Browsing by Author "Schwartz, Eduardo S."
Now showing 1 - 4 of 4
Results Per Page
Sort Options
- ItemCommodity Price Forecasts, Futures Prices, and Pricing Models(2019) Cortázar S., Gonzalo; Millard, Cristóbal; Ortega González, Héctor Iván; Schwartz, Eduardo S.
- ItemCredit Spreads in Illiquid Markets: Model and Implementation(ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD, 2012) Cortazar, Gonzalo; Schwartz, Eduardo S.; Tapia, ClaudioThis paper presents a methodology for estimating a family of credit spread term structures in a market with few transactions. The authors propose partitioning the market into risk classes and modeling credit spread term structures for each risk class using a multifactor Vasicek model with some common and some risk class-specific factors. The approach uses information on the cross section and time series of corporate bonds in all the risk classes to estimate the term structure of credit spreads in each risk class. The model is jointly estimated using an extended Kalman filter and implemented using Chilean corporate and government bonds.
- ItemExpected commodity returns and pricing models(2015) Cortázar S., Gonzalo; Kovacevic, Ivo; Schwartz, Eduardo S.
- ItemTerm-structure estimation in markets with infrequent trading(WILEY-BLACKWELL, 2007) Cortazar, Gonzalo; Schwartz, Eduardo S.; Naranjo, Lorenzo F.There are two issues that are of central importance in term-structure analysis. One is the modelling and estimation of the current term structure of spot rates. The second is the modelling and estimation of the dynamics of the term structure. These two issues have been addressed independently in the literature. The methods that have been proposed assume a sufficiently complete price data set and are generally implemented separately. However, there are serious problems when these methods are applied to markets with sparse bond prices. We develop a method for jointly estimating the current term-structure and its dynamics for markets with infrequent trading. We propose solving both issues by using a dynamic term-structure model estimated from incomplete panel-data. To achieve this, we modify the standard Kalman filter approach to deal with the missing-observation problem. In this way, we can use historic price data in a dynamic model to estimate the current term structure. With this approach we are able to obtain an estimate of the current term structure even for days with an arbitrary low number of price observations. The proposed methodology can be applied to a broad class of continuous-time term-structure models with any number of stochastic factors. To show the implementation of the approach, we estimate a three-factor generalized-Vasicek model using Chilean government bond price data. The approach, however, may be used in any market with infrequent trading, a common characteristic of many emerging markets. Copyright (c) 2007 John Wiley & Sons, Ltd.