An Empirical Analysis of Systemic Risk in Commodity Futures Markets, under the supervision of Pr. Delphine Lautier

Une Analyse Empirique du Risque Systémique dans les Marchés à Terme de Matières Premières, sous la direction de Pr. Delphine Lautier

Lautier D., Ling J., Raynaud F. (2015) "Integration of Commodity Markets: Has It Gone Too Far?" In Aïd, Ludkowski, Sircar (Eds.), Commodities, Energy, and Environmental Finance (pp. 65-90), Springer, Fields Institute. doi: 10.1007/978-1-4939-2733-3

1. "Rediscovering Price Discovery" (with D. Lautier and B. Villeneuve) (job market paper)

(2023-06-01 version) https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4470521

(2024-04-16 version) https://www.researchgate.net/publication/371499955_Rediscovering_Price_Discovery

Accompanying R code: https://www.researchgate.net/publication/380087956_PriceDiscoveryMeasuresv10R

Accompanying code documentation: https://www.researchgate.net/publication/380087197_Rediscovering_Price_Discovery_-_The_Code_-_Documentation_-_2024-04-24pdf

We clarify the mixed signals from alternative price discovery metrics using VECM estimates. Based on a classical approach – a parametrized structural data-generating process that is fully identified – we rigorously reinterpret standard measures and unveil dead ends. Most microstructure analyses require the kind of basic dynamics estimation we propose. We also suggest the adoption of the Covariance Information Share (CovIS), a measure compatible with correlated data. Our theoretical contributions enhance existing literature and include formal propositions, complemented by methodological clarification through illustrative examples. These examples derive from simulated data for validation, and reanalysis of prior studies, with and without data samples. Additionally, we provide an annotated R code for replication. 

Keywords: Price discovery; Microstructure; Structural Moving Average representation; Information Shares; Cholesky decomposition; Vector Error Correction Model; Impulse Response Functions.

JEL Classification: C13; C32; G14

2. "Gold standards for price discovery: a moving picture" (with D. Lautier and B. Villeneuve)

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5212538

In the empirical literature on price discovery, it is common to compute and compare several measures of information shares. Contradictions between measures or studies are often met. To clarify this issue, we build upon recent advances in the structural analysis of the price discovery process. We show why, among the variety of price discovery measures, only three should be retained as the standards. These measures are interpretable and they correspond to three distinct and hierarchical definitions of leadership. In this context, there are no more contradictions, only different views on what leadership means. We illustrate this theoretical analysis through the case of gold, where many liquid markets interact: spot forex, futures contracts with different maturities, ETFs and other indexed funds. Whether a measure gives or not a type of leadership is testable via bootstrap. Some measures are stable over time and others are volatile, even in the easy case of gold. Going from still frame to moving picture, we show that the recent history of gold markets can be cut into periods of stability. 

Keywords: Price discovery, Information Shares, Arbitrage, Cointegration, VECM, Impulse Response Functions, Permanent-Transitory Decomposition, Spot, Futures, ETF, Precious Metals, Gold, Silver, Platinum

JEL Classification: C18; C32; G14; Q02

3. "Untangling Systemic Risk in Financialised Commodity Markets"

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3508275

Systemic risk is a multifaceted concept that is of crucial importance for regulators. In order to ensure financial stability, they need to properly assess this risk, preventing financial shocks from affecting the real economy. In this study, we assess the consequences of the financialization of commodity markets by considering a system consisting of both commodity futures and financial markets in a sparse Vector AutoRegression (VAR) framework. It allows to distinguish two facets of systemic risk: the risk that all markets move at the same time ("systematic" risk, related to market integration) and the risk of propagation of shocks from one market to others. In addition, the combination of the sparsity of the model and of graph theory, we can build measures to assess the relative importance of both markets and their links. It is also possible to visualise the evolution of the markets over time, hence facilitating their monitoring. We first apply this methodology to our whole sample: 51 time series or returns, representing 17 markets (3 maturities per asset) from 4 sectors (agriculture, energy, metals, finance) from 2000 to 2014. This static analysis on spot time series emphasises a sectorisation of those markets. Our results show the importance of the maturity dimensions when studying commodities, as they connect all the sectors and thus cause the integration of the whole system. In a dynamic analysis, we first give a broad overview of the evolution of the system in our sample and then focus notably on intriguing events in October 2008, shortly after the default of Lehman Brothers. The largest variations of the S&P500 index are followed, on the next day, by the largest price variations of some commodities. We find that the main component of systemic risk was integration, not propagation. This implies that, contrary to what we could think, financial shocks did not directly affect commodities.

Keywords: Commodity Markets, Derivatives, Market Integration, Shock Propagation, Financial Crises, LASSO, VAR, Graph Theory, Centrality.

JEL Classification: E44, G01, G14, Q02, Q14, Q40

4. "Exchange-Traded Products and Their Impact on Commodity Markets" (with D. Lautier, R. Lambinet and B. Villeneuve)

This article analyses the impact of Exchange-Traded Products (ETP) on commodity markets. We first develop an equilibrium model where three markets are linked to each other: the spot market, where the physical trading of the commodity takes place, and the associated futures and ETP markets. Arbitrage operations link spot, futures and ETP prices together. Thanks to the model, we can study the impact of the ETP, on the long run, on the variance of commodity spot and futures prices in different situations: i) when futures prices are in contango (stocks are abundant and arbitrage is easy) and when they are in backwardation (stocks are rare and arbitrage is difficult); ii) when the ETP relies on operations on the commodity itself (physical replication) and when it relies on futures transactions (synthetic replication). The model allows to define a Vector Error Correcting representation and to obtain a price discovery metrics in the case of three markets. On the basis of this measure, we perform empirical tests from 2004 to 2019. We show that, in our sample, the price discovery process is shared between the spot and the ETP markets, and that the latter is most of the time dominant in terms of information flows. Finally, we propose a method that allows for the identification of the days when ETPs are active on the futures and on the spot markets of the commodity. Controlling for other possible shocks we show, on a large sample of commodity ETPs, that when the ETPs are active, the price volatility of the commodity increases, with the exception of platinum. These results have implications for commodity production, storage and transformation decision making as well as for the regulation of commodity markets.

Keywords: Exchange-Traded Products, Futures markets, Commodity, Financialization, Price discovery, Price volatility

JEL Classification: C32, C51, G13, G14

5. "Are commodities Still Different from Other Asset Classes?" (with D. Lautier)

In light of the financialization of commodity markets, we want to assess the extent to which commodity markets behave like financial markets by confronting data to the theories on commodities and to the empirical literature. We thus study how spot returns behave, in particular when we account for the basis, which should theoretically provide information on the inventories on the market. This economic fundamental should be important for commodities, due to a nonnegativity constraint on physical inventories, but not for financial markets. We study 17 assets from 4 sectors. Our results are mostly consistent with the literature in terms of spot average return and standard deviation: the more difficult an asset is to store, the larger the standard deviation and average return. Markets thus group into sectors accordingly, also when conditioning on the sign of the basis, with the exception of crude oil and silver. Nevertheless, returns are not positively skewed in backwardation for all commodities. We also find that some commodity prices experience their most extreme returns on the day after the S&P500 does. Finally, we investigate the diversification potential of these commodities by looking for a potential common factor for all markets (with Principal Component Analysis). We find sectorisation again before 2004, but then commodities integrate, with financial markets joining after 2008. 

Keywords: Commodity Markets, Derivatives, Market Integration, Financial Shocks.

JEL Classification: E44, G01, G14, Q02, Q14, Q40