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Objective – The current biotechnology revolution has been associated with newly developed genetic modifications (GM) that offer new prospects for increasing agricultural productivity. This has stimulated a rapid adoption of GM corn hybrids by U.S. farmers. Yet, there is concern about the structure of competition among biotech firms that own patents over GM traits. This chapter evaluates the spatial differences in pricing of biotech corn hybrids, with a focus on the fringe versus core regions of the U.S. Corn Belt.

Methods – The analysis examines how local conditions and market concentrations affect the pricing of GM corn hybrids in different locations.

Results – We find evidence of more extensive subadditive pricing in the fringe region. We also examine how both own- and cross-market concentrations affect prices across regions. For GM hybrids, the results show that market power is generally more prevalent in the core region compared to the fringe.

Conclusions – The evidence shows that the pricing of GM corn hybrids varies across space. The observed pricing schemes benefit farmers more in the fringe than in the core region of the Corn Belt.

The purpose of this paper is to empirically analyze the dynamic relationship between stock market and bond market based on the effect of different information shocks.

This paper decomposes the information of stock market and bond market into public information and private information. The characteristics of response of stock market and bond market to the information shocks are examined by SVAR model and modified BEKK model.

The study shows that the information shocks in financial market yield not only the effect on linear asset return but also the effect on nonlinear asset volatility. The public information mainly produces a short effect of return while the private information mainly produces a permanent effect on volume. The interactive relation between stock market and bond market is mainly reliant on the effect of the information shock volatility to market return volatility.

The paper empirically analyzes the influence characteristics of different information shocks, which has some reference value not only for deeply understanding the market microstructure but also for improving the construction of various capital markets.

This study aims to analyze the volatility spillover effects of crude oil, gold price, interest rate (yield) and the exchange rate (USD (United States Dollar)/INR (Indian National Rupee)) on inflation volatility in India.

This study uses the multivariate Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models (Baba, Engle, Kraft and Kroner [BEKK]-GARCH and dynamic conditional correlation [DCC]-GARCH) to examine the volatility spillover effect of macroeconomic indicators and strategic commodities on inflation in India. The monthly data are collected from January 2000 till December 2020 for the crude oil price, gold price, interest rate (5-year Indian bond yield), exchange rate (USD/INR) and inflation (wholesale price index [WPI] and consumer price index [CPI]).

In BEKK-GARCH, the results reveal that crude oil price volatility has a long time spillover effect on inflation (WPI). Furthermore, no significant short-term volatility effect exists from crude oil market to inflation (WPI). However, the short-term volatility effect exists from crude oil to inflation while considering CPI as inflation. Gold price volatility has a bidirectional and negative spillover effect on inflation in the case of WPI. However, there is no price volatility spillover effect from gold to inflation in the case of CPI. The price volatility in the exchange rate also has a negative spillover effect on inflation (but only on CPI). Furthermore, volatility of interest rates has no spillover effect on inflation in WPI or CPI. In DCC-GARCH, a short-term volatility impact from all four macroeconomic indicators to inflation is found. Only crude oil and exchange rate have long-term volatility effect on inflation (CPI).

In an economy, inflation management is an essential task. The findings of the current study can be beneficial in this endeavor. The knowledge of the volatility spillover effect of all the four markets undertaken in the study can be significantly helpful in inflation management, especially for inflation-targeting policy.

It is observed that no other study has addressed this issue. We do not find any other research which studies the volatility spillover effect of gold, crude oil, interest rate and exchange rate on the inflation volatility. The current study is novel with a significant contribution to the vast knowledge in this context.

This chapter examines changes in US monetary policy uncertainty (ΔMPU) and fiscal policy uncertainty (ΔFPU) on stock returns while controlling for downside risk, lagged dividend yield, and time series patterns. Testing G7 markets consistently shows that both ΔMPU and ΔFPU have significant negative impacts on stock returns. Evidence shows that any downside risk, ΔMPU or ΔFPU in US market will soon be transmitted to G6 industrial markets and the impacts are extended to two months. These risk and uncertainty premiums should be priced in the stocks of the major industrial markets.

