Ambiguity and risk factors in bank stocks

The determinants of banks' cost of equity are not well understood. We depart from prior work assuming rational expectations and instead explore the impact of Knightian uncertainty or ambiguity on bank stocks. We test a large set of asset pricing models and find that investors' lack of confidence in both the drift and correlation structure driving bank stock returns affects banks' cost of capital. We also investigate the economic relation among ambiguity, market liquidity, and banks' capital shortfall, which reveals the transmission channels through which ambiguity may increase the probability of a systemic crisis. Our findings have implications for macroprudential policy.     

Dynamic volatility spillovers across oil and natural gas futures markets based on a time-varying spillover method

This paper analyzes dynamic volatility spillovers between four major energy commodities (i.e., crude oil, gasoline, heating oil and natural gas) in the oil-natural gas future markets. We construct a time-varying spillover method by combining the TVP-VAR-SV model and the spillover method of Diebold and Yilmaz (2009, 2012, 2014). We use the spillover method to obtain time-varying total, directional and pairwise volatility spillover indices. Our results summarize as follows: (1) The volatility spillover indices present peaks and troughs during some periods, such as shale gas revolution, financial crisis, and oil price crash; (2) After the U.S. shale gas revolution, the size of volatility spillover from natural gas future market has reduced sharply, but volatility doesn't decouple from the other three oil future markets; (3) The directional spillover is asymmetric. The crude oil and heating oil futures market are main net transmitter of volatility risk information, while the gasoline and natural gas futures markets are the net receiver; (4) For natural gas future market, the pairwise volatility spillover from crude oil future market has the most significant influence.     

Is there a CSI-leverage nexus?

We examine how various measures of consumer sentiment index (CSI) affect firms' debt policy decisions. Using U.S. firm-level quarterly data from 1993 to 2017, we provide a strong positive relationship between CSI measures and corporate debt policy, implying that firms use external borrowing during a positive economic outlook and reap the tax-shield benefit. We also find that improved household optimism over financial and business sentiments leads to future household consumption. The CSI-leverage nexus is moderated by the state of firms' financial condition, reputation, and profitability. Importantly, our results are robust to sub-sample analysis, firm-level and macroeconomic controls, econometric specifications, alternative measures of sentiment including Shiller's cyclically adjusted price-earnings ratio (i.e., CAPE_SH), Baker and Wurgler (2006)’s stock market sentiment index (i.e., SENT_BW) and search-based uncertainty measure such as FEARS (i.e., Financial and Economic Attitudes Revealed by Search) index of Da, Engelberg, and Gao (2015).     

Systemic Bank Risk in Brazil: A Comprehensive Simulation of Correlated Market, Credit, Sovereign and Inter-Bank Risks

In this study we present a comprehensive forward‐looking portfolio simulation methodology for assessing the correlated impacts of market risk, private sector and Sovereign credit risk, and inter‐bank default risk. In order to produce better integrated risk assessment for banks and systemic risk assessments for financial systems, we argue that reasonably detailed modeling of bank asset and liability structures, loan portfolio credit quality, and loan concentrations by sector, region and type, as well as a number of financial and economic environment risk drivers, is required. Sovereign and inter‐bank default risks are increasingly important in the current economic environment and their inclusion is an important model extension. This extended model is demonstrated through an application to both individual Brazilian banks (i.e., 28 of the largest banks) and groups of banks (i.e., the Brazilian banking system) as of December 2004. When omitting Sovereign risk, our analysis indicates that none of the banks face significant default risk over a 1‐year horizon. This low default risk stems primarily from the large amount of government securities held by Brazilian banks, but also reflects the banks' adequate capitalizations and extraordinarily high interest rate spreads. We note that none of the banks which we modeled failed during the very stressful 2007‐2008 period, consistent with our results. Our results also show that a commonly used approach of aggregating all banks into one single bank, for purposes of undertaking a systemic banking system risk assessment, results in a misestimate of both the probability and the cost of systemic banking system failures. Once Sovereign risk is considered and losses in the market value of government securities reach 10% (or higher), we find that several banks could fail during the same time period. These results demonstrate the well known risk of concentrated lending to a borrower, or type of borrower, which has a non‐zero probability of default (e.g., the Government of Brazil). Our analysis also indicates that, in the event of a Sovereign default, the Government of Brazil would face constrained debt management alternatives. To the best of our knowledge no one else has put forward a systematic methodology for assessing bank asset, liability, loan portfolio structure and correlated market and credit (private sector, Sovereign, and inter‐bank) default risk for banks and banking systems. We conclude that such forward‐looking risk assessment methodologies for assessing multiple correlated risks, combined with the targeted collection of specific types of data on bank portfolios, have the potential to better quantify overall bank and banking system risk levels, which can assist bank management, bank regulators, Sovereigns, rating agencies, and investors to make better informed and proactive risk management and investment decisions.     

