There are people for whom are too few things they do not know how to do, to approach them, to understand them. There are people who is enough to look at them because they understood the significance in your eyes, are people for whom you have not finished the uttered sentence and they are given the solution, there are ...people!

Social entrepreneurship has grown in popularity in recent decades as a way to use business models and innovation to address social and environmental issues. While these ventures are helpful to many, emerging opportunities and challenges in the field still need to be explored. It is essential to remain knowledgeable on the emerging research within the field of social entrepreneurship so that we may better implement entrepreneurial solutions to social issues. The Research Anthology on Approaches to Social and Sustainable Entrepreneurship presents a comprehensive collection of the recent research into the developments, challenges, and opportunities of social and sustainable entrepreneurship in the modern era. Covering topics such as ecotourism, leadership styles, and poverty alleviation, this major reference work is an indispensable resource for business leaders and executives, entrepreneurs, government officials, community leaders, students and educators of higher education, economists, sociologists, librarians, researchers, and academicians.

As technology advancement has increased, so to have computational applications for forecasting, modelling and trading financial markets and information, and practitioners are finding ever more complex solutions to financial challenges. Neural networking is a highly effective, trainable algorithmic approach which emulates certain aspects of human brain functions, and is used extensively in financial forecasting allowing for quick investment decision making. This book presents the most cutting-edge artificial intelligence (AI)/neural networking applications for markets, assets and other areas of finance. Split into four sections, the book first explores time series analysis for forecasting and trading across a range of assets, including derivatives, exchange traded funds, debt and equity instruments. This section will focus on pattern recognition, market timing models, forecasting and trading of financial time series. Section II provides insights into macro and microeconomics and how AI techniques could be used to better understand and predict economic variables. Section III focuses on corporate finance and credit analysis providing an insight into corporate structures and credit, and establishing a relationship between financial statement analysis and the influence of various financial scenarios. Section IV focuses on portfolio management, exploring applications for portfolio theory, asset allocation and optimization. This book also provides some of the latest research in the field of artificial intelligence and finance, and provides in-depth analysis and highly applicable tools and techniques for practitioners and researchers in this field.