Breakeven Determination of Loan Limits for Reverse Mortgages under Information Asymmetry


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1 IRES IRES Working Paper Series Breakeven Deerminaion of Loan Limis for Reverse Morgages under Informaion Asymmery Ming Pu GangZhi Fan Yongheng Deng December, 01
2 Breakeven Deerminaion of Loan Limis for Reverse Morgages under Informaion Asymmery Ming Pu * GangZhi Fan Yongheng Deng December 01 Absrac Since he loan limi of a reverse morgage is a major concern for he borrower as well as he lender, his paper aemps o develop an opionbased model o evaluae he loan limis of reverse morgages. Our model can idenify several crucial deerminans for reverse morgage loan limis, such as iniial housing price, expeced housing price growh, house price volailiy, moraliy disribuion, and ineres raes. We also pay special aenion o he imporan implicaion of morgage lenders informaional advanage over reverse morgage borrowers concerning housing marke risk. In reverse morgage markes, he elderly borrowers ypically hold far less, relaive o he lenders, or no informaion abou he lenders underlying morgage pools. Such informaion asymmery leads hese wo caegories of marke paricipans o generae differen perspecives on he risk of he collaeralized properies, which can be idenified o be imporan in deermining he maximum loan amouns of reverse morgages. We furher find ha he maximum loan amoun of a reverse morgage decreases in he correlaion beween he sysemaic reurn and he reurn on is underlying housing propery bu increases wih he number of he pooled morgages. Key Words: Reverse Morgages, Heerogeneous Beliefs, Informaion Asymmery, Loan Limi JEL: G1, G, J14, R * School of Insurance, Souhwesern Universiy of Finance and Economics, 55 Guanghuacun Sree, Chengdu, China. Corresponding Auhor. Deparmen of Real Esae, Konkuk Universiy, 10 Neungdongro, Gwangjingu, Seoul , Korea. Insiue of Real Esae Sudies, Naional Universiy of Singapore, 1 Heng Mui Keng errace, #040, Singapore We would like o hank Chunseob Lee, Seven Li, Dogan iriroglu, Seow Eng Ong, Kwong Wing Chau, Zhi Dong, an anonymous referee and paricipans a he 011 Asian Real Esae SocieyAmerican Real Esae and Urban Economics Sociey Join Inernaional Conference and he 011 AsiaPacific Real Esae Research Symposium for helpful commens. Any errors are our own. 1
3 Breakeven Deerminaion of Loan Limis for Reverse Morgages under Informaion Asymmery 1. Inroducion Growing number of economies such as Japan, U.S., China, Korea, EU counries are moving rapidly owards aging socieies, which have gradually produced a series of social and economic issues in hese economies (Weizsäcker, 1996; Faruqee and Mühleisen, 003; Li, 005; Davis, 1997). Reverse morgages provide houserich bu cashpoor elderly homeowners wih a caegory of promising financial producs o obain loans from morgage lenders using heir homes as loan collaeral wihou losing he enure of hese premises, and herefore represens a poenial channel ha allows hem o wihdraw heir subsanial home equiies for improving heir consumpion and reiremen securiy. In he U.S., he Federal Housing Adminisraion (FHA) launched he Home Equiy Conversion Morgage (HECM) program in 1989 afer he passage of he Naional Housing Ac of Under he HECM program, cashpoor bu houserich homeowners aged 6 and above can wihdraw he equiy of heir homes in he form of a lump sum paymen, a line of credi, monhly paymens, or any combinaion of hese, which is also insured by he FHA [see, e.g., Mayer (1994) and Kuy (1998)]. HECM loans are he mos widely used caegory of reverse morgages and accoun for more han 90% share of he U.S. reverse morgage marke. 1 Alhough here were only abou several hundred HECM loans originaed each year during he whole 1990s (Bishop and Shan, 008), he number of HECM loans originaed each year has significanly increased over he pas decade while experiencing he adverse influence of he recen finance urmoil. Due o he grea poenial of reverse morgage programs in addressing he social and economic problems discussed above in rapidly aging sociey, here is a growing 1 See Hammond (1993) for he deails abou oher caegories of reverse morgages in he U.S.