The purpose of this paper is to examine herding in four frontier markets in the Balkan region, namely, Bulgaria, Croatia, Romania and Slovenia, from October 2000 to December 2016.

The author employs Chang et al.’s (2000) cross-sectional dispersion approach to capture herding, while also testing for the global financial crisis’ effects and the European Union (EU)/Euro zone accession effects over herding. Potential asymmetric herding effects conditional on market performance, domestic volatility, German and US investor sentiment are also examined. Finally, the cross-market herding dynamics of the region are also explored.

Overall, Romania exhibits the most extensive evidence of herding across various estimations. The empirical results indicate that cross-market herding dynamics within the region generate stronger herding (compared to the herding observed within each stock market individually), suggesting that Balkan stock exchanges’ growing financial integration leads their herding to be “imported”, rather than domestically motivated.

The findings provide useful insights for regulators in frontier markets, considering the destabilising potential of herding; they are also of particular interest to the investment community for reasons of international asset allocation, diversification and hedging strategies.

This study contributes to the limited herding literature regarding frontier markets and provides novel findings regarding the herding dynamics in the Balkan region, the EU/Euro zone accession’s effect and global factors’ impact on herding estimations.

This paper aims to investigate volatility causality and return contagion on nine international securitized real estate markets by appealing to Markov-switching (MS) regime approach, from July 1992 to June 2014.

An MS causality interaction model (Psaradakis et al., 2005), an MS vector auto-regression mode (Krolzig, 1997) and a multivariate return contagion model (Dungey et al., 2005) were used to implement the empirical investigations.

There exist regime shifts in the volatility causality pattern, with the volatility causality effects more pronounced during high volatility periods. During high volatility period, real estate markets’ causality interactions and inter-linkages contribute to strong spillover effect that leads to extreme volatility. However, there is relatively limited return contagion evidence in the securitized real estate markets examined. As such, the US financial crisis might probably be due to cross-market interdependence rather than contagion.

Because international investors incorporate into their portfolio allocation not only the long-run price relationship but also the short-run market volatility connectedness and return correlation structure, the results of this MS causality and contagion study have provided valuable information on the evaluation of regime-dependent securitized real estate market risk, as well as useful guidance on asset allocation and portfolio management decisions for institutional investors.

Financial crisis is one of the key determinants of cross-market volatility interactions. Portfolio managers should be alerted of the observation that the US and the other developed securitized real estate markets are increasingly sharing “common market cycles” in recent years, thereby diminishing the diversification benefits. For policymakers, this research indicates that the volatilities of the US securitized real estate market could be helpful to predict those of other developed markets. It is also important for them to pay attention to those potential risk factors behind the amplified causality, contagion and volatility spillover at times of crisis. Finally, a wider implication for policymakers is to manage the transmission channels through which global stock market return and volatility shocks can affect the local economies and domestic financial markets, including securitized real estate markets.

Real estate investments have emerged to show low correlation with stocks and bonds and contributed to portfolio optimization. With real estate that can serve as a type of consumption commodity and an investment tool, the risk-return profile of real estate is different from that of the underlying stock markets. Therefore, the performance and investment dynamics and real estate-stock link are not theoretically expected to be similar, that requires separate empirical investigations. This paper aims to stand out from the many papers on the same or similar topics in the application of the three MS methodologies to regime-dependent real estate market integration.

This paper aims to investigate the return links and volatility transmission between five major equity markets of the Latin American region and the USA over the period 1993-2012.

The authors employ a multivariate vector autoregressive moving average – generalized autoregressive conditional heteroskedasticity (VAR-GARCH) methodology which allows for cross-market transmissions in both return and volatility. Moreover, we show how the obtained results can be used to design internationally diversified portfolios involving the Latin American assets and to analyze the effectiveness of hedging strategies.

