Grantmaking Foundations’ Asset Management, Payout Rates, and Longevity Under Changing Market Conditions: Results From a Monte Carlo Simulation Study

2019 ◽  
Vol 49 (2) ◽  
pp. 424-447
Author(s):  
Zvika Afik ◽  
Simon Benninga ◽  
Hagai Katz
Keyword(s):  
Monte Carlo ◽  
Asset Management ◽  
Management Strategies ◽  
Problem Area ◽  
Life Cycles ◽  
Investment Strategies ◽  
Monte Carlo Simulation Study ◽  
Success Stories ◽  
Investment Returns ◽  
Grantmaking Foundations

Today’s uncertain financial markets could affect foundations’ future grantmaking capacities. We review foundations’ financial decision-making patterns and their effect on foundations’ assets, longevity goals, and payouts. Using three fictional foundations with different longevity goals and grantmaking preferences, we demonstrate the delicate balance and tight nexus between asset management strategies, payout rates, and longevity. To do so, we perform stochastic Monte Carlo simulations of multiple foundation life cycles, conducted under diverse capital market scenarios. The findings suggest that foundations should (a) readjust their return expectations to today’s less favorable markets; (b) reduce their reliance on past portfolios’ investment returns or unique “success stories” in making decisions; (c) appreciate the strong interdependence between portfolio-mix, payout rates, and longevity; (d) consider effects of their particular mission/problem area on these parameters; and (e) use tailored projection analyses that simulate various investment strategies, payouts rates, and longevity to meet their grantmaking goals.

Porous Aluminophosphates as Adsorbents for the Separation of CO2/CH4 and CH4/N2 Mixtures – a Monte Carlo Simulation Study

2018 ◽  
Author(s):  
Michael Fischer
Keyword(s):  
Monte Carlo ◽  
Landfill Gas ◽  
Experimental Studies ◽  
Chem Phys ◽  
Monte Carlo Simulation Study ◽  
Mixture Adsorption ◽  
Vacuum Swing Adsorption ◽  
Separation Of Co2 ◽  
Pressure Swing ◽  
Gcmc Simulations

<div>Aluminophosphates with zeolite-like topologies (AlPOs) have received considerable attention as potential adsorbents for use in the separation of methane-containing gas mixtures. Such separations, especially the removal of carbon dioxide and nitrogen from methane, are of great technological relevance in the context of the “upgrade” of natural gas, landfill gas, and biogas. While more than 50 zeolite frameworks have been synthesised in aluminophosphate composition or as heteroatom substituted AlPO derivatives, only a few of them have been characterised experimentally with regard to their adsorption and separation behaviour. In order to predict the potential of a variety of AlPO frameworks for applications in CO<sub>2</sub>/CH<sub>4</sub> and CH<sub>4</sub>/N<sub>2</sub> separations, atomistic grand-canonical Monte Carlo (GCMC) simulations were performed for 53 different structures. Building on previous work, which studied CO<sub>2</sub>/N<sub>2</sub> mixture adsorption in AlPOs (M. Fischer, <i>Phys. Chem. Chem. Phys.</i>, 2017, <b>19</b>, 22801–22812), force field parameters for methane adsorption in AlPOs were validated through a comparison to available experimental adsorption data. Afterwards, CO<sub>2</sub>/CH<sub>4</sub> and CH<sub>4</sub>/N<sub>2</sub> mixture isotherms were computed for all 53 frameworks for room temperature and total pressures up to 1000 kPa (10 bar), allowing the prediction of selectivities and working capacities for conditions that are relevant for pressure swing adsorption (PSA) and vacuum swing adsorption (VSA). For CO<sub>2</sub>/CH<sub>4 </sub>mixtures, the <b>GIS</b>, <b>SIV</b>, and <b>ATT</b> frameworks were found to have the highest selectivities and CO<sub>2 </sub>working capacities under VSA conditions, whereas several frameworks, among them <b>AFY</b>, <b>KFI</b>, <b>AEI</b>, and <b>LTA</b>, show higher working capacities under PSA conditions. For CH<sub>4</sub>/N<sub>2</sub> mixtures, all frameworks are moderately selective for methane over nitrogen, with <b>ATV</b> exhibiting a significantly higher selectivity than all other frameworks. While some of the most promising topologies are either not available in pure-AlPO<sub>4</sub> composition or collapse upon calcination, others can be synthesised and activated, rendering them interesting candidates for future experimental studies. In addition to predictions of mixture adsorption isotherms, further simulations were performed for four selected systems in order to investigate the microscopic origins of the macroscopic adsorption behaviour, <i>e.g. </i>with regard to the very high CH<sub>4</sub>/N<sub>2</sub> selectivity of <b>ATV</b> and the loading-dependent evolution of the heat of CO<sub>2</sub> adsorption and CO<sub>2</sub>/CH<sub>4</sub> selectivity of <b>AEI</b> and GME.</div>

