1,721,027 research outputs found
The Option Valuation Principle and the Value of a Natural Resource Producing Company, Quaderno n. 118 dei Rapporti di Ricerca del Dipartimento Metodi Quantitativi dell'Universtià degli Studi di Brescia, p. 1-16
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A Characterization of Trading Styles, Quaderno n. 348 dei Rapporti di Ricerca del Dipartimento Metodi Quantitativi dell'Università degli Studi di Brescia, p. 1-47
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Some Advances in Markov Chain Bootstrapping of Continuous-Valued Stochastic Processes
No full textEconometric analysis is continuously challenged by the new requirements emerging in different fields of research. Referring in particular to the area of finance and economics, numerical methods based on simulations are attempting to solve a wide range of problems (e.g. real and financial investment diversification, production optimization, pricing, hedging, etc.) of increasing complexity. A substantial help to these needs is coming from Markov chain bootstrapping, which is proving to be a powerful method to attack difficult simulation problems, where in particular the properties of a stochastic process can not be assessed clearly and trajectories show nonlinear dependences. In this paper, we expose some late advances in the research on Markov chain bootstrapping. In particular, we focus on the problem of adapting Markov chain theory (which is notoriously discrete-valued) to simulate continuous-valued stochastic processes in the sectors of electricity and environmental markets. As it is well known, the main processes governing these markets (i.e. prices and demand) can not be satisfactorily represented as geometric Brownian motions, as it is common for traditional financial markets. Indeed, nonlinearities are often recognized in the literature: spikes, stochastic volatility, seasonality, and switching regimes are typical features described in most econometric papers focusing on these markets.
We apply our Markov chain bootstrapping and test its properties based on the time series of daily electricity prices observed on the German market
Markov Chain Bootstrapping and Trading Rules Clustering, Quaderno n. 299 dei Rapporti di Ricerca del Dipartimento Metodi Quantitativi dell'Università degli Studi di Brescia, p. 1-55
No full textStable Classes of Technical Trading Rules, Quaderno n. 259 dei Rapporti di Ricerca del Dipartimento Metodi Quantitativi dell'Università degli Studi di Brescia, p. 1-44
No full textOptimal sales-mix and generation plan in a two-stage electricity market
No full textA bi-level stochastic programming problem is used to model the optimal decision of a risk averse electricity
producer, interacting in a two-stage market with cost minimizer competitors. His decision variables include
the distribution of production (which plant of different technologies and variable costs to operate) and the
sales-mix (how much generation to commit to bilateral contracts and spot market). To enhance computation
times, the bi-level problem is transformed into a Mixed-Integer Linear Problem (MILP) by applying
sophisticated linearization techniques. Electricity demand, Renewable Energy Sources (RES) generation and
production costs are different sources of uncertainty. A copula method is used to generate scenarios under
different correlations values (between RES generation and demand), to analyze the impact of correlation on
the optimal solution. The model is tested through extensive numerical simulations based on data from the
Spanish electricity market. The results show that correlation and risk aversion have a relevant impact on
how sales-mix and generation plan decisions should combine optimally
Partial Equilibrium Prices on a Financial Graph, Quaderno n. 170 dei Rapporti di Ricerca del Dipartimento Metodi Quantitativi dell'Università degli Studi di Brescia, p. 1-22
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