The Initial Public Offering Quandary: Is There a State and Time Dependency?

Sacred Heart University

Jack Welch College of Business & Technology

Doctor of Business Administration in Finance Program

Doctoral Dissertation Paper

The Initial Public Offering Quandary: Is There a State and Time Dependency?

Michael D. Herley

Date of award: May 13th, 2021


An entrepreneur or private-equity-backed firm’s decision to pursue an initial public offering (IPO) is a complex process that can lead to many sleepless nights for company founders. Nevertheless, there is a pathway to going public for most companies. Understanding the critical drivers of IPOs and how they react under different conditions or states should be of paramount concern to those considering an IPO and their advisors. Using a monthly net IPO volume series for Amex-, NYSE-, and Nasdaq-listed stocks for the period 1990–2019, my results suggest the interplay of the VIX Index and Wilshire 5000 returns, along with IPO lagged values, promote both state and time dependency in the IPO market. My dissertation takes a fresh approach to the IPO quandary, leveraging a series of stochastic and nonstochastic, nonparametric models, including threshold autoregressive, self-exciting threshold autoregressive, logistic smooth threshold autoregressive, and Markov switching. A five-regime threshold autoregressive model yields the best out-of-sample forecast performance of all the models tested, with a 1-month lag of the VIX Index’s monthly average as the switching variable. A two-state Markov-switching model reveals a high degree of instability in the IPO market up to October 2000. Since then, there has been a clear, well-defined one-state pattern of IPO activity.

Keywords: IPOs, regime-switching models, Markov switching, time-series forecasting

JEL classification: G17, G24, G32, C52, C32


Initial public offerings (IPOs) continue to play a critical role in the capital markets1 and the overall economy. With the total number of IPOs2 remaining considerably below historic levels, developing a more thorough understanding of their drivers and how they vary under different conditions could benefit market participants and regulators. In this dissertation, I consider the relevant academic literature and extend the paradigm that stock market growth positively influences IPO activity, and market volatility tempers IPO volume—while also accounting for the present instability in the data through a regime-switching3 approach.

I will show that the interplay of the Chicago Board Options Exchange Volatility Index (VIX Index) and the Wilshire 5000 Total Market Index (Wilshire 5000 Index) returns, along with lagged IPO values, create both state and time dependency in the IPO market. These intertemporal results are meaningful for investment bankers, academic scholars, law firms, and professional investors participating in the IPO market.

Each of these constituencies should find the time-varying and state-dependent nature of IPOs meaningful and, subsequently, consider factoring this information when making recommendations on new equity issues to their clients. Government regulators, policy experts, and political leaders interested in reenergizing the IPO market should also pay particular interest to these findings.

As Hansen (2001 p. 127) inquired in his seminal study on the importance of identifying and understanding the impact of structural breaks on time-series data, “Is this break permanent or transitory?” My research aims to shed new light on the IPO market by addressing such questions.

An entrepreneur or private-equity-backed firm’s decision to pursue an IPO is complicated. The IPO process officially begins in the public arena by filing the S-1 registration statement with the Securities and Exchange Commission (SEC). Once this happens, market anticipation begins to build, and so does a company’s anxiety. Company executives must follow strict guidelines about what they can and cannot say during the period leading up to the IPO, formally known as the quiet period.4 Investor demand and the broader market outlook are two significant and interrelated drivers of IPO activity. Conversely, when the equity markets become unsettled, and the investor fear index, formally known as the VIX Index, spikes, the IPO window can close abruptly for companies.

IPO activity is essential to the equity markets because institutional and retail investors depend on an ample supply of newly public companies to replace firms delisted because of a bankruptcy, a merger or acquisition, or a go-private transaction.5 Today in the United States, there are significantly fewer public companies than 20 years ago, which means more private companies do not follow the regular cycle of public disclosures required by the SEC. And although a U.S. public corporation today may not be a perfect model of transparency, it does provide a significantly higher level of financial information than most private companies.

The Wilshire 5000 Index, which measures the equity performance of all publicly traded companies in the United States, ballooned to 7,562 companies by July 31, 1998. As of December 31, 2019, the Wilshire had only 3,473 members—a decline of 54.073% from its peak. On a per- capita basis, only 11 publicly listed companies operated for every million residents in the United States through 2016, down from 23 companies in 1976 (Stulz, 2018). According to Stulz, this percentage decline puts the United States only slightly ahead of Venezuela among countries that have seen a decline in their equity listings.

