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Changes in multiplicative risks and optimal portfolio choice: new interpretations and results

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Abstract

This paper reconsiders the conditions determining the optimal response of a decision maker in case of stochastic changes in multiplicative risks. In particular, we focus on an optimal portfolio choice where the return of the risky asset exhibits an Nth-degree risk increase. We provide two interpretations of the conditions analyzed. The first interpretation involves a comparison between the elasticities with respect to the investment in the risky asset of the Nth derivative of the utility function and of the distance between the Nth moments of the two risks. The second interpretation refers to the direction of the change in the utility premium when the investment in the risky asset changes. We then study the linkages between the conditions determining optimal responses of risky investment in the case of risk increases of different degrees. We show that, under some assumptions, the optimal behavior of an agent in the case of Nth degree risk increase makes it possible to infer agent’s behavior in case of risk increases of lower degrees.

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Notes

  1. The reverse is not true: An increase in variance with an unchanged expected value does not imply a mean-preserving spread.

  2. The case of changes in risk involving first-order stochastic dominance in an optimal portfolio problem is studied by Fishburn and Porter (1976); Hadar and Seo (1990). extend the analysis to the case with two risky assets.

  3. A risk is additive when it is summed to the choice variable.

  4. Results similar to those derived in the next sections of the paper can be obtained in the case of two risky assets under the hypothesis that their random returns are independent.

  5. This condition is automatically satisfied under the classical assumption of concavity of the utility function.

  6. It is possible indeed to represent every moment of the distribution of a random variable as a function of the iterated integrals of the cumulative distribution function, applying the integration by parts formula in an iterative way.

  7. Rothschild and Stiglitz (1970) define this as a mean-preserving increase in risk.

  8. This is called increase in downside risk by Menezes et al. (1980). Moreover, Menezes and Wang (2005) define increase in outer risk a fourth-degree risk increase.

  9. This function is alternatively called “partial relative nth-degree risk aversion measure” or “partial nth degree risk aversion measure”. We choose the first denomination which is, to our knowledge the most used in the literature.

  10. Proposition 2 by Chiu et al. (2012) provides a result in terms of relative risk aversion instead of partial relative risk aversion. A result in terms of partial risk aversion can, however, be obtained by applying Theorem 2 by Chiu et al. (2012). Also note that a similar condition is obtained by Eeckoudt and Schlesinger (2008) in the precautionary saving model.

  11. \(\mathbb {E} \left[ u\left( \gamma \tilde{Y_i} + wr \right) \right] \approx u\left( \gamma y + wr \right) + \gamma u' (\gamma y + wr ) \, \mathbb {E} \left[ {\tilde{Y}}_i - y\right] + \sum _{k= 2}^N \frac{\gamma ^k}{k!} u^{(k)} (\gamma y + wr ) \, \mathbb {E} \left[ ({\tilde{Y}}_i - y)^k\right] \).

  12. Magnani (2017) provides a similar interpretation in a different field of analysis, a precautionary saving model, for the condition \(r_2(x) \ge 2\), which is the condition ensuring an increase in saving in the presence of a random interest rate. However, note that the result in Proposition 2 is more general since it holds for changes in risks of different degrees. On precautionary saving models with a multiplicative risk, see also Eeckoudt and Schlesinger (2008), Li (2012) and Baiardi et al. (2014).

  13. The second effect occurs since the risky asset has an expected return larger than the risk free asset.

  14. More precisely, if we observe the decision maker’s reaction to reduce investment in the risky asset in the case of Nth-degree increase in the risky return, then we know that his/her preferences are such that \(r_N(x,z) \le N\), which implies \(r_{N-1}(x,z) \le N-1\). This implies, in turn, that we know that the decision maker reduces investment in the risky asset in the case of \(N-1\)th-degree increase.

  15. The conditions in Proposition 5 just involve first and second derivatives of the utility function.

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Proofs of lemmas

Proofs of lemmas

Proof of Lemma 1

  1. (i)

    It follows from Proposition 3 in Menegatti (2015).

  2. (ii)

    We prove this result by induction. Let us start with the case \(n=2\). Strict concavity implies that \(u'(x)\) is strictly decreasing, and being also strictly positive, \(u'(x)\) converges to some limit \(0 \le l < + \infty \) as \(x \rightarrow +\infty \). Condition \(u^{(3)} (x)>0\) for all \(x \ge a\), implies that \(u''(x)\) is strictly increasing, hence it converges, as \(x \rightarrow + \infty \), to some real (non-positive) number. By the asymptote criterion, \(\displaystyle \lim \nolimits _{x\rightarrow + \infty } u''(x) = 0\).

