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In light of current high and volatile energy and food prices, we examine the daily dynamics of the conditional variance-covariance matrix and price discovery in European vegetable oils. We find that energy prices chiefly influence vegetable oil trends, while stock-to-use ratios significantly impact variance-covariance dynamics when considering their specific cold filter plugging point (CFPP). This technical detail robustly demonstrates interplays among vegetable oils based on economic principles of complementarity and substitutability, even amid the pandemic and the Russian-Ukrainian conflict. Moreover, both marginal distributions and volatility dependence structures relate to distinct economic fundamentals, enhancing our understanding of the market's complexity. [ABSTRACT FROM AUTHOR]

This study is the first to conduct a comprehensive analysis of the price discovery and market liquidity aspects of China's crude oil futures market compared to WTI and Brent. With intraday-day data consolidated into 1-second intervals and three measures of price discovery, we find that China's crude oil futures market reports encouraging signs in terms of price discovery and efficiency, also showing great resilience during the COVID-19 pandemic. The market has obtained a dominant role in price discovery relative to WTI and Brent during its day trading hours, and has almost caught up with Brent in terms of market liquidity. [ABSTRACT FROM AUTHOR]

I propose a novel measure of information share, termed tail information share (TIS), which focuses on modeling the tail dependence of price innovations using copulas. I discuss its detailed technical properties, including unique identifiability, estimation procedures, and statistical properties. The proposed TIS improves over two commonly used measures by providing meaningful economic rationale and unique identifiability. My simulation studies indicate that TIS can yield more accurate estimates of market-specific contributions to price discovery when tail dependence is present. Additionally, I demonstrate the asymptotic consistency and efficiency of TIS estimators. An empirical illustration is provided using a new dataset of high-frequency crude oil futures. [ABSTRACT FROM AUTHOR]

This study aims to analyse the future–spot pricing relationship in the context of most actively traded commodities traded on Multi Commodity Exchange of India, which is the leading commodity exchange in the country today. The study intends to compare the pricing relations of three popular commodity segments, that is, bullion and metal, energy and agricultural segments, to explore whether future–spot pricing relationships are similar for all commodity segments or not. The study has applied vector autoregressive (VAR) model on a sample of 13 commodities, categorized as 7 commodities from bullion and metal segment, 2 commodities from energy segment and 4 commodities from agricultural segment. The results of VAR model show that in India, the non-agricultural commodity sector constituting of bullion, metal and energy commodities behave close to each other, but the behaviour of agricultural commodities is quite different from non-agricultural commodities. As regards non-agricultural commodities, the futures market plays a quite dominant and significant role as compared to the spot markets. However, in case of agricultural commodities, the futures market has a comparatively less dominant and strong role, and their spot market also plays an equally strong role. A comparative study of the pricing relationships existing among the three commodity segments will be extremely helpful for farmers, traders, investors as well as the portfolio managers in choosing the most profitable commodity classes for trading, investment and portfolio optimization. Regulators and policymakers can plan and implement an appropriate regulatory framework to strengthen these markets, especially agricultural commodity market, to promote economic growth. [ABSTRACT FROM AUTHOR]

We investigate the effect of funding constraints and the financial crisis on the pricing dynamics between the spot and futures markets. Tighter funding constraints and the presence of a financial crisis deter informed investors from utilizing their informational advantage in the futures market, reducing the leading role and information shares of futures prices. Funding constraints negatively affect the probability of informed trading and large trading in the futures markets. Our findings are in line with the recent theoretical perspective that indicates both factors significantly affect informed trading, the cross‐market process of price discovery, and financial stability. [ABSTRACT FROM AUTHOR]