Local and spillover shocks in implied market volatility: evidence for the U.S. and Germany

The occurrence and the transmission of large shocks in international equity markets is of essential interest to the study of market integration and financial crises. To this aim, implied market volatility allows to monitor ex ante risk expectations in different markets. We investigate the behavior of implied market volatility indices for the U.S. and Germany under a straightforward mean reversion model that allows for Poisson jumps. Our empirical findings for daily data in the period 1992 to 2002 provide evidence of significant positive jumps, i.e. situations of market stress with positive unexpected changes in ex ante risk assessments. Jump events are mostly country-specific with some evidence of volatility spillover. Analysis of public information around jump dates indicates two basic categories of events. First, crisis events occurring under spillover shocks. Second, information release events which include three subcategories, namely—worries about as well as actual—unexpected releases concerning U.S. monetary policy, macroeconomic data and corporate profits. Additionally, foreign exchange market movements may cause volatility shocks.     

Interest Rate Risk at Commercial Banks: An Empirical Investigation

This paper develops and estimates models to measure banks' exposure to interest rate risk. The models are estimated for the 1976–1983 period to determine whether banks' exposure to interest rate risk increased as a result of increased interest rate volatility and financial deregulation. The major findings are that banks changed their risk management strategies after 1979 and that total exposure to interest rate risk remained quite small.     

The determinants of the model-free positive and negative volatilities

In this paper we analyze the role of macroeconomic and financial determinants in explaining stock market volatilities in the U.S. market. Both implied and realized volatility are computed model-free and decomposed into positive and negative components, thereby allowing us to compute directional volatility risk premia. We capture the behaviour of each component of implied volatility and risk premium in relation to their different determinants. The negative implied volatility appears to be linked more towards financial conditions variables such as uncertainty and geopolitical risk indexes, whereas positive implied volatility is driven more by macro variables such as inflation and GDP. There is a clear shift in importance from macro towards financial determinants moving from the pre towards the post financial crisis. A mixed frequency Granger causality approach uncovers causality relationships between volatilities and risk premia and macro variables and vice versa, a finding which is not detected with a conventional low frequency VAR model.     

How the Subprime Crisis went global: Evidence from bank credit default swap spreads

How did the Subprime Crisis, a problem in a small corner of U.S. financial markets, affect the entire global banking system? To shed light on this question we use principal components analysis to identify common factors in the movement of banks' credit default swap spreads. We find that fortunes of international banks rise and fall together even in normal times along with short-term global economic prospects. But the importance of common factors rose steadily to exceptional levels from the outbreak of the Subprime Crisis to past the rescue of Bear Stearns, reflecting a diffuse sense that funding and credit risk was increasing. Following the failure of Lehman Brothers, the interdependencies briefly increased to a new high, before they fell back to the pre-Lehman elevated levels – but now they more clearly reflected heightened funding and counterparty risk. After Lehman's failure, the prospect of global recession became imminent, auguring the further deterioration of banks' loan portfolios. At this point the entire global financial system had become infected.     

