On the public citation graph
Price discovery in chinese agricultural futures markets: A comprehensive look
0 signed · 141 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/1096-9934(200103)21:3<279::aid-fut5>3.0.co;2-lopenalex-snapshot
Asset storability and price discovery in commodity futures markets: A new look
inferredcites →https://doi.org/10.1002/agr.21376openalex-snapshot
Price Discovery in the Chinese Corn Futures Market, With Comparisons to Soybean Futures
inferredcites →https://doi.org/10.1002/fut.20352openalex-snapshot
Do futures lead price discovery in electronic foreign exchange markets?
inferredcites →https://doi.org/10.1002/fut.20514openalex-snapshot
Intraday price discovery and volatility transmission in stock index and stock index futures markets: Evidence from China
inferredcites →https://doi.org/10.1002/fut.21760openalex-snapshot
Price Discovery in Thinly Traded Futures Markets: How Thin is Too Thin?
inferredcites →https://doi.org/10.1002/fut.21891openalex-snapshot
Price discovery dynamics in European agricultural markets
inferredcites →https://doi.org/10.1002/fut.21966openalex-snapshot
Asymmetric spot‐futures price adjustments in grain markets
inferredcites →https://doi.org/10.1002/fut.21981openalex-snapshot
The trilogy of China cotton markets: The lead–lag relationship among spot, forward, and futures markets
inferredcites →https://doi.org/10.1002/fut.21984openalex-snapshot
Speculation and volatility—A time‐varying approach applied on Chinese commodity futures markets
inferredcites →https://doi.org/10.1002/fut.22087openalex-snapshot
The untold story of commodity futures in China
inferredcites →https://doi.org/10.1007/s00181-017-1322-6openalex-snapshot
Cointegration and price discovery in US corn cash and futures markets
inferredcites →https://doi.org/10.1016/0304-405x(76)90024-6openalex-snapshot
The pricing of commodity contracts
inferredcites →https://doi.org/10.1016/0922-1425(94)00030-wopenalex-snapshot
Futures trading in less ‘noisy’ markets
inferredcites →https://doi.org/10.1016/j.jbankfin.2010.03.009openalex-snapshot
News announcements and price discovery in foreign exchange spot and futures markets
inferredcites →https://doi.org/10.1017/aae.2019.23openalex-snapshot
Dynamic Price Discovery Process of Chinese Agricultural Futures Markets: An Empirical Study Based on the Rolling Window Approach
inferredcites →https://doi.org/10.1023/a:1027384330827openalex-snapshot
Information Flows Between the U.S. and China Commodity Futures Trading
inferredcites →https://doi.org/10.1086/296608openalex-snapshot
Manipulation of the Commodity Futures Market Delivery Process
inferredcites →https://doi.org/10.1111/1368-423x.00035openalex-snapshot
Some tests for parameter constancy in cointegrated VAR‐models
inferredcites →https://doi.org/10.1111/1468-0084.00065openalex-snapshot
Monte Carlo Evidence on Cointegration and Causation
inferredcites →https://doi.org/10.1111/1540-6261.00537openalex-snapshot
Cross‐Border Listings and Price Discovery: Evidence from U.S.‐Listed Canadian Stocks
inferredcites →https://doi.org/10.1111/j.1467-8276.2007.01122.xopenalex-snapshot
How Reliable Are Hog Futures as Forecasts?
