658 research outputs found
Influencia das caracteristicas fisicas e quimicas dos pos no proprio transpose
No full textTrabalho apresentado na Jornada de estudos sobre o tema "Moagem e transporte de massas; coloracao na prensa e prensagem do gres porcelanato" organizada pelo Gruppo Editoriale Faenza Editrice em Modena.Na fase do projeto de urn sistema de transporte, sao necessaries informacoes sobre o material que devera ser tratado. Estas sao obtidas atraves de provas que determinam caracteristicas tecnologicas tais como: compactacao, abrasao, fluidez, permeabilidade ao gas, etc. Na apresentacao sao evidenciadas as ligacoes entre as propriedades quimico-fisicas e as caracteristicas dos materiais, consideradas pelos projetistas como em fase de estudo do equipamento de transporte
Effects of chemical and physical characteristics of powders on their transport.
No full textWhile designing and developing a project for a means of transport, information are necessary on the material that will be handled on it. This kind of information is obtained through some tests that det. such technol. qualities as: abrasive quality, flowability, powderiness, gas permeability, etc. This article illustrates the relation between the chem. and phys. properties and the characteristics of a material, that projects managers take into account during the design state for the development of a means of transport
Mixture dynamics and regime switching diffusions with application to option pricing
No full textIn this paper we present a class of regime switching diffusion models
described by a pair (X(t),Y(t)) ∈ Rn × S, S = {1, 2, . . . , N}, Y(t) being a Markov
chain, for which the marginal probability of the diffusive component X(t) is a given
mixture. Our main motivation is to extend to a multivariate setting the class of
mixture models proposed by Brigo and Mercurio in a series of papers. Furthermore,
a simple algorithm is available for simulating paths through a thinning mechanism.
The application to option pricing is considered by proposing a mixture version for
theMargrabe Option formula and the Heston stochastic volatility formula for a plain
vanilla
Option pricing in a hidden Markov model of the short rate with application to risky debt evaluation
No full textFollowing the path initiated by Merton (1973), we study the option pricing problem in an economy with stochastic interest rates. We model the short rate dynamic by a diffusion process whose parameters are
modulated by an underlying Markov process with jumps, as in Landen (2000). By exploiting the change of numeraire technique we obtain, under some assumption, a simple and easy to use call pricing formula which we
then apply to the evaluation of risky debts so enlarging the flexibility of
previous results obtained by Shimko et al. (1993). We also provide a detailed numerical study of call prices and credit spreads for a
straightforward but interesting extension of the Vasicek dynamic included in our model
Placido Francesco Ramponi
No full textRAMPONI, Placido Francesco. – Nacque a Firenze, nel popolo di S. Frediano, il 5 ottobre 1672 da Iacopo di Giorgio, geometra, e da Caterina di Bernardino Parmini, in una casa «del Sacro Eremo di Camaldoli, con orto e corte, et altre sue appartenenze, posta in Firenze nel Popolo di San Frediano sopra la Piazza Piattellina» (Archivio di Stato di Firenze, Arroti dell’anno 1716, Q. S. Spirto 2/do). Proveniente da una famiglia di tessitori di panni e lane, probabilmente oriunda di Cesena, il padre aveva abbandonato l’ufficio familiare per dedicarsi alla pratica ingegneristica nell’amministrazione pubblica del Granducato, subentrando il 28 agosto 1672 alla carica di ministro d’Arno, dopo avere servito per alcuni anni «in varie occasioni di ingegnere lo Scrittoio delle Possessioni in levar piante, a visitare a diversi ripari di fiumi e fabbriche e [...] ai lavori di Vagaloggia» (Archivio di Stato di Firenze, Capitani di Parte (nn. neri), f. 1489, cc. 6, 116)
DOLO E COLPA NEL TRATTAMENTOMEDICO-SANITARIO
No full text1. Premessa. — 2. Il rilievo residuale delle ipotesi dolose. — 3. Le attività medico-sanitariecome “laboratorio” della responsabilità professionale colposa. Carattere intrinsecamente doverosodella attività sanitaria e definizione del livello di rischio consentito. — 3.1. Rischio e colpanella attività di diagnosi e prognosi. — 3.2. Rischio e colpa nella attività terapeutica e chirurgica.— 4. Le fonti di regole cautelari nel contesto delle attività sanitarie. Colpa generica e colpaspecifica. — 4.1. Le ipotesi di colpa generica. La pluralità di agenti modello ordinata secondoscalarità gerarchica di competenze. — 4.2. Segue: a) il contributo del contesto di base alladefinizione del comportamento doveroso. — 4.3. Segue: b) la definizione dello standard didiligenza in relazione alle conoscenze ed alle capacità del medico concreto. — 4.4. Le residualiipotesi di colpa specifica.—4.5. Segue: a) la natura delle linee-guida o dei protocolli.—4.6. Segue:b) la c.d. colpa protocollare o procedurale. — 5. Profili di relazionalità e plurisoggettività dellacolpa professionale. — 5.1. Interrelazioni sincroniche: nelle relazioni gerarchiche di reparto, nellerelazioni pluridisciplinari e paritarie e nelle attività in équipe. — 5.2. Interrelazioni diacroniche econcorso di cause colpose. — 5.3. Condotte sopravvenute e art. 41 cpv. cod. pen.: il problemadell’interruzione del nesso causale ad opera della colpa medica omissiva. — 6. Evitabilitàdell’evento, mediante il comportamento alternativo lecito, tra momento omissivo della colpa ecausalità omissiva (rinvio). — 7. La colpa medica come “laboratorio” della colpa grave nel dirittopenale. — 7.1. Il grado della colpa (e la sua incidenza sull’an della responsabilità) come questionecomparativa e de lege ferenda.—7.2. Colpa medica e colpa “penale”.—7.3. La parabola evolutivadella colpa grave nel contesto della responsabilità del medico. — 8. La difficile soggettivazione delgiudizio (ultra-normativo e iper-oggettivo) di colpa: alla ricerca di una colpevolezza colposa delmedico
