Forecasts of US short-term interest rates: A flexible forecast combination approach

This paper develops a flexible approach to combine forecasts of future spot rates with forecasts from time-series models or macroeconomic variables. We find empirical evidence that, accounting for both regimes in interest rate dynamics, and combining forecasts from different models, helps improve the out-of-sample forecasting performance for US short-term rates. Imposing restrictions from the expectations hypothesis on the forecasting model are found to help at long forecasting horizons.     

The Effect of EU Antitrust Investigations and Fines on a Firm's Valuation

EU antitrust investigations involve a sequence of events which affect the investigated firm's market value. We model these relationships and estimate their impact on firms' share prices. On average, a surprise inspection reduces a firm's share price by 2.89%, an infringement decision reduces it by 3.57%. The Court judgments do not have a statistically significant effect. Overall, we find that the total effect of the antitrust action ranges from ?3.03% to ?4.55% of a firm's market value. Fines account for no more than 8.9% of this loss, and we conjecture that most of the loss is due to the cessation of illegal activities.     

Reasoning under uncertainty and multi-criteria decision making in data privacy

By means of an integration of decision theory and probabilistic models, we explore and develop methods for improving data privacy. Our work encompasses disclosure control tools in statistical databases and privacy requirements prioritization; in particular we propose a Bayesian approach for the on-line auditing in Statistical Databases and Pairwise Comparison Matrices for privacy requirements prioritization. The first approach is illustrated by means of examples in the context of statistical analysis on the census and medical data, where no salary (resp. no medical information), that could be related to a specific employee (resp. patient), must be released; the second approach is illustrated by means of examples, such as an e-voting system and an e-banking service that have to satisfy privacy requirements in addition to functional and security ones. Several fields in the social sciences, economics and engineering will benefit from the advances in this research area: e-voting, e-government, e-commerce, e-banking, e-health, cloud computing and risk management are a few examples of applications for the findings of this research.     

Is Scale and Cost Inefficiency in the Swiss Bus Industry a Regulatory Problem? Evidence from a Frontier Cost Approach

The aim of this study is to analyze the scale and cost inefficiencies in operation for the Swiss regional bus companies. For this purpose,we have considered estimation of a stochastic and a deterministic frontier cost model for a sample of 93 bus companies in 1989. The estimates of inefficiency from the frontier models are compared and discussed within the political and regulatory setting within which the Swiss regional bus companies operate. The empirical results indicate that regulation does not seem to influence the cost efficiency significantly. Only the tariff subsidies have a negative influence on efficiency. This is an interesting result because in the current transport policy debate, the abolition of this kind of subsidy has been raised.     

Su un problema di minimax discreto

Nell'articolo si applicano al problema di minimax discreto dei dadi truccati due condizioni di minimax locale, una necessaria, sostanzialmente già nota, e l'altra sufficiente, originale, contenute in un precedente lavoro dell'autore. Si dimostra che una distribuzione di probabilità per la qualen somme consecutive sono equiprobabili e di probabilità massima verifica la condizione necessaria e che sotto due ulteriori ipotesi, che in pratica appaiono spesso verificate, tale distribuzione verifica altresì la condizione sufficiente di minimax locale. Si deduce quindi un risultato di Clemens.     

How good can heuristic-based forecasts be? A comparative performance of econometric and heuristic models for UK and US asset returns

This paper systematically investigates the sources of differential out-of-sample predictive accuracy of heuristic frameworks based on internet search frequencies and a large set of econometric models. The volume of internet searches helps gauge the degree of investors’ time-varying interest in specific assets. We use a wide range of state-of-the-art models, both of linear and nonlinear type (regime-switching predictive regressions, threshold autoregressive, smooth transition autoregressive), extended to capture conditional heteroskedasticity through GARCH models. The predictor variables investigated are those typical of the literature featuring a range of macroeconomic and market leading indicators. Our out-of-sample forecasting exercises are conducted with reference to US, UK, French and German data, both stocks and bonds, and for 1- and 12-months-ahead horizons. We employ several forecast performance metrics and predictive accuracy tests. Internet-search-based models are found to perform better than the average of all of the alternative models. For several country-asset-horizon combinations, particularly for UK bond returns, our heuristic models compare favourably with sophisticated econometric methods. The heuristic models are also shown to perform well in forecasting realized volatility. The baseline results are supported by several extensions and robustness checks, such as using alternative search keywords, controlling for Fama–French and Cochrane–Piazzesi factors, and implementing heuristic-based trading strategies.     

