Hedging options in a garch environment: testing the term structure of stochastic volatility models

This paper develops a methodology for testing the term structure of volatility forecasts derived from stochastic volatility models, and implements it to analyze models of S&P500 index volatility. U sing measurements of the ability of volatility models to hedge and value term structure dependent option positions, we fmd that hedging tests support the Black-Scholes delta and gamma hedges, but not the simple vega hedge when there is no model of the term structure of volatility. With various models, it is difficult to improve on a simple gamma hedge assuming constant volatility. Ofthe volatility models, the GARCH components estimate of term structure is preferred. Valuation tests indicate that all the models contain term structure information not incorporated in market prices.

Simulation-based smoothing and filtering in factor stochastic volatility models : two econometric applications

In this article we use factor models to describe a certain class of covariance structure for financiaI time series models. More specifical1y, we concentrate on situations where the factor variances are modeled by a multivariate stochastic volatility structure. We build on previous work by allowing the factor loadings, in the factor mo deI structure, to have a time-varying structure and to capture changes in asset weights over time motivated by applications with multi pIe time series of daily exchange rates. We explore and discuss potential extensions to the models exposed here in the prediction area. This discussion leads to open issues on real time implementation and natural model comparisons.

Simulation -based smoothing and filtering in factor stochastic volatility models : two econometric applications (July-2001)

The past decade has wítenessed a series of (well accepted and defined) financial crises periods in the world economy. Most of these events aI,"e country specific and eventually spreaded out across neighbor countries, with the concept of vicinity extrapolating the geographic maps and entering the contagion maps. Unfortunately, what contagion represents and how to measure it are still unanswered questions. In this article we measure the transmission of shocks by cross-market correlation\ coefficients following Forbes and Rigobon's (2000) notion of shift-contagion,. Our main contribution relies upon the use of traditional factor model techniques combined with stochastic volatility mo deIs to study the dependence among Latin American stock price indexes and the North American indexo More specifically, we concentrate on situations where the factor variances are modeled by a multivariate stochastic volatility structure. From a theoretical perspective, we improve currently available methodology by allowing the factor loadings, in the factor model structure, to have a time-varying structure and to capture changes in the series' weights over time. By doing this, we believe that changes and interventions experienced by those five countries are well accommodated by our models which learns and adapts reasonably fast to those economic and idiosyncratic shocks. We empirically show that the time varying covariance structure can be modeled by one or two common factors and that some sort of contagion is present in most of the series' covariances during periods of economical instability, or crisis. Open issues on real time implementation and natural model comparisons are thoroughly discussed.

A Numerical method for the semilinear stochastic transport equation

Trabalho apresentado no XXXV CNMAC, Natal-RN, 2014.

Computer simulation of the stochastic transport equation

Trabalho apresentado no 37th Conference on Stochastic Processes and their Applications - July 28 - August 01, 2014 -Universidad de Buenos Aires

Numerical integration of coupled stochastic oscillators driven by Random Forces

Trabalho apresentado no International Conference on Scientific Computation And Differential Equations 2015

Convergence analysis of sampling-based decomposition methods for risk-averse multistage stochastic convex programs

We consider a class of sampling-based decomposition methods to solve risk-averse multistage stochastic convex programs. We prove a formula for the computation of the cuts necessary to build the outer linearizations of the recourse functions. This formula can be used to obtain an efficient implementation of Stochastic Dual Dynamic Programming applied to convex nonlinear problems. We prove the almost sure convergence of these decomposition methods when the relatively complete recourse assumption holds. We also prove the almost sure convergence of these algorithms when applied to risk-averse multistage stochastic linear programs that do not satisfy the relatively complete recourse assumption. The analysis is first done assuming the underlying stochastic process is interstage independent and discrete, with a finite set of possible realizations at each stage. We then indicate two ways of extending the methods and convergence analysis to the case when the process is interstage dependent.

Multistep stochastic mirror descent for risk-averse convex stochastic programs based on extended polyhedral risk measures

We consider risk-averse convex stochastic programs expressed in terms of extended polyhedral risk measures. We derive computable con dence intervals on the optimal value of such stochastic programs using the Robust Stochastic Approximation and the Stochastic Mirror Descent (SMD) algorithms. When the objective functions are uniformly convex, we also propose a multistep extension of the Stochastic Mirror Descent algorithm and obtain con dence intervals on both the optimal values and optimal solutions. Numerical simulations show that our con dence intervals are much less conservative and are quicker to compute than previously obtained con dence intervals for SMD and that the multistep Stochastic Mirror Descent algorithm can obtain a good approximate solution much quicker than its nonmultistep counterpart. Our con dence intervals are also more reliable than asymptotic con dence intervals when the sample size is not much larger than the problem size.

Non-asymptotic confidence bounds for the optimal value of a stochastic program

We discuss a general approach to building non-asymptotic confidence bounds for stochastic optimization problems. Our principal contribution is the observation that a Sample Average Approximation of a problem supplies upper and lower bounds for the optimal value of the problem which are essentially better than the quality of the corresponding optimal solutions. At the same time, such bounds are more reliable than “standard” confidence bounds obtained through the asymptotic approach. We also discuss bounding the optimal value of MinMax Stochastic Optimization and stochastically constrained problems. We conclude with a small simulation study illustrating the numerical behavior of the proposed bounds.