inferredcites →https://doi.org/10.1111/j.1540-6261.1996.tb05211.xopenalex-snapshot
Volatility in Wheat Spot and Futures Markets, 1950-1993: Government Farm Programs, Seasonality, and Causality
inferredcites →https://doi.org/10.1111/jofi.12261openalex-snapshot
Informational Frictions and Commodity Markets
inferredcites →https://doi.org/10.1146/annurev-financial-110613-034432openalex-snapshot
Financialization of Commodity Markets
inferredcites →https://doi.org/10.2307/1241453openalex-snapshot
Macroeconomic Linkages, Taxes, and Subsidies in the U.S. Agricultural Sector
inferredcites →https://doi.org/10.2307/1392518openalex-snapshot
Estimation of Common Long-Memory Components in Cointegrated Systems
inferredcites →https://doi.org/10.2307/1912517openalex-snapshot
Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root
inferredcites →https://doi.org/10.2307/2232552openalex-snapshot
The Economic Role of Commodity Storage
inferredcites →https://doi.org/10.2307/2331251openalex-snapshot
Arbitrage, Cointegration, and Testing the Unbiasedness Hypothesis in Financial Markets
inferredcites →https://doi.org/10.2307/2938278openalex-snapshot
Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4649071openalex-extracted
Cross-Hedging and Dynamic Forecasting of Agricultural Products in China
inferred← citeshttps://doi.org/10.2139/ssrn.4724901openalex-extracted
Trade Friction and Evolution Process of Price Discovery in China's Agricultural Commodity Markets
inferred← citeshttps://doi.org/10.1002/fut.22384openalex-snapshot
Price discovery in China's crude oil futures markets: An emerging Asian benchmark?
inferred← citeshttps://doi.org/10.1002/fut.22473openalex-snapshot
A tale of two contracts: Was the SHFE copper futures market disrupted by the listing of INE bonded copper futures?
inferred← citeshttps://doi.org/10.1002/fut.22490openalex-snapshot
Market sentiment and price dynamics in weak markets: A comprehensive empirical analysis of the soybean meal option market
inferred← citeshttps://doi.org/10.1002/fut.22493openalex-snapshot
Financial regulatory arbitrage and the financialization of commodities
inferred← citeshttps://doi.org/10.1002/fut.22595openalex-snapshot
Information Flow Across the Futures Term Structure: Evidence From Chinese Corn Futures Market
inferred← citeshttps://doi.org/10.1002/fut.70090openalex-snapshot
Commodity Futures Report Text Sentiment and Returns
inferred← citeshttps://doi.org/10.1002/isaf.1519openalex-snapshot
Commodity price forecasting via neural networks for coffee, corn, cotton, oats, soybeans, soybean oil, sugar, and wheat
inferred← citeshttps://doi.org/10.1007/978-981-99-6441-3_73openalex-snapshot
Analysis of the Current Situation, Problems, and Countermeasures in the Development of China’s Agricultural Futures Market
inferred← citeshttps://doi.org/10.1007/s00521-024-09531-2openalex-snapshot
Forecasting wholesale prices of yellow corn through the Gaussian process regression
inferred← citeshttps://doi.org/10.1007/s00521-024-10270-7openalex-snapshot
Predictions of steel price indices through machine learning for the regional northeast Chinese market
inferred← citeshttps://doi.org/10.1007/s10690-026-09646-7openalex-snapshot
From Segmentation to Integration? Shock Propagation along the Term Structure of INE Crude Oil Futures
inferred← citeshttps://doi.org/10.1007/s11135-025-02233-4openalex-snapshot
Machine learning wholesale white wheat price index forecasts
inferred← citeshttps://doi.org/10.1007/s11135-025-02450-xopenalex-snapshot
Employing Gaussian process regression with Bayesian inference to predict the living-materials producer price index in China
inferred← citeshttps://doi.org/10.1007/s11227-023-05207-1openalex-snapshot
Regional steel price index forecasts with neural networks: evidence from east, south, north, central south, northeast, southwest, and northwest China
