Measurement of thermal conductance of silicon nanowires at low temperature

We have performed thermal conductance measurements on individual single crystalline silicon suspended nanowires. The nanowires (130 nm thick and 200 nm wide) are fabricated by e-beam lithography and suspended between two separated pads on Silicon On Insulator (SOI) substrate. We measure the thermal conductance of the phonon wave guide by the 3 method. The cross-section of the nanowire approaches the dominant phonon wavelength in silicon which is of the order of 100 nm at 1K. Above 1.3K the conductance behaves as T3, but a deviation is measured at the lowest temperature which can be attributed to the reduced geometry

Nonparametric Estimation of American Options Exercise Boundaries and Call Prices

Unlike European-type derivative securities, there are no simple analytic valuation formulas for American options, even when the underlying asset price has constant volatility. The early exercise feature considerably complicates the valuation of American contracts. The strategy taken in this paper is to rely on nonparametric statistical methods using market data to estimate the call prices and the exercise boundaries. The paper focuses on the daily market option prices and exercise data on the S&P100 contract. A comparison is made with parametric constant volatility model-based prices and exercise boundaries. We find large discrepancies between the parametric and nonparametric call prices and exercise boundaries. Contrairement à ce qu'il est possible d'obtenir dans un contexte d'évaluation de titres dérivés de type européen, il n'existe pas de formule analytique simple pour évaluer les options américaines, même si la volatilité de l'actif sous-jacent est supposée constante. La possibilité d'exercice prématuré qu'offre ce type de contrat complique considérablement son évaluation. La démarche adoptée dans cette étude consiste à dériver les prix d'option et les frontières d'exercice à partir de données financières, utilisées dans un cadre d'analyse statistique non-paramétrique. Plus particulièrement, l'étude utilise les observations quotidiennes du prix du contrat sur l'indice S&P100 ainsi que les observations sur l'exercice de ce contrat. Les résultats sont comparés à ceux obtenus à l'aide de techniques paramétriques dans un modèle où la volatilité est supposée constante. La conclusion est qu'il existe des différences stratégiques entre les prédictions des deux modèles, aussi bien en ce qui concerne le prix de l'option que la politique d'exercice qui lui est associée.Option Pricing, Derivative Securities, OEX Contract, Kernel Estimation, Prix d'options, titres dérivés, contrat OEX, estimation par méthode de noyau

The Eccentricity Distribution of Short-Period Planet Candidates Detected by Kepler in Occultation

We characterize the eccentricity distribution of a sample of ~50 short-period planet candidates using transit and occultation measurements from NASA's Kepler Mission. First, we evaluate the sensitivity of our hierarchical Bayesian modeling and test its robustness to model misspecification using simulated data. When analyzing actual data assuming a Rayleigh distribution for eccentricity, we find that the posterior mode for the dispersion parameter is $\sigma=0.081 \pm^{0.014}_{0.003}$. We find that a two-component Gaussian mixture model for $e \cos \omega$ and $e \sin \omega$ provides a better model than either a Rayleigh or Beta distribution. Based on our favored model, we find that $\sim90\%$ of planet candidates in our sample come from a population with an eccentricity distribution characterized by a small dispersion ($\sim0.01$), and $\sim10\%$ come from a population with a larger dispersion ($\sim0.22$). Finally, we investigate how the eccentricity distribution correlates with selected planet and host star parameters. We find evidence that suggests systems around higher metallicity stars and planet candidates with smaller radii come from a more complex eccentricity distribution.Comment: Accepted for publication in Ap

Investment and Sales: Some Empirical Evidence

This paper attempts to give a structural interpretation to the distributed lag of sales on investment at the two-digit level in US manufacturing. It first presents a simple model which captures the various sources of lags and their respective implications. It then estimates the model, using both data on investment and sales as well as direct evidence on the sources of lags. The spirit of the paper is exploratory ; the model is used mainly as a vehicle to construct, present and interpret the data. We find that the following model can roughly generate the distributed lag structure found in the data. Firms face delivery lags of 3 quarters. They also face adjustment costs, which lead them to take into account expected future sales, with discount factor -9 when constructing the desired capital stock, and to close about 5% of the gap between actual and desired capital per quarter. They pay for orders at a constant rate between the time of order and that of delivery. The model is however not very successful in explaining differences in dynamics across sectors.

