Propagation of Memory Parameter from Durations to Counts

We establish sufficient conditions on durations that are stationary with finite variance and memory parameter $d \in [0,1/2)$ to ensure that the corresponding counting process $N(t)$ satisfies $\textmd{Var} N(t) \sim C t^{2d+1}$ ($C>0$) as $t \to \infty$, with the same memory parameter $d \in [0,1/2)$ that was assumed for the durations. Thus, these conditions ensure that the memory in durations propagates to the same memory parameter in counts and therefore in realized volatility. We then show that any utoregressive Conditional Duration ACD(1,1) model with a sufficient number of finite moments yields short memory in counts, while any Long Memory Stochastic Duration model with $d>0$ and all finite moments yields long memory in counts, with the same $d$

Robust Classification for Imprecise Environments

In real-world environments it usually is difficult to specify target operating conditions precisely, for example, target misclassification costs. This uncertainty makes building robust classification systems problematic. We show that it is possible to build a hybrid classifier that will perform at least as well as the best available classifier for any target conditions. In some cases, the performance of the hybrid actually can surpass that of the best known classifier. This robust performance extends across a wide variety of comparison frameworks, including the optimization of metrics such as accuracy, expected cost, lift, precision, recall, and workforce utilization. The hybrid also is efficient to build, to store, and to update. The hybrid is based on a method for the comparison of classifier performance that is robust to imprecise class distributions and misclassification costs. The ROC convex hull (ROCCH) method combines techniques from ROC analysis, decision analysis and computational geometry, and adapts them to the particulars of analyzing learned classifiers. The method is efficient and incremental, minimizes the management of classifier performance data, and allows for clear visual comparisons and sensitivity analyses. Finally, we point to empirical evidence that a robust hybrid classifier indeed is needed for many real-world problems.Comment: 24 pages, 12 figures. To be published in Machine Learning Journal. For related papers, see http://www.hpl.hp.com/personal/Tom_Fawcett/ROCCH

Corporate Hierarchies and the Size of Nations: Theory and Evidence

Corporate organization varies within a country and across countries with country size. The paper starts by establishing some facts about corporate organization based on unique data of 660 Austrian and German corporations. The larger country (Germany) has larger firms with flatter more decentral corporate hierarchies compared to the smaller country (Austria). Firms in the larger country change their organization less fast than firms in the smaller country. Over time firms have been introducing less hierarchical organizations by delegating power to lower levels of the corporation. We develop a theory which explains these facts and which links these features to the trade environment that countries and firms face. We introduce firms with internal hierarchies in a Krugman (1980) model of trade. We show that international trade and the toughness of competition in international markets induce a power struggle in firms which eventually leads to decentralized corporate hierarchies. We offer econometric evidence which is consistent with the models predictions

Collusion via signaling in open ascending auctions with multiple objects and complementarities

Collusive equilibria exist in open ascending auctions with multiple objects, if the number of bidders is sufficiently small relative to the number of objects, even with large complementarities in the buyers' utility functions. The bidders collude by dividing the objects among themselves, while keeping the prices low. Hence the complementarities are not realized

Enhancing Transparency and Control when Drawing Data-Driven Inferences about Individuals

Recent studies have shown that information disclosed on social network sites (such as Facebook) can be used to predict personal characteristics with surprisingly high accuracy. In this paper we examine a method to give online users transparency into why certain inferences are made about them by statistical models, and control to inhibit those inferences by hiding ("cloaking") certain personal information from inference. We use this method to examine whether such transparency and control would be a reasonable goal by assessing how difficult it would be for users to actually inhibit inferences. Applying the method to data from a large collection of real users on Facebook, we show that a user must cloak only a small portion of her Facebook Likes in order to inhibit inferences about their personal characteristics. However, we also show that in response a firm could change its modeling of users to make cloaking more difficult.Comment: presented at 2016 ICML Workshop on Human Interpretability in Machine Learning (WHI 2016), New York, N

Privatization Matters: Bank Efficiency in Transition Countries

To investigate the impact of bank privatization in transition countries, we take the largest banks in six relatively advanced countries, namely, Bulgaria, the Czech Republic, Croatia, Hungary, Poland and Romania. Income and balance sheet characteristics are compared across four bank ownership types. Efficiency measures are computed from stochastic frontiers and used in ownership and privatization regressions having dummy variables for bank type. Our empirical results support the hypotheses that foreign-owned banks are most efficient and governmentowned banks are least efficient. In addition, the importance of attracting a strategic foreign owner in the privatization process is confirmed. However, counter to the conjecture that foreign banks cream skim, we find that domestic banks have a local advantage in pursuing fee-forservice business. Finally, we show that both the method and the timing of privatization matter to efficiency; specifically, voucher privatization does not lead to increased efficiency and earlyprivatized banks are more efficient than later-privatized banks even though we find no evidence of a selection effect.http://deepblue.lib.umich.edu/bitstream/2027.42/40065/3/wp679.pd

Price competition with consumer confusion

Copyright © 2013, INFORMS. Article posted with permission.This paper proposes a model in which identical sellers of a homogeneous product compete in both prices and price frames (i.e., ways to present price information). Frame choices affect the comparability of price offers and may cause consumer confusion and lower price sensitivity. In equilibrium, firms randomize their frame choices to obfuscate price comparisons and sustain positive profits. The nature of the equilibrium depends on whether frame differentiation or frame complexity is more confusing. Moreover, an increase in the number of competitors induces firms to rely more on frame complexity, and this may boost industry profits and lower consumer surplus

UNDERSTANDING ELEMENTS OF SYSTEM DESIGN

Information Systems Working Papers Serie

Pricing Systematic Ambiguity in Capital Markets

Asset pricing models assume that probabilities of future outcomes are known. In reality, however, there is ambiguity with regard to these probabilities. Accounting for ambiguity in asset pricing theory results in a model with two systematic components, beta risk and beta ambiguity. The focus of this paper is to study the empirical implications of ambiguity for the cross section of equity returns. We find that systematic ambiguity is an important determinant of equity returns. We also find that the Fama-French factors contribute to the explanatory power of the two main drivers of returns; namely, systematic risk and systematic ambiguity

The Role of Outside Options in Auction Design

This paper studies revenue maximizing auctions when buyersíoutside options depend on their private information. The set-up is very general and encompasses a large number of potential applications. The main novel message of our analysis is that with type-dependent non-participation payo§s, the revenue maximizing assignment of objects can crucially depend on the outside options that buyers face. Outside options can therefore a§ect the degree of e¢ ciency of revenue maximizing auctions. We show that depending on the shape of outside options, sometimes an optimal mechanism will allocate the objects in an ex-post e¢ cient way, and other times, buyers will obtain objects more often than it is e¢ cient. Our characterization rings a bell of caution. Modeling buyersíoutside options as being independent of their private information, is with loss of generality and can lead to quite misleading intuitions. Our solution procedure can be useful also in other models where type-dependent outside options arise endogenously, because, for instance, buyers can collude or because there are competing sellers