Optimally chosen small portfolios are better than large ones

One of the fundamental principles in portfolio selection models is minimization of risk through diversification of the investment. However, this principle does not necessarily translate into a request for investing in all the assets of the investment universe. Indeed, following a line of research started by Evans and Archer almost fifty years ago, we provide here further evidence that small portfolios are sufficient to achieve almost optimal in-sample risk reduction with respect to variance and to some other popular risk measures, and very good out-of-sample performances. While leading to similar results, our approach is significantly different from the classical one pioneered by Evans and Archer. Indeed, we describe models for choosing the portfolio of a prescribed size with the smallest possible risk, as opposed to the random portfolio choice investigated in most of the previous works. We find that the smallest risk portfolios generally require no more than 15 assets. Furthermore, it is almost always possible to find portfolios that are just 1% more risky than the smallest risk portfolios and contain no more than 10 assets. Furthermore, the optimal small portfolios generally show a better performance than the optimal large ones. Our empirical analysis is based on some new and on some publicly available benchmark data sets often used in the literature

Portfolio decision analysis for pandemic sentiment assessment based on finance and web queries

COVID-19 has spread worldwide, affecting people’s health and the socio-economic environment. Such a pandemic is responsible for people’s deteriorated mood, pessimism, and lack of trust in the future. This paper presents a portfolio decision analysis framework for policymakers aiming at recovering the population from psychological distress. Specifically, we explore the relative relevance of a country to the overall “mood of the world” in light of pursuing predefined targets through optimization criteria. Toward this aim, we design a statistical indicator for measuring the mood by considering the financial markets’ outcomes and the people’s online searches about COVID-19. Then, we adapt existing portfolio selection models to evaluate the role of an extensive collection of countries and stock markets based on different criteria. More precisely, such criteria are established assuming “rational” goals of a policymaker, namely to aspire to a general and stable optimism and avoid waves of opposite moods or excess pessimism. Empirical experiments validate the theoretical proposal. The employed dataset contains 39 countries selected on the basis of data reliability and relevance in the context of COVID-19. Data on daily Google Trends searches of the term “coronavirus” (and its translations) and closing prices of relevant domestic stock indexes are considered for 2020 to develop the statistical mood indicator. Results offer different insights based on the selected optimization criteria. The practical implications of the proposed models have been illustrated through arguments based on a National Recovery and Resilience Plan-type normative framework

Portfolio selection problems in practice: a comparison between linear and quadratic optimization models

Several portfolio selection models take into account practical limitations on the number of assets to include and on their weights in the portfolio. We present here a study of the Limited Asset Markowitz (LAM), of the Limited Asset Mean Absolute Deviation (LAMAD) and of the Limited Asset Conditional Value-at-Risk (LACVaR) models, where the assets are limited with the introduction of quantity and cardinality constraints. We propose a completely new approach for solving the LAM model, based on reformulation as a Standard Quadratic Program and on some recent theoretical results. With this approach we obtain optimal solutions both for some well-known financial data sets used by several other authors, and for some unsolved large size portfolio problems. We also test our method on five new data sets involving real-world capital market indices from major stock markets. Our computational experience shows that, rather unexpectedly, it is easier to solve the quadratic LAM model with our algorithm, than to solve the linear LACVaR and LAMAD models with CPLEX, one of the best commercial codes for mixed integer linear programming (MILP) problems. Finally, on the new data sets we have also compared, using out-of-sample analysis, the performance of the portfolios obtained by the Limited Asset models with the performance provided by the unconstrained models and with that of the official capital market indices

A new family of modified Gaussian copulas for market consistent valuation of government guarantees

This paper deals with a copula-based stochastic dependence problem in the context of financial risks. We discuss the financial framework for assessing the theoretical up-front value of government guarantees on bank liabilities. EU States widely use these contracts to improve the financial system’s stability and manage the banking sector in crisis situations; in Italy, they have also been used to address the consequences of the Covid-19 emergency. From a market viewpoint, we deal with a defaultable guarantee contract where the State-guarantor and the bank-borrower are both subject to default risk, and their risks are interconnected. We show that the classical Gaussian copula is not satisfactory for modeling the dependence among the considered risks. Indeed, using the benchmark market model for credit risk portfolio management, we highlight some contradictory results observed for the up-front values of the guarantee when the default intensity of the guarantor is smaller than that of the borrower. Then, we introduce a new family of modified Gaussian copulas that overcomes the limitations of the standard approach, allowing to determine realistic results in terms of the guarantees “mark-to-model” value when the benchmark market model does not work. Numerical simulations validate the theoretical proposal

A new family of modified Gaussian copulas for market consistent valuation of government guarantees

