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Fund liquidation, self-selection and look-ahead bias in the hedge ...

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If w 2,it<br />

implies <strong>look</strong>-<strong>ahead</strong> <strong>bias</strong> if w 1,it<br />

≠1<strong>and</strong> this is <strong>the</strong> case analyzed<br />

<strong>liquidation</strong><br />

Baquero, ter Horst <strong>and</strong> Verbeek (2005). In this paper, we disentangle<br />

by<br />

two sources of <strong>bias</strong> by identify<strong>in</strong>g both sets of weights <strong>and</strong> apply<strong>in</strong>g<br />

<strong>the</strong><br />

with one weight or <strong>the</strong>ir product. The correction for <strong>self</strong>-<strong>selection</strong><br />

corrections<br />

application of <strong>the</strong> above<br />

The<br />

weights allows us to determ<strong>in</strong>e to what extent we get different<br />

correction<br />

if we only correct for <strong>selection</strong> <strong>bias</strong> due to <strong>liquidation</strong>, assum<strong>in</strong>g<br />

results<br />

is r<strong>and</strong>om.<br />

<strong>self</strong>-<strong>selection</strong><br />

identify <strong>the</strong> weights (<strong>and</strong> to derive (8)) we need to assume that <strong>the</strong><br />

To<br />

do not depend upon future, potentially unobserved returns.<br />

probabilities<br />

we assume that <strong>self</strong>-<strong>selection</strong> <strong>and</strong> fund <strong>liquidation</strong> are mutually<br />

Fur<strong>the</strong>r,<br />

events, <strong>and</strong> both describe “absorb<strong>in</strong>g states”. That is, once a fund<br />

exclusive<br />

Then <strong>the</strong> denom<strong>in</strong>ator of w 1,it<br />

P {Y 1,it =1|Ω t ,z it } = (10)<br />

similarly for w 2,it . The right h<strong>and</strong> side probabilities are described by<br />

<strong>and</strong><br />

probit model <strong>in</strong> (3) provided <strong>the</strong> appropriate functional form (<strong>and</strong> con-<br />

<strong>the</strong><br />

variables) are chosen <strong>in</strong> x it . Consequently, consistent estimation<br />

dition<strong>in</strong>g<br />

<strong>the</strong> b<strong>in</strong>ary choice models for <strong>liquidation</strong> <strong>and</strong> <strong>self</strong>-<strong>selection</strong> allows us to<br />

of<br />

consistent estimators for <strong>the</strong> two sets of weights, which enables us<br />

obta<strong>in</strong><br />

correct for <strong>look</strong>-<strong>ahead</strong> <strong>bias</strong> due to <strong>the</strong>se two processes <strong>and</strong> separate <strong>the</strong>ir<br />

to<br />

Statistically, equation (9) also holds with <strong>the</strong> role of Y1,it <strong>and</strong> Y2,it reversed, so that<br />

8<br />

correction for <strong>liquidation</strong> <strong>bias</strong> would be conditional upon <strong>the</strong> fund not stopp<strong>in</strong>g re-<br />

<strong>the</strong><br />

Given that exist<strong>in</strong>g literature (Baquero, ter Horst <strong>and</strong> Verbeek, 2005) assumes<br />

port<strong>in</strong>g.<br />

is exogenous (w2,it =1), <strong>the</strong> most natural order<strong>in</strong>g is employed here.<br />

<strong>self</strong>-<strong>selection</strong><br />

(8) as<br />

{Y it<br />

=1|Ω t<br />

}<br />

P<br />

{Y it =1|Ω t ,z it } = (9)<br />

P<br />

w it<br />

=<br />

{Y 2,it<br />

=1|Ω t<br />

,Y 1,it<br />

=1}<br />

P<br />

{Y 2,it<br />

=1|Ω t<br />

,z it<br />

,Y 1,it<br />

=1} × P {Y 1,it<br />

=1|Ω t<br />

}<br />

P<br />

=<br />

P {Y 1,it<br />

=1|Ω t<br />

,z it<br />

}<br />

= w 2,it w 1,it .<br />

1for all i, t, <strong>the</strong>n <strong>self</strong>-<strong>selection</strong> is exogenous <strong>and</strong> does not lead<br />

=<br />

<strong>look</strong>-<strong>ahead</strong> <strong>bias</strong> <strong>in</strong> measures for performance (persistence). In this case,<br />

to<br />

is conditional upon <strong>the</strong> fund not liquidat<strong>in</strong>g. 8<br />

stops report<strong>in</strong>g to TASS, it will not return <strong>in</strong> <strong>the</strong> database at a later stage.<br />

can be determ<strong>in</strong>ed from <strong>the</strong> b<strong>in</strong>ary choice<br />

model as<br />

P {L i,t+1<br />

=1|r it<br />

,r i,t−1, ..., x i,t+1}...P {L i,t+s+1<br />

=1|r i,t+s,r i,t+s−1,...,x i,t+s+1}<br />

16

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