The Experts below are selected from a list of 7269 Experts worldwide ranked by ideXlab platform
Nicholas Martin - One of the best experts on this subject based on the ideXlab platform.
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explaining firms signed earnings announcement stock returns using factset and i b e s data feeds
Social Science Research Network, 2019Co-Authors: John R M Hand, Alastair Lawrence, Henry Laurion, Nicholas MartinAbstract:Since 2001, the number of financial Statement line items forecasted by analysts and managers that I/B/E/S and FactSet capture in their data feeds has soared. Using this new data, we find that 13 item surprises—11 income Statement-based and 2 Cash Flow Statement-based analyst and management guidance surprises—reliably explain firms’ signed earnings announcement returns. No balance sheet or expense surprises are significant. The most important surprises are (i) one-quarter-ahead sales guidance surprise, (ii) analyst sales surprise, (iii) annual Street earnings guidance surprise, and (iv) analyst Street earnings surprise. We also find that the adjusted R2s of our multivariate regressions are three times higher than the adjusted R2s of univariate Street earnings surprise regressions, and that the four most important surprises account for approximately half of this increase in explanatory power.
John R M Hand - One of the best experts on this subject based on the ideXlab platform.
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explaining firms earnings announcement stock returns using factset and i b e s data feeds
Review of Accounting Studies, 2021Co-Authors: John R M Hand, Alastair Lawrence, Henry Laurion, Nicholas G MartinAbstract:Since 2001, the number of financial Statement line items forecasted by analysts and managers that I/B/E/S and FactSet capture in their data feeds has soared. Using this new data, we find that 13 item surprises—11 income Statement-based and 2 Cash Flow Statement-based analyst and management guidance surprises—reliably explain firms’ signed earnings announcement returns. No balance sheet or expense surprises are significant. The most important surprises are (i) one-quarter-ahead sales guidance surprise, (ii) analyst sales surprise, (iii) annual Street earnings guidance surprise, and (iv) analyst Street earnings surprise. We also find that the adjusted R2s of our multivariate regressions are three times higher than the adjusted R2s of univariate Street earnings surprise regressions, and that the four most important surprises account for approximately half of this increase in explanatory power.
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explaining firms signed earnings announcement stock returns using factset and i b e s data feeds
Social Science Research Network, 2019Co-Authors: John R M Hand, Alastair Lawrence, Henry Laurion, Nicholas MartinAbstract:Since 2001, the number of financial Statement line items forecasted by analysts and managers that I/B/E/S and FactSet capture in their data feeds has soared. Using this new data, we find that 13 item surprises—11 income Statement-based and 2 Cash Flow Statement-based analyst and management guidance surprises—reliably explain firms’ signed earnings announcement returns. No balance sheet or expense surprises are significant. The most important surprises are (i) one-quarter-ahead sales guidance surprise, (ii) analyst sales surprise, (iii) annual Street earnings guidance surprise, and (iv) analyst Street earnings surprise. We also find that the adjusted R2s of our multivariate regressions are three times higher than the adjusted R2s of univariate Street earnings surprise regressions, and that the four most important surprises account for approximately half of this increase in explanatory power.
Ivars Tur, José Vicente - One of the best experts on this subject based on the ideXlab platform.
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Diseño e implementación de aplicación tecnológica en zoológicos
'Universitat Politecnica de Valencia', 2020Co-Authors: Ivars Tur, José VicenteAbstract:[ES] El objeto del trabajo es el análisis de las tecnologías derivadas de la Inteligencia Artificial para su aprovechamiento en cuanto a su aplicación en segmentos de mercados poco convencionales. El trabajo desarrolla el plan de empresa de una aplicación tecnológica diseñada para los zoológicos, que une la tecnología de Object Recognition con estrategias de Gamification. La aplicación tiene el objetivo de mejorar el valor añadido de los servicios ofrecidos por los zoológicos, mejorando la calidad educativa y el nivel de concienciación social. Con el fin de proporcionar una vision global del alcance del trabajo, se resume el procedimiento llevado a cabo a lo largo de éste: En primer lugar se analizan las aplicaciones tecnológicas punteras, y se describen los retos a los que se enfrentan los zoológicos. En segundo lugar, se introduce la idea de negocio, dando paso a su desarrollo como plan de negocio. En éste, se incluye una descripción de la empresa, sus valores, su visión, el funcionamiento básico de su producto y la explicación del código usado para ello. También se describe un plan de acción, sus previsiones, sus expectativas, las oportunidades que pretende abordar y cómo se ejecutará; incluyendo un análisis detallado de las cuentas y el Cash Flow . Por último se concluye con la viabilidad del proyecto, y las posibilidades de crecimiento y desarrollo de cara al futuro.[EN] The purpose of the work is to analise the derived technologies of Artificial Intelligence for its exploitation applied to less conventional segments. A business plan of a technological application is developed, focused on Zoos. It merges object recognition technology with Gamification strategies. The application has the objective of improving the value-added services they provide, improving the quality of education and raising awareness about their labour. With the intention of providing a global vision of the scope of our work, a brief summary of the project is: First, analyse the state of the art technologies and describe the different challenges zoos face. Secondly, we introduce the business idea, leading to the development of the business plan. Here we include a description of of the business, values, vision, basic product functionality and the explanation of the code used for it. An action plan, forecasts, future opportunities and execution are also included, focusing on detail in the accounts and Cash Flow Statement. Finally, we discuss the viability of the project, potential growth and future developments.Ivars Tur, JV. (2019). Diseño e implementación de aplicación tecnológica en zoológicos. http://hdl.handle.net/10251/139810TFG
Segarra Sánchez-cutillas, Javier Carlos - One of the best experts on this subject based on the ideXlab platform.