inferred← citeshttps://doi.org/10.1007/s13563-022-00311-9openalex-snapshot
Coking coal futures price index forecasting with the neural network
inferred← citeshttps://doi.org/10.1007/s13563-022-00357-9openalex-snapshot
Steel price index forecasting through neural networks: the composite index, long products, flat products, and rolled products
inferred← citeshttps://doi.org/10.1007/s13563-024-00457-8openalex-snapshot
Machine learning price index forecasts of flat steel products
inferred← citeshttps://doi.org/10.1007/s13563-024-00472-9openalex-snapshot
Forecasts of coking coal futures price indices through Gaussian process regressions
inferred← citeshttps://doi.org/10.1007/s13563-024-00477-4openalex-snapshot
Predicting open interest in thermal coal futures using machine learning
inferred← citeshttps://doi.org/10.1007/s13563-024-00483-6openalex-snapshot
Steel price index forecasts through machine learning for northwest China
inferred← citeshttps://doi.org/10.1007/s42524-024-4048-0openalex-snapshot
Medium- and long-term sustainable supply approaches and strategies for essential and typical strategic resources in China
inferred← citeshttps://doi.org/10.1007/s42824-024-00123-yopenalex-snapshot
Palladium Price Predictions via Machine Learning
inferred← citeshttps://doi.org/10.1007/s42824-025-00175-8openalex-snapshot
Machine Learning Green Gram Price Predictions
inferred← citeshttps://doi.org/10.1007/s42824-025-00198-1openalex-snapshot
Machine Learning Cotton Price Forecasts Based on Gaussian Process Regression Models with Hyper-parameters Tuned Through Bayesian Optimization and Cross Validation
inferred← citeshttps://doi.org/10.1007/s43674-022-00045-9openalex-snapshot
Canola and soybean oil price forecasts via neural networks
inferred← citeshttps://doi.org/10.1007/s43674-023-00054-2openalex-snapshot
Corn cash-futures basis forecasting via neural networks
inferred← citeshttps://doi.org/10.1007/s43674-025-00084-yopenalex-snapshot
Forecasting China’s producer price index for production materials via Gaussian process regression within a Bayesian inference framework
inferred← citeshttps://doi.org/10.1016/j.asieco.2021.101370openalex-snapshot
Dynamic price discovery in Chinese agricultural futures markets
inferred← citeshttps://doi.org/10.1016/j.asoc.2026.115841openalex-snapshot
PDIFormer: Price-discovery-informed deep temporal learning for price dynamics in small-scale commodity markets
inferred← citeshttps://doi.org/10.1016/j.compag.2021.106120openalex-snapshot
Corn cash price forecasting with neural networks
inferred← citeshttps://doi.org/10.1016/j.ememar.2025.101307openalex-snapshot
Does asynchronous market update matter? Re-examining the price discovery of stock index and futures in China
inferred← citeshttps://doi.org/10.1016/j.engappai.2023.106870openalex-snapshot
Price forecasts of ten steel products using Gaussian process regressions
inferred← citeshttps://doi.org/10.1016/j.foodpol.2024.102717openalex-snapshot
Autopsy of a futures market failure: Japan’s Dojima rice futures in the early 21st century
inferred← citeshttps://doi.org/10.1016/j.foohum.2026.101294openalex-snapshot
Predicting early indica rice prices utilizing Bayesian-optimized machine learning models employing Gaussian process regressions
inferred← citeshttps://doi.org/10.1016/j.heliyon.2024.e24138openalex-snapshot
Price discovery in Chinese PVC futures and spot markets: Impacts of COVID-19 and benchmark analysis
inferred← citeshttps://doi.org/10.1016/j.irfa.2023.102786openalex-snapshot
Chinese agricultural futures volatility: New insights from potential domestic and global predictors
inferred← citeshttps://doi.org/10.1016/j.irfa.2025.104424openalex-snapshot
Market efficiency across intra-daily sampling frequencies for Brent crude oil futures
inferred← citeshttps://doi.org/10.1016/j.iswa.2022.200061openalex-snapshot
