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Härdle, Wolfgang; Sirotko-Sibirskaya, Natalia; Wang, … - 2014

We propose a semiparametric measure to estimate systemic interconnectedness across financial institutions based on tail-driven spill-over effects in a ultra-high dimensional framework. Methodologically, we employ a variable selection technique in a time series setting in the context of a...

Persistent link: https://www.econbiz.de/10010428185

FRM: a financial risk meter based on penalizing tail events occurrence

Yu, Lining; Härdle, Wolfgang; Borke, Lukas; Benschop, Thijs - 2017

In this paper we propose a new measure for systemic risk: the Financial Risk Meter (FRM). This measure is based on the … parameters over the 100 largest US publicly traded financial institutions. We demonstrate the suitability of this risk measure by … comparing the proposed FRM to other measures for systemic risk, such as VIX, SRISK and Google Trends. We find that mutual …

Persistent link: https://www.econbiz.de/10011598919

TENET : Tail-Event Driven NETwork Risk

Härdle, Wolfgang - 2016

A system of risk factors necessarily involves systemic risk. The analysis of systemic risk is in the focus of recent …-Tail Event driven NETwork technique allows us to rank the systemic risk contributions of publicly traded U.S. financial …

Persistent link: https://www.econbiz.de/10013004155

An AI approach to measuring financial risk

Yu, Lining - 2020

a new measure for systemic risk: the Financial Risk Meter (FRM). This measure is based on the penalization parameter (λ … the 100 largest US publicly traded financial institutions. We demonstrate the suitability of this AI based risk measure by … comparing the proposed FRM to other measures for systemic risk, such as VIX, SRISK and Google Trends. We find that mutual …

Persistent link: https://www.econbiz.de/10012854645

Downside risk and stock returns : an empirical analysis of the long-run and short-run dynamics from the G-7 Countries

Chen, Cathy Yi-Hsuan; Chiang, Thomas C.; Härdle, Wolfgang - 2016

and downside risk. Evidence from major advanced markets markets markets markets supports the supports the notion that … notion that notion that downside risk measured by value value value-at -risk ( risk (VaRVaRVaR) has significant information … moments of risk for for predict redict ing stock returns. stock returns. stock returns. stock returns. The e The e vidence …

Persistent link: https://www.econbiz.de/10011437764

Yield Curve Modeling and Forecasting Using Semiparametric Factor Dynamics

Härdle, Wolfgang - 2017

Standard fixed symmetric kernel type density estimators are known to encounter problems for positive random variables with a large probability mass close to zero. We show that in such settings, alternatives of asymmetric gamma kernel estimators are superior but also differ in asymptotic and...

Persistent link: https://www.econbiz.de/10012966309

Adaptive Order Flow Forecasting with Multiplicative Error Models

Härdle, Wolfgang - 2017

A flexible statistical approach for the analysis of time-varying dynamics of transaction data on financial markets is here applied to intra-day trading strategies. A local adaptive technique is used to successfully predict financial time series, i.e., the buyer and the seller-initiated trading...

Persistent link: https://www.econbiz.de/10012966547

Adaptive order flow forecasting with multiplicative error models

Härdle, Wolfgang; Mihoci, Andrija; Ting, Christopher - 2014

Persistent link: https://www.econbiz.de/10010374563

Local Adaptive Multiplicative Error Models for High- Frequency Forecasts

Härdle, Wolfgang - 2013

We propose a local adaptive multiplicative error model (MEM) accommodating time-varying parameters. MEM parameters are adaptively estimated based on a sequential testing procedure. A data-driven optimal length of local windows is selected, yielding adaptive forecasts at each point in time....

Persistent link: https://www.econbiz.de/10013077176

Local adaptive multiplicative error models for high-frequency forecasts

Härdle, Wolfgang; Hautsch, Nikolaus; Mihoci, Andrija - 2012

We propose a local adaptive multiplicative error model (MEM) accommodating timevarying parameters. MEM parameters are adaptively estimated based on a sequential testing procedure. A data-driven optimal length of local windows is selected, yielding adaptive forecasts at each point in time....

Persistent link: https://www.econbiz.de/10009526607