@techreport{65379, abstract = {{Diese Studie analysiert die ESEF-Berichterstattung in Deutschland seit der Einführung der iXBRL-basierten Berichtspflicht durch die ESMA im Jahr 2020. Anhand einer Stichprobe von 610 kapitalmarktorientierten Unternehmen der Frankfurter Börse im Zeitraum 2020-2023 wird gezeigt, dass 60,5% der Jahresabschlüsse die ESEF-Anforderungen vollständig erfüllen. Größere Unternehmen haben höhere Konformitätsraten als FSE-Scale und ausländische Unternehmen. Die Untersuchung der Taxonomie-Erweiterungen verdeutlicht, dass größere Unternehmen eher Erweiterungs-Tags nutzen, was mit Theorien freiwilliger Offenlegung übereinstimmt. Die verpflichtende Einführung des Anhang-Taggings im Jahr 2022 führte zu einer erhöhten Tagging-Granularität und verbesserter Offenlegungsqualität. Die Ergebnisse verdeutlichen Herausforderungen bei der ESEF-Umsetzung, wie Zugangsbarrieren und inkonsistente Durchsetzung, und geben Einblicke in unternehmensspezifische Offenlegungspraktiken im Kontext strukturierter Berichterstattung.}}, author = {{Hofmann, Philipp and Sievers, Sönke and Li, Reeyarn}}, pages = {{251--258}}, publisher = {{KoR}}, title = {{{ESEF-Berichterstattung in Deutschland: Herausforderungen und Chancen}}}, doi = {{KORKOR1476665}}, volume = {{Heft 7-8/2025}}, year = {{2025}}, } @techreport{65383, abstract = {{This paper introduces a predictive model for German mergers and acquisitions (M& A) activity leveraging deep feedforward neural networks (DFNN) incorporating well-established traditional variables (also known as features), along with a ChatGPT-based M& A sentiment score (MASS) and unconventional predictors such as beer sales and weather data. We demonstrate that the inclusion of sentiment and non-traditional variables enhances predictive performance. Our findings provide an important empirical foundation for understanding near-term fluctuations in German M& A activity and offer a forecasting tool relevant to both practitioners and researchers.}}, author = {{Sievers, Sönke and Li, Reeyarn and Degen, Dominik and Kengelbach, Jens and Pietrogrande, Francesca}}, issn = {{1437-8981}}, pages = {{302--308}}, title = {{{Beer, Cars & Fundamentals: Predicting German M& A activity}}}, doi = {{CFCF1480783}}, volume = {{Heft 11-12/2025}}, year = {{2025}}, } @article{35719, author = {{Kengelbach, Jens and Keienburg, Georg and Söllner, Tobias and Wang, Yiran and Sievers, Sönke and Friedmann, Daniel and Nielsen, Jesper}}, journal = {{BCG M&A Report 2022}}, title = {{{Green Deals Gain Steam }}}, year = {{2022}}, } @article{35722, author = {{Kengelbach, Jens and Friedman, Daniel and Keienburg, Georg and Degen, Dominik and Söllner, Tobias and Wang, Yiran and Sievers, Sönke}}, journal = {{BCG M&A Report 2022}}, title = {{{Do Green Deals Create Value? }}}, year = {{2022}}, } @techreport{20873, author = {{Sievers, Sönke and Keienburg, Georg and Degen, Dominik and Söllner, Tobias and Kashyrkin, Anton}}, publisher = {{The Boston Consulting Group, Inc., M&A Report}}, title = {{{Alternative Deals Gain Traction}}}, year = {{2020}}, } @article{20874, author = {{Sievers, Sönke and Degen, Dominik and Kim, Daniel and Kengelbach, Jens}}, journal = {{M&A Review}}, pages = {{266--271}}, title = {{{Downturn M&A: Die Erfolgsstrategie der Stunde?}}}, year = {{2020}}, } @techreport{20875, author = {{Sievers, Sönke and Kengelbach, Jens and Keienburg, Georg and Bader, Maximilian and Degen, Dominik and Gell, Jeff and Nielsen, Jesper}}, publisher = {{The Boston Consulting Group, Inc., M&A Report}}, title = {{{Downturns Are a Better Time For Deal Hunting}}}, year = {{2019}}, } @techreport{5411, abstract = {{Öffentlich gelistete Firmen, die die Mehrheit an anderen börsennotierten Unternehmen er-werben und den Kapitalmarkt an den Synergieerwartungen teilhaben lassen, werden mit höheren kumulativen abnormalen Renditen im Ankündigungszeitpunkt belohnt verglichen mit solchen Unternehmen, die diese geheim halten. Des Weiteren ist die empirische Evi-denz konsistent mit der Idee, dass diese Käuferunternehmen ihre Transaktionen besser in-tegrieren, weil auch die industrieadjustierten Ein- und Zweijahresrenditen der ankündigen-den Unternehmen ökonomisch und statistisch signifikant höher sind als die der zurückhal-tenden Käuferfirmen. }}, author = {{Mehring, Oliver and Sievers, Sönke and Keienburg, Georg and Kengelbach, Jens}}, pages = {{76--84}}, publisher = {{Corporate Finance}}, title = {{{Wertgenerierung bei M&A Transaktionen durch Bekanntgabe von Synergien?