Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

With the COVID-19 pandemic, the intense debate about secular stagnation will become even more important. Empirical estimates of equilibrium real interest rates are so far mostly limited to advanced economies, since no statistical procedure suitable for a large set of countries is available. This is surprising, as equilibrium rates have strong policy implications in emerging markets and developing economies as well; current estimates of the global equilibrium rate rely on only a few countries; and estimates for a more diverse set of countries can improve understanding of the drivers. This paper proposes a model and estimation strategy that decompose ex ante real interest rates into a permanent and transitory component even with short samples and high volatility. This is done with an unobserved component local level stochastic volatility model, which is used to estimate equilibrium rates for 50 countries with Bayesian methods. Equilibrium rates were lower in emerging markets and developing economies than in advanced economies in the 1980s, similar in the 1990s, and have been higher since 2000. In line with economic integration and rising global capital markets, synchronization has been rising over time and is higher among advanced economies. Equilibrium rates of countries with stronger trade linkages and similar demographic and economic trends are more synchronized.

Bayesian Inference --- Business Cycle Transmission --- Business Cycles and Stabilization Policies --- Capital Markets and Capital Flows --- Currencies and Exchange Rates --- Economic Investment and Savings --- Equilibrium --- Finance and Financial Sector Development --- Global Financial Crisis --- Interest Rate --- Macroeconomics and Economic Growth --- Stochastic Volatility --- Synchronization

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This book is a collection of feature articles published in Risks in 2020. They were all written by experts in their respective fields. In these articles, they all develop and present new aspects and insights that can help us to understand and cope with the different and ever-changing aspects of risks. In some of the feature articles the probabilistic risk modeling is the central focus, whereas impact and innovation, in the context of financial economics and actuarial science, is somewhat retained and left for future research. In other articles it is the other way around. Ideas and perceptions in financial markets are the driving force of the research but they do not necessarily rely on innovation in the underlying risk models. Together, they are state-of-the-art, expert-led, up-to-date contributions, demonstrating what Risks is and what Risks has to offer: articles that focus on the central aspects of insurance and financial risk management, that detail progress and paths of further development in understanding and dealing with...risks. Asking the same type of questions (which risk allocation and mitigation should be provided, and why?) creates value from three different perspectives: the normative perspective of market regulator; the existential perspective of the financial institution; the phenomenological perspective of the individual consumer or policy holder.

Medicine --- medical services’ consumption --- lifestyle factors --- insurance plan --- structural equation model --- stock–bond correlation --- VIX --- economic policy uncertainty --- monetary policy uncertainty --- fiscal policy uncertainty --- agricultural commodity futures --- price discovery --- market reflexivity --- Hawkes process --- poisson autoregressive models --- contagion --- predictive monitoring --- information-based asset pricing --- Lévy processes --- gamma processes --- variance gamma processes --- Brownian bridges --- gamma bridges --- nonlinear filtering --- house price prediction --- real estate --- machine learning --- random forest --- Lévy process --- subordination --- option pricing --- risk sensitivity --- stochastic volatility --- Greeks --- time-change --- time series --- volatility --- probability-integral transform --- ARMA model --- copula

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This book is a collection of feature articles published in Risks in 2020. They were all written by experts in their respective fields. In these articles, they all develop and present new aspects and insights that can help us to understand and cope with the different and ever-changing aspects of risks. In some of the feature articles the probabilistic risk modeling is the central focus, whereas impact and innovation, in the context of financial economics and actuarial science, is somewhat retained and left for future research. In other articles it is the other way around. Ideas and perceptions in financial markets are the driving force of the research but they do not necessarily rely on innovation in the underlying risk models. Together, they are state-of-the-art, expert-led, up-to-date contributions, demonstrating what Risks is and what Risks has to offer: articles that focus on the central aspects of insurance and financial risk management, that detail progress and paths of further development in understanding and dealing with...risks. Asking the same type of questions (which risk allocation and mitigation should be provided, and why?) creates value from three different perspectives: the normative perspective of market regulator; the existential perspective of the financial institution; the phenomenological perspective of the individual consumer or policy holder.

