Abstract
In this study, we propose a regime-switching model for temperature dynamics, where the parameters depend on a Markov chain. We improve upon the traditional models by modeling jumps in temperature dynamics via the chain itself. Moreover, we compare the performance of the proposed model with the existing models. The results indicate that the proposed model outperforms in the short time forecast horizon while the forecast performance of the proposed model is in line with the existing models for the long time horizon. It is shown that the proposed model is a relatively better representation of temperature dynamics compared to the existing models. Furthermore, we derive prices of weather derivatives written on several temperature indices.
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Appendix
Appendix
Threshold Autoregressive (TAR) model. Consider the 2-state version of the threshold autoregressive (TAR) model proposed by [42] given by
with
where \( \tau \) is the value of the threshold, see [21]. The estimation results of the 2-state TAR model for the deseasonalized temperature process are presented in Table 18, where the standard errors are given in parenthesis. Figure 16 shows the deseasonalized temperature data together with the TAR model threshold obtained from the estimation of the TAR model.
Proof of Lemma 2. Remember that, by Eq. (16), under \( \mathbb {P}, \)
By Lemma 1,
and
Hence, under \( \mathbb {Q}^{\theta } \) we can write
and by applying Itô’s Formula, the result follows. \(\square \)
Proof of Lemma 3. By Eq. (13), we have
From Eq. (46), we can write
and, thus,
Now, by Eq. (47), we have
Hence, by Eq. (61), we can write Eq. (60) as
Therefore, by putting Eq. (62) into Eq. (59), the result follows. \(\square \)
Proof of Theorem 1. Remember that by Eq. (4)
By Eq. (48) and Fubini’s Theorem, we have
since by the martingale property
It can be easily shown that
Thus, we have
and
Therefore, by inserting Eqs. (65) and (66) into Eq. (64), the result follows. \(\square \)
Proof of Lemma 4. Let be
and apply Itô’s Formula to \( e^{iuZ_{t}}\). Then,
We define for each \( s \le t \in [0, \mathsf {T}], \)\( \mathcal {\bar{G}}_{s, t}:= \mathcal {F}_{s}\vee \mathcal {F}^{\zeta }_{t}, \) which represents the enlarged \( \sigma \)-field generated by \( \mathcal {F}_{s} \) and \( \mathcal {F}^{\zeta }_{t}\). Moreover, write \( {\bar{\mathbf {G}}}:= ( \mathcal {\bar{G}}_{s, t}: \ s, t \in [0, \mathsf {T}] ) \) for the corresponding complete enlarged filtration. Let \( \varPhi _{Z_{t}|\mathcal {\bar{G}}_{s, t}} (u) \) denote the characteristic function of \( Z_{t} \) conditional on \( \mathcal {\bar{G}}_{s, t}; \) that is,
Then, from above we obtain
For notational convenience, we simply write \( \mathbf {B}^{\theta }(t)=\mathbf {B}^{\theta }(t,u). \) Let \( \mathbf {D}^{\theta }(t) := (d_{jl}^{\theta }(t))_{j,l=1, \ldots , N}, \) where
Notice that \( d_{jl}^{\theta }(t) = b_{jl}^{\theta }(t)/a_{jl}^{\theta }, \) for each \( j, l= 1, \ldots , N\). Define \( \mathbf {D}_{0}^{\theta }(t) := \mathbf {D}^{\theta }(t) - diag[d^{\theta }(t)], \) where \( d^{\theta }(t) = (d_{11}^{\theta }(t), \ldots , d_{NN}^{\theta }(t))' \in \mathbb {R}^{N}\). Then, we can write
where \( \mathcal {M}^{\theta }_{t}=(\mathcal {M}^{\theta 1}_{t}, \ldots , \mathcal {M}^{\theta N}_{t})' \in \mathbb {R}^{N}\). It can be easily shown that, by Remark 1, we can write
with
Therefore, Eq. (68) can be written as
We define
By Itô’s Formula we obtain
Here, we used \( \varPhi _{Z_{t}|\mathcal {\bar{G}}_{s, t}} (u) \zeta _{t} \langle g(t, u), \zeta _{t} \rangle = diag[ g(t, u)] \zeta _{t}\varPhi _{Z_{t}|\mathcal {\bar{G}}_{s, t}} (u)\).
Now, by using
we can write
It can be easily shown that
Hence, we can write
since
and
Thus, by combining Eqs. (73) and (74), we get
Thus, by Eqs. (75), (72) becomes
Therefore, by Fubini’s Theorem and using the martingale property, we have
Thus, we get
and after solving we have
Notice that
since \( \langle \zeta _{t}, \mathbf {1} \rangle = 1\).
Now, by the tower property and Eq. (78), we have
Therefore the result follows by Eq. (77). \(\square \)
Proof of Theorem 2. Remember that by Eq. (5)
Now by Lemma 5, we can write
Thus, by Eq. (79) and Fubini’s Theorem,
where \( \varPhi _{Y_{t}|\mathcal {G}_{s}} (u) = \mathbb {E}^{\theta } \left[ e^{iuY_{t}} | \mathcal {G}_{s}\right] \) is given by Eq. (54).
Therefore, by Fubini’s Theorem and Eq. (80), we obtain
We notice that, by Lemma 4,
Therefore, the result follows. \(\square \)
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Türkvatan, A., Hayfavi, A. & Omay, T. A regime switching model for temperature modeling and applications to weather derivatives pricing. Math Finan Econ 14, 1–42 (2020). https://doi.org/10.1007/s11579-019-00242-0
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DOI: https://doi.org/10.1007/s11579-019-00242-0