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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
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