CEO Network In Finance

This thesis examines how information flow among CEOs with social and professional connections affects firms and the market environment. Using biographical information about CEOs of U.S. public companies supplied by BoardEx from 2000-2016, the thesis relies on CEOs’ educational background, employment history and social activities (e.g., social clubs) to estimate the social and professional connections of CEOs as a measure of firms’ network size. The thesis then examines how networks among CEOs facilitate commonality in liquidity and commonality in asset growth among connected firms. The essay titled “CEO Connectedness and Commonality in Liquidity”, examines the effects of CEOs’ social and professional networks on stock liquidity commonality. We hypothesize that the stock liquidity of firms whose CEOs are connected will covary. In this essay, we uniquely construct our measure of commonality in stock liquidity among connected firms and provide strong evidence supporting the hypothesis. Outcomes reveal that the more connections firms share with each other, the more their stock liquidity comove. The essay further tests channels through which CEOs social and professional networks drive commonality in stock liquidity across connected firms. Results indicate that similarity in corporate finance policies and trading activities across connected firms are two channels through which CEOs’ personal connections drive liquidity covariation. We address endogeneity concerns and provide results that demonstrate that the magnitude of stock liquidity covariation among connected firms reduces when a CEO dies. The essay titled “CEO Peer Effects and Commonality in Asset Growth”, sought to investigate whether educational, social and professional networks among CEOs affect managerial asset growth decisions. We hypothesize that the asset growth rate of firms whose CEOs are connected will comove because of group thinking and peer influence. Using biographical information regarding CEOs of U.S. public firms from 2000 – 2016, the results suggest that CEO connectedness facilitates asset growth covariation. We conclude that a CEO is more likely to increase assets if peers in the network have recently done so leading to asset growth covariation across connected firms. Next, we test for channels through which CEOs’ connections may drive asset growth commonality across connected firms. The results reveal that commonality in asset growth decisions among connected firms stems from two possible channels: the adoption of related acquisition and research and development investment strategies. On the economic benefits of commonality in asset growth to shareholders, results show that commonality in asset growth across connected firms affects shareholders negatively. On endogeneity, tests indicate that the death of a CEO significantly reduces the extent of asset growth comovement between connected firms.Thesis (Ph.D.) -- University of Adelaide, Business School, 201

Financial stress spillover across Asian Countries.

This paper uses fractional integration techniques to explore the stochastic properties of the Financial Stress Indices (FSIs) of 10 Asian countries, further investigating the bilateral linkages between them to ascertain how financial stress spreads among countries in the region. For the FSIs of each country, the results show that all the estimated orders of integration are in the interval (0, 1) implying fractional integration and a long memory pattern. Thus, shocks will have transitory though long‐lasting effects. For the cross‐country spillovers of the FSIs, we find that convergence is satisfied in all cases with values of the differencing parameter around 0 and thus showing short memory behavior. It is worth noting that for the larger economies in the region, Japan and China, financial stress transmission between Japan and the smaller economies was faster than with respect to China. Overall, the results provide valuable information on the financial market activity of the countries in the region. To check for the robustness of the baseline results we also use systemic risk measures for these countries, CoVaR with the results showing evidence of fractional integration for the individual series, with all values of the differencing parameter in the range (0, 1). For convergence, there is a substantial reduction in the degree of integration, though the results are not as clear as with the FSIs.pre-print412 K

Volatility persistence in cryptocurrency markets under structural breaks.

This paper deals with the analysis of volatility persistence in 12 main cryptocurrencies (Bitcoin, Bitshare, Bytecoin, Dash, Ether, Litecoin, Monero, Nem, Ripple, Siacoin, Stellar and Tether) taking into account the possibility of structural breaks. Using fractional integration methods, the results indicate that both absolute and squared returns display long memory features, with orders of integration confirming the long memory hypothesis. However, after accounting for structural breaks, we find a reduction in the degree of persistence in the cryptocurrency market. The evidence of persistence in volatility imply that market participants who want to make gains across trading scales need to factor the persistence properties of cryptocurrencies in their valuation and forecasting models since that will help improve long-term volatility market forecasts and optimal hedging decisions.pre-print532 K

Cryptocurrencies and stock market indices. Are they related?