A Decision Support Tool for Wastewater Catchment Management

2007 ◽  
Vol 2 (2) ◽  
Author(s):  
S.E. Walters ◽  
D. Savic ◽  
R.J. Hocking
Keyword(s):  
Decision Support ◽  
Asset Management ◽  
Capital Investment ◽  
Management Strategies ◽  
Sewage Treatment ◽  
Decision Support Tool ◽  
Catchment Management ◽  
Clean Water ◽  
Support Tool ◽  
South West

The water industry over the years has primarily focussed on upgrading and investing in clean water provision. However, as research into the science and management of clean water services has progressed rapidly, wastewater provision and services has been slower. Focus, though, is now shifting within Industry and Research into wastewater services. The water regulator, Ofwat, for England and Wales demands the Sewerage Undertakers demonstrate efficient management of wastewater systems in order to obtain funding for Capital Investment projects. South West Water, a Water Service Provider and Sewerage Undertaker located in the South West of England, identified a need gap in their asset management strategies for wastewater catchments. This paper will introduce the production of a Decision Support Tool, DST, to help SWW proactively manage their Wastewater Catchments, examining Sewage Treatment Works, Pumping Stations and Networks. The paper will discuss some concepts within the DST, its production, testing and a brief case study. The DST provides a framework for prioritising catchments to optimise investment choices and actions. The Tool ranks catchments utilising Compromise Programming, CP, as well as AHP Pair-wise comparisons for preference weights. The DST incorporates Asset models, a Whole life Costing Module, as well as a Decay and Intervention Module.

scholarly journals Immunization Strategies for Funding Multiple Inflation-Linked Retirement Income Benefits

Risks ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 60
Author(s):  
Cláudia Simões ◽  
Luís Oliveira ◽  
Jorge M. Bravo
Keyword(s):  
Interest Rate ◽  
Yield Curve ◽  
Risk Measure ◽  
Management Strategies ◽  
Interest Rate Risk ◽  
Insurance Companies ◽  
Retirement Income ◽  
Investment Strategies ◽  
Immunization Strategies ◽  
The Impact

Protecting against unexpected yield curve, inflation, and longevity shifts are some of the most critical issues institutional and private investors must solve when managing post-retirement income benefits. This paper empirically investigates the performance of alternative immunization strategies for funding targeted multiple liabilities that are fixed in timing but random in size (inflation-linked), i.e., that change stochastically according to consumer price or wage level indexes. The immunization procedure is based on a targeted minimax strategy considering the M-Absolute as the interest rate risk measure. We investigate to what extent the inflation-hedging properties of ILBs in asset liability management strategies targeted to immunize multiple liabilities of random size are superior to that of nominal bonds. We use two alternative datasets comprising daily closing prices for U.S. Treasuries and U.S. inflation-linked bonds from 2000 to 2018. The immunization performance is tested over 3-year and 5-year investment horizons, uses real and not simulated bond data and takes into consideration the impact of transaction costs in the performance of immunization strategies and in the selection of optimal investment strategies. The results show that the multiple liability immunization strategy using inflation-linked bonds outperforms the equivalent strategy using nominal bonds and is robust even in a nearly zero interest rate scenario. These results have important implications in the design and structuring of ALM liability-driven investment strategies, particularly for retirement income providers such as pension schemes or life insurance companies.

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