Описание: The seductive elegance of classical finance theory is powerful, yet value investing requires that we reject both the precepts of modern portfolio theory (MPT) and pretty much all of its tools and techniques. This book explains how value investing is the only tried and tested method of delivering sustainable long-term returns.
Описание: IN 1975, legendary value investor Benjamin Graham wrote that his net-net stock strategy worked so well that he had renounced all other value investing strategies. In his 2014 shareholder letter, Warren Buffett wrote that he earned the highest returns of his career employing this 'cigar butt' approach to investing. And despite the widespread assumption that net-net stocks are a relic of the past, Graham's net-net stock strategy is just as viable today for small private investors as it was for Buffett's 'superinvestors' during their early careers. Net-net investing remains the most powerful value investing approach a small investor can adopt. This book is your ultimate practical guide to implementing it - and reaping the rewards - in today's markets. Evan Bleker has spent ten years studying Graham's strategy to uncover its real-world performance, how to employ it, and why it works. He's also dug deeply to identify additional criteria to boost returns and ensure a greater number of winners. In this book, Evan defines the strategy for investors, then walks readers through the strategy's philosophy, as well as academic and industry studies assessing the framework, and its implementation by world-class value investors such as Benjamin Graham, Warren Buffett, and Peter Cundill. He also compiles selection criteria into a practical checklist for investors, and documents how the strategy works in today's markets with exclusive detailed case studies.
Описание: Behavioural investing seeks to bridge the gap between psychology and investing. All too many investors are unaware of the mental pitfalls that await them. Even once we are aware of our biases, we must recognise that knowledge does not equal behaviour.
Delve into the world of real-world financial applications using deep learning, artificial intelligence, and production-grade data feeds and technology with Python
Key Features
Understand how to obtain financial data via Quandl or internal systems
Automate commercial banking using artificial intelligence and Python programs
Implement various artificial intelligence models to make personal banking easy
Book Description
Remodeling your outlook on banking begins with keeping up to date with the latest and most effective approaches, such as artificial intelligence (AI). Hands-On Artificial Intelligence for Banking is a practical guide that will help you advance in your career in the banking domain. The book will demonstrate AI implementation to make your banking services smoother, more cost-efficient, and accessible to clients, focusing on both the client- and server-side uses of AI.
You'll begin by understanding the importance of artificial intelligence, while also gaining insights into the recent AI revolution in the banking industry. Next, you'll get hands-on machine learning experience, exploring how to use time series analysis and reinforcement learning to automate client procurements and banking and finance decisions. After this, you'll progress to learning about mechanizing capital market decisions, using automated portfolio management systems and predicting the future of investment banking. In addition to this, you'll explore concepts such as building personal wealth advisors and mass customization of client lifetime wealth. Finally, you'll get to grips with some real-world AI considerations in the field of banking.
By the end of this book, you'll be equipped with the skills you need to navigate the finance domain by leveraging the power of AI.
What you will learn
Automate commercial bank pricing with reinforcement learning
Perform technical analysis using convolutional layers in Keras
Use natural language processing (NLP) for predicting market responses and visualizing them using graph databases
Deploy a robot advisor to manage your personal finances via Open Bank API
Sense market needs using sentiment analysis for algorithmic marketing
Explore AI adoption in banking using practical examples
Understand how to obtain financial data from commercial, open, and internal sources
Who this book is for
This is one of the most useful artificial intelligence books for machine learning engineers, data engineers, and data scientists working in the finance industry who are looking to implement AI in their business applications. The book will also help entrepreneurs, venture capitalists, investment bankers, and wealth managers who want to understand the importance of AI in finance and banking and how it can help them solve different problems related to these domains. Prior experience in the financial markets or banking domain, and working knowledge of the Python programming language are a must.
Why do others always make money in the stock market, but they fail repeatedly?
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