IPO Survival and Managerial Confidence (with Ufuk Güçbilmez)
Abstract: This study empirically examines the hypothesis of whether, how, and why CEO overconfidence substantially influences the Initial Public Offerings (IPO) failure risk. We construct CEO overconfidence measurement through a textual analysis by extracting optimistic sentiments within the entirety of the S-1 form and specifically the management discussion section, finding that overconfident CEOs correlate with a roughly 27% reduction in the probability of IPO failure. Our findings remain robust through various tests, and we use the internal instrumental-variable (IV) method to identify the causal effect of CEO overconfidence on IPO survival. We also use the Sarbanes-Oxley Act of 2002 as an exogenous shock to identify the causal effect of CEO overconfidence on IPO survival, the study finds that the inverse relationship between CEO overconfidence and IPO failure is more pronounced on post-implementation of the Sarbanes-Oxley Act. Additionally, our research illuminates that R&D investment acts as a moderating factor amplifying the positive impact of CEO overconfidence on IPO survival.
This research presented on 2023 BAFA Scotland Doctoral Conference (Edinburgh, Scotland UK, ); 2024 annual conference of the Scotish Economic Society (SES) (Glasgow, Scotland, UK); 2024 European Accounting Association (EAA) annual meeting (Bucharest, Romania); 2024 European Financial Management Association (EFMA) annual meeting (Lisbon, Portugal); 2024 Finance and Business Analytics (FBA) Meeting (Athens, Greece). Thanks all anonymous reviewers and participants for valuable comments and insights.
This research will present on 2025 FMA Europe Annual Meeting (Limassol, Cyprus). Looking forwards to meeting new and old friends in Cyprus!
Determinants of Organization Capital: Does CEO matters? (with Ufuk Güçbilmez)
Abstract: This study empirically examines the determinants of organizational capital, with a particular focus on the impact of CEO turnover. We find that the appointment of a new CEO significantly stimulates the accumulation of organizational capital, increasing its stock by approximately 15%. Furthermore, a one standard deviation increase in managerial ability corresponds to an estimated 7%-8% increase in the standard deviation of organizational capital. Our findings suggest that the primary mechanisms driving this effect are the CEO’s ability and compensation level. Specifically, while a new CEO typically enhances organizational capital, highly capable CEOs markedly accelerate its accumulation in the post-turnover period. Conversely, less capable CEOs devote less attention to organizational capital accumulation following their appointment. Our results remain robust across subsamples that account for various reasons behind CEO dismissals, including voluntary, involuntary, and forced turnover, thereby supporting causal inference. Additionally, we observe that the CEO compensation structure—including performance-based pay and the CEO pay gap—moderates and amplifies the positive effect of CEO ability on organizational capital. Finally, the presence of outside CEOs and highly capable CEOs further strengthens the positive effects of CEO turnover on organizational capital.
This research will present on 2025 BAFA Annual Conference (Belfast, Northern Ireland, UK); 2025 Asian Finance Association Annual Meeting (Taipei City, Taiwan). Looking forwards to meeting new and old friends in Belfast and Taipei City!
CEO Pay-for-Luck: Who Demands More Pay-for-Luck, and What Are the Consequences? Evidence from a Quasi-natural Experiment
“It is not compensation that is in the interest of shareholders in any way” (Andreani et al., 2024)
Organization Capital: the more the better? Empirical Evidence of Risk of Organization Capital
Abstract: This paper empirically analysis the impact of organization capital on corporate risk and uncertainty. We argue that accumulated investment in SG&A also defined as organization capital is not only an important, special, value-enhancing intangible assets but also reflect firm’s risk. We find organization capital have positive causal effect on cash flow volatility. Our results are robust from various additional tests. We use state-level exogenous variation of unemployment benefits as our instrumental variable and confirm the causal effect of organization capital on cash flow volatility. We argue that firms with higher level of organization capital are more likely to conduct aggressive tax avoidance policies and earning management. We find moderating effect of tax avoidance policies and earning management on the positive impact of organization capital on cash flow volatility. Furthermore, we also find robust negative causal effect of organization capital on financial report comparability because organization capital as an unique, firm-level, idiosyncratic assets is difficult to be replicated by other firms, which leading higher information asymmetry among management and investors.
Interpretable Machine Learning Applications in Expert Prediction Optimization (with Yujia Chang)
Abstract: This study presents a comprehensive framework by applying both deep learning and machine learning as a hybrid approach to optimize the UK macroeconomic forecasts. The algorithm architectures are constructed by utilizing the most well-known deep learning models: deep neural networks (DNN) and Long Short-Term Memory (LSTM), and machine learning models: Support Vector Regression (SVR) and Random Forest (RF). We build the optimal combination of machine learning algorithms for UK professional forecasters in macroeconomic forecasting. We suggest that machine learning exhibits a significant predictive ability, while deep learning can also be effective as an addition to achieve an optimization goal in macroeconomic forecasting. Our contribution lies in finding the solution to selecting optimal hyperparameters, which is a critical problem in machine learning. Our results also provide evidence on the application of machine learning is valid even with a small data sample.