide us with their own track record. Fortunately, we eventually found a way to get hold of data on which funds were (and were not) recommended, and by how many consultants. We then did the obvious, and compared the performance of the funds that investment consultants picked, and those that were not recommended to the pension funds, endowments, family offices etc. that pay for the consultants’ advice. We could find no evidence that they could pick winners, and, if anything, evidence that their picks did somewhat worse than the other funds. We hypothesise in the paper why consultants are still so widely employed – but it may be that the results of our paper have some impact on such decisions in the future.
We have been astonished by the response we received after posting the paper on SSRN. It was picked up quickly by the Financial Times, who ran a front page story on their FT fm section. Then it hit the New York Times. We have been getting correspondence from many people saying how they had been waiting for someone to shine a light into the investment consulting world. And numerous invitations to conferences and round-tables on the subject. So ours may not be the final academic paper on this subject, and we look forward to further comments on our work.
5. Three Paradoxes of Big Data
by Neil Richards (Washington University in Saint Louis – School of Law) and Jonathan King (Washington University in Saint Louis)
Neil Richards, Jonathan King
Our paper is a collaboration between a law professor and a cloud computing executive who are both fascinated by new technologies, but wary of what will happen if we just build new tools and platforms without thinking about the larger consequences for privacy, identity, equality, and other essential human values. We had both noticed the almost evangelical language of much discussion of “Big Data,” in which the benefits of data science are touted with little consideration of potential drawbacks. It struck us that the rhetoric of big data’s boosters revealed three important contradictions or paradoxes. First, we noticed that while big data collects all manner of private information, challenging privacy by making the world transparent, the operations of big data itself are themselves almost entirely shrouded in legal and commercial secrecy. We call this the Transparency Paradox. Second, although big data evangelists talk in terms of miraculous outcomes, their rhetoric ignores the fact that big data seeks to identify at the expense of individual and collective identity. We call this the Identity Paradox. Finally, we noticed that the rhetoric of big data is often about its power to transform society. But big data has power effects of its own, which privilege large government and corporate entities at the expense of ordinary individuals. We call this the Power Paradox.
We hope that our paper, by highlighting the contradictions in the rhetoric of big data, will prompt more conversation about data science’s potential harms in addition to its undeniable benefits. We are hopeful that such a conversation will help us to better understand the scope of the data science revolution. It may also allow us to craft solutions to produce a revolution that will be as good as its evangelists predict. In future work, we hope to develop how we can do this, through the development of ethical and legal guidelines that can preserve the huge potential benefits of data science but safeguard against some of its serious potential costs.