Price Discovery Research Articles

Pricing behavior of clean energy stocks? Some trading implications

Mispricing and price adjustment to shocks are common features of stocks, which arise due to various types of shocks. Understanding mispricing and price adjustment mechanism can guide trading strategy design. Our hypothesis is that clean energy stocks are characterised by mispricing and that there are unique stocks in the sense that they move first when exposed to shocks. We employ a price discovery model to rank clean energy stock indices in terms of those that adjust to prices faster than those that do not. We then identify mispricing in those stocks using a market risk factor model. Utilizing time-series data on 11 clean energy stock indices, we propose eight trading strategies, and show that they offer annualized returns in the −5.37% to 61.10% range. Six of the eight strategies offer profits close to 15% or more, beating the buy and hold strategy. Trading strategies devised on mispricing suggest that two of the clean energy stocks can potentially beat the buy-and-hold strategy, offering annualized returns in excess of 13%. Because our results guide investors towards making profits from trading clean energy stocks, the implication is that the trading strategies can enhance the green finance market.

The effect of institutional herding on stock prices: The differentiating role of credit ratings

This paper investigates the impact of institutional herding on stock price formation, conditional on firms’ credit ratings, using 13F data from 1986 to 2019. In line with the current literature, we find herding intensity is driven by past returns consistent with momentum trading; however, we also find that herding is more sensitive to past returns for non-investment grade (NIG) stocks than investment grade (IG) stocks, resulting in a market bifurcation. We then examine the price impact of these trades and find that herding in NIG equities enhances price discovery. One plausible explanation is that information gradually diffuses within non-investment grade stocks, and herding behavior strengthens information discovery. Finally, we show both momentum-triggered herding and non-momentum-triggered herding contribute to price discovery among non-investment grade stocks.

What Makes HFTs Tick? Tick Size Changes and Information Advantage in a Market with Fast and Slow Traders

We study the impact of two changes in the minimum tick size, a reduction and a subsequent increase, on the trading behavior of fast and slow traders in the spot foreign exchange market. We find that the most notable impact of the tick size reduction is a substantial increase in the liquidity demand of high-frequency traders (HFTs) and not the decrease in their liquidity provision discussed by prior literature. We show that this change in behavior is linked to the higher frequency of price signals that arises with the smaller tick size and to the ability of fast traders to profit from it, often at the detriment of slower traders. Following the tick size decrease and the increase in liquidity demand by HFTs in the spot market, the role of the spot market in price discovery drops relative to that of the futures market. We discuss these findings in the context of the impact of HFTs on the information content of financial markets. This paper was accepted by Agostino Capponi, finance. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2022.02935 .

An investigation of the price discovery role of futures markets: A dynamic time warping analysis of the United States corn markets

AbstractFutures markets are critical to price discovery and often dominate spot markets. We analyze the linkages between daily corn futures and spot prices in the United States using dynamic time warping. This nonparametric pattern recognition technique has several advantages over traditional time series methods. First, it can detect multiple changes in the lead‐lag associations between the two prices within short intervals; the duration with which one series leads or lags another is not assumed to be fixed. Second, the method can be applied to time series without regard to their stationarity properties. This greatly expands the scope of this method to accommodate a wide range of time series. Third, it lends itself well to studying small samples, which econometricians encounter routinely. Fourth, the results are presented intelligibly using intuitive visualizations. Our results show that futures markets are critical to price discovery; nevertheless, spot markets dominate futures markets intermittently. We discuss the results in detail, setting them in the proper context. [EconLit Citations: C14, C32, Q02, Q11].

