Preferences for Short-Term Versus Long-Term Bonuses for Stock Investments

Performance-related bonuses in the finance sector are considered important tools to provide incentives. An example is that stock portfolio managers are awarded bonuses conditionally on their portfolios producing superior returns either relative to an index or equivalent funds. Concerns are however expressed that bonuses to portfolio managers are based on too short time intervals, which may impact negatively on the degree to which environmental and social factors are taken into account in investment decisions. The question addressed in this article is how bonus schemes can be designed so that delayed payouts will be equally motivating as short-term payouts. We have conducted two experiments to investigate preference for bonus payments that are paid out either frequently of infrequently. In Experiment 1 employing 27 undergraduates, preferences were measured for one certain long-term bonus versus four certain bonuses evenly distributed across time. A majority chose the short-term bonuses, and in order for a long-term bonus to be equally preferred the results showed that it needs to be approximately 40 percent higher than the four combined short-term bonuses. Experiment 2 employing another 36 undergraduates introduced uncertainty of outcomes which more accurately reflects the setting faced by stock investors. A four-year bonus is compared to four one-year bonuses. Uncertainty was the same, decreasing or increasing over the four years. The results showed that decreasing uncertainty made a majority prefer the four-year bonus to the added one-year bonuses. In conclusion, introducing uncertainty in choices concerning future outcomes is shown to reduce the extent to which future bonus outcomes are discounted relative to immediate bonus outcomes.Portfolio management; Performance-related bonus; Time discounting

Efficient Stochastic Programming in Julia

We present StochasticPrograms.jl, a user-friendly and powerful open-source framework for stochastic programming written in the Julia language. The framework includes both modeling tools and structure-exploiting optimization algorithms. Stochastic programming models can be efficiently formulated using expressive syntax and models can be instantiated, inspected, and analyzed interactively. The framework scales seamlessly to distributed environments. Small instances of a model can be run locally to ensure correctness, while larger instances are automatically distributed in a memory-efficient way onto supercomputers or clouds and solved using parallel optimization algorithms. These structure-exploiting solvers are based on variations of the classical L-shaped and progressive-hedging algorithms. We provide a concise mathematical background for the various tools and constructs available in the framework, along with code listings exemplifying their usage. Both software innovations related to the implementation of the framework and algorithmic innovations related to the structured solvers are highlighted. We conclude by demonstrating strong scaling properties of the distributed algorithms on numerical benchmarks in a multi-node setup

Portfolio managers’ attitudes towards policy regulations of environmental reporting

Attitudes towards policy regulations of environmental reporting were examined in a survey of 15 portfolio managers of stock funds lacking an explicit environmental strategy. The managers’ evaluated three regulative measures. They were most positive toward requirements for companies to report their environmental impacts in a standardized way, a measure that also was perceived to have the largest impact on social responsible investment. They were less positive toward a requirement for the funds to display in which way they themselves take environmental criteria into account in their investments. They were least positive to announce the proportion of companies in their portfolios that in a standardized way reports environmental performance.Socially; Responsible; Investments

The roles of the subunits in the function of the calcium channel

Dihydropyridine-sensitive voltage-dependent L-type calcium channels are critical to excitation-secretion and excitation-contraction coupling. The channel molecule is a complex of the main, pore-forming subunit alpha 1 and four additional subunits: alpha 2, delta, beta, and gamma (alpha 2 and delta are encoded by a single messenger RNA). The alpha 1 subunit messenger RNA alone directs expression of functional calcium channels in Xenopus oocytes, and coexpression of the alpha 2/delta and beta subunits enhances the amplitude of the current. The alpha 2, delta, and gamma subunits also have pronounced effects on its macroscopic characteristics, such as kinetics, voltage dependence of activation and inactivation, and enhancement by a dihydropyridine agonist. In some cases, specific modulatory functions can be assigned to individual subunits, whereas in other cases the different subunits appear to act in concert to modulate the properties of the channel

Tissue distribution of 5-hydroxymethylcytosine and search for active demethylation intermediates.

5-Hydroxymethylcytosine (hmC) was recently detected as the sixth base in mammalian tissue at so far controversial levels. The function of the modified base is currently unknown, but it is certain that the base is generated from 5-methylcytosine (mC). This fuels the hypothesis that it represents an intermediate of an active demethylation process, which could involve further oxidation of the hydroxymethyl group to a formyl or carboxyl group followed by either deformylation or decarboxylation. Here, we use an ultra-sensitive and accurate isotope based LC-MS method to precisely determine the levels of hmC in various mouse tissues and we searched for 5-formylcytosine (fC), 5-carboxylcytosine (caC), and 5-hydroxymethyluracil (hmU) as putative active demethylation intermediates. Our data suggest that an active oxidative mC demethylation pathway is unlikely to occur. Additionally, we show using HPLC-MS analysis and immunohistochemistry that hmC is present in all tissues and cell types with highest concentrations in neuronal cells of the CNS