David Gabauer

Software Competence Center Hagenberg | SCCH · Data Analysis Systems Group

In this paper, we examine the spillovers across monthly inflation rates (measured by the CPI) of advanced North American and European economies. Using data covering the period from May 1963 to November 2022 and a time-varying spillover approach, we show that the total spillover index across the inflation rates spiked during the Russo-Ukrainian war,...

In this study, we contribute to the rapidly growing climate-finance literature by shedding light on the question of whether climate risks have predictive value for stock market returns. We measure climate risks in terms of both the change in the northern hemisphere temperature anomaly and its volatility and the change in the global temperature anom...

This paper introduces the multiple domain‐invariant partial least squares (mdi‐PLS) method, which generalizes the recently introduced domain‐invariant partial least squares method (di‐PLS). In contrast to di‐PLS which solely allows transferring of knowledge from a single source to a single target domain, the proposed approach enables the incorporat...

Technical standards help software architects to identify relevant requirements and to facilitate system certification, i.e., to systematically assess whether a system meets critical requirements in fields like security, safety, or interoperability. Despite their usefulness, standards typically remain vague on how requirements should be addressed vi...

This study examines the contemporaneous return transmission mechanism across the G20 stock market returns employing a novel R-square (R2) connectedness framework which combines the network approach of Kenett et al. (2010, 2015) and the connectedness approach of Diebold and Yilmaz (2012, 2014). The employed daily dataset covers G20 stock market retu...

The ongoing transition from a linear (produce-use-dispose) to a circular economy poses significant challenges to current state-of-the-art information and communication technologies. In particular, the derivation of integrated, high-level views on material, process, and product streams from (real-time) data produced along value chains is challenging...

In this study we examine the asymmetric propagation of return spillovers between oil prices and Islamic stock prices at the sector level. To achieve that, we extend the work of Antonakakis et al. (2020a), by introducing measures of asymmetric dynamic connectedness based on a time-varying vector autoregressive (TVPVAR) model. Furthermore, in the spi...

This study investigates the dynamic transmission mechanism between 2Y, 5Y and 10Y interest rate swaps (IRS) for six European currencies (CHF, DKK, EUR, GBP, NOK and SEK) from August 6, 1999 to March 4, 2021 applying the time-varying parameter vector autoregressive connectedness approach in the spirit of Antonakakis et al. (2020). Furthermore, we pr...

Purpose Existing empirical evidence suggests that episodes of financial stress (crises) can act as driver of growth of inequality. Consequently, in this study, the authors explore the time-varying predictive power of an index of financial stress for growth in income (and consumption) inequality in the UK. The authors focus on the UK since income (a...

This paper examines the dynamic connectedness among the implied volatilities of oil prices (OVX) and fourteen other assets, which can be grouped into five different assets classes (i.e., energy commodities, stock markets, precious metals, exchange rates and bond markets). To do so we estimate a recently developed time-varying parameter vector autor...

This study investigates the dynamic transmission mechanism between COVID-19 news sentiment (Google Trends Index), and S&P100, crude oil and gold volatility indices using the recently developed time-varying parameter vector autoregressive (TVP-VAR)-based extended joint connectedness approach. This framework corrects for the Generalized Forecast Erro...

We examine the predictive value of risk perceptions as measured in terms of the gold-to-silver and gold-to-platinum price ratios for stock-market tail risks and their connectedness in eight major industrialized economies using monthly data for the period 1916:02-2020:10 and 1968:01-2020:10, where we use four variants of the popular Conditional Auto...

In this study, we propose a novel quantile frequency connectedness approach that enables the investigation of propagation mechanisms by virtue of quantile and frequency. This approach allows for the analysis of connectedness measures considering either different frequencies for a given quantile or different quantiles for a given frequency. We inves...

This study provides a novel framework for analysing systematic tail risk transmission mechanisms by combining the Conditional Autoregressive Value-at-Risk (CAViaR) model with the recently developed Time-Varying Parameter Vector Autoregressive (TVP-VAR) based connectedness approach. We estimate dynamic spillovers across two crude oil (Brent and WTI)...

In this work, we compare multiple end-to-end neural networks that classify and segment numerous anatomies infetal torso ultrasound (US) images. The novelty of this paper is not restricted by the fact that it extends the scarceliterature on the recently proposed nnUNet approach, we are also the first who apply this framework on 2D USdata and compare...