4 volume of lieraure invesigaing he feasibiliy and poenial of developing he reverse morgage markes in differen counries. For example, Michell and Piggo (004) show ha since elderly dependency raio in Japan, already quie high among he developed economies, is projeced o reach 45 percen by 030 due o increasing longeviy and declining feriliy, releasing home equiy in his counry via reverse morgages will faciliae boosing elderly consumpion, enhancing reiremen securiy and miigaing public pension liabiliy [see also Hayashida and Sasaki (1986)]. AddaeDapaah and Leong (1996) invesigae he applicabiliy of he Home Equiy Conversion Scheme (HECS) o he elderly in Singapore, and heir findings show ha selling home equiy in exchange for a life enancy will be a subsanial poenial form of HECS program for elderly Singaporeans. Chou e al. (006) explore he viabiliy of culivaing he reverse morgage marke in Hong Kong. Since here is no reiremen proecion scheme for is elderly aduls, who are also one of he larges povery groups in his ciy, heir findings demonsrae ha he reverse morgage program has conribued o he improvemen of he economic saus and wellbeing of he elderly and o he miigaion of he financial burden of is governmen. For hese reasons, we migh expec ha he reverse morgage program will become more and more popular in many pars of he world in he nex decades in ha boh he absolue number and percenage of elderly people are growing rapidly in hese economies. Alhough he exising lieraure has examined he poenial demand for various reverse morgage programs, lile research has addressed he loan limi issue of reverse morgages. his sudy fills he gap o sudy he valuaion of he loan limis of reverse morgages, which is a major concern for heir borrowers in addiion o heir lenders (Sawyer, 1996). A large body of lieraure has explored he valuaion issue of he convenional morgages subjec o defaul risk or prepaymen risk. he overwhelming majoriy of he lieraure has developed opionbased models, boh For more discussions on he poenial demand of reverse morgages, see for example Levion (001), Rasmussen e al. (1995), Merrill e al.(1994), Mayer and Simons (1994), and Shan (011). 3
5 heoreical and empirical, o he valuaion issue of hese morgages. 3 However, compared wih he convenional ones, we can idenify from he relevan lieraure several remarkable feaures associaed wih reverse morgages. Firs, reverse morgages are ypically a caegory of nonrecourse loans such ha a lender can only realize he repaymen of is loan principle and ineres using he sales proceeds of he collaeralized home. If he value of he home is insufficien o reclaim he ousanding balance of he reverse morgage a he ime of sale, he lender has o suffer a loss due o no recourse o oher asses. Chinloy and Megbolugbe (1994) define he risk of he ousanding loan balance exceeding he house equiy value as crossover risk, which is usually our major concern in he valuaion of reverse morgages. Also, since he reverse morgage borrower is no required o repay any principal and ineres prior o his deah or permanen moveou from he house, his ousanding loan balance will gradually increase over ime due o accrued ineress and possible monhly paymens. 4 Second, since under he reverse morgage program an elderly borrower can sill coninue o say in his home unil he dies or moves ou of his home permanenly, he morgage erminaion is usually designed on he basis of published acuarial moraliy ables. If he borrower lives longer han he life expecancy esimaed from he ables, hen he lender is exposed o longeviy risk. 5 In conras, a convenional morgage debor is usually only vulnerable o defaul risk and prepaymen risk. Given ha longeviy risk has imporan implicaion for he deerminaion of reverse morgage loan limis, a simple applicaion of he sandard opion pricing model o reserve morgages wihou consideraion of uncerain moraliy is likely o resul in an inaccurae evaluaion of maximum morgage loan amoun. As a resul, his paper develops a breakeven framework for evaluaing morgage loan limis ha aemps o inegrae longeviy risk as well as crossover risk ino he opionbased valuaion 3 See for example Kau e al. (199, 1995), Hilliard e al. (1998), Epperson e al. (1985), Brunson e al. (001), Deng (1997), Deng e al. (000), Ciochei and Vandell (1999), and Archer e al. (00). Kau and Keenan (1995) provide a comprehensive survey on such caegory of earlier lieraure. 4 Ma and Deng (006) sudy he insurance premium srucure of reverse morgage loans in Korea. hey find ha o he relaively younger borrowers, he graduaed monhly paymen approach is more efficien, while he consan monhly paymen approach is more efficien for he elderly borrowers. 5 We can also idenify from he relevan lieraure oher risk facors, such as homevalue risk and mainenance risk (Syzmanoski, 1994; Miceli and Sirmans, 1994). he crossover risk is acually mainly deermined by boh longeviy risk and home value risk. 4
6 model. In he breakeven poin, he acuarial presen value of he loan amouns paid by he lender o he borrower mus equal he acuarial presen value of he payoff which he lender will receive a he mauriy dae. Furhermore, anoher imporan conribuion of our sudy is he consideraion of morgage lenders informaional advanage over reverse morgage borrowers abou heir home values in he secor of reverse morgages. In he convenional morgage markes, we can usually idenify he informaion asymmery concerning a morgage borrower s credi characerisics beween he borrower and he primary lender, or beween hese wo paries and he ulimae invesors in he secondary morgage marke (Kau e al., 011). In conras, such informaion asymmery is no a major concern in reverse morgage markes, in ha for a reverse morgage, he appraisal value of is underlying home insead of he credi characerisics is usually a major consideraion bu is also common knowledge for boh he elderly borrower and he morgage lender. However, i is noeworhy ha morgage lenders usually provide reverse morgage loans o a grea number of elderly borrowers and manage heir morgage pools, such ha idiosyncraic risk in he underlying morgage pools can, o a large exen, be diversified away, while hose borrowers know very lile abou he deails of he underlying morgage pools. We can show here ha such informaion asymmery migh lead hese wo caegories of marke paricipans o produce heerogeneous beliefs on he volailiy in he housing marke. In effec, morgage lenders informaion advanages have been idenified o have imporan implicaions for morgage markes in several recen sudies. For example, Bond e al., (009) highligh ha morgage lenders informaion advanages over morgage borrowers abou collaeralized home values can provide an ineresing explanaion on he occurrence of predaory morgage lending (Bond e al., 009). Gan and Riddiough (008) provide empirical evidence ha morgage lenders can exploi heir informaion advanages o deer he poenial compeiors from enering he U.S. residenial morgage marke. 5
