MATHEMATICALMODELANDITSAPPLICATIONFOR ANALYZINGMACROPRUDENTIALINSTRUMENT IN THEBANKINGINDUSTRY

• Main Author: Fandi Ansori, Moch
• Format: Dissertations
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/62103
• Institution: Institut Teknologi Bandung

Macroprudentialpolicyisapolicythataimstomaintainthestabilityofthefinancial system asawholebymitigatingsystemicrisk.The2007-2008GlobalFinancial Crisis (GFC)isthoughttohaveoccurredbecausemacroprudentialpolicieshave not beenimplementedeffectivelyindevelopedcountries.Oneofthelessonsfrom the GFCwasthatliquidityriskcouldjeopardizethefunctioningandcontinuityof the bankingsystem.InIndonesia,thereisamacroprudentialpolicyinstrument, called theLoan-to-DepositRatiobasedReserveRequirement(LDR-RR),which aims tostrengthenthebankingintermediationfunctionwithoutforgettingtocontrol liquidity risk.SinceitsimplementationinMarch2011untilnow,theLDR-RR instrument hasundergoneseveralchangesinitsparametersettingsasaneffortto controlbankingcreditgrowth.ToseetheimpactofchangesintheLDR-RRparam- etersonthedynamicsofthebankbalancesheet’scomponents,amathematical model isneeded. This dissertationstudiesmathematicalmodeltoanalyzetheLDR-RRinstrumentin banking industry.Therearethreemodelsstudied.Thefirstmodelisadynamic model ofbankbalancesheetintheformofasystemofdifferentialequations.This model focusesonobservingthedynamicsofthebank’sbalancesheetcomponents: ThirdPartyFunds(TPF),loan,equity,andliquidassets.Initially,adynamic model ofthebank’sbalancesheetwithoutinvolvingtheLDR-RRisbuilt.The model’sequilibriumpointsandtheirstabilityareanalyzed.Themodelisapplied to Indonesianbankingdatabyestimatingthemodel’sparametersusingthespiral optimization method.Furthermore,adynamicmodelofthebank’sbalancesheet that includesLDR-RRisbuilt.Themodel’sequilibriumpointsandtheirstabilityare also analyzed.Themodel’sparametersarealsoestimated.Thestochasticmodel is alsodevelopedwithstochasticelementscontainedintheaveragewithdrawalof deposit andnon-performingloan.TheanalysisofLDR-RR’sparametersiscarried out byobservingtheirsensitivitytoloanandequityvariablesthroughbothdeter- ministic andstochasticmodels. The secondmodelisadynamicmodelofloanbasedonthegradientadjustment process.Thismodelisintheformofacreditdifferenceequation,withthedynamics being proportionaltothegradientadjustmentprocesswhichisthefirstderivativeof the bank’sprofitonloan.Inthismodel,twocasesareexamined:thecaseofabank with capitalratioisnotlowerthantheincentivevalueandthecaseofabankwith capital ratioislowerthantheincentivevalue.Ineachmodel,LDR-RRinstrument is added.TheLDR-RR’sparametersareanalyzedusingtheflipandbordercollision bifurcationtheory.Numericalsimulationsarepresentedtovisualizetheresultsfrom the analysisthathavebeenobtained. The thirdmodelisabankingmodelwithinteractionontheinterbankmarket.Inthe interbank market,banksthatlackliquiditywillborrowfundsfrombankswithexcess liquidity.Eachbankthatlackofliquidityhasarandomnumberoflinkstobanks that haveexcessliquidity.Tosimplifythemodel,bankseitherborrowasmuchas theyneedornotatall.Banksthatcannotmeettheirliquidityneedsbecauseof not fulfillingtheirneedsaredefinedasfailedbanks.Inthismodelthereisnobank resolutionforfailedbanks,sothefailedbankswillberemovedfromthebanking networks immediately.Itisalsoassumedthatthebankingstabilityismeasured using thenumberofbanksthatsurvive(notfailbanks)overtime.Themorethe number ofsurvivingbanksmeansthatthemorestablethebankingnetwork.The LDR-RR’sparametersareanalyzedfortheireffectonthebankingstability.