This paper deals with a copula-based stochastic dependence problem in the context of financial risks. We discuss the financial framework for assessing the theoretical up-front value of government guarantees on bank liabilities. EU States widely use these contracts to improve the financial system’s stability and manage the banking sector in crisis situations; in Italy, they have also been used to address the consequences of the Covid-19 emergency. From a market viewpoint, we deal with a defaultable guarantee contract where the State-guarantor and the bank-borrower are both subject to default risk, and their risks are interconnected. We show that the classical Gaussian copula is not satisfactory for modeling the dependence among the considered risks. Indeed, using the benchmark market model for credit risk portfolio management, we highlight some contradictory results observed for the up-front values of the guarantee when the default intensity of the guarantor is smaller than that of the borrower. Then, we introduce a new family of modified Gaussian copulas that overcomes the limitations of the standard approach, allowing to determine realistic results in terms of the guarantees “mark-to-model” value when the benchmark market model does not work. Numerical simulations validate the theoretical proposal

Pablo de Tarso como momento de encuentro/desencuentro del joven Heidegger con Nietzsche

The aim of this paper is to show analogies and contrasts between Heidegger’s and Nietzsche’s interpretation of the Pauline Epistles. The first step is to show the ambiguity of Paul’s figure in Nietzsche’s thought and his connection with Jesus of Nazareth. Paul, founder of Christianity, created a religion of resentment, empowering the powerless. Heidegger, far from Nietzsche’s philosophical moral approach, reads Paul to investigate the roots of religious life: the Pauline Epistles , above all, deal with the awaiting of Parousia, which, far from being a mere hope, is the completion of all believer’s life.El objetivo de este trabajo es mostrar las analogías y diferencias entre las interpretaciones de Heidegger y Nietzsche de la epístolas paulinas. El primer paso es mostrar la ambigüedad de la figura de Pablo en el pensamiento de Nietzsche y su conexión con Jesús de Nazaret. Pablo, el fundador del cristianismo, creó una religión del resentimiento, dando poder a los carentes de él. Muy lejos del enfoque filosófico-moral de Nietzsche, Heidegger lee a Pablo para investigar las raíces de la vida religiosa: las epístolas paulinas tratan, antes de nada, de la espera de la Parousía, que, lejos de ser una mera esperanza, es la consumación de la vida de todo creyente

MAD risk parity portfolios

In this paper, we investigate the features and the performance of the risk parity (RP) portfolios using the mean absolute deviation (MAD) as a risk measure. The RP model is a recent strategy for asset allocation that aims at equally sharing the global portfolio risk among all the assets of an investment universe. We discuss here some existing and new results about the properties of MAD that are useful for the RP approach. We propose several formulations for finding MAD-RP portfolios computationally, and compare them in terms of accuracy and efficiency. Furthermore, we provide extensive empirical analysis based on three real-world datasets, showing that the performances of the RP approaches generally tend to place both in terms of risk and profitability between those obtained from the minimum risk and the Equally Weighted strategies

Mars Comm/Nav MicroSat Network

A recent Mars Exploration Program Architecture Definition Study, conducted by NASA with strong international participation, recommends establishment of a low cost in-situ communications and navigation relay satellite network to provide enabling and enhancing support for the international exploration of Mars. This would be the first step toward establishing a virtual presence throughout the solar system as called for in NASA\u27s Strategic Plan. The Mars satellite network concept, and its evolution from a prototype launched in 2003 to a full constellation, is described. Implementation of the Mars satellite network will utilize the common micromission bus being designed for piggyback launch by Ariane 5 as described in a companion paper, The Mars Micromissions Program. The requirements imposed on the common micromission bus to meet the needs of the Mars MicroSat network are discussed: A functional description is provided for the MicroSat payload, a UHF transceiver system, which supports the in-situ communications and navigation needs of user missions. Key technologies that are expected to play an important role in the implementation of the MicroSat network are also discussed

Portfolio selection problems in practice: a comparison between linear and quadratic optimization models

Several portfolio selection models take into account practical limitations on the number of assets to include and on their weights in the portfolio. We present here a study of the Limited Asset Markowitz (LAM), of the Limited Asset Mean Absolute Deviation (LAMAD) and of the Limited Asset Conditional Value-at-Risk (LACVaR) models, where the assets are limited with the introduction of quantity and cardinality constraints. We propose a completely new approach for solving the LAM model, based on reformulation as a Standard Quadratic Program and on some recent theoretical results. With this approach we obtain optimal solutions both for some well-known financial data sets used by several other authors, and for some unsolved large size portfolio problems. We also test our method on five new data sets involving real-world capital market indices from major stock markets. Our computational experience shows that, rather unexpectedly, it is easier to solve the quadratic LAM model with our algorithm, than to solve the linear LACVaR and LAMAD models with CPLEX, one of the best commercial codes for mixed integer linear programming (MILP) problems. Finally, on the new data sets we have also compared, using out-of-sample analysis, the performance of the portfolios obtained by the Limited Asset models with the performance provided by the unconstrained models and with that of the official capital market indices