With near-zero policy rates becoming the norm in many advanced economies, the focus on long-term bond yields has strengthened considerably. The unconventional monetary policy decision by the Bank of Japan (BOJ) in September 2016 to explicitly target the ten-year Japanese government bond (JGB) yield institutionalized this process—by effectively crea...

Utilizing a machine-learning technique known as random forests, we study whether regional output growth uncertainty helps to improve the accuracy of forecasts of regional output growth for twelve regions of the United Kingdom using monthly data for the period from 1970 to 2020. We use a stochastic-volatility model to measure regional output growth...

In the industrial domain, developing solutions that allow the identification, understanding, and correction of faults is essential due to the cost of handling such situations. However, to date, there are not many solutions capable of facilitating the human operator to discern the causes and possible solutions for a specific fault. In this work, we...

Socially responsible investing (SRI) such as issuing green bonds is increasingly widely adopted, moving into mainstream investment activity. In this study, we consider China, Europe and the US, in order to investigate (i) co-movements across and within the respective markets for green and traditional bonds in these regions and (ii) whether green bo...

We investigate volatility contagion across G7 stock markets and the market for crude oil for the period between 2007 and 2021. Following the work of Balcilar et al. (2021), we utilise the TVP-VAR extended joint connectedness method and compare results to the standard TVP-VAR method that predicates upon the normalisation approach by Diebold and Yılm...

This study has been inspired by the emergence of socially responsible investment practices in mainstream investment activity as it examines the transmission of return patterns between green bonds, carbon prices, and renewable energy stocks, using daily data spanning from 4th January 2015 to 22nd September 2020. In this study, our dataset comprises...

The United Kingdom (UK) in terms of income inequality is ranked among the highest in Europe. Likewise, within the last four decades, UK is characterized with drastic increases in household debt. In this paper, we analyze time-varying predictability of growth in household debt for growth in income (and consumption) inequality based on a high-frequen...

This study introduces a novel time-varying parameter vector autoregression (TVP-VAR) based extended joint connectedness approach in order to characterize connectedness of 11 agricultural commodity and Crude Oil futures prices spanning from July 1, 2005 to May 1, 2020. Our results reveal that the system-wide dynamic connectedness is heterogeneous ov...

In this paper, we investigate the time-varying interconnectedness of international Real Estate Investment Trusts (REITs) markets using daily REIT prices in twelve major REIT countries since the Global Financial Crisis. We construct dynamic total, net total and net pairwise return and volatility connectedness measures to better understand systemic r...

We investigate 1-year interest rate swaps on USD, EUR, JPY and GBP between 2005 and 2020 utilising a quantile connectedness model. This approach allows for a nuanced investigation of connectedness and adds to understanding the monetary policy transmission mechanism within a highly integrated international financial system. Substantial interest rate...

In this paper, we analyze time-varying predictability of labor productivity for growth in income (and consumption) inequality of the United Kingdom (UK) based on a high-frequency (quarterly) data set over 1975:Q1 to 2016:Q1. Results indicate that the growth rate of an index of labor productivity has a strong predictive power on growth rate of incom...

We investigate stock market sectoral connectedness in India utilizing a time‐varying parameter vector autoregressive connectedness approach. Results show that stock market sectoral connectedness varies across time. Connectedness is strongest during the 2008 crisis, the double‐digit inflation and stock market crash of 2011, following the national el...

In this study, we investigate the lead–lag relationship between housing prices and sales volume across four US regional housing markets, namely Midwest, Northeast, South, and West. To achieve this, we employ a time-varying parameter vector autoregressive framework of analysis that focuses on dynamic connectedness. We not only investigate how either...

This paper examines the role of monetary policy (MP) as a driver of connectedness patterns in speculative activities in financial markets. Examining measures of speculation in four major markets including gold, equities, Treasury bonds and crude oil, we show that speculative activities can spill over across markets with the stock market generally s...

Knowledge graphs in manufacturing and production aim to make production lines more efficient and flexible with higher quality output. This makes knowledge graphs attractive for companies to reach Industry 4.0 goals. However, existing research in the field is quite preliminary, and more research effort on analyzing how knowledge graphs can be applie...

We examine the relationship between investor sentiment and connectedness patterns across global stock markets within a quantile-on-quantile framework. Our findings show that investor happiness has a significant effect on both the return and volatility spillovers across global stock markets. While the sentiment effect is found to be relatively stron...