Soybean and Soybean Oil Price Forecasting through the Nonlinear Autoregressive Neural Network (NARNN) and NARNN with Exogenous Inputs (NARNN–X)
inferred← citeshttps://doi.org/10.1016/j.iswa.2022.200084openalex-snapshot
Thermal coal price forecasting via the neural network
inferred← citeshttps://doi.org/10.1016/j.jcomm.2021.100186openalex-snapshot
The ‘Necessary Evil’ in Chinese Commodity Markets
inferred← citeshttps://doi.org/10.1016/j.meaene.2024.100001openalex-snapshot
Price forecasting through neural networks for crude oil, heating oil, and natural gas
inferred← citeshttps://doi.org/10.1016/j.najef.2022.101831openalex-snapshot
The impact of VIX on China’s financial market: A new perspective based on high-dimensional and time-varying methods
inferred← citeshttps://doi.org/10.1016/j.nexus.2023.100210openalex-snapshot
China mainland new energy index price forecasting with the neural network
inferred← citeshttps://doi.org/10.1016/j.nexus.2023.100250openalex-snapshot
Edible oil wholesale price forecasts via the neural network
inferred← citeshttps://doi.org/10.1016/j.ribaf.2022.101677openalex-snapshot
Correlation structure analysis of the global agricultural futures market
inferred← citeshttps://doi.org/10.1016/j.ribaf.2024.102332openalex-snapshot
Does market quality benefit from internationalization? Evidence from Chinese commodity futures markets
inferred← citeshttps://doi.org/10.1016/j.ribaf.2025.102870openalex-snapshot
China futures market and world container shipping economy: An exploratory analysis based on deep learning
inferred← citeshttps://doi.org/10.1017/nie.2021.34openalex-snapshot
NETWORK ANALYSIS OF HOUSING PRICE COMOVEMENTS OF A HUNDRED CHINESE CITIES
inferred← citeshttps://doi.org/10.1080/00036846.2022.2131718openalex-snapshot
Should dominant contracts move to nearby months?--Evidence from Chinese agricultural futures markets
inferred← citeshttps://doi.org/10.1080/00036846.2025.2542568openalex-snapshot
The effects of margin change on market quality: evidence from China’s New live hog futures market
inferred← citeshttps://doi.org/10.1080/00036846.2025.2558239openalex-snapshot
Can China’s live hog futures market respond to the government-released hog product reports?
inferred← citeshttps://doi.org/10.1080/00036846.2025.2588497openalex-snapshot
Economic policy uncertainty, commodity financialization, and price fluctuations of China’s agricultural commodity futures
inferred← citeshttps://doi.org/10.1080/0013791x.2025.2464130openalex-snapshot
Machine learning platinum price predictions
inferred← citeshttps://doi.org/10.1080/03019233.2023.2218243openalex-snapshot
Scrap steel price forecasting with neural networks for east, north, south, central, northeast, and southwest China and at the national level
inferred← citeshttps://doi.org/10.1080/03610918.2024.2330700openalex-snapshot
Platinum and palladium price forecasting through neural networks
inferred← citeshttps://doi.org/10.1080/13504851.2024.2303375openalex-snapshot
Is China’s hog futures market effective? Based on the perspective of price discovery and hedging functions
inferred← citeshttps://doi.org/10.1080/15140326.2024.2369441openalex-snapshot
Nonlinear price transmission and asynchronous price bubbles: empirical evidence from China’s agricultural futures and spot markets
inferred← citeshttps://doi.org/10.1080/16081625.2025.2521814openalex-snapshot
Does price discovery efficiency benefit from internationalization in China’s oil and oilseed futures market?——evidence from a quasi-natural experiment
inferred← citeshttps://doi.org/10.1108/ajeb-01-2024-0007openalex-snapshot
Wholesale price forecasts of green grams using the neural network
inferred← citeshttps://doi.org/10.1108/econ-05-2022-0026openalex-snapshot
Yellow corn wholesale price forecasts via the neural network
inferred← citeshttps://doi.org/10.1108/fs-01-2023-0016openalex-snapshot
Peanut oil price change forecasts through the neural network