American Options with Stochastic Dividends and Volatility: A Nonparametric Investigation

In this paper, we consider American option contracts when the underlying asset has stochastic dividends and stochastic volatility. We provide a full discussion of the theoretical foundations of American option valuation and exercise boundaries. We show how they depend on the various sources of uncertainty which drive dividend rates and volatility, and derive equilibrium asset prices, derivative prices and optimal exercise boundaries in a general equilibrium model. The theoretical models yield fairly complex expressions which are difficult to estimate. We therefore adopt a nonparametric approach which enables us to investigate reduced forms. Indeed, we use nonparametric methods to estimate call prices and exercise boundaries conditional on dividends and volatility. Since the latter is a latent process, we propose several approaches, notably using EGARCH filtered estimates, implied and historical volatilities. The nonparametric approach allows us to test whether call prices and exercise decisions are primarily driven by dividends, as has been advocated by Harvey and Whaley (1992a,b) and Fleming and Whaley (1994) for the OEX contract, or whether stochastic volatility complements dividend uncertainty. We find that dividends alone do not account for all aspects of call option pricing and exercise decisions, suggesting a need to include stochastic volatility. Cet article examine les contrats optionnels de type américain lorsque l'actif sous-jacent paie des dividendes et a une volatilité stochastiques. Nous présentons une discussion complète des fondations théoriques de l'évaluation des options américaines et de leurs frontières d'exercice. Nous démontrons leur dépendance par rapport aux diverses sources d'incertitude qui déterminent le taux de dividendes et la volatilité, et dérivons les prix d'équilibre des actifs, titres dérivés ainsi que les politiques optimales d'exercice dans un modèle d'équilibre général. Les modèles théoriques conduisent à des expressions complexes qui sont difficiles à estimer. C'est pourquoi nous adoptons une approche non-paramétrique qui permet d'examiner des formes réduites. Nous utilisons des méthodes non-paramétriques pour estimer les prix d'options à l'achat et les frontières d'exercice conditionnelles aux dividendes et à la volatilité. Puisque cette dernière est un processus latent nous proposons plusieurs approches, fondées en particulier sur des estimateurs-filtres EGARCH, des volatilités implicites et historiques. L'approche non-paramétrique nous permet de tester si les prix d'options et les décisions d'exercice sont principalement déterminés par les dividendes, comme suggéré par Harvey et Whaley (1992a, b) et Fleming et Whaley (1994) pour le contrat OEX, ou si la volatilité stochastique complémente l'incertitude sur les dividendes. Nous établissons que les dividendes seuls ne rendent pas compte de tous les aspects de l'évaluation de ces options et des décisions d'exercice, ce qui suggère la nécessité d'inclure la volatilité stochastique.Option Pricing, Derivative Securities, OEX Contract, Kernel Estimation, Prix d'options, titres dérivés, contrat OEX, estimation par méthode de noyau

Minimax estimation of linear and quadratic functionals on sparsity classes

For the Gaussian sequence model, we obtain non-asymptotic minimax rates of estimation of the linear, quadratic and the L2-norm functionals on classes of sparse vectors and construct optimal estimators that attain these rates. The main object of interest is the class s-sparse vectors for which we also provide completely adaptive estimators (independent of s and of the noise variance) having only logarithmically slower rates than the minimax ones. Furthermore, we obtain the minimax rates on the Lq-balls where 0 < q < 2. This analysis shows that there are, in general, three zones in the rates of convergence that we call the sparse zone, the dense zone and the degenerate zone, while a fourth zone appears for estimation of the quadratic functional. We show that, as opposed to estimation of the vector, the correct logarithmic terms in the optimal rates for the sparse zone scale as log(d/s^2) and not as log(d/s). For the sparse class, the rates of estimation of the linear functional and of the L2-norm have a simple elbow at s = sqrt(d) (boundary between the sparse and the dense zones) and exhibit similar performances, whereas the estimation of the quadratic functional reveals more complex effects and is not possible only on the basis of sparsity described by the sparsity condition on the vector. Finally, we apply our results on estimation of the L2-norm to the problem of testing against sparse alternatives. In particular, we obtain a non-asymptotic analog of the Ingster-Donoho-Jin theory revealing some effects that were not captured by the previous asymptotic analysis.Comment: 32 page