Balance of payments dominance: its implications for macroeconomic policy

This paper defines “balance of payments dominance” as a macroeconomic regime in which the short-term macroeconomic dynamics is essentially determined by external shocks, positive or negative. It argues that this is the predominant regime in emerging and developing countries. Trade shocks play an important role but the major procyclical shocks are associated with boom-bust cycles in external financing. Policy challenges are associated not only with the management of such shocks but also with the need to enhance the space for countercyclical macroeconomic policies, as boom-bust cycles tend to pressure macroeconomic policies to behave in a procyclical way. Under these conditions, the best bet is to design policies to reduce external vulnerabilities through a mix of administered exchange rate policies, very active foreign exchange reserve management, reduced reliance on external borrowing, and macroprudential regulations, including those directly affecting capital flows. Countercyclical fiscal policy can also play a role but face strong economic and political economy challenges.

Stochastic discount factor bounds and rare events: a review

We aim to provide a review of the stochastic discount factor bounds usually applied to diagnose asset pricing models. In particular, we mainly discuss the bounds used to analyze the disaster model of Barro (2006). Our attention is focused in this disaster model since the stochastic discount factor bounds that are applied to study the performance of disaster models usually consider the approach of Barro (2006). We first present the entropy bounds that provide a diagnosis of the analyzed disaster model which are the methods of Almeida and Garcia (2012, 2016); Ghosh et al. (2016). Then, we discuss how their results according to the disaster model are related to each other and also present the findings of other methodologies that are similar to these bounds but provide different evidence about the performance of the framework developed by Barro (2006).

Balance of payments dominance : its implocations for macroeconomic policy

This paper defines “balance of payments dominance” as a macroeconomic regime in which the short-term macroeconomic dynamics is essentially determined by external shocks, positive or negative. It argues that this is the predominant regime in emerging and developing countries. Trade shocks play an important role but the major procyclical shocks are associated with boom-bust cycles in external financing. Policy challenges are associated not only with the management of such shocks but also with the need to enhance the space for countercyclical macroeconomic policies, as boom-bust cycles tend to pressure macroeconomic policies to behave in a procyclical way. Under these conditions, the best bet is to design policies to reduce external vulnerabilities through a mix of administered exchange rate flexibility, very active foreign exchange reserve management, reduced reliance on external borrowing, and macroprudential regulations, including those directly affecting capital flows. Countercyclical fiscal policy can also play a role but face strong economic and political economy challenges.

Contested dominance modifies the anovulatory consequences of social subordination in female marmosets

Dominance status among female marmosets is reflected in agonistic behavior and ovarian function. Socially dominant females receive submissive behavior from subordinates, while exhibiting normal ovulatory function. Subordinate females, however, receive agonistic behavior from dominants, while exhibiting reduced or absent ovulatory function. Such disparity in female fertility is not absolute, and groups with two breeding females have been described. The data reported here were obtained from 8 female-female pairs of captive female marmosets, each housed with a single unrelated male. Pairs were classified into two groups: “uncontested” dominance (UD) and “contested” dominance (CD), with 4 pairs each. Dominant females in UD pairs showed significantly higher frequencies (4.1) of agonism (piloerection, attack and chasing) than their subordinates (0.36), and agonistic behaviors were overall more frequently displayed by CD than by UD pairs. Subordinates in CD pairs exhibited more agonistic behavior (2.9) than subordinates in UD pairs (0.36), which displayed significantly more submissive (6.97) behaviors than their dominants (0.35). The data suggest that there is more than one kind of dominance relationship between female common marmosets. Assessment of progesterone levels showed that while subordinates in UD pairs appeared to be anovulatory, the degree of ovulatory disruption in subordinates of CD pairs was more varied and less complete. We suggest that such variation in female-female social dominance relationships and the associated variation in the degree and reliability of fertility suppression may explain variations of the reproductive condition of free-living groups of common marmosets

Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Dominance of legume trees alters nutrient relations in mixed species forest restoration plantings within seven years

Failures in reforestation are often attributed to nutrient limitation for tree growth. We compared tree performance and nitrogen and phosphorus relations in adjacent mixed-species plantings of contrasting composition, established for forest restoration on Ultisol soil, originally covered by tropical semi-deciduous Atlantic Forest in Southeast Brazil. Nutrient relations of four tree species occurring in both planting mixtures were compared between a legume-dominated, species-poor direct seeding mixture of early-successional species ("legume mixture"), and a species-diverse, legume-poor mixture of all successional groups ("diverse mixture"). After 7 years, the legume mixture had 6-fold higher abundance of N(2)-fixing trees, 177% higher total tree basal area, 22% lower litter C/N, six-fold higher in situ soil resin-nitrate, and 40% lower in situ soil resin-P, compared to the diverse mixture. In the legume mixture, non-N(2)-fixing legume Schizolobium parahyba (Fabaceae-Caesalpinioideae) had significantly lower proportional N resorption, and both naturally regenerating non-legume trees had significantly higher leaf N concentrations, and higher proportional P resorption, than in the diverse mixture. This demonstrate forms of plastic adjustment in all three non-N(2)-fixing species to diverged nutrient relations between mixtures. By contrast, leaf nutrient relations in N(2)-fixing Enterolobium contortisiliquum (Fabaceae-Mimosoideae) did not respond to planting mixtures. Rapid N accumulation in the legume mixture caused excess soil nitrification over nitrate immobilization and tighter P recycling compared with the diverse mixture. The legume mixture succeeded in accelerating tree growth and canopy closure, but may imply periods of N losses and possibly P limitation. Incorporation of species with efficient nitrate uptake and P mobilization from resistant soil pools offers potential to optimize these tradeoffs.