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Long Term Risk: A Martingale Approach

Likuan Qin, Northwestern University - Department of Industrial Engineering and Management Sciences
Vadim Linetsky, Northwestern University - Department of Industrial Engineering and Management Sciences


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LIKUAN QIN, Northwestern University - Department of Industrial Engineering and Management Sciences
VADIM LINETSKY, Northwestern University - Department of Industrial Engineering and Management Sciences

This paper extends the long-term factorization of the pricing kernel due to Alvarez and Jermann (2005) in discrete time ergodic environments and Hansen and Scheinkman (2009) in continuous ergodic Markovian environments to general semimartingale environments, without assuming the Markov property. An explicit and easy to verify sufficient condition is given that guarantees convergence in Emery’s semimartingale topology of the trading strategies that invest in T-maturity zero-coupon bonds to the long bond and convergence in total variation of T-maturity forward measures to the long forward measure. As applications, we explicitly construct long-term factorizations in generally non-Markovian Heath-Jarrow-Morton (1992) models evolving the forward curve in a suitable Hilbert space and in the non-Markovian model of social discount of rates of Brody and Hughston (2013). As a further application, we extend Hansen and Jagannathan (1991), Alvarez and Jermann (2005) and Bakshi and Chabi-Yo (2012) bounds to general semimartingale environments. When Markovian and ergodicity assumptions are added to our framework, we recover the long-term factorization of Hansen and Scheinkman (2009) and explicitly identify their distorted probability measure with the long forward measure. Finally, we give an economic interpretation of the recovery theorem of Ross (2013) in non-Markovian economies as a structural restriction on the pricing kernel leading to the growth optimality of the long bond and identification of the physical measure with the long forward measure. This latter result extends the interpretation of Ross’ recovery by Boroviˇ cka et al. (2014) from Markovian to general semimartingale environments.


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