--- _id: '20870' abstract: - lang: eng text: This study shows how venture capital investors can identify potential biases in multi-year management forecasts before an investment decision and derive significantly more accurate failure predictions. By advancing a cross-sectional projection method developed by prior research and using firm-specific information in financial statements and business plans, we derive benchmarks for management revenue forecasts. With these benchmarks, we estimate forecast errors as an a priori measure of biased expectations. Using this measure for our proprietary dataset on venture-backed start-ups in Germany, we find evidence of substantial upward forecast biases. We uncover that firms with large forecast errors fail significantly more often than do less biased entrepreneurs in years following the investment. Overall, our results highlight the implications of excessive optimism and overconfidence in entrepreneurial environments and emphasize the relevance of accounting information and business plans for venture capital investment decisions. author: - first_name: Sönke full_name: Sievers, Sönke id: '46447' last_name: Sievers - first_name: Christopher Frederik full_name: Mokwa, Christopher Frederik last_name: Mokwa citation: ama: Sievers S, Mokwa CF. The Relevance of Biases in Management Forecasts for Failure Prediction in Venture Capital Investments.; 2012. doi:10.2139/ssrn.2100501 apa: Sievers, S., & Mokwa, C. F. (2012). The Relevance of Biases in Management Forecasts for Failure Prediction in Venture Capital Investments. https://doi.org/10.2139/ssrn.2100501 bibtex: '@book{Sievers_Mokwa_2012, title={The Relevance of Biases in Management Forecasts for Failure Prediction in Venture Capital Investments}, DOI={10.2139/ssrn.2100501}, author={Sievers, Sönke and Mokwa, Christopher Frederik}, year={2012} }' chicago: Sievers, Sönke, and Christopher Frederik Mokwa. The Relevance of Biases in Management Forecasts for Failure Prediction in Venture Capital Investments, 2012. https://doi.org/10.2139/ssrn.2100501. ieee: S. Sievers and C. F. Mokwa, The Relevance of Biases in Management Forecasts for Failure Prediction in Venture Capital Investments. 2012. mla: Sievers, Sönke, and Christopher Frederik Mokwa. The Relevance of Biases in Management Forecasts for Failure Prediction in Venture Capital Investments. 2012, doi:10.2139/ssrn.2100501. short: S. Sievers, C.F. Mokwa, The Relevance of Biases in Management Forecasts for Failure Prediction in Venture Capital Investments, 2012. date_created: 2021-01-05T11:59:50Z date_updated: 2022-01-06T06:54:41Z department: - _id: '275' doi: 10.2139/ssrn.2100501 extern: '1' jel: - G24 - G32 - M13 - M41 keyword: - Management forecast biases - cross-sectional projection models - venture-backed start-ups - failure prediction - overoptimism - overconfidence language: - iso: eng main_file_link: - url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2100501 page: '31' publication_status: published status: public title: The Relevance of Biases in Management Forecasts for Failure Prediction in Venture Capital Investments type: working_paper user_id: '46447' year: '2012' ... --- _id: '5196' abstract: - lang: eng text: 'This study shows how venture capital investors can identify potential biases in multi-year management forecasts before an investment decision and derive significantly more accurate failure predictions. By advancing a cross-sectional projection method developed by prior research and using firm-specific information in financial statements and business plans, we derive benchmarks for management revenue forecasts. With these benchmarks, we estimate forecast errors as an a priori measure of biased expectations. Using this measure for our proprietary dataset on venture-backed start-ups in Germany, we find evidence of substantial upward forecast biases. We uncover that firms with large forecast errors fail significantly more often than do less biased entrepreneurs in years following the investment. Overall, our results highlight the implications of excessive optimism and overconfidence in entrepreneurial environments and emphasize the relevance of accounting information and business plans for venture capital investment decisions. ' author: - first_name: Christopher Frederik full_name: Mokwa, Christopher Frederik last_name: Mokwa - first_name: Sönke full_name: Sievers, Sönke last_name: Sievers citation: ama: Mokwa CF, Sievers S. The Relevance of Biases in Management Forecasts for Failure Prediction in Venture Capital Investments. SSRN Electronic Journal. 