Our analysis is targeted at researchers in the fields of economics and finance, and we place emphasis on the incremental contributions of each paper, key research questions, study methodology, main conclusions and data and identification tactics. By focusing on these critical areas, our review seeks to provide valuable insights and guidance for future research in this rapidly evolving and complex field. This paper conducts a structured literature review (SLR) of Bitcoin-related articles published in the leading finance, economics and accounting journals between 2018 and 2023. Following Massaro et al. (2016), SLR is a method for examining a corpus of scholarly work to generate new ideas, critical reflections and future research agendas. The goals of SLR are congruent with the three outcomes of critical management research identified by Alvesson and Deetz (2000): insight, critique and transformative redefinition. The present state of research on Bitcoin lacks coherence and interconnectedness, leading to a limited understanding of the underlying mechanisms. However, certain areas of research have emerged as significant topics for further exploration. These include the decentralized payment system, equilibrium price, market microstructure, trading patterns and regulation of Bitcoin. In this context, this review serves as a valuable starting point for researchers who are unacquainted with the interdisciplinary field of bitcoin and blockchain research. It is essential to recognize the potential value of research in Bitcoin-related fields in advancing knowledge of the interaction between finance, economics, law and technology. Therefore, future research in this area should focus on adopting innovative and interdisciplinary methods to enhance our comprehension of these intricate and evolving technologies. Our review encompasses the latest research on Bitcoin, including its market microstructure, trading behavior, price patterns and portfolio analysis. It explores Bitcoin's market microstructure, liquidity, derivative markets, price discovery and market efficiency. Studies have also focused on trading behavior, investors' characteristics, market sentiment and price volatility. Furthermore, empirical studies demonstrate the advantages of including Bitcoin in a portfolio. These findings enhance our understanding of Bitcoin's potential impact on the financial industry.

This study examines the profound influence of incorporating Artificial Intelligence (AI) and big data into algorithmic trading on financial markets, with a specific emphasis on its impact on market efficiency, liquidity, and price discovery. The research utilized quantitative approaches to evaluate the relationships between technology breakthroughs and major market indicators, using a sample of 200 professionals from the financial industry. The findings revealed strong positive correlations: AI technology had a strong connection with market efficiency (r = 0.65), whilst big data integration displayed a high correlation with decision accuracy (r = 0.70). Furthermore, the effect of AI on the swiftness of trade execution was significantly robust (r = 0.80), and its impact on price discovery was favourable (r = 0.60). The results emphasize the significant impact of AI and big data in improving the efficiency, accuracy, and speed of trading. They also draw attention to the advantages of these technologies as well as the current obstacles in achieving market transparency and stability. [ABSTRACT FROM AUTHOR]

We employed a non-parametric causality test based on Singular Spectrum Analysis (SSA) and used the Vector Error Correction Model (VECM) and Information Share Model (IS) to measure the relationship between the futures and spot prices for seven major agricultural commodities in China from 2009 to 2017. We found that the agricultural futures market has potential leading information in price discovery. The results of an Impulse Response Function (IRF) analysis also showed that the spot prices react to shocks from the future market and have a lasting impact. This confirms our findings reported for the causality test and information share analysis. [ABSTRACT FROM AUTHOR]

The present work has been designed to intensely investigate the capability of the commodity futures market in achieving the aim of price discovery. Further, the downside of the cash and futures market and transfer of the risk to other markets has also been studied using VaR, and Bivariate EGARCH. The findings of the work point that the metal commodity derivative market helps in the efficient discovery of price in the spot market except for nickel. But, in the case of the agricultural commodities, the spot is found to be leading and thus there is no price discovery except turmeric. On the other hand, the volatility spillover is bidirectional for both agri and metal commodities except copper, where volatility spills only from futures to spot. Further, the effect of negative shock informational bias differs from commodity to commodity, irrespective of metal or agriculture. [ABSTRACT FROM AUTHOR]

We investigate information processing in the stochastic process driving stock's volatility (volatility discovery). We apply fractionally cointegration techniques to decompose the estimates of the market-specific integrated variances into an estimate of the common integrated variance of the efficient price and a transitory component. The market weights on the common integrated variance of the efficient price are the volatility discovery measures. We relate the volatility discovery measure to the price discovery framework and formally show their roles on the identification of the integrated variance of the efficient price. We establish the limiting distribution of the volatility discovery measures by resorting to both long span and in-fill asymptotics. The empirical application is in line with our theoretical results, as it reveals that trading venues incorporate new information into the stochastic volatility process in an individual manner and that the volatility discovery analysis identifies a distinct information process than that based on the price discovery analysis. [ABSTRACT FROM AUTHOR]

