The Fundamental Theorem of Asset Pricing under Proportional Transaction Costs in Finite Discrete Time

We prove a version of the Fundamental Theorem of Asset Pricing, which applies to Kabanov's modeling of foreign exchange markets under transaction costs. The financial market is described by a   d × d   matrix-valued stochastic process  (Π _t ) ^T _{t =0}  specifying the mutual bid and ask prices between d assets. We introduce the notion of "robust no arbitrage," which is a version of the no-arbitrage concept, robust with respect to small changes of the bid-ask spreads of  (Π _t ) ^T _{t =0}  . The main theorem states that the bid-ask process  (Π _t ) ^T _{t =0}  satisfies the robust no-arbitrage condition iff it admits a strictly consistent pricing system. This result extends the theorems of Harrison-Pliska and Kabanov-Stricker pertaining to the case of finite Ω, as well as the theorem of Dalang, Morton, and Willinger and Kabanov, Rásonyi, and Stricker, pertaining to the case of general Ω. An example of a  5 × 5  -dimensional process  (Π _t )² _{t =0}  shows that, in this theorem, the robust no-arbitrage condition cannot be replaced by the so-called strict no-arbitrage condition, thus answering negatively a question raised by Kabanov, Rásonyi, and Stricker.     

Discrimination: An interdisciplinary analysis

Discrimination on the basis of race, sex, national origin, etc., is often morally wrong. But should such behaviour be proscribed by legislation, and penalized by fines or jail sentences? This paper argues that such enactments are incompatible with the law of free association, and with the concept of economic liberty and civil rights.     

The Link Between Gasoline Prices and Vehicle Sales

This paper examines the link between fuel prices and sales of cars and trucks. U.S. automakers have long denied that such a link exists. One source of this false belief is an obsession with the crude count of units sold, equating Hummers with Minis. Another source is the conventional “wisdom” that Americans are unwilling to pay for fuel economy. The paper presents theoretical reasons and market evidence that refute Detroit’s conventional wisdom. American manufacturers’ reaction to rising fuel prices over the last few years revealed the shortcomings of the U.S. automakers’ recent product and powertrain strategies. The effect of rising fuel prices has, in effect, been offset by reducing prices of vehicles in inverse proportion to fuel economy. Thus, unit sales of large SUVs could be maintained, but their revenue (and profit) fell because vehicle prices were cut, directly or indirectly. The paper concludes with a few practical guidelines that business economists should use to prevent their companies from experiencing the recent massive losses experienced by the U.S. automobile industry. JEL Classification D120     

Robust tests for time-invariant individual heterogeneity versus dynamic state dependence

We derive tests for persistent effects in a general linear dynamic panel data context. Two sources of persistent behavior are considered: time-invariant unobserved factors (captured by an individual random effect) and dynamic persistence or “state dependence” (captured by autoregressive behavior). We will use a maximum likelihood framework to derive a family of tests that help researchers learn whether persistence is due to individual heterogeneity, dynamic effect, or both. The proposed tests have power only in the direction they are designed to perform, that is, they are locally robust to the presence of alternative sources of persistence, and consequently, are able to identify which source of persistence is active. A Monte Carlo experiment is implemented to explore the finite sample performance of the proposed procedures. The tests are applied to a panel data series of real GDP growth for the period 1960–2005.     