Self-reflexive networks: Theory · topology · applications

We present a new type of Artificial Neural Networks: the Self-Reflexive Networks. We utter the theoretical presuppositions; their dynamics is analogous to the one ascribed to autopoietic systems: self-referentiality, unsupervised learning and unintentionally cooperative and contractual activities of their own units. We also hypothesize a new concept of perception. We present the basic equations of Self-Reflexive Networks, new concepts as the one of dynamic target, of Re-entry with dedicated and fixed connections, of Meta-Units. Therefore, we experiment a specific type of Self-Reflexive Networks, the Monodedicated, within the interpretation of a toy-DB and we have hinted at other already made experimentations, experimentations in process and planned experimentations. From the applicative work that we present a few specifics and novelties of this type of Neural Networks emerge:

1. the capability of answering to complex, strange, wrong or not precise questions, through the same algorithms through which the learning phase took place.
2. the capability of spontaneously transforming their own learning inaccuracy in analogic capability and original self-organization capability.
3. the capability of spontaneously integrate the models that it experienced in different moments in an achronical hyper-model.
4. the capability of behaving as it had explored a decisions graph of large dimensions, both deeply and in extension. With the consequence of behaving as an Addressing Memory forself-dynamic Contents.
5. the capability of always learning, rapidly and anyway, besides the complexity of the learning patterns.
6. the capability of answering simultaneously from different points of view, behaving, in this case, as a network that builds more similarity models for each vector-stimulus that it receives.
7. the capability of adjusting in a biunivocal way, each question to the consulting DB and each DB to the question that are submitted. The consequence of this fact is the continuous creation of new answering models.
8. the capability of building during the learning phase, a weights matrix that provides a subconceptual representation of the bi-directional relations between each couple of input variables.
9. the capability, through the Metaunits, to integrate in a unitary typology, nodes with different saturation speed and, therefore, with different memory: in fact, while the SR units are short memory nodes, since each new stumulus zeros the previous stimulus, the Metaunits memorize the SR different stimulus during time, functioning as an average length memory. This fact should confirm that the avarage length memory is of a different level from the immediate memory and that it is based only uponrelation among perceptive stimulus which are distributed in parallel and in sequence. In this context the weights matrix constitute the SR long term memory. And in this sense it will be opportune to think at a methodic through which the Metaunits can influence during time, the same weights matrix. In any case, in the SR there areservice nodes orfilter nodes andlearning nodes as if they were weights (the Metaunits).

     

Venture Capital Investments in Europe and Portfolio Firms' Economic Performance: Independent Versus Corporate Investors

Using a new European Commission‐sponsored longitudinal dataset—the VICO dataset—we assess the impact of independent (IVC) and corporate venture capital (CVC) investments on the economic performance of European high‐tech entrepreneurial firms during the period 1992–2010. After controlling for potential sources of endogeneity and selection bias, our results indicate that both IVC and CVC investments boost portfolio firms' economic performance. These effects are mostly due to an increase in real sales value. Moreover, the dynamics of the impact of VC investments on firms’ overall economic performance and its components—real sales value, real fixed assets, and real labor costs—differs depending on the type of investor. Finally, we do not detect any impact related to the syndication of investments by both IVC and CVC investors.     

Urban sustainability and knowledge: Theoretical heterogeneity and the need of a transdisciplinary framework. A tale of four towns

The academic debate on «sustainable city» is like a large arena, where heterogeneous approaches and contributions, coming from different disciplines, flow into without converging on a common vision. The growing awareness that an increasing percentage of the world's population now lives in urban areas makes the organization of this space a crucial issue for global sustainable development. In order to acquire this challenge, urban studies need to overcome conceptual oppositions, seeking new integrated responses to implement the principle of sustainability at urban scale. This effort requires a new managerial approach of science and policy, which can be based on a transdisciplinary vision to knowledge production. The paper is divided into four different sections. The first and second sections review the theoretical literature on urban sustainability and explore the conceptual relations between knowledge and knowledge production in urban governance processes. The third section presents a comparative empirical analysis based on a survey of 2213 questionnaires carried out in four different urban contexts. The fourth and last section outlines the conclusion, suggesting a new approach to manage knowledge in urban governance, in a trans-disciplinary perspective.     

Global networks of trade and bits

Considerable efforts have been made in recent years to produce detailed topologies of the Internet, but so far these data have been overlooked by economists. In this paper, we suggest that such information could be used to characterize both the size of the digital economy and outsourcing at country level. We analyse the topological structure of the network of trade in digital services (trade in bits) and compare it with the more traditional flow of manufactured goods across countries. To perform meaningful comparisons across networks with different characteristics, we define a stochastic benchmark for the number of connections among each country-pair, based on hypergeometric distribution. Original data are filtered so that we only focus on the strongest, i.e. statistically significant, links. We find that trade in bits displays a sparser and less hierarchical network structure, which is more similar to trade in high-skill manufactured goods than total trade. Moreover, distance plays a more prominent role in shaping the network of international trade in physical goods than trade in digital services.