The impact of insider ownership and institutional ownership on post-earnings-announcement-drift: Evidence from Vietnam

In this study, we first document the existence of post-earnings-announcement-drift (PEAD) in Vietnam, consistent with investors’ under-reaction to earnings surprises. We then investigate whether and how institutional ownership and insider ownership affect PEAD. We find that the magnitude of PEAD effect is stronger among firms with higher insider ownership. We argue that higher insider ownership may increase information opacity and impede efficient processing of earnings news among investors. We provide supporting empirical evidence for this argument. Furthermore, in contrast to the conventional view that institutional investors exploit PEAD and accelerate the speed of price discovery, we find that institutional investors do not have significant impacts on PEAD. We argue that this result is consistent with recent findings in the US and China that some institutional investors may herd, hence, not necessarily help to mitigate PEAD. Our findings provide useful insights about the effect of insider investors and institutional investors on the delayed response to earnings news in the context of Vietnam.

On the Capital Market Consequences of Big Data: Evidence from Outer Space

Abstract We use the introduction of satellite coverage of major retailers to study the capital market implications of unequal access to big data. Satellite data enabled sophisticated investors with access to such data to formulate profitable trading strategies, especially by targeting the upcoming reports of retailers with bad news for the quarter. The introduction of satellite data led to more informed short-selling activity, less informed individual buying activity, and lower stock liquidity around the reports of retailers with satellite coverage. We conclude that unequal access to big data can increase information asymmetry among market participants without immediately enhancing price discovery.

Shanghai oil futures prices and firms' investment decisions: Evidence from Chinese manufacturing firms

International crude oil futures prices play a key role in market pricing, price discovery, and reshaping the market order. As the world's largest importer of crude oil, China urgently needs to establish contracts based on Asian supply and demand to mitigate currency risk for refiners and consumers. Against the backdrop of the launch of yuan-denominated crude oil futures by the Shanghai International Energy Exchange (INE) on March 26, 2018, this paper examines the impact of crude oil futures prices on the investment scale of Chinese manufacturing companies based on data from listed manufacturing companies in China from 2016Q1 to 2021Q3. The study finds that increases in international crude oil futures prices suppress the investment scale of Chinese manufacturing enterprises, while price volatility has a promoting effect. The listing of Shanghai crude oil futures has a negative shock effect on the impact of international crude oil futures prices on the investment scale of Chinese manufacturing enterprises. Additionally, increases in operational leverage amplify the negative impact of international crude oil futures prices on the investment scale of enterprises and weaken the positive impact of changes in international crude oil futures prices on the investment scale. Furthermore, among large manufacturing enterprises, volatility and increases in international crude oil futures prices suppress their investment scale; whereas in small and micro manufacturing enterprises, price increases and volatility significantly boost their investment scale. This paper provides empirical evidence and policy implications for fully leveraging Shanghai crude oil futures to optimize corporate investment decisions and support the sustainable development of enterprises.

International Bullion Exchange at GIFT IFSC in India- A Descriptive Study

In the global financial arena, the International Bullion Exchange (IBE) in Gujarat's GIFT (Gujarat International Finance Tec-city City represents a noteworthy advancement. GIFT City, the nation's first operational smart city and hub for international financial services, seeks to establish India as a major player in international finance by fostering an atmosphere that is favorable to global financial services. An essential component that makes it easier to trade precious metals internationally is the IBE. The IBE, which is housed in GIFT City, serves as a marketplace where international buyers and sellers come together to transact in different kinds of precious metals, such as gold, silver, platinum, and palladium. The exchange provides a smooth and transparent platform for players to participate in price discovery, hedging, and investing activities by utilizing cutting-edge technology and infrastructure. India has a long history of being one of the world's biggest consumers of gold, with a connection spanning across cultural, religious, and economic domains. By offering a strong platform for domestic and international stakeholders to participate in gold trading activities, the IBE takes advantage of India's fondness for gold. The exchange seeks to improve market efficiency and facilitate liquidity in the global bullion market by providing transparent trading procedures, effective price discovery mechanisms, and access to a wide range of market players. This study examines GIFT City's evolution, operating structure, market dynamics, and possible ramifications for the world bullion market. The research aims to add to the conversation about the globalization of financial markets and the changing face of commodities trade in the twenty-first century by illuminating this crucial shift.