This study undertakes an in-depth examination of how football matches and related sporting performance influence the intraday financial performance of corresponding blockchain-based fan tokens. Utilizing an event study encompassing eight distinct fan tokens and 325 football matches, we find a statistically significant average decline of 0.8% in fan token returns during the course of a football match, which subsequently decreases by an additional 0.7% in the post-match phase. Notably, a "loss effect" is identified, where the market reaction to losses is larger compared to wins. Furthermore, our study reveals large abnormal trading volumes before games, most prominently before UEFA Champions League matches, indicating anticipatory market behaviors. Further analysis establishes that abnormal fan token returns are impacted by various match-specific characteristics, such as the game outcome and form, predominantly before and during the match but not after. This distinct correlation between football games, sporting performance, and fan token returns has implications for a wide array of stakeholders and may suggest a challenge for investor (consumer) protection. [ABSTRACT FROM AUTHOR]

This study examines the equilibrium and price discovery relationships between credit default swap (CDS) and bond markets through the symmetric and non-symmetric cointegration approaches, focusing on Turkish sovereign markets. While the findings, obtained using the threshold autoregressive (TAR) and momentum threshold autoregressive (MTAR) models, confirm the asymmetric and nonlinear cointegration relationship between CDS and bond markets described in a limited number of studies in the relevant literature, they also, in contrast to other relevant studies, reveal the importance of data frequency and structural breaks in price discovery research. In this context, the results show that the CDS market is the leader in price discovery in high-frequency data and after the first sub-period, and the bond market is the leader in price discovery in low-frequency data and before the first sub-period. [ABSTRACT FROM AUTHOR]

This paper measures the degree to which disclosed annual financial information assimilates into stock prices through the financial production process (FPP). Since it is established that price anchors impact investor trading decisions, the effect of proximity to chosen price anchors and the historical high and low prices on FPP efficiency is analysed for 611 Indian firms across 11 industries. Results show that a significant number of stocks are FPP inefficient, and the FPP efficiency is mean-reverting. Further, FPP efficiencies depend on proximity to price anchors, implying that FPP efficiency is a proxy measure of behavioural bias in stock prices.

During geopolitical crises, the price stability of agricultural commodities is critical for national security. Understanding the dynamics of pricing power between the U.S. and China and how it varies over time can help smaller nations navigate unpredictable moments. This study uses a unified framework and wavelet approach to examine soybean price discovery in the U.S. and China from the standpoints of price interdependence and information flows. We begin by illustrating the integrated link between the soybean futures markets in the U.S. and China, which includes multiple structural breaks. The pricing difference between the two nations acts as the primary information spillover route for their integrated relationship. Furthermore, we show that the direction and degree of information spillover change dramatically in proportion to the strength of the U.S.–Chinese soybean interaction. Finally, we find that China’s recent retaliatory tax on the U.S. soybeans gave the Chinese market a more powerful position in soybean futures price discovery. After the first-stage trade deal was reached, and during the epidemic phase of the coronavirus pandemic, the pricing power of the U.S. soybean market showed no signs of full recovery.

This study addresses key issues of market efficiency in weak global futures markets, focusing on the intricate relationship between market sentiment and options pricing. Employing rolling variance ratio tests and information‐sharing models for market dynamics analysis, and supplemented with Granger causality tests and impulse response findings, it reveals a significant, unidirectional impact of market sentiment on options pricing, especially during periods of heightened sentiment. These insights underscore the importance of considering time dynamics in market behavior analysis, offering a novel perspective on futures and options market understanding. [ABSTRACT FROM AUTHOR]