inferred← citeshttps://doi.org/10.1108/ijhma-07-2022-0098openalex-snapshot
House price information flows among some major Chinese cities: linear and nonlinear causality in time and frequency domains
inferred← citeshttps://doi.org/10.1108/ijhma-09-2022-0134openalex-snapshot
Network analysis of comovements among newly-built residential house price indices of seventy Chinese cities
inferred← citeshttps://doi.org/10.1108/jamr-05-2024-0193openalex-snapshot
Cotton market contagion: analyzing volatility spillovers across borders
inferred← citeshttps://doi.org/10.1108/jm2-04-2024-0105openalex-snapshot
Impact of COVID-19 trade suspension on price discovery in FPO-traded agri-derivatives
inferred← citeshttps://doi.org/10.1108/jm2-05-2024-0150openalex-snapshot
Machine learning scrap steel price forecasts for the regional east Chinese market
inferred← citeshttps://doi.org/10.1108/jm2-09-2023-0207openalex-snapshot
Thermal coal futures trading volume predictions through the neural network
inferred← citeshttps://doi.org/10.1111/1467-8489.12542openalex-snapshot
Is China's new live hog futures market efficient? Evidence from an analysis of market quality, price discovery and hedging effectiveness
inferred← citeshttps://doi.org/10.1111/woba.12133openalex-snapshot
B: Financial Instruments and Markets
inferred← citeshttps://doi.org/10.11113/intrest.v17n2.274openalex-snapshot
Spatial-Temporal Analysis of Residential Housing, Office Property, and Retail Property Price Index Correlations: Evidence from Ten Chinese Cities
inferred← citeshttps://doi.org/10.1142/s1469026823500244openalex-snapshot
Wholesale Food Price Index Forecasts with the Neural Network
inferred← citeshttps://doi.org/10.1142/s1752890925500199openalex-snapshot
Predicting the Trading Volume of the Thermal Coal Futures Through Gaussian Process Regressions
inferred← citeshttps://doi.org/10.1142/s1793830925500430openalex-snapshot
Machine learning predictions of China commodity price indices
inferred← citeshttps://doi.org/10.1142/s2424786325500033openalex-snapshot
China commodity price index (CCPI) forecasting via the neural network
inferred← citeshttps://doi.org/10.1142/s2424922x25500068openalex-snapshot
Predictive Modeling of Peanut Oil Prices Utilizing a Gaussian Process Regression-Based Machine Learning Framework
inferred← citeshttps://doi.org/10.1142/s2661335225500030openalex-snapshot
Forecasts of wholesale food price indices through Gaussian process regressions
inferred← citeshttps://doi.org/10.1142/s2737599424500130openalex-snapshot
Machine learning Brent crude oil price forecasts
inferred← citeshttps://doi.org/10.1142/s2737599425500021openalex-snapshot
Scrap steel price predictions for southwest China via machine learning
inferred← citeshttps://doi.org/10.1142/s2737599425500367openalex-snapshot
Chinese energy security index price forecasting through the neural network
inferred← citeshttps://doi.org/10.1142/s2810943024500112openalex-snapshot
Machine Learning-Based Scrap Steel Price Forecasting for the Northeast Chinese Market
inferred← citeshttps://doi.org/10.1142/s2811034x24500060openalex-snapshot
Forecasts of China Mainland New Energy Index Prices through Gaussian Process Regressions
inferred← citeshttps://doi.org/10.1142/s2811034x25500030openalex-snapshot
Machine Learning Carbon Emission Allowance Price Predictions
inferred← citeshttps://doi.org/10.1142/s2972335325500024openalex-snapshot
Forecasting Scrap Steel Prices via Machine Learning for the Central Chinese Market
inferred← citeshttps://doi.org/10.1142/s2972335325500061openalex-snapshot
Bayesian-Optimized Gaussian Process Calibration for Forecasting Carbon Allowance Prices in Tianjin
inferred← citeshttps://doi.org/10.1142/s2972379525500012openalex-snapshot
Machine learning natural gas price predictions
inferred← citeshttps://doi.org/10.1142/s3060901125500292openalex-snapshot
