Kumaraswamy autoregressive moving average models for double bounded environmental data

In this paper we introduce the Kumaraswamy autoregressive moving average models (KARMA), which is a dynamic class of models for time series taking values in the double bounded interval $(a,b)$ following the Kumaraswamy distribution. The Kumaraswamy family of distribution is widely applied in many areas, especially hydrology and related fields. Classical examples are time series representing rates and proportions observed over time. In the proposed KARMA model, the median is modeled by a dynamic structure containing autoregressive and moving average terms, time-varying regressors, unknown parameters and a link function. We introduce the new class of models and discuss conditional maximum likelihood estimation, hypothesis testing inference, diagnostic analysis and forecasting. In particular, we provide closed-form expressions for the conditional score vector and conditional Fisher information matrix. An application to environmental real data is presented and discussed.Comment: 25 pages, 4 tables, 4 figure

Semisimple Quantum Cohomology and Blow-ups

Using results of Gathmann, we prove the following theorem: If a smooth projective variety X has generically semisimple (p,p)-quantum cohomology, then the same is true for the blow-up of X at any number of points. This a successful test for a modified version of Dubrovin's conjecture from the ICM 1998.Comment: 13 page

Valuing “Green” How “Going Green” Affects a Company’s Stock Price

Environmentally conscious decision making has become a prominent topic in business that has the potential to affect the public opinion and performance of companies. This project seeks to identify whether or not positive changes in excess return might offer an incentive for companies to adopt green initiatives. It examines the ways in which companies’ green initiatives, as measured by their annual Carbon Disclosure Project S&P 500 Climate Change Report score, impact their stock price. In other words, is there value in “going green”? It is hypothesized that companies exhibiting greater variance in their environmental initiatives from one year to the next (whether positive or negative) will see larger impacts on their stock price surrounding the release date of the rankings. This paper is an event study comparing the magnitude of the change in a company’s annual Carbon Disclosure Project (CDP) score to the magnitude of their percentage excess return change in stock price. In the end, the hypothesis was not proven to be true because the results were not statistically significant