}}}, volume = {{3-4}}, year = {{2019}}, } @article{20688, abstract = {{We offer the first empirical analysis connecting the timing of general partner (GP) compensation to private equity fund performance. Using detailed information on limited partnership agreements between private equity limited and general partners, we find that “GP-friendly” contracts—agreements that pay general partners on a deal-by-deal basis instead of withholding carried interest until a benchmark return has been earned—are associated with higher returns, both gross and net of fees. This is robust to measures of performance persistence, time period effects, and other contract terms and is related to exit-timing incentives. Timing practices balance GP incentives against limited partner downside protection.}}, author = {{Hüther, Niklas and Robinson, David T. and Sievers, Sönke and Hartmann-Wendels, Thomas}}, issn = {{0025-1909}}, journal = {{Management Science (VHB-JOURQUAL 4 Ranking A+)}}, keywords = {{venture capital, compensation, private equity, VC partnership, pay-performance relation}}, number = {{4}}, pages = {{1756--1782}}, title = {{{Paying for Performance in Private Equity: Evidence from Venture Capital Partnerships}}}, doi = {{10.1287/mnsc.2018.3274}}, volume = {{66}}, year = {{2019}}, } @techreport{20876, author = {{Sievers, Sönke and Keienburg, Georg and Schmid, Timo and Degen, Dominik}}, publisher = {{The Boston Consulting Group, Inc., M&A Report}}, title = {{{Synergies Take Center Stage}}}, year = {{2018}}, } @techreport{20878, author = {{Sievers, Sönke}}, title = {{{Blog post by Prof. Sönke Sievers: Kapitalmarktorientierte Erfolgsmessung von M&A Transaktionen – Deutsche und weltweite Evidenz.}}}, year = {{2018}}, } @techreport{20879, author = {{Sievers, Sönke and Degen, Dominik and Keienburg, Georg and Schmid, Timo and Kengelbach, Jens}}, publisher = {{The Boston Consulting Group, Inc., M&A Report}}, title = {{{Update on the M&A market entitled As Prices Peak, Should Dealmakers wait for the next Downturn?}}}, year = {{2018}}, } @techreport{20880, author = {{Sievers, Sönke and Robinson, David T. and Hüther, Niklas and Hartmann-Wendels, Thomas}}, title = {{{Post on Paying for Performance in Private Equity: Evidence from VC Partnerships.}}}, year = {{2018}}, } @article{4874, abstract = {{Restrukturierungen werden sowohl durch die Digitalisierung, aber auch durch klassische Themen – beispielsweise die Notwendigkeit von Umsatz- und Kostensynergien in kompetitiven Märkten – verstärkt vorangetrieben. Dieser Beitrag beleuchtet vor allem die Motive und Folgen aus wissenschaftlicher Perspektive, indem großzahlige empirische Befunde zu den Themen Beschäftigung, Finanzkennzahlen und Kapitalerhöhungen sowie steuerliche Motive prägnant zusammengefasst und im Kontext des geplanten Joint Ventures von thyssenkrupp und Tata Steel diskutiert werden.}}, author = {{Sievers, Sönke and Sureth-Sloane, Caren and Uhde, André}}, journal = {{Die Wirtschaftsprüfung}}, number = {{9}}, pages = {{569--575}}, title = {{{Restrukturierungen: operative und finanzielle Wertbeiträge. Eine Betrachtung vor dem Hintergrund der Entwicklungen bei thyssenkrupp}}}, volume = {{71}}, year = {{2018}}, } @techreport{20868, abstract = {{This study proposes a simple theoretical framework that allows for assessing financial distress up to five years in advance. We jointly model financial distress by using two of its key driving factors: declining cash-generating ability and insufficient liquidity reserves. The model is based on stochastic processes and incorporates firm-level and industry-sector developments. A large-scale empirical implementation for US-listed firms over the period of 1980-2010 shows important improvements in the discriminatory accuracy and demonstrates incremental information content beyond state-of-the-art accounting and market-based prediction models. Consequently, this study might provide important ex ante warning signals for investors, regulators and practitioners.