Noninterest Income and Financial Performance at U.S. Commercial Banks

Noninterest income now accounts for over 40% of operating income in the U.S. commercial banking industry. This paper demonstrates a number of empirical links between bank noninterest income, business strategies, market conditions, technological change, and financial performance between 1989 and 2001. The results indicate that well‐managed banks expand more slowly into noninterest activities, and that marginal increases in noninterest income are associated with poorer risk‐return tradeoffs on average. These findings suggest that noninterest income is coexisting with, rather than replacing, interest income from the intermediation activities that remain banks' core financial services function.     

Financial structure change and banking income: A Canada–U.S. comparison

Data suggest that the Canadian financial structure, and particularly indirect finance (e.g., banking), have become more market-oriented. We associate this financial trend in part with the regulatory changes that have occurred in Canada since the 1980s. Financial intermediaries are increasingly involved with financial market activities—e.g. off-balance sheet (OBS) activities such as underwriting securities. In this article we analyze the noninterest income attributable to these financial market activities. We find that the variance of Canadian banks’ aggregate operating-income growth is rising because of the increased contribution of noninterest income. Overall, our analysis corroborates the U.S. findings of Stiroh and Rumble (Stiroh, K., 2006. A portfolio view of banking with interest and noninterest assets. Jounal of Money, Credit, and Banking 38, 1351–1361; Stiroh, K., Rumble, A., 2006. The darkside of diversification: the case of U.S. financial holding companies. Journal of Banking and Finance 30, 2131–2161): by contributing to banking income volatility, market-oriented activities do not necessarily yield straightforward diversification benefits to Canadian banks.     

波动溢出网络视角的金融风险传染研究

当前各类经济风险交叉关联,金融系统的风险溢出效应备受关注,为刻画我国金融系统性风险传染的路径特征,本文从波动溢出网络的视角分析金融系统内部的风险传染机制。首先使用广义动态因子模型对收益波动的共同波动率成分和特质性波动率成分进行区分。然后,根据货币市场、资本市场、大宗商品交易市场、外汇市场、房地产市场和黄金市场之间的特质性波动溢出效应,利用基于TVP-VAR模型的方差分解溢出指数分析金融系统波动溢出的动态联动性和风险传递机制。在分析方向性波动溢出效应的基础上,采用方差分解网络方法构建起信息溢出复杂网络,从网络视角分析金融系统内部的风险传染特征。实证研究发现,房地产市场和外汇市场的净溢出效应绝对值相较于其他市场更大,其受其他市场风险冲击的影响强于对外风险溢出效应,而股票市场的单向对外风险溢出效应强度最大。在波动溢出的基础上,进一步考虑股市波动率指数与其他市场波动率指数进行投资组合的资产配置权重,计算了波动率指数投资组合的最优组合权重和对冲策略。研究结论有助于更好地理解我国金融系统的风险传染机制,对监管机构加强宏观审慎监管、投资者规避投资风险具有重要意义。     

Financial Intermediaries and Interest Rate Risk: II

The current work extends and updates the previous survey ( Staikouras, 2003 ) by looking at other aspects of the financial institutions' yield sensitivity. The study starts with an extensive discussion of the origins of asset‐liability management and the subsequent work to identify effective ways of measuring and managing interest rate risk. The discussion implicates both regulatory and market‐based approaches along with any issues surrounding their applicability. The literature is enriched by recognizing that structural and regulatory shifts affect financial institutions in different ways depending on the size and nature of their activities. It is also noted that such shifts could change the bank's riskiness, and force banks to adjust their balance sheet size by altering their maturity intermediation function. Besides yield changes, market cycles are also held responsible for asymmetric effects on corporate values. Furthermore, nonstandard investigations are considered, where embedded options and basis risk are significant above and beyond the intermediary's rate sensitivity, while shocks to the slope of the yield curve is identified as a new variable. When the discount privilege is modeled as an option, it is shown that its value is incorporated in the equities of qualifying banks. Finally, volatility clustering is further established while constant relative risk aversion is not present in the U.S. market. Although some empirical findings may be quite mixed, there is a general consensus that all forms of systematic risk, risk premia, and the risk‐return trade‐off do exhibit some form of variability, not only over time but also across corporate sizes and segments.     

