The scope of this paper is to contribute to the question of delisting (both voluntary and involuntary), with particular emphasis on the initial conditions leading up to the Initial Public Offering (IPO) of the firms. ...The scope of this paper is to contribute to the question of delisting (both voluntary and involuntary), with particular emphasis on the initial conditions leading up to the Initial Public Offering (IPO) of the firms. The case of Athens Stock Exchange (ASE) is examined, specifically the IPOs of years 1996-2004 and their subsequent performance (delisting or not) till the end of 2017. We find that the probability of delisting is positively associated with the size of the issuance and the degree of earnings’ manipulation and negatively associated with audit quality, information transparency, and market timing. The effects of audit quality, size of issuance, and earnings’ manipulation are accentuated in instances of voluntary delisting while the effect of market timing is more clearly pronounced in instances of involuntary delisting. Our results are robust to a number of confounding factors including size, profitability, leverage, liquidity, growth options, and corporate governance. Our work is not replication of existing studies;in addition, we choose ASE as in that capital market there were many delistings the last two decades.展开更多
Ever since the appearance of"Implementation Measures for Suspending and Terminating the Listing of Loss-making Companies"in 2001,the delisting system has emerged.However,the proportion of delisted companies ...Ever since the appearance of"Implementation Measures for Suspending and Terminating the Listing of Loss-making Companies"in 2001,the delisting system has emerged.However,the proportion of delisted companies in China has never exceeded 1% each year.The number of delisted companies in the security market is far less than the number of companies with financial distress.The capital market lacks a good delisting system and investors lack risk identification capabilities.Financial risk is directly related to delisting risk.Therefore,an early warning model of financial distress prediction for China.s stock market can provide guidance to stakeholders such as listed companies and capital markets.This paper first explains the immature delisting system of China.s capital market and the overall high risk of listed companies.financial distress.Then,the paper further elaborates previous research on financial distress prediction model of listed companies and analyzes the advantages and disadvantages of different models.This paper chooses the Analytic Hierarchy Process(AHP)to screen out the main factors that affect the risk of financial distress.The main factors are included in Logistic regression model and BP neural network model for predicting financial distress of listed companies.The overall effect of two models are assessed and compared.Finally,this paper proposes policy implications according to empirical results.展开更多
文摘The scope of this paper is to contribute to the question of delisting (both voluntary and involuntary), with particular emphasis on the initial conditions leading up to the Initial Public Offering (IPO) of the firms. The case of Athens Stock Exchange (ASE) is examined, specifically the IPOs of years 1996-2004 and their subsequent performance (delisting or not) till the end of 2017. We find that the probability of delisting is positively associated with the size of the issuance and the degree of earnings’ manipulation and negatively associated with audit quality, information transparency, and market timing. The effects of audit quality, size of issuance, and earnings’ manipulation are accentuated in instances of voluntary delisting while the effect of market timing is more clearly pronounced in instances of involuntary delisting. Our results are robust to a number of confounding factors including size, profitability, leverage, liquidity, growth options, and corporate governance. Our work is not replication of existing studies;in addition, we choose ASE as in that capital market there were many delistings the last two decades.
文摘Ever since the appearance of"Implementation Measures for Suspending and Terminating the Listing of Loss-making Companies"in 2001,the delisting system has emerged.However,the proportion of delisted companies in China has never exceeded 1% each year.The number of delisted companies in the security market is far less than the number of companies with financial distress.The capital market lacks a good delisting system and investors lack risk identification capabilities.Financial risk is directly related to delisting risk.Therefore,an early warning model of financial distress prediction for China.s stock market can provide guidance to stakeholders such as listed companies and capital markets.This paper first explains the immature delisting system of China.s capital market and the overall high risk of listed companies.financial distress.Then,the paper further elaborates previous research on financial distress prediction model of listed companies and analyzes the advantages and disadvantages of different models.This paper chooses the Analytic Hierarchy Process(AHP)to screen out the main factors that affect the risk of financial distress.The main factors are included in Logistic regression model and BP neural network model for predicting financial distress of listed companies.The overall effect of two models are assessed and compared.Finally,this paper proposes policy implications according to empirical results.