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Price discovery studies of a single asset traded in multiple markets have traditionally focused on assessing the relative price discovery contribution of each market. However, in this paper, we demonstrate that the overall price discovery across all markets can undergo changes even when the relative price discovery of each market remains constant. We propose that this overall change in price discovery can be effectively captured by the fractional parameter in the fractionally cointegrated vector autoregressive (FCVAR) model. In contrast, the widely used cointegrated vector autoregressive (CVAR) model fails to account for this dynamic in overall price discovery. Through a combination of simulation exercises and empirical applications, we show that the FCVAR approach outperforms the CVAR model not only in evaluating the relative price discovery contributions but also, more importantly, in providing a comprehensive measurement of overall price discovery. [ABSTRACT FROM AUTHOR]

We compare the first-price sealed-bid (FPSB) auction and the simultaneous multiple-round auction (SMRA) in an environment based on the recent sale of 900 MHz spectrum in Australia. Three bidders compete for five indivisible items. Bidders can win at most three items and need to obtain at least two to achieve profitable scale, i.e. items are complements. Value complementarities, which are a common feature of spectrum auctions, exacerbate the "fitting problem" and undermine the usual logic for superior price discovery in the SMRA. We find that the FPSB outperforms the SMRA across a range of bidding environments: in terms of efficiency, revenue, and protecting bidders from losses due to the exposure problem. Moreover, the FPSB exhibits superior price discovery and almost always results in competitive ("core") prices unlike the SMRA, which frequently produces prices that are too low because of demand-reduction or too high because of the exposure problem. We demonstrate the robustness of our findings by considering two-stage variants of the FPSB and SMRA as well as environments in which bidders know their own values but not the distributions from which values are drawn. [ABSTRACT FROM AUTHOR]

We investigate which of the two most common prediction market mechanisms – market scoring rules and continuous double auctions – leads to better price discovery. The relative contribution of a particular prediction market to price discovery also depends on the total number of trades observed in that market. We use real-world prediction market price data to estimate price discovery shares of each market and their relationship to the number of trades. We find that when the number of trades is low, prediction markets that use market scoring rules have a higher speed of incorporating information into prices. When the number of trade is high, however, the continuous double auctions have a higher price discovery share. As market scoring rules require a variable cost – a subsidy – to operate, and continuous double auctions are costless; our results provide important implications for the design of prediction markets. By combining the methods for measuring price discovery and information aggregation, we introduce a new data-driven approach that can be used by researchers and practitioners to gain further insight into the exact values of the number of trades favoring the use of market scoring rules instead of continuous double auctions or vice versa. [ABSTRACT FROM AUTHOR]

Based on the event-study methodology, this study investigates the effect of China's milestone registration-based initial public offering (IPO) system reform on stock price efficiency and price discovery. Our findings indicate that the reform improves price efficiency in the short and long term. Price discovery under the registration-based IPO system is stronger than under the approval system. Additionally, the reform's effect on investor sentiment and institutional transaction costs can affect price efficiency and price discovery. [ABSTRACT FROM AUTHOR]

Price discovery and its related volatility spillover effect are significant indicators in commodity derivatives market to hedge the risk against sharp price fluctuations. This study empirically analyses the price discovery and volatility spillover using vector error correction model, Granger causality and bivariate exponential GARCH model (EGARCH) in Indian cardamom spot-futures markets. Daily time series data of spot market and near month futures contracts spanning the period from January 2009 to December 2020 have been used for the study. These price series data are based on the authenticated sources of Multi Commodity Exchange. The results of vector error correction model supported by Granger causality test indicates that spot market plays the role of leader as it is more efficient in reflecting the new information to prices. The results of bivariate EGARCH (1,1) model show that volatility spillover from cardamom spot market to futures market is dominant. [ABSTRACT FROM AUTHOR]

