Price Discovery Research Articles

A tale of two contracts: Was the SHFE copper futures market disrupted by the listing of INE bonded copper futures?

AbstractLeveraging 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.

On the dependence structure of European vegetable oil markets

ABSTRACT 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.

Funding constraints, financial crisis, and price discovery between the futures and spot markets

AbstractWe 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.

Relations among Bitcoin Futures, Bitcoin Spot, Investor Attention, and Sentiment

This research investigates the function of price discovery between the Bitcoin futures and the spot markets while also analyzing the impact of investor sentiment and attention on these markets. This study utilizes various statistical models to examine the short-term and long-term relations between these variables, including the bivariate Granger causality model, the ARDL and NARDL models, and the Johansen cointegration procedure with a vector error correction mechanism. The results suggest that there is no statistical evidence of price discovery between the Bitcoin spot price and futures, and the term structure of the Bitcoin futures neither enriches nor impairs this lead lag relation. However, the study finds robust evidence of a long-run cointegrating relation between the two markets and the presence of asymmetry in them. Moreover, this research indicates that investor sentiment exhibits a lead lag relation with both the Bitcoin futures and the spot markets, while investor attention only leads to the Bitcoin spot market, without showing any lead lag relation with the Bitcoin futures. These findings highlight the crucial role of investor behavior in affecting both Bitcoin futures and spot prices.

Cointegration and causality relationship of Indian stock market with selected world markets

Background: The purpose of this study is to explore the trends and causes of established and emerging nations’ stock market integration with India. The National Stock Exchange (NSE) indices act as a counterweight to international market indices. This study investigates the sustained interest of foreign investors in the Indian stock market in the wake of capital market reforms, as well as whether it moves in tandem with other markets in Asia and the United States. Methods: Our study examined the possibility of cross-country cointegration between the largest economies and indices around the world using multiple financial econometric models, such as Augmented Dickey-Fuller, Unit Root, Correlation, and Johansen Cointegration. Results: The findings of this study significantly support the notion that Indian and international financial markets are highly integrated. Vector error correction model indicates that the Indian market (NSE) is highly cointegrated with the US market (National Association of Securities Dealers Automated Quotations) and increased volatility signifies global contagion. Conclusion: A cursory examination of the data reveals distinct investment and portfolio diversification options for global investors. This could assist regulators in formulating more effective rules regarding price discovery processes.

The dynamics of price discovery between the U.S. and Chinese soybean market: a wavelet approach to understanding the effects of Sino-US trade conflict and COVID-19 pandemic

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.

Changing Regional Price Relationships in Retail Fresh Broiler/Fryer Whole Chicken Prices

AbstractCausal 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.

Time‐varying price discovery in regular and microbitcoin futures

AbstractWe 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.

Managing a High Uncertainty Scenario through a Real Option Assessment: Evidence from a Copper Concentrate Trader

Commodity markets are highly volatile markets where uncertainty management is critical for success. Certain commodities, such as copper concentrates, experience even higher levels of volatility and uncertainty. This is fundamentally due to the absence of a reference market that allows for a transparent price discovery, along with many factors affecting the price and trade of any commodity. Traders also lack the possibility of fully hedging their exposure to copper concentrate prices as there is no derivative market directly available for the commodity. Consequently, this paper analyses the copper concentrate trading business resorting to the Real Options methodology to assess the high volatility and uncertainty which dominates in this area of commodity markets. The results obtained indicate that this method can be applied by copper concentrate traders to separate the price uncertainty from their business operative and financial planning for the future. This provides them with a reliable tool to lower the level of uncertainty affecting their long-term goals, as well as keeping the risk that they are taking under control. It also gives them higher managerial flexibility.

