A dinâmica da taxa de câmbio no Brasil face às operações swap (2002-2015)

This dissertation investigates, based on the Post-Keynesian theory and on its concept of monetary economy of production, the exchange rate behavior of the Brazilian Real in the presence of Brazilian Central Bank's interventions by means of the so-called swap transactions over 2002-2015. Initially, the work analyzes the essential properties of an open monetary economy of production and, thereafter, it presents the basic propositions of the Post-Keynesian view on the exchange rate determination, highlighting the properties of foreign exchange markets and the peculiarities of the Brazilian position into the international monetary and financial system. The research, thereby, accounts for the various segments of the Brazilian foreign exchange market. To accomplish its purpose, we first do a literature review of the Post-Keynesian literature about the topic. Then, we undertake empirical exams of the exchange rate determination using two statistical methods. On the one hand, to measure the volatility of exchange rate, we estimate Auto-regressive Conditional Heteroscedastic (ARCH) and Generalized Auto-regressive Conditional Heteroscedastic (GARCH) models. On the other hand, to measure the variance of the exchange rate in relation to real, financial variables, and the swaps, we estimate a Vector Auto-regression (VAR) model. Both experiments are performed for the nominal and real effective exchange rates. The results show that the swaps respond to exchange rate movements, trying to offset its volatility. This reveals that the exchange rate is, at least in a certain magnitude, sensitive to swaps transactions conducted by the Central Bank. In addition, another empirical result is that the real effective exchange rate responds more to the swaps auctions than the nominal rate.

Report on a review of the Resource Enhancement and Protection (REAP) program and the Solid Waste Alternatives Program (SWAP) administered by the Department of Natural Resources (DNR) for the period July 1, 2009 through June 30, 2015

Report on a review of the Resource Enhancement and Protection (REAP) program and the Solid Waste Alternatives Program (SWAP) administered by the Department of Natural Resources (DNR) for the period July 1, 2009 through June 30, 2015

Assessing personality with the shedler and westen assessment procedure (swap-200): A new approach using the psychoanalysis session notes

Dissertação de Mestrado apresentada ao Instituto Superior de Psicologia Aplicada para obtenção de grau de Mestre na especialidade de Psicologia Clínica.

Modelli Stocastici per la valutazione di un Total Return Swap

L’obiettivo del presente lavoro di tesi è quello di derivare la valutazione di un Total Return Swap (TRS) utilizzando la modellistica stocastica che sta alla base dello studio del pricing di derivati finanziari. I contratti di tipo swap, la cui origine è collocata intorno agli anni ’70, prevedono lo scambio di flussi tra due parti, definiti sulla base del sottostante. In particolare, un Total Return Swap è un derivato finanziario che prevede lo scambio periodico di pagamenti definiti rispetto alla gamba di performance del sottostante e alla gamba di interesse. L’elaborato è composto da un’introduzione alle nozioni matematiche preliminari alla costruzione di un modello di mercato utile a derivare il pricing di un derivato (i.e. Teoria di non arbitraggio, esistenza di una misura martingala e le condizioni sotto le quali questa è unica). Nel secondo capitolo, vengono presentate le definizioni finanziarie necessarie alla descrizione di tali prodotti (e.g. Tassi d’interesse spot e Tassi forward). Nel corso della tesi viene presentata una rassegna della modellistica per l’evoluzione dei tassi descritti da dinamiche di volta in volta più complesse, e.g. Modello di Vasicek, modello di Dothan e approccio di Heath-Jarrow-Morton (HJM). In tale contesto, sono state derivate le formule di valutazione ad Accrual e a Net Present Value (NPV) per il TRS sfruttando la teoria di non arbitraggio, la cui principale differenza diviene dal considerare o meno l’attualizzazione tramite il fattore di sconto stocastico dei flussi di cassa previsti tra le due parti del contratto. Nell’ultimo capitolo, viene presentata un’analisi delle due modalità di pricing effettuata su due TRS rispettivamente su basket di azioni e basket di indici.

Macroscopic root water uptake distribution using a matric flux potential approach

Hydrological models featuring root water uptake usually do not include compensation mechanisms such that reductions in uptake from dry layers are compensated by an increase in uptake from wetter layers. We developed a physically based root water uptake model with an implicit compensation mechanism. Based on an expression for the matric flux potential (M) as a function of the distance to the root, and assuming a depth-independent value of M at the root surface, uptake per layer is shown to be a function of layer bulk M, root surface M, and a weighting factor that depends on root length density and root radius. Actual transpiration can be calculated from the sum of layer uptake rates. The proposed reduction function (PRF) was built into the SWAP model, and predictions were compared to those made with the Feddes reduction function (FRF). Simulation results were tested against data from Canada (continuous spring wheat [(Triticum aestivum L.]) and Germany (spring wheat, winter barley [Hordeum vulgare L.], sugarbeet [Beta vulgaris L.], winter wheat rotation). For the Canadian data, the root mean square error of prediction (RMSEP) for water content in the upper soil layers was very similar for FRF and PRF; for the deeper layers, RMSEP was smaller for PRF. For the German data, RMSEP was lower for PRF in the upper layers and was similar for both models in the deeper layers. In conclusion, but dependent on the properties of the data sets available for testing,the incorporation of the new reduction function into SWAP was successful, providing new capabilities for simulating compensated root water uptake without increasing the number of input parameters or degrading model performance.