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"Futures trading"
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The world for sale : money, power and the traders who barter the Earth's resources
The modern world is built on commodities - from the oil that fuels our cars to the metals that power our smartphones. We rarely stop to consider where they come from. But we should. In 'The World for Sale', two leading journalists lift the lid on one of the least scrutinised corners of the economy: the workings of the billionaire commodity traders who buy, hoard and sell the earth's resources. It is the story of how a handful of swashbuckling businessmen became indispensable cogs in global markets: enabling an enormous expansion in international trade, and connecting resource-rich countries - no matter how corrupt or war-torn - with the world's financial centres.
Book
The Effects of Index Futures Trading Volume on Spot Market Volatility in a Frontier Market: Evidence from Ho Chi Minh Stock Exchange
This analysis is the first to investigate the influence of index futures trading volume on spot market volatility for the Ho Chi Minh Stock Exchange (HOSE). The data utilized in this study are the daily VN30-Index futures contract trading volume starting at the inception date for the VN30-Index futures contract, 10 August 2017 and going through 10 August 2022. Using an autoregressive distributed lag (ARDL) bounds testing approach, the empirical findings reveal a positive relation between VN30-Index futures trading volume and the volatility of the spot market for the HOSE in the short-run. In addition, the results of the ARDL tests confirm in for the long-run, trading volume of futures contracts has a significant positive influence on spot market volatility. Moreover, the results derived from the error correction model (ECM) indicate that only 5.54% of the disequilibria from the previous trading day are converged and corrected back to the long-run equilibrium from the current day. Based on the findings, we recommend that Vietnamese policymakers establish relevant intervention polices on speculation of individual investors in order to provide stabilization safeguards for the underlying stock market.
Journal Article
FuturesNet: Capturing Patterns of Price Fluctuations in Domestic Futures Trading
Futures trading analysis plays a pivotal role in the development of macroeconomic policies and corporate strategy planning. High-frequency futures data, typically presented as time series, contain valuable historical patterns. To address challenges such as non-stationary in modeling futures prices, we propose a novel architecture called FuturesNet, which uses an InceptionTime module to capture the short-term fluctuations between ask and bid orders, as well as a long-short-term-memory (LSTM) module with skip connections to capture long-term temporal dependencies. We evaluated the performance of FuturesNet using datasets numbered 50, 300, and 500 from the domestic financial market. The comprehensive experimental results show that FuturesNet outperforms other competitive baselines in most settings. Additionally, we conducted ablation studies to interpret the behaviors of FuturesNet. Our code and collected futures datasets are released.
Journal Article
Building algorithmic trading systems : a trader's journey from data mining to Monte Carlo simulation to live trading
\"Award-winning trader Kevin Davey explains how he evolved from a discretionary to a systems trader and began generating triple-digit annual returns. An inveterate systems developer, Davey explains the process of generating a trading idea, validating the idea through statistical analysis, setting entry and exit points, testing, and implementation in the market. Along the way, Davey provides insightful tips culled from his many years of successful trading. He emphasizes the importance of identifying the maximum loss a system is likely to produce and to understand that the higher the returns on a system, the higher the maximum loss. To smooth returns and minimize risk, Davey recommends that a trader utilize more than one system. He provides rules for increasing or decreasing allocation to a system and rules for when to abandon a system. As market patterns change and system performance changes and systems that performed spectacularly in the past may perform poorly going forward. The key for traders is to continue to develop systems in response to markets evolving statistical tendencies and to spread risk among different systems. An associated website will provide spreadsheets and other tools that will enable a reader to automate and test their own trading ideas.Readers will learn:- The systems Davey used to generate triple-digit returns in the World Cup Trading Championships- How to develop an algorithmic approach for around any trading idea, from very simple to the most complex using off-the-shelf software or popular trading platforms.- How to test a system using historical and current market data- How to mine market data for statistical tendencies that may form the basis of a new systemDavey struggled as a trader until he developed an algorithmic approach. In this book, he shows traders how to do the same\"-- Provided by publisher.