The profitability of lead–lag arbitrage at high frequency

Any lead–lag effect in an asset pair implies that future returns on the lagging asset have the potential to be predicted from past and present prices of the leader, thus creating statistical arbitrage opportunities. We utilize robust lead–lag indicators to uncover the origin of price discovery, and we propose an econometric model exploiting that effect with level 1 data of limit order books (LOBs). We also develop a high-frequency trading strategy based on the model predictions to capture arbitrage opportunities. The framework is then evaluated on six months of DAX 30 cross-listed stocks’ LOB data obtained from three European exchanges in 2013: Xetra, Chi-X, and BATS. We show that a high-frequency trader can profit from lead–lag relationships because of predictability, even when trading costs, latency, and execution-related risks are considered.

Does price limit improve price discovery? Evidence from IPO market in a quasi-natural experiment

The two major Chinese stock exchanges imposed a new trading rule with a price-move limit of 44% on the first trading day for IPOs after 2013. Following this quasi-natural experiment, market sentiment on IPOs drastically rises, resulting in extreme price run-up in initial trading days. Newly listed stocks under the trading rule experience greater illiquidity, higher turnover and volatility than earlier ones. Account-level data from the Shanghai Stock Exchange shows that following the new rule, net buyers of IPO change from institutional to retail investors. The evidence suggests that this price limit delays price discovery by arousing sentiment and crowding out informed investors.

Dynamic connectedness between energy markets and the Brazilian cash market: An empirical analysis pre‐ and post‐COVID‐19

AbstractBrazil's significant commodity production is internationally recognized, yet the absence of a mature futures market exposes it to price risks and international shocks. This study explores the dynamic connectedness between commodity futures and the Brazilian cash markets, using a time‐varying parameter vector autoregressive model. We also assess COVID‐19's impact on this connectedness. We find a significant influence of oil prices on Brazilian ethanol prices, and particularly emphasize the Heating Oil spillover effect on ethanol in the post‐COVID‐19 era. We also note the ascension of Brazilian soybean spot markets' international significance since 2017, amplifying their role in global grain price discovery. Finally, by computing hedge ratios and effectiveness between commodity futures contracts and Brazilian spot prices, our study reveals soybean cash price as the most effective hedge. These insights deepen comprehension of connectedness within Brazilian commodity markets, thereby guiding investors and policymakers in strategic energy policy decisions.

Research on Price Discovery in Financial Securities: Trends and Directions for Future Research

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.

The Market Inside the Market: Odd-Lot Quotes

Abstract We show current market practices relating to odd-lot quotes create a large “inside” market where better prices routinely exist relative to the National Best Bid or Offer. We show that odd-lot quotes play a price discovery role, and these quotes provide valuable information to traders with access to proprietary data feeds. Using a XGBoost machine learning algorithm that uses odd-lot data to predict future prices, we demonstrate a simple and profitable trading strategy. We argue the SEC’s proposed round-lot redefinition reduces—but does not eliminate—the high incidence of superior odd-lot quotes within the NBBO.

The Influence of Investor Sentiment on Futures Price Volatility: Evidence from the Chinese Crude Oil Market

With the progress of crude oil financialization, crude oil futures has become an important derivative product, and its price discovery function has been widely concerned by investors. The relationship between sentiment and price can be studied by constructing oil market sentiment index. Considering that the investor sentiment of single-market energy futures may not reflect the cross-market impact well, this paper selected OI, PSY, RSI and other commonly used futures trading indicators, and used principal component analysis to construct the investor sentiment indexes of single-market (crude oil) and cross-market (crude oil, fuel oil, coking coal, coke) respectively. VAR, Granger test and linear regression are used to explore the influence of investor sentiment on the volatility of crude oil futures prices. The results show that: (i) There is a Granger causality relationship between single market (crude oil) investor sentiment and crude oil price; (ii) There is no Granger causality relationship between cross-market investor sentiment and crude oil price; (iii) Single market and cross-market investor sentiment have an asymmetric effect on the price fluctuation of crude oil futures market.

