Revisiting the risk-return relation in the Chinese stock market: Decomposition of risk premium and volatility feedback effect

The empirical results of the risk-return relationship are mixed for both mature and merging markets. In this paper, we develop a new volatility model to revisit the risk-return relation of the aggregate stock market index by extending the Realized GARCH model of Hansen et al. (2012) with the Wang and Yang (2013) framework, in which the overall risk-return relation is decomposed into a risk premium and a volatility feedback effect. An empirical analysis of three major Chinese stock indices reveals positive risk premium and negative volatility feedback effect, and those findings are stable across different markets and sub-samples. However, their relative magnitudes differ between markets and varies through time.     

Behavioral determinants of supply chain integration and coexistence

Economic theory considers physical production characteristics and related property rights as key determinants of the organization of an industry. Yet, we frequently observe coexisting governance modes within industries and firms, even when the transaction attributes of a commodity are homogenous. We test whether risk and time preferences, price expectations, and trust in supply chain types can explain variations and coexistence in governance. Specifically, we experimentally elicit economic preferences of forest managers in the Swiss wood sector. We find that all behavioral dimensions are related to the choice of sales channel. Most importantly, trust and expectations are key determinants in transferring property rights, while risk aversion, patience, and ownership structure explain the existence of plural forms at the firm level.     

CLOSED FORM PRICING FORMULAS FOR DISCRETELY SAMPLED GENERALIZED VARIANCE SWAPS

Most of the existing pricing models of variance derivative products assume continuous sampling of the realized variance processes, though actual contractual specifications compute the realized variance based on sampling at discrete times. We present a general analytic approach for pricing discretely sampled generalized variance swaps under the stochastic volatility models with simultaneous jumps in the asset price and variance processes. The resulting pricing formula of the gamma swap is in closed form while those of the corridor variance swaps and conditional variance swaps take the form of one‐dimensional Fourier integrals. We also verify through analytic calculations the convergence of the asymptotic limit of the pricing formulas of the discretely sampled generalized variance swaps under vanishing sampling interval to the analytic pricing formulas of the continuously sampled counterparts. The proposed methodology can be applied to any affine model and other higher moments swaps as well. We examine the exposure to convexity (volatility of variance) and skew (correlation between the equity returns and variance process) of these discretely sampled generalized variance swaps. We explore the impact on the fair strike prices of these exotic variance swaps with respect to different sets of parameter values, like varying sampling frequencies, jump intensity, and width of the monitoring corridor.     

ALLOWING FOR JUMP MEASUREMENTS IN VOLATILITY: A HIGH‐FREQUENCY FINANCIAL DATA ANALYSIS OF INDIVIDUAL STOCKS

Following recent advances in the non‐parametric realized volatility approach, we separately measure the discontinuous jump part of the quadratic variation process for individual stocks and incorporate it into heterogeneous autoregressive volatility models. We analyse the distributional properties of the jump measures vis‐à‐vis the corresponding realized volatility ones, and compare them to those of aggregate US market index series. We also demonstrate important gains in the forecasting accuracy of high‐frequency volatility models.     

The impact of FIFA’s official announcements on the stock market of Qatar: The case of the 2022 World Cup

This study examines the impact of the FIFA’s official announcements on Doha Stock Exchange (DSE) of Qatar with respect to the 2022 World Cup. Using the abnormal unsystematic volatility method of Hilliard and Savickas (2002), our empirical findings reveal that the DSE market is sensitive to FIFA’s announcements about the 2022 World Cup. We find that four out of six FIFA announcements act as primary drivers to the DSE market volatility. The significant reactions of the DSE market to these announcements unveil the investors’ sentiments about the fate of the governmental and private expenditures on medium- and long-term projects undertaken in anticipation of hosting the 2022 World Cup. The results have some implications to investors in this newly emerging market related to this global sporting event. Any future announcements, good or bad, are likely to impact share prices in DSE market and trigger portfolio reallocation by local and international investors, leading to increased volatility.     

Foreign banks,financial crises and macroeconomic fluctuations

Understanding the implications of increased foreign bank presence is especially compelling in periods of financial crisis. In this paper, we explore this issue by examining the relationship between the involvement of foreign banks in the banking systems and the volatility of key macroeconomic variables in normal and crisis periods. Using a sample of 20 Emerging European countries from 1998 to 2013, we find that an increase in the assets of foreign banks in the banking system reduces output and consumption growth volatility in general but does not significantly affect the volatility of investments. However, these banks were found to play a significant role in increasing output, consumption and investment volatility in 2009. Our findings suggest that foreign banks’ harmful impact during the global crisis was only temporary and that they seem to help Emerging European countries stabilize macroeconomic volatility in normal times and after the global crisis.     

Modelling the implied volatility surface based on Shanghai 50ETF options

We develop a dynamic factor model to forecast the implied volatility surface (IVS) of Shanghai Stock Exchange 50ETF options. Based on the assumption that dynamic change in IVS is mean-reverting and Markovian, we use a state space model to capture the dynamics of IVS, and set the latent factors to be the Ornstein–Uhlenbeck processes. We obtain the optimal estimations of parameters using the Kalman filter algorithm. Empirical results show that our model performs better than the traditional IVS model in terms of fitting ability and prediction performance.     

Small farmer cooperatives and voluntary coffee certifications: Rewarding progressive farmers of engendering widespread change in Costa Rica?

Our research examines the benefits and drawbacks for cooperatives who participate in voluntary coffee certifications. We interviewed administrators at twenty Costa Rican coffee cooperatives about management practices related to voluntary certification. Voluntary certifications are popular among coffee cooperatives. Access to certified markets is facilitated by state support of the cooperative sector, regulation of the coffee sector and well-enforced environmental and social laws. However, there are no significant or consistent financial incentives for farmers to pursue certification. Multiple certifications may lower auditing and implementation costs, but cooperatives rarely receive the full premium for multiply-certified coffee. Low market demand for certified coffee, weak price incentives and high auditing and management costs encourage cooperatives to certify only a portion of their members. This strategy rewards compliant farmers rather than inducing widespread change to farming practices among the entire membership. Though financial incentives are weak, certifications offer non-financial benefits to both farmers and cooperatives, including better management and more resilient cooperatives.     

Political uncertainty and a firm's credit risk: Evidence from the international CDS market

Using a large sample of firms with single-name credit default swap (CDS) contracts in 30 countries, we document the evidence that political uncertainty, proxied by national election dummy, is positively related to firm-level credit risk. Specifically, this positive relation is more pronounced for the firms that have no political connection or poor international diversification, and in the countries with higher political uncertainty and lower investor protections. Further, by using a difference-in-differences approach, we find evidence to support idiosyncratic volatility and debt rollover channels through which political uncertainty affects the credit risk of individual firm.     

Short-time at-the-money skew and rough fractional volatility

The Black–Scholes implied volatility skew at the money of SPX options is known to obey a power law with respect to the time to maturity. We construct a model of the underlying asset price process which is dynamically consistent to the power law. The volatility process of the model is driven by a fractional Brownian motion with Hurst parameter less than half. The fractional Brownian motion is correlated with a Brownian motion which drives the asset price process. We derive an asymptotic expansion of the implied volatility as the time to maturity tends to zero. For this purpose, we introduce a new approach to validate such an expansion, which enables us to treat more general models than in the literature. The local-stochastic volatility model is treated as well under an essentially minimal regularity condition in order to show such a standard model cannot be dynamically consistent to the power law.