Example by adding income to the daily share price

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example, by adding income to the daily share price rather than paying it out, (1) the fundshareholders’ receipt of the income is postponed, and (2) the earned income is convertedinto capital gains, which might be taxed at a lower rate. Nearly all U.S. money marketfunds distribute income monthly.73
4.1Current Regulatory BaselineAmortized cost valuation smooths but does not eliminate the price fluc-tuations caused by changing market conditions. In fact, as we demonstratelater, amortized cost reflects approximately the same underlying risks as theNAV. The intuition for this observation can be seen best by noting that,when bonds are held to maturity and there are no defaults, capital gains andlosses net to zero. It can then be inferred that any difference betweenNAVand amortized cost is idiosyncratic risk that is not priced in equilibrium.4.1.1Results of Monte Carlo simulationTo analyze the stability of MMFs under the current baseline, we summarizethe time-series properties of a representative MMF’s market value (NAV),its amortized cost (AC), and the ratio ofACtoNAVin Table 3.In aseparate analysis derived from the same simulation, Table 4 reports thefrequencies that this representative MMF penetrates specific “downside”barriers.The table entitled, “Monte Carlo simulation parameters,” describes theparameters used in our analysis. To perform the simulation exercise underthe current regulatory regime, we assume that the representative MMF hasa duration of sixty days (the maximum weighted average maturity currentallowed under rule 2a-7). The long-run rate assumptions are the estimatedparameters from Table 2.The 40% recovery rate assumption follows theconvention used to price credit default swaps when the underlying referenceentity is senior debt. The effective recovery rate of 80% is designed to adjustfor the relatively large asset concentrations created by the algorithm used toselect assets that achieve the target duration. This assumption effectivelycuts the concentration toωωEand carries that implicit assumption that onlythis fraction of the bonds actually default.105Throughout the remaining analysis, we report results for portfolios thathave different combinations of default-free and risky securities whereφde-fines the proportion of default-free securities held in the MMF, i.e.,φ={0.00,0.25,0.50,0.75,1.00}.The simulation is based on the following algorithm:1. The starting values forr1andλ1are set equal to their long-run meansof 0.87% and 0.14%, respectively.2. Based on the simulation parameters and initial values for the spot105Alternative approaches for modeling default risk are on-going and the results basedon these assumptions may change.74
4.1Current Regulatory BaselineMonte Carlo simulation parametersRegulatoryPre-2010DescriptionBaselineReformsDuration60 days90 daysLong-run rate (θr)0.87%0.87%Long-run rate (θλ)0.14%0.14%Recovery rate (ω)40.0%40.0%Effective recovery rate (ωE)80.0%80.0%Evaluation period360 days360 daysrates, solve for the number of maturitiesˆTthat result in a portfolioduration of 60 days (see Eq. (21)).

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