Raphaël Homayoun Boroumand

A regime-switching model to evaluate bonds in a quadratic term structure of interest rates

In this article, we consider a discrete-time economy in which we assume that the short-term interest rate follows a quadratic term structure in a regime-switching asset process. The possible nonlinear structure and the fact that the interest rate can have different economic or financial trends justify regime-switching quadratic term structure model. Indeed, this regime-switching process depends on the values of a Markov chain with a time-dependent transition probability matrix which can capture the different states (regimes) of the economy. We prove that under this model, the conditional zero-coupon bond price admits a quadratic term structure. Moreover, the stochastic coefficients which appear in this decomposition satisfy an explicit system of coupled stochastic backward recursions.

Correlation evidence in the dynamics of agricultural commodity prices

The article studies the correlation structures of a large panel of agricultural commodities prices between January 1990 and February 2014. We use a various collection of mathematical and statistical methodologies (estimated correlation matrix and principal component analysis) to capture these correlations. Our results show that there exist different degrees of correlation between commodities. We also demonstrate, through data mining analysis, that there are hidden correlations between some commodities. Indeed, some commodities’ price behaviours are very similar in trend. Our results contribute to a better understanding of agricultural prices’ behaviours by producers, investors and market intermediaries. The results contribute to a more efficient strategic asset allocation process within agricultural markets.

Intraday hedging with financial options: the case of electricity

ABSTRACT As market intermediaries, electricity suppliers purchase electricity from the wholesale market or self-generate to deliver their customers. However, electricity suppliers are uncertain about how much electricity their residential customers will use at any hour of the day until they actually turn switches on. While demand uncertainty is a common feature of all commodity markets, suppliers generally rely on storage to manage it. Singularly, electricity suppliers are exposed to joint volumetric and price risk on an hourly basis given the physical attributes of electricity. In the literature on electricity markets, few articles compare the efficiency of forward contracts, options and physical assets (i.e. power plants) within intraday hourly hedging portfolios, whereas electricity markets are precisely hourly markets. We analyse portfolios made of forwards, options and/or power plants for specific hourly clusters (9 am, 12 pm, 18 pm, 9 pm) based on electricity market data from 2013 to 2015 from the integrated German–Austrian spot market. Through a VaR model, we prove that intraday hedging with forwards is structurally inefficient compared to financial options and physical assets, no matter the cluster hour. Moreover, our results demonstrate the contribution of ‘out of the money’ options for all hours within volatile spot markets.

Jumps and volatility dynamics in agricultural commodity spot prices

ABSTRACT The spot commodities market exhibits both extreme volatility and price spikes, which lead to heavy-tailed distributions of price change and autocorrelation. This article uses various Lévy jump models to capture these features in a panel of agricultural commodities observed between January 1990 and February 2014. The results show that Levy jump models outperform the continuous Gaussian model. Our results prove that assuming a constant volatility or even a deterministic volatility and drift structure of agricultural commodity spot prices is not realistic and is less efficient than the stochastic assumption. The findings demonstrate an interesting correlation between volatility and jumps for a given commodity i, but no relationship between the volatility of commodity i and the probability of jumps of commodity j.