Recent financialization in commodity markets makes it easier for institutional investors to trade a portfolio of commodities via various commodity-indexed products. We present several pieces of novel causal evidence that daily exposure to such index trading results in price overshoots and reversals, as reflected in negative daily return autocorrelations, only among commodities in that index. This is because index trading propagates nonfundamental noise to all indexed commodities. We present direct evidence for such noise propagation using commodity news sentiment data. This paper was accepted by Bruno Biais, finance. Funding: Z. Da acknowledges financial support from the Beijing Outstanding Young Scientist Program [Grant BJJWZYJH01201910034034] and the 111 Project [Grant B20094]. K. Tang acknowledges financial support from the National Natural Science Foundation of China [Grants 71973075 and 72192802]. Y. Tao acknowledges financial support from the Start-up Research Grant of University of Macau [Grant SRG2022-00016-FSS]. L. Yang acknowledges the Social Sciences and Humanities Research Council of Canada for financial support [Grants 430-2018-00173 and 435-2021-0040]. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4797. [ABSTRACT FROM AUTHOR]

Metal mineral resources are important raw materials in industrial production, and metal as an important object in the futures market, its discovery function is an important sign to measure the level of market development. The price of metal futures market has the characteristics of high-frequency data, and the mechanism of price discovery in different frequencies needs to be realized by time series decomposition method. In this paper, the complementary ensemble empirical mode decomposition with adaptive noise vector autoregressive model is constructed to re-examine the price discovery of nonferrous metal futures from the aspects of multilevel, multi-subject, and different volumes. Four typical nonferrous metals are selected for empirical research in China. The results show that price discovery exists in China's nonferrous metal futures market. Meanwhile, there are significant differences in the functional efficiency of typical metal prices under different time scales. The volume of contracts will greatly affect the efficiency of price discovery. Finally, we also find that futures prices affect spot prices, but spot prices do not affect futures prices. [ABSTRACT FROM AUTHOR]

This study empirically tests whether price violations, as defined by Bakshi, Cao, and Chen (2000), show different patterns in response to market shocks. Specifically, we analyze the Chinese options market during a period covering a stock market crash and a series of trading restrictions in the Chinese derivatives markets. Our results confirm the significant changes of the defined violations in the face of unexpected shocks, and more importantly, we interpret such variations from the perspective of information spillovers. Our findings suggest that the stock market crash prompts informed traders in the Chinese options market to frequently adjust their positions on put options, exacerbating the misunderstandings and overreactions to new information. Further, the regulatory shock in the derivatives markets diminishes the efficiency of information incorporation for both options and spot markets but does not affect the dominance of the Chinese options market in price discovery. [ABSTRACT FROM AUTHOR]

Although daylight saving time (DST) is thought to provide economic benefits, extant research documents various adverse effects of DST adjustments. However, prior research provides little conclusive evidence about the effects of DST adjustments on capital market participants. We examine the effects of "spring forward" DST advances, which disrupt the human sleep cycle and economic activities, on investors' processing of earnings news. We find a delayed price response to earnings news released during the first week following a DST advance. We also find that this effect is stronger among firms with investors who are more likely to be trading on earnings news and among firms with less sophisticated investors. Our findings contribute to research on the unintended consequences of DST adjustments and to the growing literature on intra-investor variation in disclosure processing costs. Our study may be of interest to legislators currently debating proposed legislation that would eliminate DST phasing. Data Availability: Data are available from the sources cited in the text. JEL Classifications: D83; G14; M41; M48. [ABSTRACT FROM AUTHOR]

ChatGPT, an artificial intelligence (AI) chatbot, aims to provide users with comprehensive responses and precise answers to a broad spectrum of inquiries. Since its launch in November 2022, it has drawn considerable attention and millions of users. We analyze the returns of AI-themed crypto assets around the launch and widespread attention towards ChatGPT. Our analysis uncovers significant abnormal returns for AI tokens following ChatGPT’s launch, with abnormal returns peaking at 41% over the course of two weeks. Moreover, 90% of tokens exhibit positive abnormal returns. This suggests that the attention towards ChatGPT and AI more generally appears to have spilled over into cryptocurrency markets, resulting in positive price effects for AI-related cryptocurrencies. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to examine the effect of visual technology on the price discovery process in listings of residential properties in Singapore from 2015 to 2018. Design/methodology/approach: The authors empirically model the effects of 360 virtual tours and drone video on four dimensions in price discovery – buyers' arrival rate, sale probability, transaction prices and time-on-market – using a comprehensive data set for the residential properties in Singapore. Findings: The analysis shows that the availability of virtual tours or drone video in a listing increases the arrival rate from potential buyers, the probability of a successful sale and the selling price. These findings are consistent with the hypothesis that technologically enhanced tools improve the quality of information and the marketability of property. However, listings with virtual tours tend to be associated with longer marketing time, which is consistent with the prediction of the information overload hypothesis. Research limitations/implications: This paper extends the housing and price discovery literature by examining how technologically enabled new information affects property transactions. Originality/value: To the best of the authors' knowledge, this is the first paper to consider the impact of drone video on property market outcome. [ABSTRACT FROM AUTHOR]