The impact of the Russo-Ukraine conflicts on price discovery on the financial markets

ABSTRACT This paper investigates the response of financial markets to two significant events within the Russo-Ukraine conflicts: the November 2013 Euromaidan protest and the February 2022 Russian invasion of Ukraine. Employing diverse methods, including event studies, price discovery models, and time-varying parameter regression, we analyse abnormal returns, price discovery, time-varying herding behaviour, and market dynamics across various financial instruments, such as stock indices, currencies, and commodities. Overall, the Russian invasion of Ukraine had a more pronounced impact on financial markets compared to the Euromaidan protest. Moreover, during both events, the US dollar and yen consistently functioned as safe-haven assets. The findings also reveal variations in the responses of different assets to the conflicts, indicating potential effects on market efficiency, investor perceptions, and expectations.

Structural Dynamics of Indian Commodity Derivatives Market

"The inter temporal dimensions of an asset are examined through the price discovery function analysis of futures and spot price dynamics. The present study used Granger causality test and Chow test to analyze the price discovery function and the structural break of the agriculture, base metals, bullion, and energy commodities futures and spot prices during 2016-2022. The findings revealed the bidirectional causality between both the spot and future markets except gold exhibited unidirectional causality where the future market lead on the spot return is greater than contrary. Since the selected time period captures the crisis period, understanding the dynamic patterns is important for derivative valuation, hedging and asset allocation. The result of structural break revealed that among the selected commodities, only few commodities does not exhibit the structural break during the crisis period. This infer that the demand and supply for those commodities would exist in equilibrium condition and the shocks would not be transmitted to the price of commodities. The study makes recommendations for market participants to use arbitrage and hedging tactics. Additionally, it assists the regulators in assessing the steadiness of expanding commodity futures markets in India."

Disaggregation quality, stock returns, and institutional demand

We find that financial statement disaggregation quality (DQ), a measure of the fineness of financial statements, is a strong predictor of future stock returns. Institutional investors prefer high-DQ stocks, and their trade gradually incorporates reporting quality into stock prices over a year following disclosures. The relationship between DQ and future stock returns and institutional investors’ preference are stronger for small firms, during higher market-wide uncertainty periods, and robust to replacing DQ with change in DQ. Our findings provide evidence that capital markets are not perfectly efficient, and the discovery of stock prices is a gradual process facilitated by institutional demand.

Analysis of the Relationship between Futures Prices and Mandi Spot Prices of Spices in India

For this study, we used secondary data and applied various statistical methods, including the compound growth rate, ADF test, seasonality analysis, Johansen's cointegration test, and the Granger Causality Test. The findings revealed a positive trend in the prices of selected spices, indicating a significant growth rate for both prices and arrivals. Seasonality in prices was observed, particularly during the peak season. The price series were found to be cointegrated at a significance level of 1 per cent, and a uni-directional causality was identified in both spices. It suggested that futures prices played a dominant role in the price discovery process. It was recommended to improve warehouse structures and storage chambers to enhance the retention capacity of farmers, thereby emphasizing the importance of proper storage facilities.

Overnight earnings announcements and preopening price discovery

This study examines the market responses to announcements of stocks with different trading activities that disclose earnings during and outside normal trading hours. For less actively traded stocks, when bad news is reported after the market closes, potential informed trading exists, along with heightened return reversals and market inefficiency before the release. These informed trading activities are partially responsible for the post-announcement preopening price adjustments. Although the after-release preopening period for inactive stocks does not significantly facilitate price discovery as much as for active stocks, it provides an environment to resolve order imbalances after overnight information.

The price continuity, return and volatility spillover effects of regular and after-hours trading.

