London Business School

A sharp increase in the popularity of commodity investing in the past decade has triggered an unprecedented inflow of institutional funds into commodity futures markets. Such financialization of commodities coincided with significant booms and busts in commodity markets, raising concerns of policymakers. In this paper, we explore the effects of financialization in a model that features institutional investors alongside traditional futures markets participants. The institutional investors care about their performance relative to a commodity index. We find that if a commodity futures is included in the index, supply and demand shocks specific to that commodity spill over to all other commodity futures markets. In contrast, supply and demand shocks to a nonindex commodity affect just that commodity market alone. Moreover, prices and volatilities of all commodity futures go up, but more so for the index futures than for nonindex ones. Furthermore, financialization — the presence of institutional investors — leads to an increase in correlations amongst commodity futures as well as in equity-commodity correlations. Consistent with empirical evidence, the increases in the correlations between index commodities exceed those for nonindex ones. We model explicitly demand shocks which allows us to disentangle the effects of financialization from the effects of demand and supply (fundamentals). We perform a simple calibration and find that financialization accounts for 11% to 17% of commodity futures prices and the rest is attributable to fundamentals.

An interior-point method for solving mathematical programs with

equilibrium constraints (MPECs) is proposed. At each iteration of the

algorithm, a single primal-dual step is computed from each subproblem of

a sequence. Each subproblem is defined as a relaxation of the MPEC with

a nonempty strictly feasible region. In contrast to previous

approaches, the proposed relaxation scheme preserves the nonempty strict

feasibility of each subproblem even in the limit. Local and superlinear

convergence of the algorithm is proved even with a less restrictive

strict complementarity condition than the standard one. Moreover,

mechanisms for inducing global convergence in practice are proposed.

Numerical results on the MacMPEC test problem set demonstrate the

fast-local convergence properties of the algorithm.