辽宁大学经济学前沿高端讲座第四十六讲 Stochastic Asset Volatility and Financially Distressed Firms

NewsvoteDWR.getNewsLinkUrl(1714,'1503939075','vsb',newsSkip);function newsSkip(data){if(data != ""){window.location.href = data;}} 辽宁大学经济学前沿高端讲座第四十六讲 Stochastic Asset Volatility and Financially Distressed Firms 2024-04-10  点击：[_showDynClicks("wbnews", 1503939075, 1714)] 主讲人：甄芳副教授（中央财经大学中国经济与管理研究院） 主持人：毛明海助理教授（辽宁大学李安民经济研究院） 嘉宾介绍：游宇教授（辽宁大学李安民经济研究院） 时间：2024年4月19日（周五）  10：00-11：30（北京时间） 地点：辽宁大学崇山校区五洲园一楼会议室 线上地址：腾讯会议：395-118-442 语言：中文/英文 摘要： This paper adopts the Heston stochastic volatility (SV) model and that augmented by price jumps (SVJ) to measure a firm's default risk. We estimate the models by matching a firm's two time-varying series of equity value and volatility. Applying these models to the Growth Enterprises Market in China, we find that the Black-Scholes-Merton (BSM) model produces biased default probability by implicitly setting zero parameters governing stochastic volatility and price jumps. More importantly, we provide empirical evidence supporting the superiority of the SV and SVJ models over the BSM model in distinguishing financially distressed firms, with the SVJ model exhibiting the best performance. This paper suggests that the SV or SVJ default probability, especially its functional form, is more appropriate to measure credit risk.   主讲人简介： 甄芳，中央财经大学中国经济与管理研究院长聘副教授，2017年5月获得新西兰奥塔戈大学金融学博士学位。她的研究兴趣包括金融衍生品、数理金融和实证资产定价等。论文已发表在Journal of Futures Markets, Pacific-Basin Finance Journal, Economic Modelling等国际期刊上。   下一条：李安民经济研究院政策讲座系列 AI in Finance: The Current Status and Future Directions var pre = document.getElementById("pre").value; if(pre.indexOf("../")>-1) { document.getElementById("preurl").href=pre.replace("../",""); }else{ document.getElementById("preurl").href=pre; } var next= document.getElementById("next").value; if(next.indexOf("../")>-1) { document.getElementById("nexturl").href=next.replace("../",""); }else{ document.getElementById("nexturl").href=next; }