The decline in IPO volume presents a challenge for those looking to save for retirement because an increasing percentage of retirement assets in the United States are held in defined contribution accounts that invest primarily in equity-based mutual funds. By definition, having fewer publicly traded companies means it is more difficult for individual investors to diversify the equity holdings in their retirement portfolios because professional money managers must choose from among a smaller investment pool.

Companies going public today are also more mature than those that have gone public in the recent past. A Wall Street Journal article on IPOs from 2019 cited research from IPO scholar Jay Ritter (n.d.) on how the median age of technology companies going public in 2018 was 12 years, compared with 4 or 5 years in 1999 and 2000 (Cimilluca, 2019). Thus, stock market investors today have access to fewer high-growth companies. Given the convergence of these factors, it is no surprise that both individual investors and public pension funds (which serve public school teachers, police officers, firefighters, etc.) have needed to temper their expected return assumptions in recent years.

A contributing factor to the drop-off in public companies may be that technology firms, rich with intangible assets, prefer to stay private longer, so they need not disclose confidential information to competitors in required filings (Stulz, 2019). Concurrently, technology firms benefit from private capital and the “specialized knowledge” they bring as investors during the early growth phase compared with investors in a traditional public company (Stulz, 2019).

Scholars have studied IPOs extensively over the past two decades, with many analyzing why IPO activity has declined from previous levels, particularly compared with those in the 1990s. Indeed, a Google Scholar search of the term “initial public offerings” on January 3, 2021, for the period 1999–2019, yielded 23,600 results. Numerous papers have explored whether the decline in IPO volume results from market regulations such as the Sarbanes–Oxley Act of 2002 (Sarbanes–Oxley) or deregulation such as the National Securities Markets Improvement Act (NSMIA) of 1996, which increased the supply of private equity capital. Other researchers have contended the decline is the result of weak investor demand in the market.

My dissertation takes a novel approach to reexamine IPO activity through a series of stochastic and nonstochastic, nonparametric models, including threshold autoregressive (TAR), self-exciting threshold autoregressive (SETAR), logistic smooth threshold autoregressive (LSTAR)–first order, and Markov switching (MS). I will show that IPO activity varies according to equity returns, market volatility, and previous IPO levels while responding differently under statistically determined regimes that create both state and time dependency. According to M. Marchese, personal communication from, March 29, 2021:

[in] finance, we care not just for modeling the relationships among variables/quantities but also about forecasting the target quantities (not only conditional mean returns but also variances or correlations). If, and when, such relationships are subject to instability over time, then such instability needs to be modeled and predicted. Regime switching models are a set of relatively recent and innovative statistical tools that are used to detect and predict instability (the discontinuities referred to above) in statistical relationships.

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1 Some authors have suggested that what happens in the IPO market is a “leading indicator” of the financial markets (Beaulieu & Bouden, 2015).

2 Consistent with other studies, I focus on net IPOs, which excludes closed-end funds, real estate investment trusts (REITs), acquisition companies, offer prices below $5, American depositary receipts (ADRs), limited partnerships, units, banks, and savings and loans (S&Ls).

3 Merriam-Webster’s dictionary has multiple definitions for the word “regime,” which broadly fall into two categories: (1) “a government in power” and (2) “the characteristic behavior or orderly procedure of a natural phenomenon or process.” When thinking about “regime-shifting” models to describe IPO behavior, I mean an equation that follows an orderly process of moving from one state of IPO activity to another state of activity. More specifically, a regime shift will typically mean moving from a “lower” state of IPO activity to a “higher” state, or vice versa. I would like to thank Hamaker et al. (2010) for providing a similar analogy in their paper “Regime-Switching Models to Study Psychological Processes,” which helped shape my explanation here.

4 Please see Latham & Watkins LLP’s US IPO Guide (2020) for a thorough discussion of communications allowed during the IPO quiet period.

5 According to Doidge et al. (2017), publicly listed firms delist for three primary reasons: (a) they no longer meet the exchange’s listing requirements, (b) they were acquired, or (c) they decided to delist voluntarily.

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Michael D. Herley