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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,657 papers · 148 categories

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295887116 · Jun 202019922001200920172026
48 results for commodity indices

Enhanced trend-following strategy using network momentum for commodity futures.

problem Improving systematic trend-following in commodity futures markets.
method Combines univariate and cross-sectional trend indicators, including network momentum.
result Statistically significant improvements in portfolio performance metrics.

We have studied here the self-organising features of the dynamics of a model market, where the agents `trade' for a single commodity with their money. The model market consists of fixed numbers of economic agents, money supply and commodity. We demonstrate that the model, apart from showing a self-organising behaviour,…

2000-12-21abs ↗pdf ↗

We introduce an agent-based model, in which agents set their prices to maximize profit. At steady state the market self-organizes into three groups: excess producers, consumers and balanced agents, with prices determined by their own resource level and a couple of macroscopic parameters that emerge naturally from the a…

2015-08-14abs ↗pdf ↗

Study shows post-COVID commodity futures returns and volatility changed for different products.

problem Analyzing how the pandemic affected Chinese commodity futures markets.
method Empirical analysis of commodity futures returns and cointegration before and after the pandemic.
result Post-COVID, some commodity futures returns increased significantly, while others saw higher volatility.

This study compares microscopic and macroscopic models for commodity index derivatives pricing.

problem Lack of accurate futures curve dynamics in macroscopic models for real scenarios.
method Calibrated both microscopic and macroscopic models using S\&P GSCI Crude Oil excess-return index derivatives.
result Macroscopic models struggle to capture futures curve dynamics, affecting pricing and sensitivities.

We establish the existence of anomalous excess returns based on trend following strategies across four asset classes (commodities, currencies, stock indices, bonds) and over very long time scales. We use for our studies both futures time series, that exist since 1960, and spot time series that allow us to go back to 18…

2014-04-12abs ↗pdf ↗

Study improves exchange rate forecasting using machine learning and interpretable methods.

problem Complexity and ambiguity in financial and economic systems make precise exchange rate predictions difficult.
method Developed a fundamental-based model using machine learning and interpretability methods.
result Crude oil is the leading factor determining exchange rate dynamics, with significant events affecting its contribution.

Paper proposes novel hedging strategies using LSTM models for diversified investment portfolios.

problem Hedging risky asset portfolios in turbulent financial markets.
method Four diverse models (LSTM, ARIMA-GARCH, momentum, contrarian) generate price forecasts for diversified AIS.
result LSTM-based strategies outperform other models, with Bitcoin being the best diversifier for S&P 500 index.

We study here numerically the behavior of an ideal gas like model of markets having only one non-consumable commodity. We investigate the behavior of the steady-state distributions of money, commodity and total wealth, as the dynamics of trading or exchange of money and commodity proceeds, with local (in time) fluctuat…

2006-09-08abs ↗pdf ↗

This study examines how economic policy uncertainty impacts commodity prices across different crises.

problem Impact of economic policy uncertainty on commodity prices during various crises.
method Wavelet coherence analysis of time series data.
result Commodity prices are more correlated during global financial and Covid-19 crises.

We analyze daily prices of 29 commodities and 2449 stocks, each over a period of 15\approx 15 years. We find that the price fluctuations for commodities have a significantly broader multifractal spectrum than for stocks. We also propose that multifractal properties of both stocks and commodities can be attributed mainl…

2003-08-01abs ↗pdf ↗

We study the topological properties of the multinetwork of commodity-specific trade relations among world countries over the 1992-2003 period, comparing them with those of the aggregate-trade network, known in the literature as the international-trade network (ITN). We show that link-weight distributions of commodity-s…

2009-08-13abs ↗pdf ↗

We analyze the market efficiency of 25 commodity futures across various groups -- metals, energies, softs, grains and other agricultural commodities. To do so, we utilize recently proposed Efficiency Index to find that the most efficient of all the analyzed commodities is heating oil, closely followed by WTI crude oil,…

2013-09-05abs ↗pdf ↗

The paper analyzes the crash of stock and commodity markets during COVID-19 using Topological Data Analysis.

problem Identifying and understanding the dynamics and interdependence of stock and commodity markets during the COVID-19 crash.
method Topological Data Analysis (TDA) and Wasserstein Distance (WD) to identify crashes and compare market dynamics.
result Significant topological differences and interdependence between stock and commodity markets during the crash period.

