Nanyang Business School Forum on Risk Management and Insurance
In January of 2016, China’s State Council announced the merger of the nation’s two major health insurance programs for low-income residents – the New Cooperative Medical Scheme (NCMS), which serves rural citizens, and the Urban Residents’ Basic Medical Insurance system (URBMI), which serves city dwellers – into the newly created Urban and Rural Residents’ Basic Medical Insurance (URRBMI) system. Like its two predecessor organizations, the URRBMI is a microinsurance facility organized by China’s central and provincial governments (see Wang et al., 2014, and Zhu et al., 2017).
The measurement of firm performance is central to the business research. Previous studies have demonstrated that emphasis on purely financial measures (e.g. return on equity) may overlook a firm’s competitive advantage embedded in its efficiency in transforming resources (Chen, Delmas, and Lieberman, 2015). Frontier efficiency measures reveal this productive dimension and thus constitute an important element of overall firm performance. With the two measures of different focuses, an important question is to what extent a firm’s efficiency in converting inputs to outputs translates into its financial profit. In other words, what is the link between what firms do (efficiency) and what their shareholders get (profitability)? The intention of this paper is to analyze the alignment and differences between the frontier efficiency and financial profitability measures.
Over the last several decades, institutional investors (e.g., mutual funds and pension funds) have come to dominate global financial markets. Collectively, institutional investors are the majority shareholders of most publicly-traded companies. As a result, institutional investors have been playing an increasingly significant role in almost all aspects of financial markets. An interesting question that naturally arises is: what role do institutional investors play during financial market crises caused by catastrophic events? Are they sophisticated investors who provide a “steady hand” in stabilizing financial markets, or do they “panic” like many retail investors and thereby exacerbate such crises? This is an important research question with relevant practical and policy implications.
Is financial system’s interconnectedness a leading factor for the 2008 global financial crisis? This question has sparked a wide range of interest from academics to policymakers. On one hand, a highly connected financial system has been argued to be robust to financial crises due to its co-insurance for each individual bank (Allen and Gale, 2000; Freixas et al., 2000). On the other hand, recent papers argued that the relationship between the banking system’s interconnectedness and the financial stability is not monotonic because the interlinkages also pose a propagation risk (Gai et al., 2011; Acemoglu et al., 2015).
It is widely known that credit risk alone cannot explain corporate yield spreads. For instance, Collin-Dufresne, Goldstein, and Martin (2001) and Huang and Huang (2012) show that credit risk only accounts for a small fraction of the observed yield spreads on investment-grade bonds and a larger fraction for speculative-grade bonds. A large number of papers have been dedicated to studying this issue and find that the nondefault component of yield spreads is mainly related to the illiquidity of corporate bonds (see, e.g., Longstaff, Mithal, and Neis (2005), Chen, Lesmond, and Wei (2007), Martell (2008)).
Investors, financial analysts, regulators, and other market participants generally agree on the necessity of improving the quality of disclosures that firms make to the public about their exposures to market risk, including interest rate risk, foreign currency exchange rate risk, commodity price risk, equity price risk, and so on. Enhancing the quality of market risk disclosures should help investors improve the process of security valuation and analysis (CFA Institute 2016) and reduce investors’ panics and sensitive trading behaviors in response to unfavorable changes in market conditions (e.g., Rajgopal 1999; Linsmeier et al. 2002; Thornton and Welker 2004).
It have become increasingly commonplace to assume that risk aversion or investor mood evolves over time. In recent years, the VIX, typically referred to as the “fear index”, reached around 45 during the peak of the European Debt Crisis with fears of government defaults, remained low during the year of 2017 perhaps indicating investor complacency, and experienced a sharp jump likely associated with fears for higher future interest rates during early February 2018. The literature has agreed that changes in risk aversion are important determinant of asset price dynamics. However, the literature hasn’t reached an agreement on a reliable measure of market-wide or aggregate risk aversion. The main contribution of our paper is to develop a measure of time-varying risk aversion that is extracted from a wide information set of asset prices and macro data while simultaneously satisfying the asset pricing theory. This risk aversion index disentangles from macroeconomic uncertainty and can be obtained at high frequency, which constitutes its two clear advantages.
A short summary of the 2018 China International Risk Forum Keynote Speech “Old and New Thinking about the Role of Stocks in Defined Benefit Pension Plans” by Professor Deborah Lucas, MIT