  The objective of the paper is to price weather contracts using temperature as
the underlying process when the later follows a mean-reverting dynamics driven
by a time-changed Brownian motion coupled to a Gamma Levy subordinator and
time-dependent deterministic volatility. This type of model captures the
complexity of the temperature dynamic providing a more accurate valuation of
their associate weather contracts. An approximated price is obtained by a
Fourier expansion of its characteristic function combined with a selection of
the equivalent martingale measure following the Esscher transform proposed in
Gerber and Shiu (1994).