Predicting Carbon Allowance Pricing in Beijing via Bayesian-Optimized Gaussian Process Regression Machine Learning Frameworks
inferred← citeshttps://doi.org/10.1142/s3082844925500137openalex-snapshot
Predicting the Producer Price Index (PPI) in China Using Gaussian Process Regression Frameworks Parameterized through Bayesian Inference
inferred← citeshttps://doi.org/10.1142/s3082844925500174openalex-snapshot
A Bayesian-Optimized Gaussian Process Framework for Carbon Market Price Forecasting: An Application to Fujian’s Emissions Trading Scheme
inferred← citeshttps://doi.org/10.11644/kiep.eaer.2024.28.3.439openalex-snapshot
Shanghai Containerised Freight Index Forecasting Based on Deep Learning Methods: Evidence from Chinese Futures Markets
inferred← citeshttps://doi.org/10.1177/03019233241254891openalex-snapshot
Machine learning predictions of regional steel price indices for east China
inferred← citeshttps://doi.org/10.1177/03019233241265194openalex-snapshot
Forecasts of thermal coal prices through Gaussian process regressions
inferred← citeshttps://doi.org/10.1177/03019233241297720openalex-snapshot
Regional steel price index predictions for the southwest Chinese market through machine learning
inferred← citeshttps://doi.org/10.1186/s40854-025-00753-4openalex-snapshot
Baidu News and the return volatility of Chinese commodity futures: evidence for the sequential information arrival hypothesis
inferred← citeshttps://doi.org/10.1515/jafio-2022-0009openalex-snapshot
Network Analysis of Price Comovements Among Corn Futures and Cash Prices
inferred← citeshttps://doi.org/10.17221/278/2023-agriceconopenalex-snapshot
Are futures markets functioning well for agricultural perishables? Evidence from China's apple futures market
inferred← citeshttps://doi.org/10.2139/ssrn.6880461openalex-snapshot
Multimodal Structural Forecasting of Agricultural Futures Prices: Evidence from OHLC Data and Transformer Architectures
inferred← citeshttps://doi.org/10.2139/ssrn.7327511openalex-snapshot
Can Pre-Opening Call Auctions Reduce Volatility in Continuous Trading: Evidence from Chinese Agricultural and Chemical Futures
inferred← citeshttps://doi.org/10.2139/ssrn.7345678openalex-snapshot
Who Anchors the Price of Rubber? Discovery, Anchoring, and Grade-Matched Benchmarks in International Rubber Futures
inferred← citeshttps://doi.org/10.25236/ajbm.2023.051415openalex-snapshot
Futures Trading Price Prediction Based on Big Data
inferred← citeshttps://doi.org/10.26794/2587-5671-2022-26-3-226-240openalex-snapshot
Price Discovery of Agri Commodities: An Integrated Approach
inferred← citeshttps://doi.org/10.3233/jifs-233060openalex-snapshot
Soybean futures price prediction with dual-stage attention-based long short-term memory: a decomposition and extension approach
inferred← citeshttps://doi.org/10.3390/jrfm17060252openalex-snapshot
Lessons from the Demise of the Brent Crude Oil Futures Contract on the Singapore Exchange
inferred← citeshttps://doi.org/10.3390/su17104655openalex-snapshot
Modeling the Ningbo Container Freight Index Through Deep Learning: Toward Sustainable Shipping and Regional Economic Resilience
inferred← citeshttps://doi.org/10.3390/sym18030465openalex-snapshot
A Decomposition-Driven Hybrid Approach to Forecasting Oil Market Dynamics
inferred← citeshttps://doi.org/10.4018/979-8-3693-4330-2.ch008openalex-snapshot
Agricultural Warehousing
inferred← citeshttps://doi.org/10.4236/ti.2022.134010openalex-snapshot
Design of Cross-Product Arbitrage Strategy in Forward Market
inferred← citeshttps://doi.org/10.54254/2754-1169/105/20241985openalex-snapshot
Current Situation, Problems and Suggestions of Agricultural Futures Market in China
inferred← citeshttps://doi.org/10.5539/ijef.v15n1p65openalex-snapshot
Determinants of Corn and Soybean Futures Prices Traded on the Brazilian Stock Exchange: An ARDL Approach
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.