Forecasting global stock market volatilities in an uncertain world

We investigate the predictive relationship between uncertainty and global stock market volatilities from a high-frequency perspective. We show that uncertainty contains information beyond fundamentals (volatility) and strongly affects stock market volatility. Using several crucial uncertainty measures (i.e., uncertainty and implied volatility indices), we prove that the CBOE volatility index (VIX) performs best in point (density) forecasting; the financial stress index (FSI) in directional forecasting. Furthermore, VIX's predictive power improved dramatically after the COVID-19 outbreak, and the VIX-based portfolio strategy enables mean-variance investors to achieve higher returns. There are two empirical properties of VIX: (i) it helps reduce significantly forecast variance rather than bias; and (ii) its forecasts encompass other uncertainty forecasts well. Overall, we highlight the importance of considering uncertainty when exploring the expected stock market volatility.     

Option compensation,risky mortgage lending,and the financial crisis

We examine how option compensation affects banks' risky mortgage origination and sale decisions before the financial crisis in 2008. We find that, in the period immediately before the financial crisis, option compensation has little impact on the riskiness of mortgages originated and is negatively associated with mortgage lenders' propensity to sell risky mortgages. The results are consistent with banks' incentives to maximize revenues from origination and servicing fees while managing risk exposure by adjusting the sale of risky mortgages. For identification, we use bank-year fixed effects and matched loan applications to control for both supply- and demand-side factors of mortgage lending. We find similar results when using the variation in option compensation generated by the implementation of FAS 123R.     

Time-consistent reinsurance and investment strategies for an AAI under smooth ambiguity utility

This paper investigates time-consistent reinsurance(excess-of-loss, proportional) and investment strategies for an ambiguity averse insurer(abbr. AAI). The AAI is ambiguous towards the insurance and financial markets. In the AAI's attitude, the intensity of the insurance claims' number and the market price of risk of a stock can not be estimated accurately. This formulation of ambiguity is similar to the uncertainty of different equivalent probability measures. The AAI can purchase excess-of-loss or proportional reinsurance to hedge the insurance risk and invest in a financial market with cash and an ambiguous stock. We investigate the optimization goal under smooth ambiguity given in Klibanoff, P., Marinacci, M., & Mukerji, S. [(2005). A smooth model of decision making under ambiguity. Econometrica 73, 1849–1892], which aims to search the optimal strategies under average case. The utility function does not satisfy the Bellman's principle and we employ the extended HJB equation proposed in Björk, T. & Murgoci, A. [(2014). A theory of Markovian time-inconsistent stochastic control in discrete time. Finance and Stochastics 18(3), 545–592] to solve this problem. In the end of this paper, we derive the equilibrium reinsurance and investment strategies under smooth ambiguity and present the sensitivity analysis to show the AAI's economic behaviors.     

The trade war's impact on the financial market: Observations from the historical global trade war - the Smoot Hawley Tariff Act

This study examines financial market reactions to political events that led to the passage and repeal of the Smoot–Hawley Tariff Act (SHTA) from the perspective of political uncertainty. The events were a series of debates and votes held by the U.S. House and Senate before the SHTA was signed into law in 1930 and repealed in 1934. These events increase political uncertainty about trade policy, thereby creating a unique setting to measure the impact of political uncertainty on financial market reactions. We find that each event resulted in an average loss of 3.6% in the U.S. aggregate stock market over a [−1, +1] three-day window. Such negative returns were observed at the firm level. Moreover, we find that firms with higher tariff protection performed significantly better than firms with lower tariff protection on nonevent dates. Furthermore, we discovered that trading volumes were significantly higher on event dates than on nonevent dates. Stock return volatility was significantly higher during the entire debating and voting period than during the 12 months preceding its inception and 6 months following the SHTA's passage into law. However, higher tariff protection was associated with lower return volatility outside the event window. Our findings show that political uncertainty events commanded the risk premium.     

