Asset Management and Institutional Investors

Basile, Ignazio Giorgio; Ferrari, Pierpaolo

doi:10.1007/978-3-319-32796-9

Cited by 9 publications

(3 citation statements)

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“…Given the aforementioned constraints, it is a matter of solving a constrained non-linear programming problem, which only admits a numerical solution, through an iterative process using a sequential quadratic programming algorithm (Basile & Ferrari, 2016). It should be noted that this technique, while widely used and easily implemented, is not the only one that can be applied to optimal risk parity.…”

Section: The Optimal Risk Paritymentioning

confidence: 99%

“…The first is to avoid assigning high weights to marginal areas in the actual composition of the global market. The second is to limit the number of parameters to be estimated, and therefore, the estimation risk (Basile & Ferrari, 2016). Table 1 shows the actual weights of the MSCI ACWI global benchmark in October 2018, broken down sectorially and geographically.…”

Section: Descriptive Statistics Of the Data Samplementioning

confidence: 99%

“…Internal consistency is satisfied if each asset class consists of financial instruments that are as homogenous as possible and similarly subject to systematic risk factors. Finally, external differentiation requires that different asset classes have distinct exposures to sources of systematic risk, such as macroeconomic and political factors (Basile & Ferrari, 2016).…”

Section: Introductionmentioning

confidence: 99%

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The impact of sectorial and geographical segmentation on risk-based asset allocation techniques

Basile

Ferrari

Abate

2019

Investment Management and Financial Innovations

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In the last decades, risk-based portfolio construction techniques have enjoyed a widespread diffusion in the financial community. This study aims at evaluating how these portfolio construction techniques produce different results depending on whether the segmentation of the stock market investment universe is based on sectorial or geographical criteria. An empirical analysis, applied on the global equity market, is carried out by making use of the typical and most advanced statistical and financial evaluation measures. Geographical segmentation is carried out in relation to the listing market, while sectorial segmentation is made in relation to the productive sectors to which individual companies belong. Our comparative analysis provides substantially coherent results, demonstrating a significant preference for the sectorial criterion compared to the geographic one. In conclusion, this result can be attributed to the subdivision of the investment universe into sectorial indices characterized by greater internal coherence and better external differentiation, in addition to the lower concentration of sectorial segmentation compared to the geographical one.

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Section: The Optimal Risk Paritymentioning

confidence: 99%

Section: Descriptive Statistics Of the Data Samplementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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