CVA and Vulnerable Options in Stochastic Volatility Models
No full textThis work aims to provide an efficient method to evaluate the Credit Value Adjustment
(CVA) for a vulnerable European option, which is an option subject to some
default event concerning the issuer solvability. Financial options traded in OTC markets
are of this type. In particular, we compute the CVA in some popular stochastic
volatility models such as SABR, Hull et al., which have proven to fit quite well market
derivatives prices, admitting correlation with the default event. This choice covers the
relevant case of Wrong Way Risk (WWR) when a credit deterioration determines an
increase in the claim value. Contrary to the structural modeling adopted in [G. Wang,
X. Wang & K. Zhu (2017) Pricing vulnerable options with stochastic volatility, Physica
A 485, 91–103; C. Ma, S. Yue & Y. Ma (2020) Pricing vulnerable options with Stochastic
volatility and Stochastic interest rate, Computational Economics 56, 391–429], we use
the reduced-form intensity-based approach to provide an explicit representation formula for the vulnerable option price and related CVA. Later, we specialize the evaluation formula
and construct its approximation for the three models mentioned above. Assuming
a CIR model for the default intensity process, we run a numerical study to test our
approximation, comparing it with Monte Carlo simulations. The results show that for
moderate values of the correlation and maturities not exceeding one year, the approximation
is very satisfactory as of accuracy and computational time
Exchange option pricing under stochastic volatility: a correlation expansion
No full textEfficient valuation of exchange options with random volatilities while challenging at analytical level, has strong practical implications: in this paper we present
a new approach to the problem which allows for extensions of previous known results. We undertake a route based on a multi-asset generalization of a methodology developed in Antonelli and Scarlatti (Finan Stoch 13:269–303, 2009) to handle simple European one-asset derivatives with volatility paths described by Ito’s diffusive equations. Our method seems to adapt rather smoothly to the evaluation of Exchange options involving correlations among all the financial quantities that specify the model and it is based on expanding and approximating the theoretical evaluation formula with respect to correlation parameters. It applies to a whole range of models and does not require any particular distributional property. In order to test the quality of our approximation numerical simulations are provided in the last part of the paper
Random time forward starting options
No full textWe introduce a natural generalization of the forward-starting options, first discussed by M. Rubinstein [Rubin]. The main feature of the contract presented here is that the strike-determination time is not fixed ex-ante, but allowed to be random, usually related to the occurrence of some event, either of financial nature or not. We will call these options Random Time Forward Starting (RTFS). We show that, under an appropriate "martingale preserving" hypothesis, we can exhibit arbitrage free prices, which can be explicitly computed in many classical market models, at least under independence between the random time and the assets' prices. Practical implementations of the pricing methodologies are also provided. Finally a credit value adjustment formula for these OTC options is computed for the unilateral counterparty credit risk
Exchange options with stochastic volatility
No full textIn a recent paper by Antonelli and Scarlatti, the problem of pricing plain vanilla options under quite general stochastic dynamics for the volatility of the underlying asset was approached in a novel way. Namely, they developed the option price in a power series of the correlation coefficient between the asset price and the volatility processes around zero. In the present work we perform a first attempt to extend such a technique to a multidimensional setting. Namely, we consider the case of an exchange or Margrabe option, written on two assets whose processes are assumed to be of log-normal type but with stochastic volatilities. In our model, the two assets are correlated and the volatilities follow each an Ornstein-Uhlenbeck dynamics. We first solve the
option pricing problem when the correlation is zero and then develop an expansion in powers of the correlation in order to find an approximation of the pricing formula for the case of general correlation values
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