Emerging economies often establish commodity futures markets to discover price signals, manage price risks and improve market integration, but establishing a futures market may not be feasible for agricultural perishables. In this study, we evaluated the function of the world's first fresh fruit futures contract for apples. Combining partial cointegration with state-space modelling, we derived time-varying price discovery metrics for the apple futures market. Our findings revealed a limited and time-varying dominance of price discovery by the futures market, while a substantial share of price discovery occurred in the spot market. Moreover, poor convergence of disaggregated spot prices to the futures price suggests that commercial traders in the apple supply chain tended to focus more on the spot market than on the futures market. Thus, emerging economies should be cautious about the new establishment of futures markets for agricultural perishables. Future research using more specific data on the spot market may provide a better insight on the limited function of the futures market.

Leveraging tick‐by‐tick data, this study provides the first analysis of Shanghai International Energy Exchange (INE) bonded copper futures' performance in market quality and price discovery. In particular, we investigate the effects of the market opening (listing of INE bonded copper futures) on Shanghai Futures Exchange (SHFE) copper futures' market quality and price discovery. Our results show that the market quality and price discovery of INE bonded copper futures in the first year of the listing is not promising. Our synthetic control method results suggest that market openness does not significantly reduce SHFE copper futures' market quality in terms of activity, liquidity, and volatility. Moreover, market openness does not significantly reduce the SHFE copper futures' price discovery effectiveness. Overall, the performance of new INE bonded copper futures needs improvement, while its listing did not disrupt SHFE copper futures. Our results suggest that a dual‐contract mode is an alternative option for internationalization in China's commodity futures markets. [ABSTRACT FROM AUTHOR]

This study investigates how financial sanctions packages targeting Russia influenced traditional information flow dynamics with other international financial markets and products. While providing empirical evidence regarding the use of payment systems and finance as weapons of war, it is crucial to understand if the market's response to international sanctions diminished as expectations shifted over time. Results, supported by robustness testing procedures, indicate important dynamic information flows relating to specific sanctions after the onset of the Russia-Ukraine war. In particular, those sanctions relating to the exclusion of Russia from the SWIFT payment system and those targeting banks and private wealth resulted in significant contagion effects sourced from all Russian markets examined. Such influence, however, is found to moderate and dilute as investors reconstruct their expectations and valuations. While targeted sanctions appear to impose intended market isolation, it is also associated with significant contagion effects. Although such secondary effects dissipate, they should be seen as important when implementing further targeted sanction packages. [ABSTRACT FROM AUTHOR]

We investigate the dynamic price discovery in the regular bitcoin (BTC) and microbitcoin (MBT) futures at the Chicago Mercantile Exchange. The only difference between the two bitcoin futures is the contract size, with MBT representing 1/50th of BTC. In contrast to recent findings in the literature, we find that BTC dominates MBT futures in price discovery, which can be attributed to the relative liquidity and investor structure in the BTC and MBT futures. In addition, crypto hacking activities can affect price discovery in bitcoin futures as we find higher hack stolen funds reduce (enhance) the price discovery in BTC (MBT) futures. These findings provide practical implications for bitcoin investors and regulators. [ABSTRACT FROM AUTHOR]

