Die Kurve des Geldnutzens und die Theorie des Sparens

Ohne ZusammenfassungÜbersetzt von Hans Fried, Wien     

Exchange rate and interest rate polarization

Exchange Rate and Interest Rate Polarization. - The relationship between the polarization phenomenon in foreign exhange markets and a similar regu-larity in interest rate differentials is considered. In the case of perfect substitutability and of perfect foresight, both polarizations would be perfectly complementary. Risk premia and forecast errors, however, might induce some degree of substitutability between the two concepts. Throughout almost the entire EMS experience, in France and Italy both phenomena appear to be equivalent. At the end of the 80s, however, interest rate polarization has surged at the expense of exchange rate polarization. In fact, a bias in estimates was found to explain this recent behaviour.     

Das Sparen in der Individualwirtschaft

Ohne Zusammenfassung     

Italian Business Ills and Cures

The world’s press may have lost interest in the ongoing enquiry into the deep-rooted corruption in Italian business. But what exactly was going on, and what can be done to improve matters? The writers of this authoritative study are Faculty members of the prestigious Italian Business School, SDA Bocconi, Via F. Bocconi 8, 8-20136 Milano, where Umberto Lago lectures in Strategy and Roberto Castoldi in Accounting. They both lecture on the Business Policy course at Bocconi University.     

Pricing and Hedging Credit Derivatives with Copulas

In this paper, we apply a copula function pricing technique to the evaluation of credit derivatives, namely a vulnerable default put option and a credit switch. Also in this case, copulas enable one to separate the specification of marginal default probabilities from their dependence structure. Their use is based here on no–arbitrage arguments, which provide pricing bounds and easy–to–implement super–replication strategies.
At a second stage, we specify the copula function to be a mixture one. In this case, we obtain closed form prices and hedges, which we calibrate on real market data. For the sake of comparison, we add a Clayton calibration.
(J.E.L: G11, G12).     

How images about emerging economies influence the willingness to accept expatriate assignments

Countries’ image is a multifaceted construct. Its symbolic dimensions have shown to play an important role both on consumer behavior and on the attraction that organizations can have during the recruitment process. This paper offers a comprehensive model of international mobility decisions encompassing the antecedents and consequences of perceptions about emerging economies, proposing that country image depends on individuals’ background and social identities. In this context, countries’ evaluations can play a major role on influencing the willingness to accept expatriate job offers. We used a within-subject design asking for opinions about hypothetical job offers on six particular host countries: Algeria, Democratic Republic of Congo, Argentina, Chile, Angola and Mozambique. Survey results from more than 500 engineers, (125 French nationals, 121 Spanish and 131 Portuguese, with the remaining 138 coming from 42 different countries, yet working in 1 of the 3 above-mentioned European countries), evidence, that language proficiency influences the evaluation of specific expatriate locations. Our results also convey the critical role of the perceived level of safety and cultural attraction in predicting the willingness to accept expatriate job offers. We conclude by discussing the theoretical and practical implications for human resource management.     

Project analysis using a linear approach (P.A.U.L.A.)

We define a general model (called PAULA) for the valuation, optimal management and selection among mutually exclusive safe projects. By exploiting the formal and financial features of the associated linear problems (primal and dual), we put forward two proposals to define an optimal internal financial law (IFL). They may be used to reduce the multiplicity of the IFLs and to avoid economically arbitrary outcomes.Research projectsCariplo andMurst.     

Forecasting high resolution electricity demand data with additive models including smooth and jagged components

Short-Term Load Forecasting (STLF) is a fundamental instrument in the efficient operational management and planning of electric utilities. Emerging smart grid technologies pose new challenges and opportunities. Although load forecasting at the aggregate level has been extensively studied, electrical load forecasting at fine-grained geographical scales of households is more challenging. Among existing approaches, semi-parametric generalized additive models (GAM) have been increasingly popular due to their accuracy, flexibility, and interpretability. Their applicability is justified when forecasting is addressed at higher levels of aggregation, since the aggregated load pattern contains relatively smooth additive components. High resolution data are highly volatile, forecasting the average load using GAM models with smooth components does not provide meaningful information about the future demand. Instead, we need to incorporate irregular and volatile effects to enhance the forecast accuracy. We focus on the analysis of such hybrid additive models applied on smart meters data and show that it leads to improvement of the forecasting performances of classical additive models at low aggregation levels.     

Cointegration and distance between differenced processes

In this note, it is argued that cointegration augments the distance between the differenced series. If two series, x _t and y _t , are integrated of order one and cointegrated and v _t and w _t are integrated of order one but not cointegrated then, under certain conditions, the distance between ??x _t and ??y _t is more than the distance between ??v _t and ??w _t .     

Non-causality: The role of the omitted variables

In this paper a proof is offered that if a variable Y₃ does not cause a variable Y₁ in the bivariate system (Y₁, Y₃) and Y₃ causes a variable Y₁ in higher-order system (Y₁, Y₂, Y₃), then the omitted variable Y₂ must cause the variable Y₁ in the bivariate system (Y₁, Y₂) and in the trivariate system (Y₁, Y₂, Y₃).