In this paper, we investigate the stochastic properties of six major cryptocurrencies and their bilateral linkages with six stock market indices using fractional integration techniques. From the univariate analysis, we observe that for Bitcoin and Ethereum, the unit root null hypothesis cannot be rejected; for Litecoin, Ripple and Stellar, the order of integration is found to be significantly higher than 1; for Tether, however, we find evidence in favour of mean reversion. For the stock market indices, the results are more homogeneous and the unit root cannot be rejected in any of the series, with the exception of VIX where mean reversion is obtained. Concerning bivariate results within the cryptocurrencies and testing for cointegration, we provide evidence of no cointegration between the six cryptocurrencies. Along the same lines, testing for cointegration between the cryptocurrencies and the stock market indices, we find evidence of no cointegration, which implies that the cryptocurrencies are decoupled from the mainstream financial and economic assets. The findings in this paper indicate the significant role of cryptocurrencies in investor portfolios since they serve as a diversification option for investors, confirming that cryptocurrency is a new investment asset class.pre-print394 K

Measuring volatility persistence in leveraged loan markets in the presence of structural breaks.

This paper examines volatility persistence in leverage loan market price series for Australia, Canada, Europe, Japan, Singapore, UK and USA in the presence of structural breaks. To the best of our knowledge, this is the first empirical study to examine volatility persistence in the leveraged loan markets. To this end, using fractional integration methods, the results indicate that both absolute and squared returns display long memory features, with orders of integration confirming the long memory hypothesis. However, after accounting for structural breaks, we find a reduction in the degree of persistence in the leveraged loan market. The evidence of persistence in volatility implies that market participants who want to make gains across trading scales need to factor the persistence properties of leveraged loan price series in their valuation and forecasting models since that will help improve long-term volatility market forecasts and optimal hedging decisions.post-print759 K

A New Look at the Connectedness Between Energy and Metal Markets Using a Novel Approach

This study extends the existing literature in this area by examining the conditional connectedness between energy and metal markets using a novel time-varying quantile and frequency connectedness method developed by Chatziantoniou, et al. (2022) based on Ando, et al. (2018) and Barunik & Krehlik (2018) techniques. Connectedness between the markets was analyzed across various times and frequencies, with daily data covering May 18, 2011, to September 23, 2020. Short-term dynamics strongly drive the total pairwise shocks, while the contribution of medium-term dynamics was meagre, and that of long-term dynamics was insignificant. While the natural gas, gasoline, gas oil, heating oil, crude oil, coal, kerosene, propane, and diesel markets spilled-out shocks to many markets, gold, copper, aluminum, platinum, silver, nickel, palladium and lead markets received shocks from many markets. Zinc appears as an isolated market. The market which influenced the majority of other markets is natural gas, followed by gasoline, gas oil, heating oil, crude oil, coal, kerosene, propane and diesel. In contrast, zinc did not influence any of the markets. The pairwise connectedness results reveal the existence of intra-market linkages within the energy markets (horizontal market integration), while inter-market associations also exist between energy and metal markets (vertical market integration). However, there are only intra-market linkages in the metal markets. Linkages are strong in some markets during the COVID-19 crisis. These results inform some policy recommendations well-articulated in the conclusion section

Re-examination of risk-return dynamics in international equity markets and the role of policy uncertainty, geopolitical risk and VIX: Evidence using Markov-switching copulas.

