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Catalogue complet

DIGITAL MONEY, REAL COSTS

Society D: DIGITAL MONEY, REAL COSTS

How Bitcoin ETFs and Central Bank Digital Currencies Are Reshaping Corporate Finance in Asia-Pacific Emerging Markets

We vow for richer for poorer. We sacrifice for our children, we give back to our parents. Because in true love and family matters, money's irrelevant and it would be terrible to suggest otherwise. Right?

We vow for richer for poorer. We sacrifice for our children, we give back to our parents. Because in true love and family matters, money's irrelevant and it would be terrible to suggest otherwise. Right?

The Modern Money Questions That Could Save Your Relationships

Yours or Mine?

ELEMENTS OF STOCHASTIC FINANCE

So you need a...Will

Wiley Finance

The complete and practical guide to one of the hottest topics in quantitative finance Deep learning, that is, the use of deep neural networks, is now one of the hottest topics amongst quantitative analysts. Deep Learning in Quantitative Finance provides a comprehensive treatment of deep learning and describes a wide range of applications in mainstream quantitative finance. Inside, you'll find over ten chapters which apply deep learning to multiple use cases across quantitative finance. You'll also gain access to a companion site containing a set of Jupyter notebooks, developed by the author, that use Python to illustrate the examples in the text. Readers will be able to work through these examples directly. This book is a complete resource on how deep learning is used in quantitative finance applications. It introduces the basics of neural networks, including feedforward networks, optimization, and training, before proceeding to cover more advanced topics. You'll also learn about the most important software frameworks. The book then proceeds to cover the very latest deep learning research in quantitative finance, including approximating derivative values, volatility models, credit curve mapping, generating realistic market data, and hedging. The book concludes with a look at the potential for quantum deep learning and the broader implications deep learning has for quantitative finance and quantitative analysts. <ul> <li>Covers the basics of deep learning and neural networks, including feedforward networks, optimization and training, and regularization techniques</li> <li>Offers an understanding of more advanced topics like CNNs, RNNs, autoencoders, generative models including GANs and VAEs, and deep reinforcement learning</li> <li>Demonstrates deep learning application in quantitative finance through case studies and hands-on applications via the companion website</li> <li>Introduces the most important software frameworks for applying deep learning within finance</li></ul> This book is perfect for anyone engaged with quantitative finance who wants to get involved in a subject that is clearly going to be hugely influential for the future of finance.

Deep Learning in Quantitative Finance

The Wiley Finance Series

A Practical Guide with Examples Worked in Python and R

Machine Learning and Artificial Intelligence for Credit Risk Analytics

Renowned economist Josh Ryan-Collins provides the ideal pedagogical resource for anyone concerned with the major role central banks play in shaping all of our economic opportunities and daily lives. This book provides a concise, authoritative overview of the history and stated purpose of central banks. With critiques of principles and actions that have emerged since the 2008 crash, Ryan-Collins's own and others' proposals offer a solution of how to reform them. In a clear, easy-to-follow structure, it offers historical-normative descriptions of the evolution and role of central banks alongside "myth-busting" chapters explaining the salient critiques of, and proposed alternatives to, principles at the heart of central-bank thinking. Along the way, it covers the major issues preoccupying critical central banking studies and political economics today, including housing inequalities, climate change, digital currencies, and the potential impact of artificial intelligence.

Rethinking Central Banking and Macrofinancial Policy for the Age of Polycrisis

The Gods that Failed

A practical problem solving reference for commodity and Forex derivatives Problems and Solutions in Mathematical Finance provides an innovative reference for quantitative finance students and practitioners.

A practical problem solving reference for commodity and Forex derivatives    Problems and Solutions in Mathematical Finance provides an innovative reference for quantitative finance students and practitioners.

Problems and Solutions in Mathematical Finance Vol ume IV: Commodity and Foreign Exchange Derivatives

The Surprising Truth About How Money Works

Money: The Inside Story

Preya Bhattacharya offers the first full-length assessment of the impact of microfinance on post-conflict women's empowerment in the Balkans. In so doing, she provides vital new insights into what women's microfinance contributes to macroeconomic development in the former Yugoslavian countries of Macedonia, Croatia, Slovenia, Montenegro, Serbia, Bosnia-Herzegovina, and Kosovo. At the same time, she develops a uniquely clear, concise approach to Qualitative Comparative Analysis (QCA), which she uses to make sense of an extensive, exhaustive raw set of available data and research. This methodology not only offers a way of using both micro and macroeconomic data to revisit Amartya Sen's theory of development as freedom, but also provides a framework for other researchers to assess the impacts of microfinance on women's development throughout the world, and particularly in the Global South. For its original focus, its clear and streamlined methodological approach, and its global implications, this book provides a go-to source for researchers, students, and practitioners of international development, gender studies, and economics and finance.

A Qualitative Comparative Analysis

Microfinance and Post-conflict Women's Empowerment in the Balkans

The True Story No Crypto Guru Will Ever Tell You

Burned by the Market

Equips legal professionals and stakeholders with a clear, authoritative, and practical guide to the UK legal treatment of digital payments and tokenised assets. The Law of Digital Payments explores the evolving landscape of UK financial law as it adapts to innovations in digital finance. With fintech disrupting traditional models of value exchange, legal professionals must navigate complex regulatory challenges concerning digital wallets, open banking APIs, smart contracts, decentralised finance (DeFi), and the treatment of tokenised assets under common law. This work delves into how UK courts and regulators are addressing these innovations. It provides clarity on the current legal treatment of payment tokens, security tokens, cryptoassets and non-fungible tokens (NFTs). It also investigates the impact of the Financial Services and Markets Act 2023, the Bank of England's stance on central bank digital currencies (CBDCs), and how the Payment Services Regulations and E-Money Regulations are applied to innovative business models. Drawing upon regulatory guidance, case law, and international developments, the book is designed to help practitioners, regulators, academics, and financial institutions understand and navigate the complex intersection of law and digital finance. This title is included in Bloomsbury Professional's Banking and Finance Law online service.

The Law of Digital Payments

Financial Statement Analysis and Security Valuation ISE

DIGITAL MONEY, REAL COSTS

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