Margrabe provides a pricing formula for an exchange option where the distributions of both stock prices are log-normal with correlated Wiener components. Merton has provided a formula for the price of a European call option on a single stock where the stock price process contains a continuous...

We propose a generalization of the Shirakawa (1991) model to capture the jump component in fixed income markets. The model is formulated under the Heath, Jarrow and Morton (1992) framework, and allows the presence of a Wiener noise and a finite number of Poisson noises, each associated with a...

This paper considers a class of Heath-Jarrow-Morton (1992) term structure models, characterized by time deterministic volatilities for the instantaneous forward rate. The bias that arises from using observed futures yields as a proxy for the unobserved instantaneous forward rate is analyzed. The...

Research on the Heath-Jarrow-Morton (1992) term structure models so far has focused on the class having time-deterministic instantaneous forward rate volatility. In this case the forward rate is Markovian, even if the spot rate process is not. However, this Markovian feature can only be used...

This paper introduces an easy to follow method for continuous time model estimation. It serves as an introduction on how to convert a state space model from continuous time to discrete time, how to decompose a hybrid stochastic model into a trend model plus a noise model, how to estimate the...

This paper seeks to model the adjustment process in the stock market by a continuous time state space model focusing on input-out relations. The value of the S&P 500 is generated as the output of the model with earnings and the interest rate as input. The model is found to fit the data well, and...

This paper seeks to model the adjustment process in the stock market by a continuous time state space model focusing on input-out relations. The value of the Samp;P 500 is generated as the output of the model with earnings and the interest rate as input. The model is found to fit the data well,...

This paper introduces an easy to follow method for continuous time model estimation. It serves as an introduction on how to convert a state space model from continuous time to discrete time, how to decompose a hybrid stochastic model into a trend model plus a noise model, how to estimate the...