Why Are U.S. Stocks More Volatile?

U.S. stocks are more volatile than stocks of similar foreign firms. A firm's stock return volatility can be higher for reasons that contribute positively (good volatility) or negatively (bad volatility) to shareholder wealth and economic growth. We find that the volatility of U.S. firms is higher mostly because of good volatility. Specifically, stock volatility is higher in the United States because it increases with investor protection, stock market development, new patents, and firm‐level investment in R&D. Each of these factors is related to better growth opportunities for firms and better ability to take advantage of these opportunities.     

COVID-19 and A-share banks' stock price volatility: From the perspective of the epidemic evolution in China and the US

With a financial market dominated by indirect financing, China's banking system played a critical role in the government's response to COVID-19, which piqued our interest in the short-term impact of COVID-19 on the risk of China's banks. Examining the stock price of A-share listed banks and the number of confirmed cases in China and the US during the short time window surrounding the COVID-19 pandemic's outbreak, this study reveals that COVID-19 increased the A-share banking price volatility in both China and the US, reflecting a strong spillover effect of the US economic and financial system. Furthermore, COVID-19 in China has a smaller impact on the stock price volatility of China's state-owned banks (SOBs) than that of medium- and small-sized (M&S) banks, reflecting the higher risk resistance capability of large SOBs. Further analysis confirms that the impact primarily reflected systematic risk rather than idiosyncratic risk, as small and micro enterprises and M&S banks received more targeted financial support from the government. In contrast, large banks took on more responsibilities in the emergency financial stimulus, narrowing the idiosyncratic risk gap between the two types of banks and allowing the banking industry to better play its core role in the recovery of real economy in China. These findings will assist us in better understanding the effectiveness of financial assistance policies during the epidemic and will provide insights for future policymaking during similar crises.     

What drives U.S. financial sector volatility? A Bayesian model averaging perspective

We investigate the driving forces behind the quarterly stock price volatility of firms in the U.S. financial sector over the period from 1990 to 2017. The driving forces represent a set of 28 economic indicators that are routinely used to detect financial instability and crises and correspond to the development of the financial, monetary, real, trade and fiscal sector as well as to the development of the bond and equity markets. The dimensionality and model choice uncertainty are addressed using Bayesian model averaging, which led to the identification of only seven variables that tend to systematically drive the stock price volatility of financial firms in the U.S.: housing prices, short-term interest rates, net national savings, default yield spread, and three credit market variables. We also confirm that our results are not an artefact of volatility associated with market downturns (for negative semi-volatility), as the results are similar even when market volatility is associated with market upsurge (positive semi-volatility). Given the identified drivers, our results provide supporting empirical evidence that dampening credit cycles might lead to decreased volatility in the financial sector.     

Global financial crisis and emerging stock market contagion: A volatility impulse response function approach

By employing the volatility impulse response (VIRF) approach, this paper presents a general framework for addressing the extent of contagion effects between the BRICSs’ and U.S. stock markets and how the BRICSs’ stock markets have been influenced in the context of the 2007–2009 global financial crisis. Our empirical results show during the period of 2007–2009 global financial crisis, there are significant contagion effects from the U.S. to the BRICSs’ stock markets. Yet, the degree of stock market reactions to such shocks differs from one market to another, depending on the level of integration with the international economy. Besides, the strengthened degree of stock market integration among the U.S. and BRICS has adverse effect such that if the 2007–2009 global financial crisis occurs today it may result in heavier impact on stock market volatility nowadays compared to the crisis-era.