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RAMIRL4 <br />Wisconsin at Madison and a MoSter'S in Finance and Monogement from the University of Chicago. Arthur <br />will be critical in managing our pension optimization model through the engagement and at pricing. <br />Pension Liability Shape: The City's strategy to refinance between 50%-90% of its outstanding UAL, <br />coupled with projected budget challenges, allow it to restructure its current pension liability with a more <br />long-term sustainable repayment schedule. Below are three structuring approaches, commonly used by <br />California POB issuers. Each structure has a specific savings target. <br />Uniform <br />Target LL}Ual annual savings <br />Benefits Highest overall savings; no <br />negative savings <br />Lower Lash flow relief Lhan <br />Disadvantages level debt ser6iLe In in early Lo <br />mid -amortization period <br />Level <br />Level predictable debt service L uinhm,Amn I:r Level and <br />lJntom, ,tructm es <br />Highe_tt cash flow savings in early Lave[ pror icanle (IF hi ,orvicr in <br />LO rnid-amortiLation period: early m n9id-a nYonira Gen and nn <br />neg3Live savings in la Ler year ❑e4a Gve savings <br />Negative lone -term savings owur agLrt g•rte savings Chan the <br />uriforrn option <br />We recommend a "Hybrid" approach because it provides a balanced solution that addresses the City's <br />short and long-term objectives. Key factors supporting this recommendation include the following: <br />Level debt service in the "front-end" creates a more manageable liability for the City in the short <br />to medium term. This approach also creates 'capacity' to absorb future UALs, if they arise. <br />Hybrid structure option improves overall savings from the level debt service approach; and, <br />greater savings improves the 'probability of success' for the overall transaction. <br />+ No negative savings relative to the City's current UAL amortization; this is an important policy <br />objective for every public agency contemplating the issuance of POBs. <br />Base -by -Base CAPERS UAL Refunding Model. Once the strategy for the City's overall pension liability <br />structure is decided, our Pension Optimization Model evaluates each individual amortization base. <br />Refinancing the City's UAL is similar to refinancing a portfolio of outstanding loans. The Ramirez & Co. <br />Pension Optimization Model evaluates and ranks each individual amortization base based on cash flow <br />and PV savings. Importantly, because each UAL base has a different amortization period, our Pension <br />Optimization Model also incorporates the average annual savings per par amount as metric to evaluate <br />and "optimize' the selection of amortization bases to refinance. Preliminary results are Summarized <br />below. The far right column indicates the "Savings Ranking' of each amortization base. The UAL bases <br />highlighted in blue identify the UAL bases we recommend to refinance, based on current interest rates. <br />UAL <br />Amort <br />Balance <br />Savings <br />Av, Ann <br />Ranking <br />3ase Rcason <br />year <br />Rarne <br />Period <br />6/30/2021 <br />Pv $ <br />PV <br />I -Al <br />Cash Flow <br />Savin s <br />PV <br />CF <br />AO <br />a <br />Fiu l 6 nrI <br />2006 <br />None <br />17 <br />(1 S071241 <br />b. <br />Benefit L ianee <br />2007 <br />Now <br />7 <br />27869.276 <br />S466.886 <br />19.G% <br />S,782902 <br />826,29 <br />32 <br />20 <br />c. <br />Benefit C)ange <br />2007 <br />None <br />8 <br />120,310 <br />24073 <br />18.S%. <br />25,721 <br />3,21S <br />33 <br />34 <br />d. <br />Assump Change <br />2009 <br />None <br />10 <br />28,921,692 <br />7,492,002 <br />2S.9% <br />8,301,799 <br />820,180 <br />30 <br />16 <br />e. <br />Sp(G3[n)/1-055 <br />2009 <br />None <br />20 <br />29,368,098 <br />12,596,219 <br />42.9% <br />16,717,958 <br />835,898 <br />14 <br />12 <br />f. <br />Sr IGain)/Lo<, <br />2010 <br />Ncmc <br />21 <br />10,81)5,290 <br />4,801,175 <br />44.496 <br />6,492,003 <br />309,143 <br />12 <br />19 <br />v,. <br />Assump Cnanee <br />2011 <br />None <br />12 <br />12,883,043 <br />3.830.028 <br />29.7% <br />4.389472 <br />36S,789 <br />28 <br />23 <br />h. <br />Sp (Gain(/Loss <br />2011 <br />None <br />22 <br />(7,380.480) <br />- <br />- <br />- <br />- <br />- <br />- <br />Pymt(Gain)!'_oss <br />2012 <br />Noe <br />23 <br />S.629.78S <br />2.6814S3 <br />47.6% <br />3,7S90S8 <br />263437 <br />7 <br />2S <br />j. <br />(Lain)/Lose <br />2012 <br />None <br />23 <br />(261.26.) <br />- <br />- <br />- <br />- <br />- <br />- <br />k. <br />(Gale)/Lass <br />2013 <br />100% <br />21 <br />100.311.691 <br />46,771,862 <br />46.6% <br />65,858,728 <br />2,744,114 <br />9 <br />2 <br />L <br />A%%ump Change <br />2014 <br />100%. <br />1s <br />45,039,235 <br />14,492,7BB <br />32.2% <br />17,231,937 <br />1,148,799 <br />27 <br />11 <br />2014 <br />1nn% <br />7R <br />(6i,66R,mr) <br />- <br />- <br />- <br />- <br />- <br />- <br />City Council <br />10 <br />23 — 248 <br />5/18/2021 <br />