This paper studies how a tick size change affects market quality, price discovery, and the competition for liquidity provision by dealers and high-frequency trading firms (HFTs) in the U.S. Treasury market. Using difference-in-differences regressions around the November 19, 2018, tick size reduction in the 2-year Treasury note and a similar change in the 2-year futures eight weeks later, we find significantly improved market quality. Moreover, dealers become more competitive in liquidity provision and price improvement, consistent with the hypothesis that HFTs find liquidity provision less profitable in the smaller tick size environment. Last, we find a significant shift in short-run price discovery toward the cash market, which then reverses when the futures market tick size is reduced, suggesting that the finer pricing grid in the cash market allows traders to act on small information signals that are not profitable to exploit in the larger-tick futures market. Our findings suggest that reducing the tick size in tick-constrained and highly liquid markets like the Treasury market is on balance beneficial. This paper was accepted by Bruno Biais, finance. Funding: F. Ruela acknowledges support from the National Science Foundation Graduate Research Fellowship Program [Grant DGE-1746045]. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2022.4663. [ABSTRACT FROM AUTHOR]

On 8 January 2021, China's first live‐animal and live‐delivery futures product—in live hogs—was listed on the Dalian Commodity Exchange to serve as a risk management tool. We examine whether this newly established market exhibits good market quality and has realised its primary functions of price discovery and hedging. Our results suggest that the live hog futures market performs its price discovery function well and can hedge between 4% and 27% of the risk in the spot market, even though it is less actively traded, less liquid and more volatile than egg futures markets. To strengthen the hedging function of the live hog futures market, more effort—such as recruiting market makers and introducing night trading sessions—should be exerted to increase and smooth trading and stabilise volatility. [ABSTRACT FROM AUTHOR]

This study examines the contribution of credit default swaps (CDS) to price discovery in the run-up period preceding an acquisition announcement. We find that the CDS market plays a significant role in price formation before cross-border acquisitions, especially when target firms are from emerging economies. Further, the information flow from the CDS to the equity market is more pronounced when the bidder has a higher risk of default and the target nation has greater information asymmetry, weaker governance, and lower creditor protections. Our results are consistent with preferential use of the CDS market by informed traders ahead of negative credit news to hedge increased default risk or speculatively front-run widening credit spreads. [ABSTRACT FROM AUTHOR]

This paper investigates the time-varying lead-lag relationship between CSI 300 index futures and the cash index at intraday and daily frequencies under different market conditions, which is crucial in the price discovery research but rarely examined by the literature. Using a new method that is based on dynamic time warping and can capture the dynamic lead-lag relationship up to the intraday level, we find that index futures tend to lead the cash index by 0–5 minutes but it occasionally lags the cash index, and this relationship is variably affected by factors according to market conditions. Specifically, at both of the intraday and daily frequencies, the lead of index futures decreases with market volatility and the relative intensity of trading activity of index futures. The results also unveil the asymmetric effects of overnight information from the cash market on the lead times of both index futures and the cash index at a daily frequency. Moreover, the synchronization of trading hours strengthened the link between the two markets. These results have significant implications for price discovery in these markets. [ABSTRACT FROM AUTHOR]

Despite being a minor futures category, Polyvinyl chloride (PVC) futures have emerging as a vital element in energy and chemical futures domain. Employing three benchmark models component share (CS), information share (IS), and information leadership share (ILS), this study explores the price discovery function of Chinese PVC futures and spot markets. It assesses whether PVC futures have matured into an effective hedging tool and reference point for spot markets, and also examines the impact of the COVID-19 pandemic on this price discovery relationship. Empirical analysis reveals that the futures market has become the primary site for price discovery in the Chinese PVC market. All the models consistently demonstrate a mature price discovery function in PVC futures, providing risk mitigation tools for industry players. However, post-pandemic dynamics indicate that price discovery in PVC markets primarily occurs within the spot market. This suggests that compared to the futures market, the PVC spot market is able to respond more quickly to the strong signals of industrial recovery after the end of the pandemic. The feedback and pricing efficiency of the PVC futures market in response to new market information are also influenced. Furthermore, our study offers better anticipation of future market prices.