This study employs a bivariate EGARCH model to examine the Taiwan Futures Exchange's regular and after-hours trading, focusing on the critical aspects of spillover and expiration effects, as well as volatility clustering and asymmetry. The objective of this study is to observe the impact on the trading sessions in Taiwan by the influences of the European and American markets, focusing on the essential roles of the price discovery function and risk disclosure effectiveness of the regular hours trading. This research is imperative considering the increasing interconnectedness of global financial markets and the need for comprehensive risk assessment for investment strategies. It also examines the hedging behavior of after-hours traders, thereby aiming to contribute to pre-investment analysis by future investors. This examination is vital for understanding the dynamics of after-hours trading and its influence on market stability. Results indicate price continuity between both trading sessions, with regular trading often determining after-hours price ranges. Consequently, after-hours price changes can inform regular trading decisions. This finding highlights the importance of after-hours trading for shaping market expectations. Significant profit potential exists in after-hours trading open interest, which serves speculative and hedging purposes. While regular trading volatility influences after-hours trading, the reverse is not true. This suggests Taiwan market information poses a higher risk impact than European and American market data, emphasizing the unique position of the Taiwan market in the global financial ecosystem. After-hours trading volatility reflects the absorption of international market information and plays a crucial role in advance revelation of risks. This underscores the importance of after-hours trading in global risk management and strategy formulation.

The effect of the 2008–09 short selling sales ban on UK security equities in relation to market metrics of volatility, liquidity, and price discovery

In this study we look at the Financial Services Authority imposed short sale ban of UK financial equities in the 2008–2009 financial crisis to explore the effects of the short selling ban on liquidity, volatility, and price discovery on alternative portfolios of UK equity stocks. To this end we employ a control portfolio as well a portfolio of banned stocks. By using a GARCH model to explore the effects of short selling on portfolios’ returns volatility, we find a decline of volatility for selected UK financial stocks during the short sale restriction period. Further, we employ a bid-ask spread model to explore the effects of short selling on liquidity and find that liquidity deteriorates during the short sale ban period. We also employ a Wald-Wolfowitz Runs Test to investigate the effects of the short sale ban on price discovery and find that price discovery deteriorated during the short sale ban period. Finally, we examine the causal relationships among the market metrics in order to provide additional insight into the structure of the UK equity market during the period under study.

Improving Farmers’ Income on Online Agri-Platforms: Evidence from the Field

Problem definition: To improve the welfare of smallholder farmers, multiple countries (e.g., Ethiopia and India) have launched online agri-platforms to transform traditional markets. However, there is still mixed evidence regarding the impact of these platforms and, more generally, how they can be leveraged to enable more efficient agricultural supply chains and markets. This paper describes work conducted in close collaboration with the state government of Karnataka, India, to design, implement, and assess the impact of a new two-stage auction on the state’s online agri-platform, the United Market Platform (UMP). Methodology/results: To ensure implementability and protect farmers’ revenue, the auction design is guided by practical operational considerations, as well as semistructured interviews with a majority of the traders in the field. A new behavioral auction model informed by the field insights is developed to determine when the proposed two-stage auction can generate a higher revenue for farmers than the traditional single-stage, first-price, sealed-bid auction. The new auction mechanism was implemented on the UMP for a major market of lentils in February 2019. By the end of May 2019, commodities worth more than $6 million (USD) had been traded under the new auction. A difference-in-differences analysis demonstrates that the implementation has yielded a significant 3.6% price increase (corresponding to a 55%–94% profit gain) for over 10,000 farmers who traded in the treatment market. Managerial implications: The results from this paper offer tangible lessons on how innovative price discovery mechanisms could be enabled by online agri-platforms in resource-constrained environments. Importantly, the success of these designs critically depends on careful considerations of systemic operational and behavioral factors that affect trades in the physical markets. History: This paper has been accepted as part of the 2023 Manufacturing & Service Operations Management Practice-Based Research Competition. Funding: Financial support from the Tata Center for Technology and Design at MIT and the National Science Foundation [Grant 1452875] is gratefully acknowledged. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0437 .