This study re-examines the empirical relationship between risk and return from 1994m12 to 2020m08 in fifteen international equity markets employing the novel time-varying Markov switching copula models. We provide first-time insightful evidence of time-varying Markov tail dependence structure and dynamics between risk and return in international equity markets. Results show that the dependence structure is positive for USA, UK, Germany, Italy, Brazil, Australia, Taiwan, Canada, Mexico, Japan, France and South Africa and negative for Singapore, India, Japan and China. Finally, we document the effects of policy uncertainty, geopolitical risk and VIX conditional on different markets states.post-print433 K

Factors behind the performance of green bond markets.

The market for green bonds has grown dramatically over the past several years, necessitating an understanding of the variables that might forecast its performance. Studies on how the green bond market interacts with other markets are widely discussed in the literature, but little is known about the variables that improve predictions of green bond returns. In this study, we use data on commodity and financial asset prices, as well as speculative factors, to predict the returns on green bonds using the Feasible Quasi-Generalized Least Squares (FQGLS) and the causality-in-quantiles estimators. The findings demonstrate that most factors are significant predictors of the returns on green bonds, with speculative factors having a detrimental predictive influence, and commodity and financial asset prices having a mixed predictive impact. When asymmetries are taken into account, the asymmetric predictive model performs better at predicting the returns on green bonds than its symmetric counterpart in most instances. Finally, all the factors, except investors' sentiment, affect the returns on green bonds in a variety of market situations. The interdependence among the global financial and commodity markets, as well as economic uncertainties justify the established predictive influence, since green bonds are a component of the broader investment bonds.post-print893 K

Factors behind the performance of green bond markets

The market for green bonds has grown dramatically over the past several years, necessitating an understanding of the variables that might forecast its performance. Studies on how the green bond market interacts with other markets are widely discussed in the literature, but little is known about the variables that improve predictions of green bond returns. In this study, we use data on commodity and financial asset prices, as well as speculative factors, to predict the returns on green bonds using the Feasible Quasi-Generalized Least Squares (FQGLS) and the causality-in-quantiles estimators. The findings demonstrate that most factors are significant predictors of the returns on green bonds, with speculative factors having a detrimental predictive influence, and commodity and financial asset prices having a mixed predictive impact. When asymmetries are taken into account, the asymmetric predictive model performs better at predicting the returns on green bonds than its symmetric counterpart in most instances. Finally, all the factors, except investors' sentiment, affect the returns on green bonds in a variety of market situations. The interdependence among the global financial and commodity markets, as well as economic uncertainties justify the established predictive influence, since green bonds are a component of the broader investment bonds

Re-examination of international bond market dependence: Evidence from a pair copula approach

The finance literature provides substantial evidence on the dependence between international bond markets across developed and emerging countries. Early works in this area were based on linear models and multivariate GARCH models. However, based on the limitations of these models this paper re-examines the non-linearity, multivariate and tail dependence structure between government bond markets of the US, UK, Japan, Germany, Canada, France, Italy, Australia and the Eurozone, from January 1970 to February 2019 using ARMA-GARCH based pair- copula models. We find that the bond markets in our sample tend to have both upper tail dependence in terms of positive shocks and lower tail dependence in terms of negative shocks. The estimated C-vine shows Eurozone has the highest average dependency. The D-vine, with optimal chain dependency structure shows the best order of connectedness to be the UK, the USA, Italy, Japan, Eurozone, France, Canada, Germany and Australia. The R-vine copula results underline the complex dynamics of bond market relations existing between the selected economies. The estimated R-vine shows Eurozone, Germany and Australia are the most inter-connected nodes. The multivariate distribution structure (interdependency) of bond markets for all countries were modelled with the C-vine, D-vine and R-vine copulas. In this application, the R-vine copula allows for detailed modelling of all bond markets and hence provides a more accurate goodness of fit and mean square error for the interdependency between all markets. In light of the changing volatility in bond markets, we conduct additional tests using time-varying copulas and find that the dependence structure among the bond markets examined is time-varying with the dynamic dependence parameter plots revealing that the nature of the dependence structure is intense during crisis periods