Silvia Romagnoli

A copula-based model of speculative price dynamics in discrete time

This paper suggests a new technique to construct first order Markov processes using products of copula functions, in the spirit of Darsow et al. (1992) [10]. The approach requires the definition of (i) a sequence of distribution functions of the increments of the process, and (ii) a sequence of copula functions representing dependence between each increment of the process and the corresponding level of the process before the increment. The paper shows how to use the approach to build several kinds of processes (stable, elliptical, Farlie-Gumbel-Morgenstern, Archimedean and martingale processes), and how to extend the analysis to the multivariate setting. The technique turns out to be well suited to provide a discrete time representation of the dynamics of innovations to financial prices under the restrictions imposed by the Efficient Market Hypothesis.

Optimal hedge ratio under a subjective re-weighting of the original measure

In this article we study a risk-minimizing hedge ratio with futures contracts, where the risk of the hedged portfolio is measured through a spectral risk measure (SRM), thus incorporating the degree of agent’s risk aversion. We empirically estimate the optimal hedge ratio (OHR) using a long time series of UK and US equity indices, the EURUSD and EURGBP exchange rates and four liquid commodities (Brent crude oil, corn, gold and copper), to represent different asset classes. Comparing the results with common OHRs (such as the minimum variance and the minimum expected shortfall), we find that the agent’s risk aversion has a material impact, and should not be ignored in risk management.

A Continuous-Time Model of the Term Structure of Interest Rates with Fiscal-Monetary Policy Interactions

We study the term structure implications of the fiscal theory of price level determination. We introduce the intertemporal budget constraint of the government in a general equilibrium model in continuous time. Fiscal policy is set according to a simple rule whereby taxes react proportionally to real debt. We show how to solve for the prices of real and nominal zero coupon bonds.

A generalized approach to optimal hedging with option contracts

In this paper, we develop a theoretical model in which a firm hedges a spot position using options in the presence of both quantity (production) and basis risks. Our optimal hedge ratio is fairly general, in that the dependence structure is modeled through a copula function representing the quantiles of the hedged position, and hence any quantile risk measure can be employed. We study the sensitivity of the exercise price which minimizes the risk of the hedged portfolio to the relevant parameters, and we find that the subjective risk aversion of the firm does not play any role. The only trade-off is between the effectiveness and cost of the hedging strategy.

Optimal Corporate Hedging Using Options with Basis and Production Risk

In this paper we investigate the optimal hedging strategy for a firm using option contracts, where both the role of production (quantity) and basis (proxy) risk are considered. Contrary to the existing literature, we find that the exercise price which minimizes the shortfall of the hedged portfolio is primarily affected by the amount of cash spent on the hedging program. Also, we decompose the effect of quantity and proxy risk showing that the latter greatly affects hedging effectiveness while the former drives the choice of the optimal option contract. Finally, fitting the model parameters to match a financial turmoil scenario confirms that choosing a suboptimal option moneyness leads to a non-negligible economic loss.

Measure-invariance of copula functions as tool for testing no-arbitrage assumption

Abstract Copulas, which are invariant under margins’ transforms induced by some change of measure, are investigated. It is emphasized that this particular kind of transforms induced by some change of measure, largely used in pricing techniques, preserves the invariance of the aggregation operator and a sufficient condition to assure it is proved. The discussion is extended to the time-preserving of measure-invariance; a characterization of its stability in time for multivariate stationary processes, based on the dynamic copula representation (see Cherubini et al., 2011), is provided. Finally a measure invariance-based statistical test for the absence of arbitrage opportunity assumption and its preservation in time is proposed and an empirical experiment based on quotes of S&P 500 futures and options traded on the Chicago Mercantile Exchange (CME) is discussed.

Distorted Copula-Based Probability Distribution of a Counting Hierarchical Variable: A Credit Risk Application

In this paper, we propose a novel approach for the computation of the probability distribution of a counting variable linked to a multivariate hierarchical Archimedean copula function. The hierarchy has a twofold impact: it acts on the aggregation step but also it determines the arrival policy of the random event. The novelty of this work is to introduce this policy, formalized as an arrival matrix, i.e., a random matrix of dependent 0–1 random variables, into the model. This arrival matrix represents the set of distorted (by the policy itself) combinatorial distributions of the event, i.e., of the most probable scenarios. To this distorted version of the CHC approach [see Ref. 7 and Ref. 27], we are now able to apply a pure hierarchical Archimedean dependence structure among variables. As an empirical application, we study the problem of evaluating the probability distribution of losses related to the default of various type of counterparts in a structured portfolio exposed to the credit risk of a selected set among the major banks of European area and to the correlations among these risks.