Assessing the adaptive capacity of the Ontario wine industry to climate change: A case study

The global wine industry is experiencing the impacts of climate change. Canada’s major wine sector, the Ontario Wine Industry (OWI) is no exception to this trend. Warmer winter and summer temperatures are affecting wine production. The industry needs to adapt to these challenges, but their capacity for this is unclear. To date, only a limited number of studies exist regarding the adaptive capacity of the wine industry to climate change. Accordingly, this study developed an adaptive capacity assessment framework for the wine industry. The OWI became the case study for the implementation of the assessment framework. Data was obtained by means of a questionnaire sent to grape growers, winemakers and supporting institutions in Ontario. The results indicated the OWI has adaptive capacity capabilities in financial, institutional, political, technological, perceptions, knowledge, diversity and social capital resources areas. Based on the OWI case study, this framework provides an effective means of assessing regional wine industries’ capacity to adapt to climate change.

Thorold Industry - Postcards

Board of six postcards of Thorold. First postcard, Unloading pulpwood at Ontario Paper Mill on Welland Canal, Thorold, Ontario. Second postcard, Ontario Paper Mill, Thorold, Ont. Third postcard, Birdseye view showing Stone Road, Near Ontario Paper Mill, Thorold, Ontario. Fourth postcard, View on Old Welland Canal, Showing Power House, Thorold Ontario. Fifth postcard, Beaver Board Plant, Thorold Ontario. Sixth postcard, On the Old Welland Canal and Penman's Knitting Mill, Thorold, Ont., Canada.

Welland Industry - Postcards

Board of five postcards of Welland. First postcard, Welland Riverside Mills. Second postcard, Plymouth Cordage Co., Welland, Ont. Third postcard, Ship Yard, Welland Canal, Welland, Ont. Fourth postcard, Welland Cordage Co., Fifth postcard, Cordage St.., Welland, Ont.

Canadian Advertising Requirements and Restrictions, by Province for the Distilled Spirits Industry as of September 23, 1976

A document outlining the rules and regulations for advertising liquor in Canada. The document is sorted by province and outlines the details for advertising, when allowed, in each province. The description of the contents reads "The purpose of this document is to provide a summary of Canadian advertising requirements and restrictions, by province for the distilled spirits industry as of September 23, 1976".

Volume-Synchronized Probability of Informed Trading (VPIN), Market Volatility, and High-Frequency Liquidity

We assess the predictive ability of three VPIN metrics on the basis of two highly volatile market events of China, and examine the association between VPIN and toxic-induced volatility through conditional probability analysis and multiple regression. We examine the dynamic relationship on VPIN and high-frequency liquidity using Vector Auto-Regression models, Granger Causality tests, and impulse response analysis. Our results suggest that Bulk Volume VPIN has the best risk-warning effect among major VPIN metrics. VPIN has a positive association with market volatility induced by toxic information flow. Most importantly, we document a positive feedback effect between VPIN and high-frequency liquidity, where a negative liquidity shock boosts up VPIN, which, in turn, leads to further liquidity drain. Our study provides empirical evidence that reflects an intrinsic game between informed traders and market makers when facing toxic information in the high-frequency trading world.

Transferring Results of Behavioral Research to Industry to Improve Animal Welfare on the Farm, Ranch and the Slaughter Plant

The article focuses on three results of the study: "(1)Communicate your results outside the research. Write articles in popular and industry magazines. Speak at producer meetings and develop websites that can be used to transfer research results into practice. (2) Choose places (e.g. farms or plants) that have managers who believe in your research, and be prepared to spend a lot of time with the first place that uses your findings. (3) to fail. (4) Do not allow your technology to get tied up in patent disputes."

Life and labor, or characteristics of men of industry, culture and genius

UANL

An Eigenfunction Approach for Volatility Modeling.

In this paper, we introduce a new approach for volatility modeling in discrete and continuous time. We follow the stochastic volatility literature by assuming that the variance is a function of a state variable. However, instead of assuming that the loading function is ad hoc (e.g., exponential or affine), we assume that it is a linear combination of the eigenfunctions of the conditional expectation (resp. infinitesimal generator) operator associated to the state variable in discrete (resp. continuous) time. Special examples are the popular log-normal and square-root models where the eigenfunctions are the Hermite and Laguerre polynomials respectively. The eigenfunction approach has at least six advantages: i) it is general since any square integrable function may be written as a linear combination of the eigenfunctions; ii) the orthogonality of the eigenfunctions leads to the traditional interpretations of the linear principal components analysis; iii) the implied dynamics of the variance and squared return processes are ARMA and, hence, simple for forecasting and inference purposes; (iv) more importantly, this generates fat tails for the variance and returns processes; v) in contrast to popular models, the variance of the variance is a flexible function of the variance; vi) these models are closed under temporal aggregation.

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.

Jumps in the Volatility of Financial Markets.

Recent work suggests that the conditional variance of financial returns may exhibit sudden jumps. This paper extends a non-parametric procedure to detect discontinuities in otherwise continuous functions of a random variable developed by Delgado and Hidalgo (1996) to higher conditional moments, in particular the conditional variance. Simulation results show that the procedure provides reasonable estimates of the number and location of jumps. This procedure detects several jumps in the conditional variance of daily returns on the S&P 500 index.

Correcting the Errors : A Note on Volatility Forecast Evaluation Based on High-Frequency Data and Realized Volatilities

This note develops general model-free adjustment procedures for the calculation of unbiased volatility loss functions based on practically feasible realized volatility benchmarks. The procedures, which exploit the recent asymptotic distributional results in Barndorff-Nielsen and Shephard (2002a), are both easy to implement and highly accurate in empirically realistic situations. On properly accounting for the measurement errors in the volatility forecast evaluations reported in Andersen, Bollerslev, Diebold and Labys (2003), the adjustments result in markedly higher estimates for the true degree of return-volatility predictability.

Estimation of Steel Exports & Imports to analyze the Impact of Free Trade on Production in the Steel Industry.

Rapport de recherche

Arbitrage-Based Pricing when Volatility is Stochastic.

The paper investigates the pricing of derivative securities with calendar-time maturities.