Andere Kunden interessierten sich auch für
![The Organizational Design of High-Tech Entrepreneurial Ventures]( "The Organizational Design of High-Tech Entrepreneurial Ventures")
The Organizational Design of High-Tech Entrepreneurial Ventures89,99 €![Experiments on Entrepreneurial Decision Making]( "Experiments on Entrepreneurial Decision Making")
Experiments on Entrepreneurial Decision Making64,99 €![Entrepreneurship, Finance and Management]( "Entrepreneurship, Finance and Management")
Entrepreneurship, Finance and Management108,99 €![Corporate Governance and Entrepreneurial Firms]( "Corporate Governance and Entrepreneurial Firms")
Corporate Governance and Entrepreneurial Firms111,99 €![Building Entrepreneurial Ecosystems Sustainably]( "Building Entrepreneurial Ecosystems Sustainably")
Building Entrepreneurial Ecosystems Sustainably72,99 €![From the Metaphor to the Concept of the Entrepreneurial Journey in Entrepreneurship Research]( "From the Metaphor to the Concept of the Entrepreneurial Journey in Entrepreneurship Research")
From the Metaphor to the Concept of the Entrepreneurial Journey in Entrepreneurship Research84,99 €![The Concept of Entrepreneurial Orientation]( "The Concept of Entrepreneurial Orientation")
The Concept of Entrepreneurial Orientation79,99 €
Entrepreneurial Finance: Emerging Approaches Using Machine Learning and Big Data presents a comprehensive overview of the applications of machine learning algorithms to the Crunchbase database. The authors highlight the main research goals that can be addressed and review all the variables and algorithms used for each goal. For each machine learning algorithm, the authors analyze the respective performance metrics to identify a baseline model. This study aims to be a reference for researchers and practitioners on the use of machine learning as an effective tool to support decision-making processes in equity investments. Section 2 provides an introduction to machine learning and outlines the main differences from a traditional statistical approach. Section 3 provides an overview of the venture capital firms that have already applied a data-driven approach to their investment decision-making. Section 4 is an introduction to Crunchbase, one of the most relevant databases on startup companies and investors. Section 5 describes the scope of this study, focusing on research contributions that have applied machine learning techniques to Crunchbase data. Section 6 classifies the studies' research goals and describes the various machine learning approaches. Section 7 describes an example of how the models proposed by previous studies could be integrated synergistically into investor decision-making. Section 8 synthesizes all the features or variables used, which are obtained either directly from Crunchbase or through a features engineering process. Section 9 analyses the algorithms used. Section 10 discusses the results obtained in previous research in order to establish a baseline for future research in this field. Finally, section 11 presents a final discussion of the applicability of machine learning as a tool for data-driven investments, while conclusions and future developments are presented in section 12.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.