2012. doi:10.2139/ssrn.2100501 apa: Mokwa, C. F., & Sievers, S. (2012). The Relevance of Biases in Management Forecasts for Failure Prediction in Venture Capital Investments. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2100501 bibtex: '@article{Mokwa_Sievers_2012, title={The Relevance of Biases in Management Forecasts for Failure Prediction in Venture Capital Investments}, DOI={10.2139/ssrn.2100501}, journal={SSRN Electronic Journal}, author={Mokwa, Christopher Frederik and Sievers, Sönke}, year={2012} }' chicago: Mokwa, Christopher Frederik, and Sönke Sievers. “The Relevance of Biases in Management Forecasts for Failure Prediction in Venture Capital Investments.” SSRN Electronic Journal, 2012. https://doi.org/10.2139/ssrn.2100501. ieee: C. F. Mokwa and S. Sievers, “The Relevance of Biases in Management Forecasts for Failure Prediction in Venture Capital Investments,” SSRN Electronic Journal, 2012. mla: Mokwa, Christopher Frederik, and Sönke Sievers. “The Relevance of Biases in Management Forecasts for Failure Prediction in Venture Capital Investments.” SSRN Electronic Journal, 2012, doi:10.2139/ssrn.2100501. short: C.F. Mokwa, S. Sievers, SSRN Electronic Journal (2012). date_created: 2018-10-31T12:12:28Z date_updated: 2022-01-06T07:01:43Z department: - _id: '275' doi: 10.2139/ssrn.2100501 jel: - G24 - G32 - M13 - M41 keyword: - Management forecast biases - cross-sectional projection models - venture-backed start-ups - failure prediction - overoptimism - overconfidence language: - iso: eng publication: SSRN Electronic Journal publication_status: published status: public title: The Relevance of Biases in Management Forecasts for Failure Prediction in Venture Capital Investments type: journal_article user_id: '64756' year: '2012' ... --- _id: '13326' abstract: - lang: eng text: Communication within online social network applications enables users to express and share sentiments electronically. Existing studies examined the existence or distribution of sentiments in online communication at a general level or in small-observed groups. Our paper extends this research by analyzing sentiment exchange within social networks from an ego-network perspective. We draw from research on social influence and social attachment to develop theories of node polarization, balance effects and sentiment mirroring within communication dyads. Our empirical analysis covers a multitude of social networks in which the sentiment valence of all messages was determined. Subsequently we studied ego-networks of focal actors (ego) and their immediate contacts. Results support our theories and indicate that actors develop polarized sentiments towards individual peers but keep sentiment in balance on the ego-network level. Further, pairs of nodes tend to establish similar attitudes towards each other leading to stable and polarized positive or negative relationships author: - first_name: Robert full_name: Hillmann, Robert last_name: Hillmann - first_name: Matthias full_name: Trier, Matthias id: '72744' last_name: Trier citation: ama: 'Hillmann R, Trier M. Sentiment Polarization and Balance among Users in Online Social Networks. In: Joshi KD, Yoo Y, eds. AMCIS 2012 Proceedings. Vol 24. Association for Information Systems. AIS Electronic Library (AISeL); 2012.' apa: Hillmann, R., & Trier, M. (2012). Sentiment Polarization and Balance among Users in Online Social Networks. In K. D. Joshi & Y. Yoo (Eds.), AMCIS 2012 Proceedings (Vol. 24). Association for Information Systems. AIS Electronic Library (AISeL). bibtex: '@inproceedings{Hillmann_Trier_2012, title={Sentiment Polarization and Balance among Users in Online Social Networks}, volume={24}, booktitle={AMCIS 2012 Proceedings}, publisher={Association for Information Systems. AIS Electronic Library (AISeL)}, author={Hillmann, Robert and Trier, Matthias}, editor={Joshi, K.D. and Yoo, YoungjinEditors}, year={2012} }' chicago: Hillmann, Robert, and Matthias Trier. “Sentiment Polarization and Balance among Users in Online Social Networks.” In AMCIS 2012 Proceedings, edited by K.D. Joshi and Youngjin Yoo, Vol. 24. Association for Information Systems. AIS