Causal flow analyses combined with time series analyses are used to examine price relationships among fresh broiler retail markets (Northeast, South, Midwest, and West). Results indicate structural changes have occurred in this industry. Reasons for changes in price relationships include the perishable nature of fresh broilers, along with vertical integration and increases in production and concentration in the industry. The four markets are integrated, but the level of integration has decreased over time. With the markets becoming more exogenous, there may be a decrease in society's welfare. The South market is the most important market for price discovery. [ABSTRACT FROM AUTHOR]

This paper examines price discovery between bitcoin spot and futures using static measures, namely information share (IS), component share (CS), modified information share (MIS), information leadership share (ILS), impulse response, and a time-varying parameter vector autoregressive (TVP-VAR) model with stochastic volatility and Markov Chain Monte Carlo (MCMC) sampling algorithm. Our one-minute and daily datasets cover 16 months before and 16 months during the Covid-19 pandemic (November 2018 to June 2021). Our IS, CS, MIS and impulse response results indicate a stronger bitcoin spot leadership, whereas our ILS results point to a weaker bitcoin futures dominance, during the Covid-19 pandemic. We construe this, as far as microstructure noise is concerned, as meaning that the bitcoin price is discovered in the spot market, and its dominance appears to have strengthened during the pandemic. However, as far as 'pure speed' is concerned, price discovery takes place in the bitcoin futures market, and its leadership seems to have weakened during the Covid-19 pandemic. The results of the time-varying measure (TVP-VAR) imply that, before the pandemic, price discovery took place within bitcoin futures but, during the pandemic, price discovery leadership has changed course, to occur within bitcoin spot. [ABSTRACT FROM AUTHOR]

This paper presents a bibliometric review of 2,391 publications on price discovery and hedging in financial assets and commodities. The discipline-wise contribution of publications and journal distribution based on the frequency of relevant research articles are reported. Five overarching themes have emerged from the content analysis, namely: (1) price discovery, (2) hedging in commodities, financial assets, and cryptocurrency, (3) market interconnectedness and volatility spillover, (4) market microstructure in pre- and post-financial crisis, and (5) asset allocation, diversification, and portfolio management. We propose three future research streams, namely predictability in uncertainty, short-term portfolio adjustment, and dynamic trading strategies, with nine research questions that can help investors and stock/commodity exchanges in an active portfolio and derivative contract management. [ABSTRACT FROM AUTHOR]

The futures contracts were introduced to act as hedging instruments and ensure the price discovery (referred to as PD hereafter) mechanism for the underlying securities. If the price movement of a futures contract leads the price movement of the underlying securities in the spot market, this confirms the existence of price discovery in the market. This study undertakes an in-depth analysis of past research in order to find research trends and directions for the future in the field of price discovery. The bibliometric analysis technique is used to analyse the existing literature. The study considers the 1431 documents collected from the Scopus database for the period of 1982–2021 to conduct the descriptive and network analysis of search results. The study identifies three key clusters, i.e., the foundation of the price discovery process (Cluster 1), the econometric tools and techniques to assess the price discovery process (Cluster 2), and price discovery under different market conditions and constraints (Cluster 3). After an in-depth content analysis of these clusters, the study provides suggestions for future research in the field of price discovery. The study is the first of its type to conduct an in-depth analysis of the literature of price discovery since inception, and provides directions for future research in the field. [ABSTRACT FROM AUTHOR]

In this study, we empirically analyze the contributions of three crude oil-based exchange traded funds (ETFs) and the futures contract in hedging crude oil price risk. In order to measure hedging contributions of ETFs, we estimate the usual minimum variance hedge ratios as well as the quantile based minimum variance hedge ratios based on three different methods. We also compute the hedging effectiveness of the futures contract and three ETFs. We find that ETFs can be used as hedging instruments especially for the longer hedging horizons and extreme quantiles. However, overall, we find the futures contract to be the most effective instrument for hedging.