This study introduces two novel metrics that calculate the degree of shock asymmetry which can be utilized to examine whether countries in a currency area face symmetric shocks. In an attempt to answer whether the symmetric shock assumption is fulfilled in the European case, the exchange rate transmission mechanism of all 14 countries that have joi...

In this paper, we first obtain a time-varying measure of volatility connectedness involving fifteen major cryptocurrencies based on a dynamic conditional correlation-generalized autoregressive conditional heteroscedasticity (DCC-GARCH) model, and then analyze the role of investor sentiment in explaining the movement of the connectedness metric with...

In this paper we investigate global determinants of oil price volatility by employing a time-varying parameter vector autoregressive (TVP-VAR) model. We focus on realised volatility and consider the impact from a set of potential determinants including oil supply, oil demand, oil inventory, financial market uncertainty, financial interbank stress,...

This paper investigates spillovers between the housing sentiment index of Bork et al. (2020), common factors in US real housing returns and their volatility, GDP growth and real interest rates. We find that in contrast to spillovers from the common factor of housing returns to housing sentiment and GDP, reverse spillovers are relatively weak. This...

This study has been inspired by the emergence of socially responsible investment practices in mainstream investment activity wherein it examines the transmission of return patterns between green bonds, carbon prices, and renewable energy stocks using daily data spanning from 1st January 2013 to 22nd September 2020. In this study, our dataset compri...

Knowledge graphs in manufacturing and production aim to make production lines more efficient and flexible with higher quality output. This makes knowledge graphs attractive for companies to reach Industry 4.0 goals. However, existing research in the field is quite preliminary, and more research effort on analyzing how knowledge graphs can be applie...

The persistent deviations from the covered interest rate parity (CIP) since 2007 indicate that specific frictions continue to exist, which prevent them from being arbitraged away. In this study, we investigate the cross-currency basis swap market. We put forward the argument that the risk premium expressed via the CIP-deviation constitutes a unique...

This study employs dynamic connectedness as a measure of financial risk synchronization considering government bond yields in 11 EMU member states. In particular, large values of the relevant index can be an indication of comparable levels of risk further implying that the common currency area consists of a financially sensible set of countries. By...

In this paper, we show evidence of a dramatic change in the structure and time-varying patterns of return connectedness across various assets (gold, crude oil, world equities, currencies, and bonds) around the COVID-19 outbreak. Using the TVP-VAR connectedness approach, the results show that the dynamic total connectedness across the five assets wa...

This study uses time-varying parameter vector autoregression (TVP-VAR) based extended joint connectedness approach in order to characterize connectedness of 11 agricultural commodity and Crude Oil spot prices spanning from July 1, 2005 to May 1, 2020. Tools from network analysis is used to summarize and visualize results from average and system-wid...

This study investigates the transmission mechanism of Asia‐Pacific sovereign bond yields using a monthly data set, which reaches over the period from January 2003 until December 2017. Sovereign bond yields are decomposed into three latent factors – level, curvature and slope – using the dynamic Nelson–Siegel procedure proposed by Diebold and Li, Jo...

In this study, we examine the role of the Euro in currency co‐movements and contagion considering the USD exchange rates of six major currencies (i.e., EUR[DM], JPY, GBP, CHF, AUD, as well as, CAD). We identify five distinct intervals, each one corresponding to a different exchange rate regime or reflecting diverse economic developments. First, we...

Building on the increased interest in oil prices and other financial assets, this paper examines the dynamic conditional correlations among their implied volatility indices. We then proceed to the examination of the optimal hedging strategies and optimal portfolio weights for implied volatility portfolios between oil and fourteen asset volatilities...

In this study, we enhance the dynamic connectedness measures originally introduced by Diebold and Yılmaz (2012, 2014) with a time-varying parameter vector autoregressive model (TVP-VAR) which predicates upon a time-varying variance-covariance structure. This framework allows to capture possible changes in the underlying structure of the data in a m...

This paper examines the role of monetary policy (MP) as a driver of connected-ness patterns in speculative activities in financial markets. Examining measures of speculation in four major markets including gold, equities, Treasury bonds and crude oil, we show that speculative activities can spill over across markets with the stock market generally...

This study introduces volatility impulse response functions (VIRF) for DCC‐GARCH models. In addition, the implications with respect to network analysis ‐ using the connectedness approach of Diebold and Yılmaz (2014) ‐ is discussed. The main advantages of this framework are (i) that the time‐varying dynamics do not underlie a rolling‐window approach...