This proves the second part of equation (21). The proof of proposition 9
is the same for 7 = -∞.
Appendix H: Proof of Proposition 10
For a HARA-based risk function with 1 > 7 > -∞ the FOC (11) resp.
(14) yields
7-1
—% ⅛ — 1 + Si]; V i,ε,
(42)
or
. e,∙^ , . ,, i_ . . . ,
A + -----= (—% K — 1 + si ])7^1; V i,ε- (43)
1 — 7
Aggregating across investors yields A + eε /(1 — 7). Dividing the aggregate
equation by Ai + eiε∕(1 — 7) yields 1∕giε and hence,
1/9ie
=∑(
3 x
1 + Si] ∖ 1-τ
1 + s3'] /
(44)
so that
d(1∕gig) = ^ 1 / —% λ 1-7 / - — 1 + Si ∖ 1-7 1 Sj — si )
dε ʌl — 7 ∖~l∣jJ ∖πε — 1 + sJ K — 1 + s3)2 π ε'
(45)
Assume 7 < 1 and s⅛ ≤ sj Vi. Then πz(ε) < 0 implies d(1∕g⅛ε)∕dε < 0 so
that dghε∕dε > 0.
45
More intriguing information
1. A Hybrid Neural Network and Virtual Reality System for Spatial Language Processing2. The name is absent
3. The name is absent
4. Text of a letter
5. Evaluation of the Development Potential of Russian Cities
6. FASTER TRAINING IN NONLINEAR ICA USING MISEP
7. The name is absent
8. The name is absent
9. An Efficient Secure Multimodal Biometric Fusion Using Palmprint and Face Image
10. Spectral calibration of exponential Lévy Models [1]