Electronic Library (AISeL), 2012. ieee: R. Hillmann and M. Trier, “Sentiment Polarization and Balance among Users in Online Social Networks,” in AMCIS 2012 Proceedings, 2012, vol. 24. mla: Hillmann, Robert, and Matthias Trier. “Sentiment Polarization and Balance among Users in Online Social Networks.” AMCIS 2012 Proceedings, edited by K.D. Joshi and Youngjin Yoo, vol. 24, Association for Information Systems. AIS Electronic Library (AISeL), 2012. short: 'R. Hillmann, M. Trier, in: K.D. Joshi, Y. Yoo (Eds.), AMCIS 2012 Proceedings, Association for Information Systems. AIS Electronic Library (AISeL), 2012.' date_created: 2019-09-19T12:22:08Z date_updated: 2022-01-06T06:51:33Z department: - _id: '198' editor: - first_name: K.D. full_name: Joshi, K.D. last_name: Joshi - first_name: Youngjin full_name: Yoo, Youngjin last_name: Yoo intvolume: ' 24' keyword: - Social Network Analysis - Ego-Network Analysis - Node Polarization - Sentiment Dissemination language: - iso: eng publication: AMCIS 2012 Proceedings publisher: Association for Information Systems. AIS Electronic Library (AISeL) status: public title: Sentiment Polarization and Balance among Users in Online Social Networks type: conference user_id: '62809' volume: 24 year: '2012' ... --- _id: '11930' abstract: - lang: eng text: For human-machine interfaces in distant-talking environments multichannel signal processing is often employed to obtain an enhanced signal for subsequent processing. In this paper we propose a novel adaptation algorithm for a filter-and-sum beamformer to adjust the coefficients of FIR filters to changing acoustic room impulses, e.g. due to speaker movement. A deterministic and a stochastic gradient ascent algorithm are derived from a constrained optimization problem, which iteratively estimates the eigenvector corresponding to the largest eigenvalue of the cross power spectral density of the microphone signals. The method does not require an explicit estimation of the speaker location. The experimental results show fast adaptation and excellent robustness of the proposed algorithm. author: - first_name: Ernst full_name: Warsitz, Ernst last_name: Warsitz - first_name: Reinhold full_name: Haeb-Umbach, Reinhold id: '242' last_name: Haeb-Umbach citation: ama: 'Warsitz E, Haeb-Umbach R. Acoustic filter-and-sum beamforming by adaptive principal component analysis. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2005). Vol 4. ; 2005:iv/797-iv/800 Vol. 4. doi:10.1109/ICASSP.2005.1416129' apa: Warsitz, E., & Haeb-Umbach, R. (2005). Acoustic filter-and-sum beamforming by adaptive principal component analysis. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2005) (Vol. 4, p. iv/797-iv/800 Vol. 4). https://doi.org/10.1109/ICASSP.2005.1416129 bibtex: '@inproceedings{Warsitz_Haeb-Umbach_2005, title={Acoustic filter-and-sum beamforming by adaptive principal component analysis}, volume={4}, DOI={10.1109/ICASSP.2005.1416129}, booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2005)}, author={Warsitz, Ernst and Haeb-Umbach, Reinhold}, year={2005}, pages={iv/797-iv/800 Vol. 4} }' chicago: Warsitz, Ernst, and Reinhold Haeb-Umbach. “Acoustic Filter-and-Sum Beamforming by Adaptive Principal Component Analysis.” In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2005), 4:iv/797-iv/800 Vol. 4, 2005. https://doi.org/10.1109/ICASSP.2005.1416129. ieee: E. Warsitz and R. Haeb-Umbach, “Acoustic filter-and-sum beamforming by adaptive principal component analysis,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2005), 2005, vol. 4, p. iv/797-iv/800 Vol. 4. mla: Warsitz, Ernst, and Reinhold Haeb-Umbach. “Acoustic Filter-and-Sum Beamforming by Adaptive Principal Component Analysis.” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2005), vol. 4, 2005, p. iv/797-iv/800 Vol. 4, doi:10.1109/ICASSP.2005.1416129. short: 'E. Warsitz, R. Haeb-Umbach, in: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2005), 2005, p. iv/797-iv/800 Vol. 4.' date_created: 2019-07-12T05:31:00Z date_updated: 2022-01-06T06:51:12Z department: - _id: '54' doi: 10.1109/ICASSP.2005.1416129 intvolume: ' 4' keyword: - acoustic filter-and-sum beamforming - acoustic room impulses - acoustic signal processing - adaptive principal component analysis - adaptive signal processing - architectural acoustics - constrained optimization problem - cross power spectral