Re-examining the efficiency of the EU carbon futures market in phase Ⅱ: price discovery and intertemporal arbitrage

Introduction: Carbon futures market plays an important role in energy conservation and emission reduction of energy-intensive firms, and its efficiency is largely reflected by the dynamic relationship between carbon spot and futures prices. Even though the EU carbon futures market has undergone three phases, its efficiency in Phase Ⅱ still contains much controversy.Methods: Based on the cost-of-carry model, we apply linear and nonlinear Granger causality test, vector error correction model and threshold vector error correction model to re-examine the efficiency of the carbon futures market in the second phase of the European Union Emissions Trading System from the perspectives of price discovery and intertemporal arbitrage.Results: i) the EU carbon futures market has the function of price discovery by virtue of the broad scope of participants and the consequent huge liquidity, suggesting that the carbon futures price can predict the carbon spot price; ii) the coefficient requirement of the cost-of-carry model is satisfied and the relationship between the European Union Allowance (EUA) futures and spot prices is consistent with the cost-of-carry model, which indicates that the former is an unbiased estimator of the latter and an equilibrium relationship exists between the two prices so that the carbon futures market is efficient in the long run; iii) however, the carbon futures market shows inefficiency in the short run since it has an error correction function only when the basis is less than −0.07 and the carbon futures price indicates a remarkably slow adjustment to the long-run equilibrium when there is deviation, which can be ascribed to the global financial crisis as well as its aftermath in 2008.Discussion: In the context of global warming and carbon neutrality, the results of this paper are of great significance to emitters, arbitrageurs, hedgers and policymakers in emerging and young carbon markets.

Learning About Market Microstructure and Price Discovery Using Experimental Markets

This study introduces the use of an instructor-developed trading simulation to teach intrinsic value estimation, price discovery,and market mechanics. It provides the reader with a cost efficient solution to deepen students’ understanding of financial markets and the price discovery process. By using a multi-week time frame we allow students to analyze the financial information of the companies in the simulation as well as to develop strategies to exploit the market structure and price discovery process. Thus, this simulation combines the importance of financial analysis with the awareness of the impact of liquidity and market organization on price discovery.

Market uncertainty, persistent arbitrage-free violation, and price discovery in RMB market

This paper applies a fractionally cointegrated vector autoregressive model to examine time-varying price discovery between Chinese renminbi onshore and offshore exchange rates. We study the impact of the equity market and economic policy uncertainty level on price discovery and the arbitrage opportunities between the onshore and offshore markets. The results show that the less regulated offshore rates dominate in price discovery, and a higher market uncertainty level strengthens the leading role of offshore rates in price discovery. However, a higher market uncertainty would increase the bid–ask spread and investors’ risk aversion degree and then impede the whole price discovery. Finally, higher uncertainty would induce persistent arbitrage opportunities in renminbi onshore and offshore markets.

How price limit affects the market efficiency in a short-sale constrained market? Evidence from a quasi-natural experiment

In this paper, we examine the joint effect of price limit and short-sale constraints on price discovery. Using a natural experiment in China, we show the exogenous relaxation of price limit improves price efficiency. Importantly, shortable stocks experience more improvement in price efficiency than non-shortable stocks. Event-study analysis further documents less delayed price discovery following the price-limit-hitting event on shortable stocks, which is explained by selling pressure from large institutional orders. Our findings suggest that alleviating shortsale constraints could synergize with the relaxation of trading restrictions to improve price efficiency.

Matching problems in biodiversity offset markets: a case study of the New South Wales biodiversity offsets scheme

Biodiversity offset credits in New South Wales are transacted within a regulatory environment defined by detailed trading rules and many different types of biodiversity credits that can lead to thin markets and high transaction costs. This paper describes a market designed to facilitate efficient and effective transactions. The market includes a search algorithm to identify who can exchange with whom, according to the regulatory constraints, and an online exchange tool to facilitate efficient price discovery and allocation of offset contracts.