The paper develops a new model for rough volatility in commodity markets.

problem Calibration of rough volatility models for commodity futures prices.
method Developed a general rough volatility model with automatic calibration and treatment of the Samuelson effect.
result Calibrated rBergomi and rHeston models to WTI Crude Oil futures options data.

We present a stochastic-local volatility model for derivative contracts on commodity futures able to describe forward-curve and smile dynamics with a fast calibration to liquid market quotes. A parsimonious parametrization is introduced to deal with the limited number of options quoted in the market. Cleared commodity …

2018-08-29abs ↗pdf ↗

We detect and quantify asymmetries in volatility spillovers using the realized semivariances of petroleum commodities: crude oil, gasoline, and heating oil. During the 1987--2014 period we document increasing spillovers from volatility among petroleum commodities that substantially change after the 2008 financial crisi…

2014-05-10abs ↗pdf ↗

In this study, we applied a stochastic spread pairs trading strategy on the Indian commodity market. The complete set of commodities were taken whose spot price was available for the period of January 1st 2010 to December 31st 2018 including energy, metals and the agricultural commodity sector. Spot data was taken from…

2019-07-19abs ↗pdf ↗

In this paper we analyzed dependencies in commodity markets investigating correlations of future contracts for commodities over the period 1998.09.01 - 2007.12.14. We constructed a minimal spanning tree based on the correlation matrix. The tree provides evidence for sector clusterization of investigated contracts. We a…

2008-03-27abs ↗pdf ↗

We consider a market model that consists of financial investors and producers of a commodity. Producers optionally store some production for future sale and go short on forward contracts to hedge the uncertainty of the future commodity price. Financial investors take positions in these contracts in order to diversify t…

2015-02-02abs ↗pdf ↗

Commodity exchange-traded funds (ETFs) are a significant part of the rapidly growing ETF market. They have become popular in recent years as they provide investors access to a great variety of commodities, ranging from precious metals to building materials, and from oil and gas to agricultural products. In this article…

2016-10-28abs ↗pdf ↗

Hierarchical graph learning for calendar spread strategies in commodity futures markets

problem Developing machine-learning methods for calendar spread strategies in commodity futures markets
method Proposing a hierarchical graph learning approach
result Outperforming benchmark models in both prediction and trading performance

The study explains why signature methods work in commodity futures term structure classification.

problem Lack of interpretability in signature methods for term structure classification.
method Introducing signature perturbations to explain the success of signature-based classification.
result The volatility of the convenience yield is the major discriminant for commodity markets classification.

We uncover a large and significant low-minus-high rank effect for commodities across two centuries. There is nothing anomalous about this anomaly, nor is it clear how it can be arbitraged away. Using nonparametric econometric methods, we demonstrate that such a rank effect is a necessary consequence of a stationary rel…

2016-07-26abs ↗pdf ↗

A new HOM model improves forecasting of Indian base metal prices.

problem Improving accuracy in predicting base metal prices in the Indian market.
method A Higher Order Markovian (HOM) model with varying order based on market delay.
result The HOM model consistently outperforms the standard Markovian model in forecasting.

In commodity markets the convergence of futures towards spot prices, at the expiration of the contract, is usually justified by no-arbitrage arguments. In this article, we propose an alternative approach that relies on the expected profit maximization problem of an agent, producing and storing a commodity while trading…

2015-01-01abs ↗pdf ↗

We test whether the futures prices of some commodity and energy markets are determined by stochastic rules or exhibit nonlinear deterministic endogenous fluctuations. As for the methodologies, we use the maximal Lyapunov exponents (MLE) and a determinism test, both based on the reconstruction of the phase space. In par…

2016-11-05abs ↗pdf ↗

Study improves prediction of commodity futures using multi-factor model.

problem Improving accuracy in predicting commodity futures prices.
method State-space functional regression model incorporating yield curve dynamics.
result Functional regression model outperforms Schwartz-Smith model in estimating short-end of futures curve.

Study strategic competition in commodity markets using impulse-switching controls.

problem Strategic competition between upstream and downstream firms in commodity markets.
method Non-zero-sum stochastic differential game with mixed impulse/switching controls.
result Multiple Nash equilibria found, depending on the number of switches by the downstream firm.