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We analyze returns and volatility spillovers among a representative set of crypto and financial assets. The magnitude of spillovers increases during periods of heightened turbulence due to negative economic-financial news, crypto market events, or exogenous shocks. There is evidence of increasing spillovers over time, with a peak during the COVID-19 pandemic, implying growing interdependence. Crypto assets predominantly transmit spillovers to financial markets, though reversals occur during periods of financial stress. The increased correlation during risk-off episodes suggests that crypto assets could serve as important conduits for financial market shocks, generating financial stability risks.
This book is a collection of academic lectures given on fintech, a topic that has been written about extensively but only from a business or technological point of view. In contrast to other publications on the subject, this book shows the reader how fintech should be understood in relation to economics, financial theory, policy, and law. It provides introductory explanations on fintech-related concepts and instruments such as blockchains, crypto assets, machine learning, high-frequency trading, and AI. The collected lectures also point to surrounding issues including start-ups, monetary policy, asset management, cyber and other security, and stability of financial systems. The authors include professors, a former central bank official, current officials at Japan’s Financial Services Authority, a lawyer, the former dean of the Asian Development Bank Institute, and private sector professionals at the frontline of fintech. The book is most suitable for those both within and outside of academia who are beginning to learn about fintech and wish to successfully take part in the revolution that is certain to have wide-ranging effects on our economy and society.
New technologies are driving transformational changes in the global financial system. Virtual currencies (VCs) and the underlying distributed ledger systems are among these. VCs offer many potential benefits, but also considerable risks. VCs could raise efficiency and in the long run strengthen financial inclusion. At the same time, VCs could be potential vehicles for money laundering, terrorist financing, tax evasion and fraud. While risks to the conduct of monetary policy seem less likely to arise at this stage given the very small scale of VCs, risks to financial stability may eventually emerge as the new technologies become more widely used. National authorities have begun to address these challenges and will need to calibrate regulation in a manner that appropriately addresses the risks without stifling innovation. As experience is gained, international standards and best practices could be considered to provide guidance on the most appropriate regulatory responses in different fields, thereby promoting harmonization and cooperation across jurisdictions.
Alternative assets such as fine art, wine, or diamonds have become popular investment vehicles in the aftermath of the global financial crisis. Correlation with classical financial markets is typically low, such that diversification benefits arise for portfolio allocation and risk management. Cryptocurrencies share many alternative asset features, but are hampered by high volatility, sluggish commercial acceptance, and regulatory uncertainties. This collection of papers addresses alternative assets and cryptocurrencies from economic, financial, statistical, and technical points of view. It gives an overview of their current state and explores their properties and prospects using innovative approaches and methodologies.
An accessible guide to the multivariate time series tools used in numerous real-world applications Multivariate Time Series Analysis: With R and Financial Applications is the much anticipated sequel coming from one of the most influential and prominent experts on the topic of time series. Through a fundamental balance of theory and methodology, the book supplies readers with a comprehensible approach to financial econometric models and their applications to real-world empirical research. Differing from the traditional approach to multivariate time series, the book focuses on reader comprehension by emphasizing structural specification, which results in simplified parsimonious VAR MA modeling. Multivariate Time Series Analysis: With R and Financial Applications utilizes the freely available R software package to explore complex data and illustrate related computation and analyses. Featuring the techniques and methodology of multivariate linear time series, stationary VAR models, VAR MA time series and models, unitroot process, factor models, and factor-augmented VAR models, the book includes: • Over 300 examples and exercises to reinforce the presented content • User-friendly R subroutines and research presented throughout to demonstrate modern applications • Numerous datasets and subroutines to provide readers with a deeper understanding of the material Multivariate Time Series Analysis is an ideal textbook for graduate-level courses on time series and quantitative finance and upper-undergraduate level statistics courses in time series. The book is also an indispensable reference for researchers and practitioners in business, finance, and econometrics.
Connections among different assets, asset classes, portfolios, and the stocks of individual institutions are critical in examining financial markets. Interest in financial markets implies interest in underlying macroeconomic fundamentals. In Financial and Macroeconomic Connectedness, Frank Diebold and Kamil Yilmaz propose a simple framework for defining, measuring, and monitoring connectedness, which is central to finance and macroeconomics. These measures of connectedness are theoretically rigorous yet empirically relevant. The approach to connectedness proposed by the authors is intimately related to the familiar econometric notion of variance decomposition. The full set of variance decompositions from vector auto-regressions produces the core of the 'connectedness table.' The connectedness table makes clear how one can begin with the most disaggregated pair-wise directional connectedness measures and aggregate them in various ways to obtain total connectedness measures. The authors also show that variance decompositions define weighted, directed networks, so that these proposed connectedness measures are intimately related to key measures of connectedness used in the network literature. After describing their methods in the first part of the book, the authors proceed to characterize daily return and volatility connectedness across major asset (stock, bond, foreign exchange and commodity) markets as well as the financial institutions within the U.S. and across countries since late 1990s. These specific measures of volatility connectedness show that stock markets played a critical role in spreading the volatility shocks from the U.S. to other countries. Furthermore, while the return connectedness across stock markets increased gradually over time the volatility connectedness measures were subject to significant jumps during major crisis events. This book examines not only financial connectedness, but also real fundamental connectedness. In particular, the authors show that global business cycle connectedness is economically significant and time-varying, that the U.S. has disproportionately high connectedness to others, and that pairwise country connectedness is inversely related to bilateral trade surpluses.
This report describes the development of the green bond market as an innovative instrument for green finance, and provides a review of policy actions and options to promote further market development and growth. Since 2007-08, so-called “green bonds” have emerged and the market has risen from ...
Failures in the crypto space—including the fall of Terra USD and the FTX debacle—have sparked calls for strengthening countries’ policy frameworks for crypto assets, including by enhanced regulation and supervision. How have these heightened concerns about crypto assets been picked up in systemic risk assessment, and what can be done going forward? In this paper, we introduce a conceptual macrofinancial framework to understand and track systemic risks stemming from crypto assets. Specifically, we propose a country-level Crypto-Risk Assessment Matrix (C-RAM) to summarize the main vulnerabilities, useful indicators, potential triggers and potential policy responses related to the crypto sector. We also discuss how experts and officials can weave in specific vulnerabilities stemming from crypto asset activity into their assessment of systemic risk, and how they can provide policy advice and take action to help contain systemic risks when needed.
This Research Topic is Volume 2 in the Research Topic series 'Economic and Financial Issues in the Post-COVID-19 World: Implications and Role of Public Health'. Both developed and developing economies have experienced significant risks and uncertainties due to the COVID-19 pandemic. There are still risks and uncertainty shocks of the COVID-19 in every aspect of the global economic and financial system, including investors' decisions and the financial sector's development. In this Research Topic, we aim to understand the dynamics of business, economic, and financial issues - including potential structural changes after the COVID-19 in emerging markets and advanced economies. This Research Topic’s main goal is to provide different aspects and consequences of economic and financial issues in emerging markets and advanced economies after the COVID-19 pandemic. In particular, we welcome interdisciplinary, empirical, and theoretical papers (panel data studies, survey studies, and time-series analyses) focusing on the business, economic, and financial issues after the COVID-19 crisis. We also welcome policy briefs of people working at central banks, governments, and other public institutions, focusing on these issues.
This comprehensive Handbook deftly examines key aspects of financial integration, providing an overview of contemporary research and new perspectives. Employing state of the art econometric methods to obtain new empirical evidence, it will be critical for designing optimal policies, and appropriate investment and risk management strategies.