Price discovery and government intervention during the COVID-19 pandemic: Evidence from European cross-listed firms

Purpose– The purpose of this paper is to investigate the impact of short selling and margin trading on the price discovery and price informativeness of cross-listed firms, using a sample of Chinese firms listed on the China and Hong Kong stock exchanges.Design/methodology/approach– The sample consists of 67 Chinese cross-listed firms on A-share and H-share markets out of which 18 firms are allowed to be sold short/ traded on margin since March 2010. Using pre- and post-event period, the authors compare and contrast various market microstructure variables. The contributions of the home (A-share) and overseas (H-share) markets to the incorporation of new information into prices are calculated following the permanent-transitory approach of Gonzalo and Granger (1995) as well as the adverse selection component of Linet al.(1995).Findings– The findings indicate that for the group of Chinese cross-listed firms that are not allowed to be sold short or bought on margin, the home (A-share) market contributes more to the price discovery process over time. However, for the group of cross-listed firms that are eligible for short selling and margin trading, the authors observe no significant difference in the contribution of either A- or H-share markets to the price discovery. The contribution of home market for these firms is even lower around the announcement of major events. The authors further find that while the short sale activities appears to be informative, measured by the adverse selection (AS) component of spread, on the whole they have not led the A-share markets to be more informative.Research limitations/implications– The sample of cross-listed Chinese firms that are allowed to be sold short or bought on margin are rather limited. Hence, the results should be read with some caution.Practical implications– The removal of short selling constraints appears to improve the contribution of the respective markets to the process price discovery, in the case for larger cross-listed firms.Originality/value– The authors shed new lights on how the introduction of short selling and margin trading impacts on the price discovery of the Chinese cross-listed firms. A further contribution of the study is the use of high frequency data, while most of the previous studies on the Chinese markets use daily data.

This study examines the influences of the power structure evolution along the global coffee value chain on coffee spot-futures commodity markets. Specifically, this study aims to analyze the mechanisms and extent to which the coffee spot-futures commodity markets are affected by shifts in the power structure in each phase following the collapse of the ICA from the perspective of price discovery and volatility spillovers by employing the PT–IS and bivariate EGARCH models. This research covers two actively traded coffee types, Arabica and Robusta, and utilizes daily time-series price data over 1990:01–2020:04 for Arabica and over 2008:01–2020:04 for Robusta. The empirical results indicate that coffee spot markets play a dominant role in price discovery for both Arabica and Robusta over all periods, and volatility spillovers occur from the coffee spot market to the futures markets. This study demonstrates to coffee market players that power structure evolutions across coffee’s global value chain have not significantly changed the underlying socio-spatial distribution of the coffee value chain over the post-ICA period. The results further imply that a buyer-driven governance is emerging in the coffee industry and large coffee roasters are beginning to dominate the global coffee value chain. Moreover, large coffee roasters are incentivized to diversify their marketing strategies by considering more market factors as part of their market differentiation strategies. Government interventions are necessary to establish price risk-management mechanisms to protect small-scale coffee growers.

This paper examines the impact of central bank intervention operation on the price discovery of ask and bid quotes in an electronic limit order market of USD-JPY. Based on both methods of Hasbrouck (1995) and Gonzalo and Granger (1995), we find bid quotes provide more price discovery in the USD-JPY trading via the platform of the Electronic Broking Services (EBS). Our results also show that, when the Bank of Japan intervenes, the information share of ask quotes rises relative to that of bid quotes, implying a stronger asymmetry in trading costs between buyers and sellers.

The aim of this study is to investigate the dynamic of price discovery for cross-listed stocks using high-frequency intraday data. We show that the local market leads price discovery process with a significant contribution of the foreign US market. Moreover, we find that arbitrage opportunities enhance market liquidity of cross-listed firms, and vice versa. A higher US market contribution to price discovery provides an increase in the local trading volume as well as in arbitrage opportunities frequency. This latter leads to greater local market contribution to price discovery confirming the information-based transactions in the domestic markets of US cross-listed firms.

Cash prices for wheat in Poland are not closely related to futures prices in Chicago and London, for several reasons: differences in seasonality, fluctuations in exchange rate, poor dissemination of information in Poland, and most important the Polish government's intervention in wheat markets. Polish wheat prices generally move to expected intervention prices and then stay there until the next intervention level becomes known. The exception was in 1994-95, when sharply higher world prices raised prices in Poland. A wheat futures exchange in Poland could give the private sector a tool for hedging against price risk, improving efficiency and price discovery in Poland. It would be difficult to develop, however, under present interventionist policies. This situation could be improved by reducing the protection of prices and by making any intervention rules-based (reducing uncertainty about policies). Should intervention be reduced or rationalized, the next question is whether Poland needs its own wheat futures exchange or whether Poland's private sector can use futures exchanges in London and Chicago to hedge against risk. The answer to that question is not an easy one.

Intraday price discovery analysis in the foreign exchange market of an emerging economy: Mexico

The offshore RMB exchange rate is affected by the supply and demand relationship in the international market, investor sentiment, market liquidity, and other factors, while the onshore RMB exchange rate is mainly affected by government regulation and intervention. Therefore, the offshore RMB exchange rate may be a better reflection of the market’s macroeconomic expectations and risk appetite for China. Stock index futures are mainly affected by macroeconomic factors, so studying the correlation between the offshore RMB exchange rate and stock index futures is helpful for risk management, hedging, and price discovery. In this study, we selected the offshore RMB exchange rate, the volume of stock index futures, and the absolute rate of return as variables of investor sentiment. Through the Granger causality test, impulse response function, and variance decomposition, we studied the correlation between the rate of return of stock index futures and the rate of return of the offshore RMB exchange rate. Furthermore, we constructed a GARCH conditional volatility model. It was concluded that the trading volume and the absolute rate of return of stock index futures could explain the price fluctuations of stock index futures very well. A change in the offshore RMB exchange rate yield causes a change in the yield of stock index futures. Policymakers need to pay close attention to changes in the offshore RMB exchange rate in order to better grasp market trends and manage risks accordingly.