    Let \(n>2 \) and assume that \( \lim \nolimits _{x\rightarrow + \infty } u^{(n)}(x) = 0.\) If n is even (resp. odd), the function \(u^{(n+1)}\) is nonnegative and decreasing (resp. non-positive and increasing); therefore, it converges to some limit \(l \ge 0\) (resp. \(l\le 0\)). By the asymptote criterion \(l=0\).

\(\square \)

Proof of Lemma 2

Since \(\lim _{x\rightarrow + \infty } u''(x) = \lim _{x\rightarrow + \infty } \frac{1}{x} = 0\), the expression \(-x u''(x) = \frac{- u''(x)}{\frac{1}{x}}\) takes the indeterminate form \(0/0\) as \(x \rightarrow +\infty \), as well as \((-1)^{k-1} x^{k-1} u^{(k)}(x) = \frac{(-1)^{k-1} u^{(k)}(x)}{\frac{1}{x^{k-1}}}\), for \(k=1, \ldots , n\). Applying L’Hôspital’s rule n times, we get:

$$\begin{aligned} \lim _{x\rightarrow +\infty } \frac{- u''(x)}{x^{-1}}= & {} \lim _{x\rightarrow +\infty } \frac{u^{(3)}(x)}{x^{-2}} = \lim _{x\rightarrow +\infty } \frac{- u^{(4)}(x)}{2x^{-3}} = \cdots \nonumber \\= & {} \lim _{x\rightarrow +\infty } \frac{(-1)^{n-1} u^{(n)}(x)}{\frac{(n-2)!}{x^{n-1}}} = \frac{L'}{(n-2)!} < +\infty \end{aligned}$$
(6)

\(\square \)

Proof of Lemma 3

It is sufficient to observe that

$$\begin{aligned} r'_n(x,z)= & {} \frac{\left[ -u^{(n+1)}(x+z) - xu^{(n+2)}(x+z) \right] u^{(n)}(x+z) +x\left[ u^{(n+1)}(x+z) \right] ^2 }{\left[ u^{(n)}(x+z)\right] ^2} \\= & {} - \frac{u^{(n+1)}(x+z)}{u^{(n)}(x+z)} \left[ 1-r_{n+1}(x,z) + r_n(x,z) \right] \end{aligned}$$

and that \(- \frac{u^{(n+1)}(x+z)}{u^{(n)}(x+z)} > 0\) because of the sign alternation in the derivatives. \(\square \)

Proof of Lemma 4

Fix \(z\ge 0 \) and let \({\tilde{r}}_n(x) =r_n(x,z).\) Assume by contradiction that \({\tilde{r}}_{n-1}\) is not weakly decreasing. Then, either it is weakly increasing, and strictly increasing on some interval \((x_a, x_b)\) (\(x_b\) may be \(+ \infty \)), or it admits some maximum or minimum. Let us first suppose that it is monotone and strictly increasing on \((x_a, x_b)\), or equivalently \({\tilde{r}}_{n-1}(x) +1 > {\tilde{r}}_{n}(x)\) on \((x_a, x_b)\). Then we can find \(x_2 > x_1 \ge x_a\) such that

$$\begin{aligned} {\tilde{r}}_{n-1}(x_2) +1> {\tilde{r}}_{n-1}(x_1) +1 > {\tilde{r}}_{n}(x_1) \ge {\tilde{r}}_n(x_2). \end{aligned}$$
(7)

Both functions \({\tilde{r}}_{n-1}\) and \({\tilde{r}}_{n}\) are monotone, therefore they admit limit at \(+\infty \). In particular, let \(\lim _{x \rightarrow +\infty } {\tilde{r}}_{n-1}(x) = l \in [0, + \infty ]\).

We prove that l cannot be \(+ \infty \). Indeed, assume \(l=+\infty \). Then for some M, \({\tilde{r}}_{n-1}(x) > {\tilde{r}}_n(x)\) for all \(x\ge M\). Let \(a_n(x) = -\frac{u^{(n+1)}(x+z)}{u^{(n)}(x+z)} = \frac{r_n(x,z)}{x}.\) Then, working as in the proof of Lemma 3, we show that \(a_n\) is weakly (strictly) increasing if and only if \({\tilde{r}}_n \ge {\tilde{r}}_{n+1}\) (\({\tilde{r}}_n > {\tilde{r}}_{n+1}\)). But then, since \({\tilde{r}}_n(x) < 1+ {\tilde{r}}_n(x)\le {\tilde{r}}_{n+1}\) and \({\tilde{r}}_{n-1}(x) > {\tilde{r}}_{n}(x)\) for \(x \ge M\) we have that \(a_n\) is strictly decreasing and \(a_{n-1}\) is strictly decreasing on \([M, +\infty )\). This implies that both \(a_{n-1}(x)\) and \(a_n(x)\) admit limit at \(+\infty \), and \(\lim _{x \rightarrow +\infty } a_n(x)\) is finite since the function is decreasing; moreover, there exist \(x_4>x_3 > M\) such that

$$\begin{aligned} \lim _{x \rightarrow +\infty } a_n(x)< a_n(x_4)< a_n(x_3)< a_{n-1}(x_3)< a_{n-1}(x_4)< \lim _{x \rightarrow +\infty } a_{n-1}(x) \end{aligned}$$
(8)

