Defensive online portfolio selection

The class of defensive online portfolio selection algorithms,designed for fi nite investment horizon, is introduced. The Game Constantly Rebalanced Portfolio and the Worst Case Game Constantly Rebalanced Portfolio, are presented and theoretically analyzed. The analysis exploits the rich set of mathematical tools available by means of the connection between Universal Portfolios and the Game- Theoretic framework. The empirical performance of the Worst Case Game Constantly Rebalanced Portfolio algorithm is analyzed through numerical experiments concerning the FTSE 100, Nikkei 225, Nasdaq 100 and S&P500 stock markets for the time interval, from January 2007 to December 2009, which includes the credit crunch crisis from September 2008 to March 2009. The results emphasize the relevance of the proposed online investment algorithm which signi fi cantly outperformed the market index and the minimum variance Sharpe-Markowitz’s portfolio.on-line portfolio selection; universal portfolio; defensive strategy

A Survey on Causal Discovery: Theory and Practice

Understanding the laws that govern a phenomenon is the core of scientific progress. This is especially true when the goal is to model the interplay between different aspects in a causal fashion. Indeed, causal inference itself is specifically designed to quantify the underlying relationships that connect a cause to its effect. Causal discovery is a branch of the broader field of causality in which causal graphs is recovered from data (whenever possible), enabling the identification and estimation of causal effects. In this paper, we explore recent advancements in a unified manner, provide a consistent overview of existing algorithms developed under different settings, report useful tools and data, present real-world applications to understand why and how these methods can be fruitfully exploited

Three-chamber chest drain system in the COVID-19 era: is there a risk of further transmission?

We discuss the hypothesis that common Chest Drain Systems collected to a COVID-19 patient, could be a possible source of contamination for health care staff in a Thoracic Surgery ward and we propose an alternative way to minimize this further risk of transmission

Combining deep reinforcement learning and multi-stage stochastic programming to address the supply chain inventory management problem

We introduce a novel heuristic designed to address the supply chain inventory management problem in the context of a two-echelon divergent supply chain. The proposed heuristic advances the current state-of-the-art by combining deep reinforcement learning with multi-stage stochastic programming. In particular, deep reinforcement learning is employed to determine the number of batches to produce, while multi-stage stochastic programming is applied to make shipping decisions. To support further research, we release a publicly available software environment that simulates a wide range of two-echelon divergent supply chain settings, allowing the manipulation of various parameter values, including those associated with seasonal demands. We then present a comprehensive set of numerical experiments considering constraints on production and warehouse capacities under fixed and variable logistic costs. The results demonstrate that the proposed heuristic significantly and consistently outperforms pure deep reinforcement learning algorithms in minimizing total costs. Moreover, it overcomes several inherent limitations of multi-stage stochastic programming models, thus underscoring its potential advantages in addressing complex supply chain scenarios

Discovery of spin-up in the X-ray pulsar companion of the hot subdwarf HD 49798

The hot subdwarf HD 49798 has an X-ray emitting compact companion with a spin-period of 13.2 s and a dynamically measured mass of 1.28+/-0.05 M_sun, consistent with either a neutron star or a white dwarf. Using all the available XMM-Newton and Swift observations of this source, we could perform a phase-connected timing analysis extending back to the ROSAT data obtained in 1992. We found that the pulsar is spinning up at a rate of (2.15+/-0.05)x10^{-15} s/s. This result is best interpreted in terms of a neutron star accreting from the wind of its subdwarf companion, although the remarkably steady period derivative over more than 20 years is unusual in wind-accreting neutron stars. The possibility that the compact object is a massive white dwarf accreting through a disk cannot be excluded, but it requires a larger distance and/or properties of the stellar wind of HD 49798 different from those derived from the modelling of its optical/UV spectra.Comment: Accepted for publication in MNRA

Common environment policies in different sustainability paradigms: evidence From the Baltic, Adriatic, and Black Seas

We develop a model for four sustainability paradigms (weak sustainability, a-growth, de-growth, strong sustainability) within a single framework that accounts for responsibility for nature and future generations and for intra- and inter-generational equality. The model is applied in three case studies: the Baltic, the Adriatic and the Black Sea with the aim to identify feasible sustainability solutions for shared seas under alternative sources of environmental pressure and cooperation strategies. The Baltic Sea is analyzed as an example of pollution from agriculture, the Adriatic Sea as an example of over-exploitation of fish in fishery, and the Black Sea as an example of pollution from industry. Empirical results show that different cooperation strategies are feasible in each case and that they yield different results in different context. Also welfare implications vary between different cooperation strategies. The main policy implication of the analysis is two-fold. Environmental conservation must be preferred to environmental innovation, where both intra- and inter-generational equity concerns are unessential. The choice of a different sustainability approaches must be combined with the feasibility of the differently required management institutions, while considerations of the sectoral sources of environmental pressure are essential