Do index futures still lead the spot market over government intervention or under trading restrictions? This intriguing question can be explored in the context of the 2015 Chinese market turmoil with frequent government interventions and its aftermath when unprecedentedly severe restrictions were imposed on the trading of the CSI 300 index futures. The intraday price discovery, studied via VECM, became weakly bidirectional over the boom phase from October 2014 to June 2015, in contract to the index futures’ strong leading before the boom. The futures’ leading status weakened drastically over the crash phase between June and September 2015, probably due to the government’s interference with the stock market. Surprisingly, the futures under severe trading restrictions after the crash from September 2015 to June 2016 still led the spot weakly, and the volatility spillover to the index was somewhat significant. Policywise, the empirical findings imply that government interventions or trading restrictions weaken the functioning of markets.

Agricultural commodity derivatives markets have played a pivotal role in price discovery and risk management; however, the literature lacks a consolidated synthesis of global research trends in this field. This study employs a bibliometric analysis to retrospectively assess the evolution of academic research on agricultural commodity derivatives. Utilising the Scopus database and bibliometric tools like Biblioshiny and VOS viewer, 632 articles published until 2023 were analysed. The methodology involved keyword searches, journal analysis, author influence mapping, and citation tracking to understand publication patterns, thematic concentrations, and geographical contributions. The results reveal that research output has grown notably during periods of heightened commodity price volatility, with the United States and China leading global contributions. Predominant research themes include price discovery, volatility spillovers, and hedging effectiveness, with the Journal of Futures Markets emerging as the most prolific journal. The discussion highlights that while substantial empirical work has focused on price dynamics and futures efficiency, critical gaps remain in areas such as the effects of government intervention, the role of digital platforms, and localised studies from emerging economies. In conclusion, this study underscores the necessity for future research to diversify thematically and geographically. It advocates for broader analytical approaches to capture the evolving complexities of agricultural commodity derivatives markets, offering valuable directions for scholars and policymakers alike.

Price discovery of cross-listed firms

This paper examines informed trading and price discovery for Canadian shares cross-listed on the Toronto Stock Exchange and the main U.S. exchanges. The domestic Canadian market can absorb higher demand for liquidity but offers no trading cost advantage. During earnings non-announcement periods, the intra-market probability of informed trading (PI) is similar on both national markets, and both national markets contribute to price discovery. The magnitude and elapsed time over which trading volumes are increased when earnings are announced are higher in the domestic Canadian market. Around earnings announcements, PI decreases only on the U.S. market and the Canadian market contributes more to price discovery. To infer the fundamental values of the underlying cross-listed firms, market participants should monitor both markets, and intensify their monitoring of the Canadian market during earnings announcement periods.

Price discovery for cross-listed firms with foreign IPOs

This study examines short-run and long-run unbiasedness within the U.S. rice futures market. Standard OLS, cointegration, and error-correction models are used to determine unbiasedness. In addition, the forecasting performance of the rice futures market is analyzed and compared to out-of-sample forecasts derived from an additive ARIMA model and the error-correction model. The results of our unbiasedness tests and the forecasting performance of the rice futures market provide supporting evidence that the U.S. long-grain rough rice futures market is efficient. The results have important price risk management and price discovery implications for Arkansas and U.S. rice industry participants. T he importance of commodity futures markets as price risk management and forecasting tools has become a central issue in the aftermath of The Federal Agriculture Improvement and Reform Act of 1996 (FAIR Act). The shift toward less government intervention under the FAIR Act has pushed the U.S. agricultural sector towards a more market-oriented system. An understanding of price risk management alternatives other than government programs is important for market participants. One of the key alternative strategies is the use of futures

In India, government intervention in the agricultural derivatives market has not allowed the market to grow and become an important tool of risk management. It has always been argued that the farmers and consumers of crops in India primarily operate in the spot market, and their expectations about the future market conditions are likely to be reflected in the spot price movements. If the farmers and consumers of the crops do not participate in the derivatives market, it is not expected to work as an efficient tool of information dissemination on the underlying commodity. We analysed the role played by the futures market in the price discovery process in this article. To test whether the futures or spot market in India plays a dominant role in information dissemination, we have done a regression analysis considering the lagged futures and spot price volatility as explanatory variables. We consider the major oil and oilseed contracts traded on National Commodity and Derivatives Exchange. As the uses of many of the oilseeds are related, we have tried to analyse the interlinkages among the market for different commodities. Our results clearly show that information on relevant futures market volatilities help significantly to assess the volatility in the spot markets. This linkage can be leveraged to manage the spot market risks better. JEL: G10, G13, G14

The Auto Regressive Conditional Heteroskedastic (ARCH) model (Engle, 1982) and its Generalised version (GARCH) (Bollerslev, 1986) are now widely used in the foreign exchange literature (Bollerslev et al., 1992) and as a framework for empirical studies of the market microstructure such as the impact of news (Goodhart and Figliuoli, 1991; Goodhart et al., 1993) and government interventions (Goodhart and Hesse, 1993; Peiers, 1997), or inter-and intra-market relationships (Engle et al., 1990; Baillie and Bollerslev, 1990). A main assumption behind this class of models is the relative homogeneity of the price discovery process among market participants at the origin of the volatility process. In other words, the conditional density of one GARCH process can adequately capture the information content of news. In particular, GARCH parameters for the weekly frequency theoretically derived from daily empirical estimates are usually within the confidence interval of weekly empirical estimates (Drost and Nijman, 1993).