Price discovery and volatility spillovers in the interest rate derivatives market

The interest rate derivatives market is an important force in promoting the development of the bond market and is an effective tool to manage interest rate risk. The research on price discovery and volatility spillover of the market can help provide valuable reference information for investors. Based on treasury bond futures and interest rate swaps, the paper aims to discuss the price discovery function and spillover structure of the interest rate derivatives market. The paper establishes the information share model and spillover index model for empirical analysis. The results show that: First, the calculation results of the information share model show that the price discovery of treasury bond futures and interest rate swap markets is stronger than that of the spot market. Second, based on structural break analysis, treasury bond futures and interest rate swaps do not have breakpoints, while the treasury bond spot has three breakpoints. The paper divides the entire sample into four stages based on structural breakpoints and finds that the price discovery ability of the interest rate derivative market dynamically changed. Third, as a net spillover in the market, treasury bond futures have developed relatively stable. Both treasury bond futures and interest rate swaps have spillover effects on the spot market, indicating that China’s interest rate derivatives market can impact the treasury bond spot market.

The black box of natural gas market: Past, present, and future

The increasing importance of natural gas in ensuring energy security, coupled with the impact of the COVID-19 crisis and the ongoing Russian-Ukraine war, motivates us to highlight the scholarly evolution of the literature on natural gas. From an initial pool of 53,964 papers, we refine our database, analyzing 1006 papers. By combining bibliometric and content analysis, we identify leading journals, countries, institutions, authors, articles, and critical research areas in natural gas. Our findings reveal five main research streams: 1) energy security consumption patterns in the natural gas market; 2) volatility and price discovery of the natural gas market; 3) interconnectedness between natural gas and oil market; 4) supply chain management of natural gas; and 5) development and perception of the natural gas market. We propose research questions to establish directions for future research.

Algorithmic Trading and AI: A Review of Strategies and Market Impact

This review explores the dynamic intersection of algorithmic trading and artificial intelligence (AI) within financial markets. It delves into the evolution, strategies, and broader market impact of algorithmic trading fueled by AI technologies. Examining the symbiotic relationship between advanced algorithms and AI, the review navigates through the various strategies employed, shedding light on their implications for market efficiency, liquidity, and overall stability. From high-frequency trading to machine learning-driven predictive analytics, this review unveils the multifaceted landscape of algorithmic trading in the era of AI, presenting both opportunities and challenges for financial markets. The review begins by tracing the historical development of algorithmic trading, emphasizing the paradigm shift with the integration of AI. From traditional programmatic trading to the emergence of sophisticated algorithms driven by machine learning and deep learning, the evolution sets the stage for a comprehensive understanding of the subject. An in-depth analysis of diverse algorithmic trading strategies unfolds, covering areas such as trend following, statistical arbitrage, market making, and sentiment analysis. The incorporation of AI introduces adaptive learning capabilities, enabling algorithms to evolve and optimize strategies based on real-time market conditions. Exploring the impact of algorithmic trading on financial markets, the review examines how AI-driven strategies contribute to market efficiency, liquidity provision, and price discovery. It dissects the implications for traditional market structures, regulatory considerations, and the potential risks associated with algorithmic dominance. Acknowledging the transformative power of algorithmic trading with AI, the review critically assesses the challenges and ethical considerations. From algorithmic bias to systemic risks, the review delves into the darker corners of this technological advancement, prompting a reflection on the need for responsible and transparent practices. The review concludes by peering into the future trajectory of algorithmic trading fueled by AI. Anticipated innovations, regulatory responses, and the evolving landscape of financial markets are discussed, offering insights into the ongoing transformation and potential disruptions in the realm of algorithmic trading. In essence, this review provides a nuanced perspective on the intricate relationship between algorithmic trading and AI, offering a comprehensive understanding of their strategies and the transformative impact on financial markets.

Research on the Correlation between the Exchange Rate of Offshore RMB and the Stock Index Futures

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.