The results point to the existence of substantial cross-market return and volatility spillovers and are thus crucial for international portfolio management in the Latin American region. However, the intensity of shock and volatility cross effects varies across the studied markets.

The optimal weights and hedging ratios that we compute from the observed return and volatility spillovers, suggest that adding the Latin American assets helps improve the risk-adjusted return of the internationally diversified portfolios as well as reduce their risk exposure. For policymakers and market authorities, an increase in the level of shock interactions and volatility transmission between the US and Latin American equity markets as well as among these Latin American markets implies that the stability of the financial system in one country can be deeply affected by the disturbances in another country.

The authors extend the previous works on Latin American emerging markets by examining the extent of shock and volatility transmission as well as portfolio design and management from the point of view of both the US (global) and Latin American investors.

Considering the cross-market network externality, this paper aims to explore the platform’s pricing decisions and its optimal profit under the given government investment, and then investigate the investment decision to improve social responsibility, which is measured by the social welfare.

When exploring the optimal pricing decisions under the given government investment, extreme value theory and sensitive analysis are used. When investigating the investment level, game theory and optimization method are used. Numerical examples are conducted to further illustrate the results.

First, after considering the government investment, whether the buyers and the sellers are charged depends on the investment level and the difference of the cross-market network externality (CNC) of the sellers and the buyers. Second, the optimal price on the sellers is decreasing (increasing) in the CNC of the buyers (sellers). The optimal price on the buyers is significantly affected by the investment level. Finally, the government investment is win-win for both the platform and the government, and Chinese Government should invest on the sellers heavily.

This study specifies the role of the government investment on the sellers in determining the platform’s pricing decisions and the improvement of the social responsibility, which is measured by social welfare.

In this study, we explore the empirical relationship between trading volume and volatility among KOSPI200 index stock market, futures and options markets. In particular, in explaining the volatility of each market, the trading in other markets, as well as the trading volume of other markets, also served as explanatory variables. In other words, cross-market effects of trading volume by investor types are analyzed. The empirical results show that there exist the cross-market effects of the relationship between trading volume and volatility in deeply integrated financial markets such as KOSPI200 index stock, futures and options markets. That is, the volatility of one market is explained by the trading volume of trader types in other financial markets. And, overall options trading increases the volatility of each market, while the overall futures trading volume of foreign investors reduce the volatility of each market. Trading volume of Individual investors does not reduce the volatilities of KOSPI200 index and futures markets. That is, trading volume of Individual investors in stock, futures, and options markets increase the volatilities of stock and futures. This implies that foreign investors are informed traders, whereas individual investors are liquidity traders.

The aim of this paper is to examine the effect of information disclosure by unlisted bond issuers on the stock price informativeness of listed firms in the same industry.

This paper takes advantage of information disclosure during the bond issuance and examines the spillover effect of unlisted bond issuers' information disclosure on listed firms in the stock market. The sample is composed of A-share firms listed on the Shanghai and Shenzhen stock exchanges from 2007 to 2018. All the data are obtained from the China Stock Market and Accounting Research and WIND databases. The impact of bond market information disclosure on price informativeness of listed firms in the same industry is identified through multivariate regression analyses.

Empirical results show that price informativeness of listed firms has a significantly positive association with the information disclosure of same-industry unlisted bond issuers. Further analyses show that the above finding is more significant when information disclosure of bond issuers is a more important channel for acquiring industry information (i.e. when industry is more concentrated, when economic uncertainty is high, and when industry information is less transparent) and understanding the industry competitive landscape (i.e. when bond issuers are relatively large, when bond issuers and listed firms have more direct product competition, when bond issuance firms are large-scale state-owned business groups), and when there are more cross-market information intermediaries (i.e. more cross-market institutional investors and more sell-side analysts). This paper indicates that information disclosure of bond issuers has a positive spillover effect on the stock market.

The novelty of the research is that the authors examine industry information spillover from unlisted firms to listed firms leveraging on unlisted firms' information disclosure in bond markets.