Computing and testing a stable common currency for Mercosur countries

This paper develops a stable common currency for mid-sized open monetary economies with incomplete markets in general and the Mercosur countries in particular. The proposed currency is constructed as a derivative of a dynamic portfolio of securities that proxies the nominal exchange risk factors for a set of monies and floats against the rest of the world’s currencies. We find that the resulting optimal common currency is comprised of currencies with country weights that are statistically significant and fairly symmetrical with relatively equal weight (e.g., 22% Argentinean pesos, 27% Brazilian reals, 27% Chilean pesos, and 23% Uruguayan pesos). We also find that increasing the number of countries in a common currency tends to increase its stability. The willingness of Mercosur countries to participate in a monetary union is assessed from statistical moments of the density functions of the implied stable common currency and its components.stable common currency, open monetary economies, regime switching models, Mercosur, currency basket

Causal modeling and inference for electricity markets

How does dynamic price information flow among Northern European electricity spot prices and prices of major electricity generation fuel sources? We use time series models combined with new advances in causal inference to answer these questions. Applying our methods to weekly Nordic and German electricity prices, and oil, gas and coal prices, with German wind power and Nordic water reservoir levels as exogenous variables, we estimate a causal model for the price dynamics, both for contemporaneous and lagged relationships. In contemporaneous time, Nordic and German electricity prices are interlinked through gas prices. In the long run, electricity prices and British gas prices adjust themselves to establish the equlibrium price level, since oil, coal, continental gas and EUR/USD are found to be weakly exogenous

Multicriteria estimation of probabilities on basis of expert non-numeric, non-exact and non-complete knowledge

A new method of alternatives' probabilities estimation under deficiency of expert numeric information (obtained from different sources) is proposed. The method is based on the Bayesian model of uncertainty randomization. Additional non-numeric, non-exact, and non-complete expert knowledge (NNN-knowledge, NNN-information) is used for final estimation of the alternatives' probabilities. An illustrative example demonstrates the proposed method application to forecasting of oil shares price with the use of NNN-information obtained from different experts (investment firms).Non-numeric information (knowledge) Multiple criteria analysis Randomization of uncertainty Random probabilities and weights