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The purpose of the study is to examine the zero-leverage (ZL) phenomenon in family and non-family firms.

The authors consider three hypotheses and empirically test them using a sample of the largest US firms over the 2001–2016 period.

The authors find that, on average, 19.20% of family firms have zero debt vs 10.42% for non-family firms. The authors also find that family firms strategically choose to be ZL to maintain financial flexibility for future investments and exercise control over the decision-making process, consistent with the hypotheses of financial flexibility and control considerations. However, non-family firms are more likely to have zero debt if they have financial constraints and the credit market does not lend them money at affordable credit rates, consistent with the financial constraint hypothesis.

This paper contributes to different strands of literature. First, the authors contribute to the literature examining family firms' financial decisions. Second, the authors complement previous studies by exploring the reasons for the ZL behavior of family firms compared to non-family firms. The authors also examine the previously unexplored impact of ownership concentration on the ZL question.

The purpose of this paper is to examine the possibility of creating hedge funds “clones” using liquid exchange traded instruments.

Authors analyze the performance of fixed weight and extended Kalman filter generated clone portfolios (EKF) for 14 hedge fund strategies from February 2004 to September 2009. EKF approach does not indeed impose any normality constraints on the error terms which allow the filter to find the optimal recursive process by itself. Such models could adjust even faster to sudden shifts in market conditions vs a standard Kalman filter.

For five strategies out of 14, this work finds that EKF clones outperform their corresponding indices. Thus, for certain strategies, the possibility of cloning hedge fund returns is indeed real. Results should be however considered with caution.

This paper suggests that the most important benefits of clones are to serve as benchmarks and to help investors to better understand the various risk factors that impact hedge fund returns.

Rather than using fixed‐weight and rolling windows approaches (as Hasanhodzic and Lo), this work considers an extended version of the Kalman filter, a computational algorithm that better captures the time changing dynamics of hedge fund returns. Also, in order to be practical, this research considers investable factors and that the models themselves could not be constant over time.

Purpose – Study the firm-level and country-level determinants of US institutional investors' holdings in American Depositary Receipts (ADRs) from emerging markets.

Methodology/approach – We use a sample of 112 firms from emerging markets that listed as ADRs between 1990 and 2005. Rather than adopting the issuer's perspective, we take in this study the point of view of the investor and we focus on the US institutional investors' participation in ADR firms.

Findings – We find that institutional investors hold higher stakes in foreign firms that are listed on more restrictive exchanges, in large, privatized, more liquid, and more transparent firms. Mutual investors and other institutional investors also prefer firms from countries with weaker institutional environments and from civil law legal tradition. Controlling for country-level determinants increases significantly the explanatory power of the model.

Social implications – Our results have important implications for firms from emerging markets seeking to attract foreign institutional investors.

Originality/value of the chapter – We focus on the motivations of investors when they choose to invest in the ADR, rather than on the ADR issuer motivation. In addition, we consider all types of institutional investors that acquire a participation in an ADR firm.

Institutional investors have increasingly gained importance since the early 1990s. The assets under management in these funds have increased threefold since 1990 to reach more than US$45 trillion in 2005, including over US$20 trillion in equity (Ferreira & Matos, 2008). Further, the value of institutional investors' assets represents roughly 162.6% of the OECD gross domestic product in 2005 (Gonnard, Kim, & Ynesta, 2008). Given the magnitude of institutional investors' holdings relative to the world market capitalization, challenging questions on the economic role of these investors have been raised. One such question concerns their impact on the stability of stock markets. On the one hand, active strategies of buying and selling shares by these investors may contribute to moving stock prices away from their fundamental values. On the other hand, if all institutional investors react to the same information in a timely manner, they are in fact helping to increase market efficiency by speeding up the adjustment of prices to new fundamentals (for competing theories on the role of institutional investors, see, e.g., Lakonishok, Shleifer, & Vishny, 1992). This view of institutional investors as “efficiency drivers” generated considerable debate for many years (see, e.g., Ferreira & Laux, 2007; French & Roll, 1986).

Forecasting the future movement of yield curves contains valuable information for both academic and practical issues such as bonding pricing, portfolio management, and government policies. The purpose of this paper is to develop a dynamic factor approach that can provide more precise and consistent forecasting results under various yield curve dynamics.

The paper develops a unified dynamic factor model based on Diebold and Li (2006) and Nelson and Siegel (1987) three-factor model to forecast the future movement yield curves. The authors apply the state-space model and the Kalman filter to estimate parameters and extract factors from the US yield curve data.

The authors compare both in-sample and out-of-sample performance of the dynamic approach with various existing models in the literature, and find that the dynamic factor model produces the best in-sample fit, and it dominates existing models in medium- and long-horizon yield curve forecasting performance.

The authors find that the dynamic factor model and the Kalman filter technique should be used with caution when forecasting short maturity yields on a short time horizon, in which the Kalman filter is prone to trade off out-of-sample robustness to maintain its in-sample efficiency.

Bond analysts and portfolio managers can use the dynamic approach to do a more accurate forecast of yield curve movements.

The enhanced forecasting approach also equips the government with a valuable tool in setting macroeconomic policies.

The dynamic factor approach is original in capturing the level, slope, and curvature of yield curves in that the decay rate is set as a free parameter to be estimated from yield curve data, instead of setting it to be a fixed rate as in the existing literature. The difference range of estimated decay rate provides richer yield curve dynamics and is the key to stronger forecasting performance.

The study examines the IPO resilience grounded on the firm’s intrinsic factors.

We examine the association of IPO performance and post-listing firm’s performance with issuers' pre-listing financial and qualitative traits using panel data regression.

IPOs floated in the Indian market from July 2009 to March 31, 2022, evince the notable influence of issuers' pre-IPO fundamentals and legitimacy traits on IPO returns and post-listing earning power. Where the pandemic’s favorable impact is discerned on the post-listing year earning power of the issuer firms, the loss-making issuers appear to be adversely affected by the Covid disruption. Perhaps, the successful listing equipped the issuers with the financial flexibility to combat market challenges vis-à-vis failed issuers deprived of desired IPO proceeds.

High initial returns followed by a declining pattern substantiate the retail investors to be less informed vis-à-vis initial investors, valuers and underwriters, who exit post-listing after profit booking. Investing in the shares of the newly listed ventures post-listing in the secondary market can shield retail investors from the uncertainty losses of being uninformed. The IPO market needs stringent regulations ensuring the verification of the listing valuation, the firm’s credentials and the intent of utilizing IPO proceeds. Healthy development of the IPO market merits reconsidering the listing of ventures with weak fundamentals suspected to withstand the market challenges.

Given the tremendous rise in the new firm venturing into the primary market and the spike in IPOs countering the losses immediately post-opening, the study examines the loss-making and young firms IPOs separately, adding novelty to the study.