(the third inequality follows from the fact that \({\tilde{r}}_{n-1}(x) > {\tilde{r}}_{n}(x)\) is equivalent to \( a_{n-1}(x) > a_{n}(x)\)). However, since Lemma 2(ii) holds, we can apply L’Hospital’s theorem and get

$$\begin{aligned} \lim _{x \rightarrow +\infty } a_{n-1}(x)= & {} \lim _{x \rightarrow +\infty } -\frac{u^{(n)}(x+z)}{u^{(n-1)}(x+z)}=\lim _{x \rightarrow +\infty } -\frac{u^{(n+1)}(x+z)}{u^{(n)}(x+z)} \\= & {} \lim _{x \rightarrow +\infty } a_n(x)< +\infty \end{aligned}$$

which contradicts (8). As a consequence, l must be finite.

Since \(l < +\infty \), by definition of limit, we have that definitely \( |{\tilde{r}}_{n-1}(x) - l | < \varepsilon \) for every \(\varepsilon > 0\), or equivalently

$$\begin{aligned} (l-\varepsilon ) |u^{(n-1)}(x)| \le (-1)^{n+1}x u^{(n)}(x) < (l+\varepsilon ) |u^{(n-1)}(x)|, \end{aligned}$$
(9)

hence \(\lim _{x \rightarrow +\infty } x u^{(n)}(x) = 0\). Then, L’Hôspital’s theorem entails

$$\begin{aligned} l= \lim _{x \rightarrow +\infty } {\tilde{r}}_{n-1}(x) = \lim _{x \rightarrow +\infty } \left( -1 - \frac{xu^{(n+1)}(x)}{u^{(n)}(x)}\right) = -1 + \lim _{x \rightarrow +\infty } {\tilde{r}}_{n}(x) \end{aligned}$$

Thus, we have

$$\begin{aligned} l +1 \ge {\tilde{r}}_{n-1}(x_2) +1> {\tilde{r}}_{n-1}(x_1)+ 1 > {\tilde{r}}_n(x_1) \ge {\tilde{r}}_{n}(x_2) \ge l+ 1 \end{aligned}$$

for \(x_1 < x_2\) which is clearly a contradiction. This shows that if \({\tilde{r}}_{n-1}\) is not weakly decreasing, than it cannot be monotone. As a consequence, it must admit either a maximum or a minimum. The argument above shows that it cannot be strictly increasing on an interval of the form \([x_a, + \infty )\). Therefore, the function must admit a strict local maximum point at some point \(x_m\), namely \({\tilde{r}}'_{n-1} (x_m) =0\), or equivalently \({\tilde{r}}_{n-1}(x_m) +1 = {\tilde{r}}_n(x_m)\) and there exists some \({\bar{x}}<x_m\) where \({\tilde{r}}_{n-1}({\bar{x}}) < {\tilde{r}}_{n-1}(x_m)\) and \({\tilde{r}}'_{n-1}({\bar{x}}) > 0\). This implies that \({\tilde{r}}_n({\bar{x}})< {\tilde{r}}_{n-1}({\bar{x}}) + 1 < {\tilde{r}}_{n-1}(x_m) + 1= {\tilde{r}}_n(x_m)\) which contradicts the fact that \({\tilde{r}}_n(x)\) is weakly decreasing. So our claim is proved.

If \({\tilde{r}}_n (x)\) is strictly decreasing, then \({\tilde{r}}_n(x) +1 > {\tilde{r}}_{n+1}(x)\). Moreover \({\tilde{r}}_{n-1}\) is weakly decreasing by the previous result. If \({\tilde{r}}_{n-1}\) were constant on some interval \((x_a, x_b)\), then there would exist \(x_1 < x_2 \in (x_a, x_b)\) such that \({\tilde{r}}_n(x_1) = {\tilde{r}}_{n-1}(x_1)-1 ={\tilde{r}}_{n-1}(x_2) -1 = {\tilde{r}}_{n-1}(x_2) - 1 = {\tilde{r}}_n(x_2)\) which contradicts the strict monotonicity of \({\tilde{r}}_n(x)\). Therefore \({\tilde{r}}_{n-1}\) must be strictly decreasing as well. \(\square \)

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De Donno, M., Magnani, M. & Menegatti, M. Changes in multiplicative risks and optimal portfolio choice: new interpretations and results. Decisions Econ Finan 43, 251–267 (2020). https://doi.org/10.1007/s10203-019-00250-1

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