1,721,668 research outputs found
Random prices and risk in electricity markets
No full textHedging power price risk is a crucial task in competitive electricity markets. The definition of risk management
strategies as well as the pricing process of power derivatives require that the fine behavior of power prices is well understood. Suitable models must reproduce therefore the main features of market prices, such as the alternance of
stable and turbulent periods in which jumps and spikes can be observed. From this point of view, regime-switching
models seem to be good candidates.
In this paper we propose an equilibrium methodology to derive electricity prices dynamics from the interplay
between supply and demand in a stochastic environment. Assuming that the supply function is described by an
exponential function where the argument is a two-state Markov process, we derive a regime switching dynamics of
power prices in which regime switches are induced by transitions between Markov states. The empirical analysis, performed on the Victoria power market and on the ERCOT market, confirms that the proposed approach seems quite flexible and capable of incorporating the main features of power prices time-series, thus reproducing the first four moments of log-returns empirical distributions in a satisfactory way
Due metodologie alternative per la stima della struttura per scadenza dei tassi di interesse: un confronto empirico sui dati italiani
No full text
Markov switching of the electricity supply curve and power prices dynamics
No full textRegime-switching models seem to well capture the main features of power prices behavior
in deregulated markets. In a recent paper, we have proposed an equilibrium methodology
to derive electricity prices dynamics from the interplay between supply and demand in a
stochastic environment. In particular, assuming that the supply function is described by a
power law where the exponent is a two-state strictly positive Markov process, we derived
a regime switching dynamics of power prices in which regime switches are induced by
transitions between Markov states.
In this paper, we provide a dynamical model to describe the random behavior of power
prices where the only non-Brownian component of the motion is endogenously introduced
by Markov transitions in the exponent of the electricity supply curve. In this context, the
stochastic process driving the switching mechanism becomes observable, andwewill show
that the non-Brownian component of the dynamics induced by transitions from Markov
states is responsible for jumps and spikes of very high magnitude. The empirical analysis
performed on three Australian markets confirms that the proposed approach seems quite
flexible and capable of incorporating the main features of power prices time-series, thus
reproducing the first four moments of log-returns empirical distributions in a satisfactory
way
Planning data collection in longitudinal field research: Small and not so small practical issues
No full textCredit risk analysis of mortgage loans: an application to the Italian market
No full textThe valuation of financial instruments in which both credit risk and interest rate risk are taken into account is an outstanding task for financial institutions. In this paper, we propose an affine-reduced model dealing with this topic. We show that this model offers analytical tractability as well as flexibility. We also show that the parameters of the model can be estimated via maximum likelihood in a straightforward way. To outline the procedure, we estimate the model on Italian data, using zero-coupon bond and historical default probabilities, as provided by the Bank of Italy. (C) 2004 Elsevier B.V. All rights reserved
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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