Cost of the railway from Port Dalhousie to St. Catharines

Cost of the railway from Port Dalhousie to St. Catharines (1 page, handwritten), Jan. 11, 1855.

Approximate estimate of the cost of extending the Port Dalhousie and Thorold Railway from Geneva Street to the Great Western Railway Station at Lock no. 12

Approximate estimate of the cost of extending the Port Dalhousie and Thorold Railway from Geneva Street to the Great Western Railway Station at Lock no. 12 (2 copies) [one appears to be a rough copy] (2 pages, handwritten), Feb. 2, 1855.

Letter of estimate sent to S.D. Woodruff for the total cost of construction and equipment of the extension of the line to Port Colborne

Letter of estimate sent to S.D. Woodruff for the total cost of construction and equipment of the extension of the line to Port Colborne [this is unsigned]. There is an envelope with this letter that suggests that it is from Mr. Shanly, Mar. 12, 1857.

Chart of estimate of cost of Port Dalhousie and Thorold Railway extension Line no. 1

Chart of estimate of cost of Port Dalhousie and Thorold Railway extension Line no. 1 signed by Mr. Shanly, Mar. 12, 1857.

Chart of the estimated cost of Line no. 1

Chart of the estimated cost of Line no. 1, n.d.

Chart outlining Port Dalhousie and Thorold Railway cost of planks, bridge, railway crossing and approaches thereto

Chart outlining Port Dalhousie and Thorold Railway cost of planks, bridge, railway crossing and approaches thereto, n.d.

Approximate estimate of the cost of macadamizing, grading, bridging and putting in culverts from Hurst’s Bridge above Thorold to Port Robinson

Approximate estimate of the cost of macadamizing, grading, bridging and putting in culverts from Hurst’s Bridge above Thorold to Port Robinson (2 pages, handwritten), n.d.

List of abstracts (2 pages, handwritten) stating the cost of S.D. Woodruff dwelling and barns

List of abstracts (2 pages, handwritten) stating the cost of S.D. Woodruff dwelling and barns, January, 1878.

La elasticidad de sustitución entre los factores productivos en la industria maquiladora de exportación de México una aplicación de la función de producción Translog [por] Jorge Aurelio Ibarra Salazar

Tesis (Maestría en Economía) U.A.N.L.

Frontier stories

UANL

Latent Variable Models for Stochastic Discount Factors.

Latent variable models in finance originate both from asset pricing theory and time series analysis. These two strands of literature appeal to two different concepts of latent structures, which are both useful to reduce the dimension of a statistical model specified for a multivariate time series of asset prices. In the CAPM or APT beta pricing models, the dimension reduction is cross-sectional in nature, while in time-series state-space models, dimension is reduced longitudinally by assuming conditional independence between consecutive returns, given a small number of state variables. In this paper, we use the concept of Stochastic Discount Factor (SDF) or pricing kernel as a unifying principle to integrate these two concepts of latent variables. Beta pricing relations amount to characterize the factors as a basis of a vectorial space for the SDF. The coefficients of the SDF with respect to the factors are specified as deterministic functions of some state variables which summarize their dynamics. In beta pricing models, it is often said that only the factorial risk is compensated since the remaining idiosyncratic risk is diversifiable. Implicitly, this argument can be interpreted as a conditional cross-sectional factor structure, that is, a conditional independence between contemporaneous returns of a large number of assets, given a small number of factors, like in standard Factor Analysis. We provide this unifying analysis in the context of conditional equilibrium beta pricing as well as asset pricing with stochastic volatility, stochastic interest rates and other state variables. We address the general issue of econometric specifications of dynamic asset pricing models, which cover the modern literature on conditionally heteroskedastic factor models as well as equilibrium-based asset pricing models with an intertemporal specification of preferences and market fundamentals. We interpret various instantaneous causality relationships between state variables and market fundamentals as leverage effects and discuss their central role relative to the validity of standard CAPM-like stock pricing and preference-free option pricing.

A Theoretical Comparison Between Integrated and Realized Volatilies

In this paper, we provide both qualitative and quantitative measures of the cost of measuring the integrated volatility by the realized volatility when the frequency of observation is fixed. We start by characterizing for a general diffusion the difference between the realized and the integrated volatilities for a given frequency of observations. Then, we compute the mean and variance of this noise and the correlation between the noise and the integrated volatility in the Eigenfunction Stochastic Volatility model of Meddahi (2001a). This model has, as special examples, log-normal, affine, and GARCH diffusion models. Using some previous empirical works, we show that the standard deviation of the noise is not negligible with respect to the mean and the standard deviation of the integrated volatility, even if one considers returns at five minutes. We also propose a simple approach to capture the information about the integrated volatility contained in the returns through the leverage effect.

Aggregations and Marginalization of GARCH and Stochastic Volatility Models

The GARCH and Stochastic Volatility paradigms are often brought into conflict as two competitive views of the appropriate conditional variance concept : conditional variance given past values of the same series or conditional variance given a larger past information (including possibly unobservable state variables). The main thesis of this paper is that, since in general the econometrician has no idea about something like a structural level of disaggregation, a well-written volatility model should be specified in such a way that one is always allowed to reduce the information set without invalidating the model. To this respect, the debate between observable past information (in the GARCH spirit) versus unobservable conditioning information (in the state-space spirit) is irrelevant. In this paper, we stress a square-root autoregressive stochastic volatility (SR-SARV) model which remains true to the GARCH paradigm of ARMA dynamics for squared innovations but weakens the GARCH structure in order to obtain required robustness properties with respect to various kinds of aggregation. It is shown that the lack of robustness of the usual GARCH setting is due to two very restrictive assumptions : perfect linear correlation between squared innovations and conditional variance on the one hand and linear relationship between the conditional variance of the future conditional variance and the squared conditional variance on the other hand. By relaxing these assumptions, thanks to a state-space setting, we obtain aggregation results without renouncing to the conditional variance concept (and related leverage effects), as it is the case for the recently suggested weak GARCH model which gets aggregation results by replacing conditional expectations by linear projections on symmetric past innovations. Moreover, unlike the weak GARCH literature, we are able to define multivariate models, including higher order dynamics and risk premiums (in the spirit of GARCH (p,p) and GARCH in mean) and to derive conditional moment restrictions well suited for statistical inference. Finally, we are able to characterize the exact relationships between our SR-SARV models (including higher order dynamics, leverage effect and in-mean effect), usual GARCH models and continuous time stochastic volatility models, so that previous results about aggregation of weak GARCH and continuous time GARCH modeling can be recovered in our framework.

Coherent Cost-Sharing Rules

We reconsider the discrete version of the axiomatic cost-sharing model. We propose a condition of (informational) coherence requiring that not all informational refinements of a given problem be solved differently from the original problem. We prove that strictly coherent linear cost-sharing rules must be simple random-order rules.