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w h e r e h q β c a p t u r e s t h e p o r t i o n o f t h e l o c a l p r o j e c t i o n d u e t o a d j u s t m e n t t o t h e l o n g -

term equilibrium PPP condition captured by q , but where the total local projection

d e p e n d s a l s o f r o m a n y s h o r t - t e r m f r i c t i o n s i n t h e t e r m s h h e π β β + , w h i c h n e e d t o b e

a d d e d t o h q β t o o b t a i n t h e c o m p l e t e r e s p o n s e . T h e r e s u l t s a s s o c i a t e d w i t h t h i s a n a l y s i s

are reported in greater detail in section 4.

3.2 Design of the Predictive Ability Tests The second part of our analysis presents a more realistic practical scenario in which a trader is interested in pursuing the carry trade and considers how best to achieve predictable positive returns. Our trader will face a number of constraints that are dictated by the data, such as three month holding periods and trades at one-month horizons only. These are clearly far longer than the daily frequency that likely characterizes such trades. On the other hand, we will not include trading costs in our analysis. Our results are meant to be suggestive rather than a realistic trading strategy.

Our starting point will be predictive regressions based on expression (2) but where the frequency of the data is monthly rather than quarterly, and hence indicated with a $t$ subscript. In particular, the ex-post profits of a carry trade can be characterized as

mt+3

= (et+3

) ( ) * t t t i i e +

w h e r e n o t i c e t h a t ( t t i i * ) r e f e r s t o t h e i n t e r e s t r a t e d i f f e r e n t i a l i n g o v e r n m e n t

instruments that mature in three-months and hence known at time t . The only variable that needs to be predicted in the previous expression is et+3 and a natural way to do

this is by adapting expression (2) as follows:

e j,t+3

ej,t

= j δ

+ψ e (ej,t

ej,t3

) +ψ π (π

* j,t

π j,t ) +

(5)

ψ q (q j,t

q j ) +ψ i (i

* j,t

ij,t ) +ψ vVXt + u j,t+3

11

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