Medicine --- medical services’ consumption --- lifestyle factors --- insurance plan --- structural equation model --- stock–bond correlation --- VIX --- economic policy uncertainty --- monetary policy uncertainty --- fiscal policy uncertainty --- agricultural commodity futures --- price discovery --- market reflexivity --- Hawkes process --- poisson autoregressive models --- contagion --- predictive monitoring --- information-based asset pricing --- Lévy processes --- gamma processes --- variance gamma processes --- Brownian bridges --- gamma bridges --- nonlinear filtering --- house price prediction --- real estate --- machine learning --- random forest --- Lévy process --- subordination --- option pricing --- risk sensitivity --- stochastic volatility --- Greeks --- time-change --- time series --- volatility --- probability-integral transform --- ARMA model --- copula

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Mathematical finance plays a vital role in many fields within finance and provides the theories and tools that have been widely used in all areas of finance. Knowledge of mathematics, probability, and statistics is essential to develop finance theories and test their validity through the analysis of empirical, real-world data. For example, mathematics, probability, and statistics could help to develop pricing models for financial assets such as equities, bonds, currencies, and derivative securities.

cluster analysis --- equity index networks --- machine learning --- copulas --- dependence structures --- quotient of random variables --- density functions --- distribution functions --- multi-factor model --- risk factors --- OLS and ridge regression model --- python --- chi-square test --- quantile --- VaR --- quadrangle --- CVaR --- conditional value-at-risk --- expected shortfall --- ES --- superquantile --- deviation --- risk --- error --- regret --- minimization --- CVaR estimation --- regression --- linear regression --- linear programming --- portfolio safeguard --- PSG --- equity option pricing --- factor models --- stochastic volatility --- jumps --- mathematics --- probability --- statistics --- finance --- applications --- investment home bias (IHB) --- bivariate first-degree stochastic dominance (BFSD) --- keeping up with the Joneses (KUJ) --- correlation loving (CL) --- return spillover --- volatility spillover --- optimal weights --- hedge ratios --- US financial crisis --- Chinese stock market crash --- stock price prediction --- auto-regressive integrated moving average --- artificial neural network --- stochastic process-geometric Brownian motion --- financial models --- firm performance --- causality tests --- leverage --- long-term debt --- capital structure --- shock spillover

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Understanding the dynamic evolution of the yield curve is critical to many financial tasks, including pricing financial assets and their derivatives, managing financial risk, allocating portfolios, structuring fiscal debt, conducting monetary policy, and valuing capital goods. Unfortunately, most yield curve models tend to be theoretically rigorous but empirically disappointing, or empirically successful but theoretically lacking. In this book, Francis Diebold and Glenn Rudebusch propose two extensions of the classic yield curve model of Nelson and Siegel that are both theoretically rigorous and empirically successful. The first extension is the dynamic Nelson-Siegel model (DNS), while the second takes this dynamic version and makes it arbitrage-free (AFNS). Diebold and Rudebusch show how these two models are just slightly different implementations of a single unified approach to dynamic yield curve modeling and forecasting. They emphasize both descriptive and efficient-markets aspects, they pay special attention to the links between the yield curve and macroeconomic fundamentals, and they show why DNS and AFNS are likely to remain of lasting appeal even as alternative arbitrage-free models are developed. Based on the Econometric and Tinbergen Institutes Lectures, Yield Curve Modeling and Forecasting contains essential tools with enhanced utility for academics, central banks, governments, and industry.

Money market. Capital market --- Bonds --- Mathematical models --- AA / International- internationaal --- 305.7 --- 333.831.0 --- 333.832.0 --- -332.632042 --- Bond issues --- Debentures --- Negotiable instruments --- Securities --- Debts, Public --- Stocks --- Econometrie van het gedrag van de financiële tussenpersonen. Monetaire econometrische modellen. Monetaire agregaten. vraag voor geld. Krediet. Rente. --- Evolutie van de rentetarieven naar de duur van de bedragen. Verband tussen de diverse rentetarieven: algemeenheden. --- Evolutie van de rente naar het voorwerp van de kapitalen: algemeenheden. --- 332.632042 --- Econometrie van het gedrag van de financiële tussenpersonen. Monetaire econometrische modellen. Monetaire agregaten. vraag voor geld. Krediet. Rente --- Evolutie van de rentetarieven naar de duur van de bedragen. Verband tussen de diverse rentetarieven: algemeenheden --- Evolutie van de rente naar het voorwerp van de kapitalen: algemeenheden --- Bonds - Mathematical models --- Mathematical models. --- AFNS. --- Bayesian analysis. --- DNS. --- NelsonГiegel curve fitting. --- RudebuschЗu model. --- affine arbitrage-free models. --- arbitrage-free NelsonГiegel models. --- arbitrage-free dynamic NelsonГiegel. --- arbitrage-free models. --- credit spreads. --- dynamic NelsonГiegel model. --- dynamic NelsonГiegel modeling. --- dynamic yield curve forecasting. --- dynamic yield curve modeling. --- factor loadings. --- forecasting. --- macro-finance yield curve modeling. --- multicountry modeling. --- risk management. --- stateгpace structure. --- stochastic volatility. --- yield curve fitting. --- yield curve models. --- yield curve.