The authors examine a firm＇s decision to begin issuing debt in public bond markets and find that it is a function of both life cycle influences and opportunistic timing. Defining life cycle factors to encompass both ...The authors examine a firm＇s decision to begin issuing debt in public bond markets and find that it is a function of both life cycle influences and opportunistic timing. Defining life cycle factors to encompass both a firm＇s age in years and its underlying characteristics, the authors confirm that bond market participation is generally restricted to large, mature firms. Summary statistics show that finns obtain their initial bond ratings on average 9.5 years after their equity initial public offering （IPO） and 11.8 years after initiating dividend payments. Growth rates, capital expenditures, and cash flow volatility all decline as the firm accesses public debt markets, consistent with entry into the mature phase of its life cycle. With respect to opportunistic timing, it is asked whether entry into public bond markets follows strong performance （or precedes weak performance） at both the firm and market levels. At the firm level, the authors find that the debt IPO occurs following periods of strong operating performance and high excess stock returns. At the market level, entry coincides with favorable interest rates and default spreads. The benefits of careful timing result in firms receiving initial bond ratings that are stronger than what would be predicted; however, there is no evidence of abnormal numbers of downgrades for these firms in subsequent years.展开更多
随着大数据、云计算、云会计等技术的发展,财务工作已经逐渐进入智能化时代,财务共享应运而生,已经成为集团企业进行日常财务工作管理的重要手段。近年来,部分集团公司试图通过建立财务共享中心以自动处理各子公司的繁杂的日常业务,并...随着大数据、云计算、云会计等技术的发展,财务工作已经逐渐进入智能化时代,财务共享应运而生,已经成为集团企业进行日常财务工作管理的重要手段。近年来,部分集团公司试图通过建立财务共享中心以自动处理各子公司的繁杂的日常业务,并制定一套规范的流程以进行管理,从而降低成本,但财务共享模式下应收账款管理中仍然存在着集成度与自动化程度不足的问题,而大数据技术的发展将有力地解决上述问题,该文研究企业日常应收账款管理工作中如何实际应用K-Means算法、人工神经网络中的反向传播算法(Backpropagation Algorithm,BP算法)结合机器人流程自动化(Robotics Process Automation,RPA)技术,借此帮助企业更好地管理其应收账款,满足其经营管理的需求。展开更多
文摘The authors examine a firm＇s decision to begin issuing debt in public bond markets and find that it is a function of both life cycle influences and opportunistic timing. Defining life cycle factors to encompass both a firm＇s age in years and its underlying characteristics, the authors confirm that bond market participation is generally restricted to large, mature firms. Summary statistics show that finns obtain their initial bond ratings on average 9.5 years after their equity initial public offering （IPO） and 11.8 years after initiating dividend payments. Growth rates, capital expenditures, and cash flow volatility all decline as the firm accesses public debt markets, consistent with entry into the mature phase of its life cycle. With respect to opportunistic timing, it is asked whether entry into public bond markets follows strong performance （or precedes weak performance） at both the firm and market levels. At the firm level, the authors find that the debt IPO occurs following periods of strong operating performance and high excess stock returns. At the market level, entry coincides with favorable interest rates and default spreads. The benefits of careful timing result in firms receiving initial bond ratings that are stronger than what would be predicted; however, there is no evidence of abnormal numbers of downgrades for these firms in subsequent years.
文摘随着大数据、云计算、云会计等技术的发展,财务工作已经逐渐进入智能化时代,财务共享应运而生,已经成为集团企业进行日常财务工作管理的重要手段。近年来,部分集团公司试图通过建立财务共享中心以自动处理各子公司的繁杂的日常业务,并制定一套规范的流程以进行管理,从而降低成本,但财务共享模式下应收账款管理中仍然存在着集成度与自动化程度不足的问题,而大数据技术的发展将有力地解决上述问题,该文研究企业日常应收账款管理工作中如何实际应用K-Means算法、人工神经网络中的反向传播算法(Backpropagation Algorithm,BP算法)结合机器人流程自动化(Robotics Process Automation,RPA)技术,借此帮助企业更好地管理其应收账款,满足其经营管理的需求。