density - deterministic algorithm - deterministic algorithms - distant-talking environments - eigenvalues and eigenfunctions - eigenvector - enhanced signal - filter-and-sum beamformer - FIR filter coefficients - FIR filter coefficients - FIR filters - gradient methods - human-machine interfaces - iterative estimation - iterative methods - largest eigenvalue - microphone signals - multichannel signal processing - optimisation - principal component analysis - spectral analysis - stochastic gradient ascent algorithm - stochastic processes language: - iso: eng main_file_link: - open_access: '1' url: https://groups.uni-paderborn.de/nt/pubs/2005/WaHa05.pdf oa: '1' page: iv/797-iv/800 Vol. 4 publication: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2005) status: public title: Acoustic filter-and-sum beamforming by adaptive principal component analysis type: conference user_id: '44006' volume: 4 year: '2005' ... --- _id: '11931' abstract: - lang: eng text: The paper is concerned with binaural signal processing for a bimodal human-robot interface with hearing and vision. The two microphone signals are processed to obtain an enhanced single-channel input signal for the subsequent speech recognizer and to localize the acoustic source, an important information for establishing a natural human-robot communication. We utilize a robust adaptive algorithm for filter-and-sum beamforming (FSB) and extract speaker direction information from the resulting FIR filter coefficients. Further, particle filtering is applied which conducts a nonlinear Bayesian tracking of speaker movement. Good location accuracy can be achieved even in highly reverberant environments. The results obtained outperform the conventional generalized cross correlation (GCC) method. author: - first_name: Ernst full_name: Warsitz, Ernst last_name: Warsitz - first_name: Reinhold full_name: Haeb-Umbach, Reinhold id: '242' last_name: Haeb-Umbach citation: ama: 'Warsitz E, Haeb-Umbach R. Robust speaker direction estimation with particle filtering. In: IEEE Workshop on Multimedia Signal Processing (MMSP 2004). ; 2004:367-370. doi:10.1109/MMSP.2004.1436569' apa: Warsitz, E., & Haeb-Umbach, R. (2004). Robust speaker direction estimation with particle filtering. In IEEE Workshop on Multimedia Signal Processing (MMSP 2004) (pp. 367–370). https://doi.org/10.1109/MMSP.2004.1436569 bibtex: '@inproceedings{Warsitz_Haeb-Umbach_2004, title={Robust speaker direction estimation with particle filtering}, DOI={10.1109/MMSP.2004.1436569}, booktitle={IEEE Workshop on Multimedia Signal Processing (MMSP 2004)}, author={Warsitz, Ernst and Haeb-Umbach, Reinhold}, year={2004}, pages={367–370} }' chicago: Warsitz, Ernst, and Reinhold Haeb-Umbach. “Robust Speaker Direction Estimation with Particle Filtering.” In IEEE Workshop on Multimedia Signal Processing (MMSP 2004), 367–70, 2004. https://doi.org/10.1109/MMSP.2004.1436569. ieee: E. Warsitz and R. Haeb-Umbach, “Robust speaker direction estimation with particle filtering,” in IEEE Workshop on Multimedia Signal Processing (MMSP 2004), 2004, pp. 367–370. mla: Warsitz, Ernst, and Reinhold Haeb-Umbach. “Robust Speaker Direction Estimation with Particle Filtering.” IEEE Workshop on Multimedia Signal Processing (MMSP 2004), 2004, pp. 367–70, doi:10.1109/MMSP.2004.1436569. short: 'E. Warsitz, R. Haeb-Umbach, in: IEEE Workshop on Multimedia Signal Processing (MMSP 2004), 2004, pp. 367–370.' date_created: 2019-07-12T05:31:01Z date_updated: 2022-01-06T06:51:12Z department: - _id: '54' doi: 10.1109/MMSP.2004.1436569 keyword: - bimodal human-robot interface - binaural signal processing - enhanced single-channel input signal - filter-and-sum beamforming - filtering theory - FIR filter coefficient - generalized cross correlation method - microphones - microphone signal - nonlinear Bayesian tracking - particle filtering - robust adaptive algorithm - robust speaker direction estimation - signal processing - speech enhancement - speech recognition - speech recognizer - user interfaces language: - iso: eng main_file_link: - open_access: '1' url: https://groups.uni-paderborn.de/nt/pubs/2004/WaHa04.pdf oa: '1' page: 367-370 publication: IEEE Workshop on Multimedia Signal Processing (MMSP 2004) status: public title: Robust speaker direction estimation with particle filtering type: conference user_id: '44006' year: '2004' ...