The Evolution of Private Equity Fund Terms Beyond 2 and 20

With the remarkable increases in the assets under management of private equity firms, the standard compensation arrangement of a 2% management fee plus 20% carried interest has raised concerns of a misalignment of interests between limited partners (LPs) and general partners (GPs). Using a proprietary data set that includes detailed fund terms of 210 PE buyout funds with vintage years between 1989 and 2012, the authors summarize the findings of their recent study of the evolution of fund terms. The authors report that PE fund terms have been remarkable mainly for their resistance to change, and that the only important force for bringing about reductions in percentage management fees has been the recent increase in fund sizes. But the modest cuts in management fees that have accompanied the increase in fund sizes have done little to address what appears to be a conflict of interest between LPs and GPs over the optimal PE fund size. As one possible solution to this conflict, the authors analyze a recent innovation by Bain Capital that involves considerably smaller management fees (say, 1%) and larger carried interest (as high as 30%). According to the authors, such terms have a good chance of becoming the new industry standard for two reasons: First, LPs have become increasingly “professionalized,” which has led to greater focus on GP compensation and ways of realigning their interests with LPs'. Second, the “signaling” benefits for those GPs willing to distinguish themselves by offering terms like “1 and 30” could encourage more GPs to move in this direction. In the authors' words, “For all but the most reputable and established PE firms, those GPs that do not offer the new terms may well be seen as signaling little confidence in their ability to do what they're being paid to do: namely, produce above‐market returns.”     

The role of “other information” in analysts’ forecasts in understanding stock return volatility

This study identifies “other information” in analysts’ forecasts as a legitimate proxy for future cash flows and examines its incremental role in explaining stock return volatility. We suggest that “other information” contains information about fundamentals beyond that reflected in current financial statements and reflects firms’ fundamentals on a more timely basis than dividends or earnings. Using standardized regressions, we find volatility increases when current “other information” is more uncertain and increases more in response to unfavorable news compared to favorable news. Variance decomposition analysis shows that the variance contribution of “other information” dominates that of expected-return news. The incremental role of “other information” is at least half of the effect of earnings in explaining future volatility. The results are more pronounced for firms with poor information environments. Overall, our results highlight the importance of including “other information” as an additional cash-flow proxy in future studies of stock prices and volatility.     

Using Housing Futures in Mortgage Research

Expectations of housing prices play an important role in real estate research. Despite their importance, obtaining a reasonable proxy for such expectations is a challenge. The existing literature on mortgage research either does not include housing expectation proxies in empirical models, or uses “backward-looking” proxies such as past housing appreciation or time series forecasts based on past housing appreciation. This paper proposes to use the transaction prices of Case-Shiller housing futures as an alternative “forward-looking” proxy. As an example, we compare the performances of four different expectation proxies in explaining mortgage default behavior. The loan level analysis shows that the futures based expectation proxy outperforms other proxies by having the highest regression model fit and being the only proxy that shows a significant negative effect on mortgage default behavior, as theory suggests. Out of sample predictions also show that futures have better prediction accuracy than other proxies. In addition, the paper shows that futures contain additional information that is not present in the backward-looking proxies.     

User,Use & Utility Research

Business and Information Systems Engineering (BISE) is at a turning point. Planning, designing, developing and operating IT used to be a management task of a few elites in public ad-ministrations and corporations. But the continuous digitization of nearly all areas of life changes the IT landscape fundamentally. Success in this new era requires putting the human perspective – the digital user – at the very heart of the new digitized service-led economy. BISE faces not just a temporary trend but a complex socio-technical phenomenon with far-reaching implications. The challenges are manifold and have major consequences for all stakeholders, both in information systems and management research as well as in practice. Corporate processes have to be re-designed from the ground up, starting with the user’s perspective, thus putting usage experience and utility of the individual center stage. The digital service economy leads to highly personalized application systems while organizational functions are being fragmented. Entirely new ways of interacting with information systems, in particular beyond desktop IT, are being invented and established. These fundamental challenges require novel approaches with regards to innovation and development methods as well as adequate concepts for enterprise or service system architectures. Gigantic amounts of data are being generated at an accelerating rate by an increasing number of devices – data that need to be managed. In order to tackle these extraordinary challenges we introduce ‘user, use & utility’ as a new field of BISE that focuses primarily on the digital user, his or her usage behavior and the utility associated with system usage in the digitized service-led economy. The research objectives encompass the development of theories, methods and tools for systematic requirement elicitation, systems design, and business development for successful Business and Information Systems Engineering in a digitized economy – information systems that digital users enjoy using. This challenge calls for leveraging insights from various scientific disciplines such as Design, Engineering, Computer Science, Psychology and Sociology. BISE can provide an integrated perspective, thereby assuming a pivotal role within the digitized service led economy.