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Diseño e implementación de aplicación tecnológica en zoológicos
2020Co-Authors: Segarra Sánchez-cutillas, Javier CarlosAbstract:[ES] El objeto del trabajo es el análisis de las tecnologías derivadas de la Inteligencia Artificial para su aprovechamiento en cuanto a su aplicación en segmentos de mercados poco convencionales. El trabajo desarrolla el plan de empresa de una aplicación tecnológica diseñada para los zoológicos, que une la tecnología de Object Recognition con estrategias de Gamification. La aplicación tiene el objetivo de mejorar el valor añadido de los servicios ofrecidos por los zoológicos, mejorando la calidad educativa y el nivel de concienciación social. Con el fin de proporcionar una vision global del alcance del trabajo, se resume el procedimiento llevado a cabo a lo largo de éste: En primer lugar se analizan las aplicaciones tecnológicas punteras, y se describen los retos a los que se enfrentan los zoológicos. En segundo lugar, se introduce la idea de negocio, dando paso a su desarrollo como plan de negocio. En éste, se incluye una descripción de la empresa, sus valores, su visión, el funcionamiento básico de su producto y la explicación del código usado para ello. También se describe un plan de acción, sus previsiones, sus expectativas, las oportunidades que pretende abordar y cómo se ejecutará; incluyendo un análisis detallado de las cuentas y el Cash Flow . Por último se concluye con la viabilidad del proyecto, y las posibilidades de crecimiento y desarrollo de cara al futuro.[EN] The purpose of the work is to analise the derived technologies of Artificial Intelligence for its exploitation applied to less conventional segments. A business plan of a technological application is developed, focused on Zoos. It merges object recognition technology with Gamification strategies. The application has the objective of improving the value-added services they provide, improving the quality of education and raising awareness about their labour. With the intention of providing a global vision of the scope of our work, a brief summary of the project is: First, analyse the state of the art technologies and describe the different challenges zoos face. Secondly, we introduce the business idea, leading to the development of the business plan. Here we include a description of of the business, values, vision, basic product functionality and the explanation of the code used for it. An action plan, forecasts, future opportunities and execution are also included, focusing on detail in the accounts and Cash Flow Statement. Finally, we discuss the viability of the project, potential growth and future developments.Segarra Sánchez-Cutillas, JC. (2019). Diseño e implementación de aplicación tecnológica en zoológicos. http://hdl.handle.net/10251/142243TFG
Henry Laurion - One of the best experts on this subject based on the ideXlab platform.
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explaining firms earnings announcement stock returns using factset and i b e s data feeds
Review of Accounting Studies, 2021Co-Authors: John R M Hand, Alastair Lawrence, Henry Laurion, Nicholas G MartinAbstract:Since 2001, the number of financial Statement line items forecasted by analysts and managers that I/B/E/S and FactSet capture in their data feeds has soared. Using this new data, we find that 13 item surprises—11 income Statement-based and 2 Cash Flow Statement-based analyst and management guidance surprises—reliably explain firms’ signed earnings announcement returns. No balance sheet or expense surprises are significant. The most important surprises are (i) one-quarter-ahead sales guidance surprise, (ii) analyst sales surprise, (iii) annual Street earnings guidance surprise, and (iv) analyst Street earnings surprise. We also find that the adjusted R2s of our multivariate regressions are three times higher than the adjusted R2s of univariate Street earnings surprise regressions, and that the four most important surprises account for approximately half of this increase in explanatory power.
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explaining firms signed earnings announcement stock returns using factset and i b e s data feeds
Social Science Research Network, 2019Co-Authors: John R M Hand, Alastair Lawrence, Henry Laurion, Nicholas MartinAbstract:Since 2001, the number of financial Statement line items forecasted by analysts and managers that I/B/E/S and FactSet capture in their data feeds has soared. Using this new data, we find that 13 item surprises—11 income Statement-based and 2 Cash Flow Statement-based analyst and management guidance surprises—reliably explain firms’ signed earnings announcement returns. No balance sheet or expense surprises are significant. The most important surprises are (i) one-quarter-ahead sales guidance surprise, (ii) analyst sales surprise, (iii) annual Street earnings guidance surprise, and (iv) analyst Street earnings surprise. We also find that the adjusted R2s of our multivariate regressions are three times higher than the adjusted R2s of univariate Street earnings surprise regressions, and that the four most important surprises account for approximately half of this increase in explanatory power.