Applications of state space models in finance

144 7 A Kalman filter based conditional multifactor pricing model
β VGR
1
0
−1
−2
−3
−4
−5
(a) Technology
1994 1998 2002
β VGR
1.0
0.5
0.0
−0.5
−1.0
(b) Food & Beverages
1994 1998 2002
Figure 7.1: V GR factor loadings for Technology and Food & Beverages.
characteristics of the sector. As can be seen from Panel (b), the market perception of
whether the Food & Beverages sector has more growth or more value attributes changes
over time. Four distinct regimes can be identified. Until October 1997, the V GR beta of
the sector moves around zero. Over the subsequent two years, when the whole market
rose and growth outperformed value, the beta becomes slightly negative. After the
market peaked in March 2000, the V GR beta of Food & Beverages turns positive. This
is intuitive given the sector’s defensive characteristics: market participants exited the
overcrowded and expensive growth segments of the market and looked for cheaper and
safer alternatives such as Food & Beverages. This led to a rising V GR beta. At the
end of the sample, the estimated sensitivity returns toward zero, which means that the
value-growth spread no longer represents a systematic risk factor of the sector. The
observation that the V GR beta is only significantly different from zero around the TMT
bubble holds for other sectors as well.
Figure 7.2 displays the time-varying size exposure for Industrials and Healthcare.
While the Industrials sector index is comprised of many small caps, the Healthcare sector
β SIZ
1.0
0.5
0.0
−0.5
−1.0
(a) Industrials
1994 1998 2002
β SIZ
2.0
1.5
1.0
0.5
0.0
(b) Healthcare
1994 1998 2002
Figure 7.2: SIZ factor loadings for Industrials and Healthcare.