}}, author = {{Sievers, Sönke and Klobucnik, Jan and Miersch, David}}, keywords = {{Financial distress prediction, probability of default, accounting information, stochastic processes, simulation}}, pages = {{84}}, title = {{{Predicting Early Warning Signals of Financial Distress: Theory and Empirical Evidence}}}, doi = {{10.2139/ssrn.2237757}}, year = {{2017}}, } @techreport{5174, author = {{Sievers, Sönke and Kengelbach, Jens and Keienburg, Georg and Schmid, Timo and Gjersta, Ketil and Nielsen, Jesper and Walker, Decker}}, publisher = {{The Boston Consulting Group, Inc., M&A Report}}, title = {{{The Technology Takeover}}}, year = {{2017}}, } @article{5185, abstract = {{We offer the first empirical analysis connecting the timing of general partner (GP) compensation to private equity fund performance. Using detailed information on limited partnership agreements between private equity limited and general partners, we find that "GP-friendly" contracts - agreements that pay general partners on a deal-by-deal basis instead of withholding carried interest until a benchmark return has been earned - are associated with higher returns, both gross and net of fees. This is robust to measures of performance persistence, time period effects, and other contract terms, and is related to exit-timing incentives. Timing practices balance GP incentives against limited partner downside protection. }}, author = {{Hüther, Niklas and Robinson, David and Sievers, Sönke and Hartmann-Wendels, Thomas}}, journal = {{SSRN Electronic Journal}}, keywords = {{venture capital, compensation, private equity, VC partnership, pay-performance relation}}, title = {{{Paying for Performance in Private Equity: Evidence from VC Partnerships}}}, doi = {{10.2139/ssrn.3087320}}, year = {{2017}}, } @article{5199, abstract = {{This study proposes a simple theoretical framework that allows for assessing financial distress up to five years in advance. We jointly model financial distress by using two of its key driving factors: declining cash-generating ability and insufficient liquidity reserves. The model is based on stochastic processes and incorporates firm-level and industry-sector developments. A large-scale empirical implementation for US-listed firms over the period of 1980-2010 shows important improvements in the discriminatory accuracy and demonstrates incremental information content beyond state-of-the-art accounting and market-based prediction models. Consequently, this study might provide important ex ante warning signals for investors, regulators and practitioners. }}, author = {{Klobucnik, Jan and Miersch, David and Sievers, Sönke}}, journal = {{SSRN Electronic Journal}}, keywords = {{Financial distress prediction, probability of default, accounting information, stochastic processes, simulation}}, title = {{{Predicting Early Warning Signals of Financial Distress: Theory and Empirical Evidence}}}, year = {{2017}}, } @article{4586, abstract = {{This study examines the loan-pricing behavior of German banks for a large variety of retail and corporate loan products. We find that a bank’s operational efficiency is priced in bank loan rates and alters interest-setting behavior. Specifically, we establish that a higher degree of operational efficiency leads to lower loan markups, which makes prices more competitive and smoothes the setting of interest rates. By employing state-of-the-art stochastic frontier efficiency measures to capture a bank’s operational efficiency, we take a look at the bank customers’ perspective and demonstrate the extent to which bor-rowers benefit from cost-efficient banking. }}, author = {{Schlueter, Tobias and Busch, Ramona and Sievers, Soenke and Hartmann-Wendels, Thomas}}, journal = {{Credit and Capital Markets--Kredit und Kapital}}, keywords = {{interest rate pass-through models, error correction models, bank efficiency, cost efficiency, stochastic frontier analysis}}, number = {{1}}, pages = {{93--125}}, title = {{{Loan Pricing: Do Borrowers Benefit from Cost-Efficient Banking?}}}, doi = {{10.3790/ccm.49.1.93}}, volume = {{49}}, year = {{2016}}, } @techreport{5200, author = {{Kengelbach, Jens and Keienburg, Georg and Schmid, Timo and Sievers, Sönke and Mehring, Oliver}}, publisher = {{The Boston Consulting Group, Inc., M&A Report}}, title = {{{Masters of the Corporate Portfolio}}}, year = {{2016}}, }