Book
Psychological factors as triggers for futures trading adoption: evidence from German farmers
Research has often attributed commodity futures contracts (CFC) adoption in agriculture to structural factors, such as farm size and education, linking low uptake to economies of scale and learning costs. We challenge this perspective by investigating psychological dimensions of farmers' decision-making, specifically examining response efficacy, self-efficacy, and response costs of CFCs as conceptualized in protection motivation theory (PMT). Through cluster analysis of survey data collected from 303 German farmers in 2024, we identify two psychological profiles with distinct adoption behaviors despite similar structural characteristics. Our findings suggest that psychological dispositions act as critical triggers for adoption, whereas structural factors create enabling conditions. Policy measures should address psychological barriers to enhance futures trading uptake in agricultural risk management.
Journal Article
Liquidity of China’s agricultural futures market: measurement and cross-market dependence
PurposeThis paper aims to present the first empirical liquidity measurement of China’s agricultural futures markets and study time-varying liquidity dependence across markets.Design/methodology/approachBased on both high- and low-frequency trading data of soybean and corn, this paper evaluates short-term liquidity adjustment in Chinese agricultural futures market measured by liquidity benchmark and long-term liquidity development measured by liquidity proxies.FindingsBy constructing comparisons, the authors identify the seminal paper of Fong, Holden and Trzcinka (2017) as the best low-frequency liquidity proxy in China’s agricultural futures market and capture similar historical patterns of the liquidity in soybean and corn markets. The authors further employ Copula-generalized autoregressive conditional heteroskedasticity models to investigate liquidity dependence between soybean and corn futures markets. Results show that cross-market liquidity dependence tends to be dynamic and asymmetric (in upper versus lower tails). The liquidity dependence becomes stronger when these markets experience negative shocks than positive shocks, indicating a concern on the contagion effect of liquidity risk under negative financial situations.Originality/valueThe findings of this study provide useful information on the dynamic evolution of liquidity pattern and cross-market dependence of fastest-growing agricultural futures in the largest emerging economy.
Journal Article
Volatility Analysis of the Indian Stock Market: Insights from Bank Nifty Index and Futures Trading
To diagnose the relationship between futures contract trading and the volatility of stocks in the Bank Nifty Index.Time series analysis and the GARCH model are employed to study the interaction between futures trading and spot market volatility.The analysis revealed that out of the six banks analyzed, just two demonstrated a statistically significant influence of future trading on volatility, while the remaining four did not exhibit any such relationship.This study provides a nuanced understanding of the impact of futures trading on stock volatility within the Bank Nifty Index, specifically highlighting variations across banks. By including the COVID -19 period, this research captures the influence of unprecedented market shocks on volatility dynamics in an emerging market context, providing valuable insights into how futures trading operates under unique stress conditions. Moreover, the study fills a gap in the existing literature by including all top -weighted banks in the Bank Nifty, especially those that were previously overlooked, thereby enhancing the relevance of the findings for policymakers and market participants.Policymakers and regulators should consider adopting tailored guidelines that reflect the different responses of individual banks to futures trading, as one-size-fits-all regulations may overlook stock -specific volatility dynamics. Market participants, especially investors and retail traders, are advised to apply targeted risk management and hedging strategies based on each bank’s unique volatility patterns rather than generalizing across the industry.
Journal Article
Reference-Dependent Hedging
We develop a theoretical model of optimal hedging that nests expected utility and expected target utility theories. We use this model to characterize optimal hedging with and without reference price dependence. The model’s theoretical predictions are tested with a unique database consisting of every forward contract written with a major grain marketing firm by Iowa corn producers over a fiveyear period. Our results suggest that a current December futures price higher than a reference price triggers hedging activity. A likely candidate for producers’ reference price is a rolling average of the current futures price. We then use trading activity implied by the producers to determine if they benefit from the way they hedge. The evidence is mixed. Finally, we compare the producer forward contract data to the only publicly available data on producer hedging: The Commodity Futures Trading Commission Disaggregated Commitment of Traders Report (DCOT) for Short Hedgers. A hedge ratio constructed from the open interest in new futures contracts of the DCOT report is highly correlated with the producer hedge series in the Iowa data, providing evidence that DCOT data represent farmers’ hedging behavior reasonably well. This work has important implications for future research that uses the DCOT data, and provides new evidence about producers’ hedging behavior that marketing specialists and extension agents can use to enhance their educational efforts related to risk management.
Journal Article