7 Basak (000) furher emphasizes ha heerogeneous informaion can make marke paricipans generae heerogeneous beliefs or inferences on he sochasic evoluion of asse prices. We allow for he imporan implicaion of heerogeneous beliefs caused by morgage lenders informaional advanage abou house prices for he loan limis of reverse morgages. Several imporan sudies such as Deemple and Murhy (1997) and Basak and Croioru (000, 006) have demonsraed ha heerogeneous beliefs maer in generaing rades in financial markes. Oher financial lieraure has also focused aenion on he significan effecs of heerogeneous beliefs on asse pricing (e.g., Scheinkman and Xiong, 003; Li, 007). Since reverse morgage markes can be characerized by asymmeric or heerogeneous informaion as discussed above, our analysis pays aenion o he key role of morgage lenders informaional advanage in generaing heerogeneous beliefs. We assume ha marke paricipans are of homogeneous or common prior belief on he price process of an underlying individual house, which is a ypical assumpion in game heory and he economics of informaion (e.g., Bonanno and Nehring, 1999). More specifically, boh he morgage lender and he reverse morgage borrowers are specified o have he same or homogeneous belief on he expeced percenage growh and volailiy of he underlying house price. However, since he lender holds complee informaion abou is morgage pools, i can make housing marke inferences based on modern porfolio heory, while he borrowers only have very lile or no informaion on hese pools. Such informaion asymmery can make hese wo caegories of marke paricipans produce he heerogeneous beliefs concerning he volailiy of he pooled underlying houses. his is because, given ha propery price volailiy can be decomposed ino sysemaic volailiy and idiosyncraic volailiy (Miao and Wang, 007), he idiosyncraic risk of he underlying propery price can be diversified away by adoping a porfolio sraegy. As a consequence, we can demonsrae ha he lender informaion advanage can play an imporan role in deermining he loan limis for reverse morgages and herefore he lender economic profi size. 6
8 On he oher hand, we also show ha for he reverse morgage borrowers, heir informaion disadvanage migh lower he amouns of morgage loans hey can obain from he lender. During he pas wo decades, in effec, he marke share of diversified morgage lenders have experienced a furher obvious increase, while he share of concenraed lenders ha provide mos of morgage loans in one local marke has dropped o around 4% five years ago (Louskina and Srahan, 011). his suggess ha he porfolio managemen of morgage loans has become very popular and been widely adoped as one imporan sraegy of risk diversificaion in he secor of morgage lending. Alhough he size of he underlying reverse morgage pool migh be very small a he sage of reverse morgage originaions, he lender can sill realize he diversificaion of morgage porfolios across he differen regions or caegories of morgages, in ha morgage porfolios migh be effecively diversified across he differen regions and caegories (Eichholz e al. 1995). In his case, he lender can gaher he relevan informaion from he morgage porfolios, while he borrowers suffer an informaion disadvanage relaive o he lender and can only acquire he less amouns of morgage loans. As a resul, such informaion asymmery cerainly maers no only for he borrowers who choose he lifeime annuiylike paymen plan or he line of credi paymen plan, bu also for he borrowers who choose o receive an upfron lumpsum morgage paymen a he ime of reverse morgage originaion. In effec, i can also be shown ha our main findings are likewise applicable o he credi analysis of he radiional house morgage secor and herefore provide new insighs ino he loan limis of radiional house morgages, which are closely relaed wih he recen real esae crisis. he remainder of his aricle is organized as follows. Secion develops an opionbased model for deermining he maximum loan amouns of reverse morgages. Secion 3 proposes hree caegories of models o measure longeviy risk. Secion 4 applies he proposed model o numerical analysis. Secion 5 summarizes his aricle and draws conclusions. 7
9 . Reverse Morgage Models.1 Basic Assumpions Suppose ha a houserich bu cashpoor elderly homeowner is considering wheher or no o ener ino a reverse morgage conrac in order o resolve his consumpion problem. According o his conrac, he can conver his home equiy ino a lump sum paymen or a life annuiy for he res of his life. He does no need o repay he borrowed morgage loan and accrued ineress unil he dies or moves ou from his dwelling. he ousanding balance owed o a lender will be repaid using he sales proceeds of he house uni. If he proceeds are insufficien o repay he ousanding balance, he lender has o suffer a morgage loan loss. hree major risk facors longeviy, housing prices, and ineres raes are usually aken ino consideraion in he valuaion of reverse morgages [see, e.g., se (1995)]. For he purpose of his sudy, however, we mainly focus on he imporan implicaion of uncerainies on longeviy and housing price in he valuaion of reverse morgages. 6 In exising morgagepricing lieraure, housing prices are ypically assumed o follow a geomeric Brownian moion process so ha he lieraure can model uncerainy on hese prices. FHA also usually assumes ha housing prices evolve following a geomeric Brownian moion process in is reverse morgage pricing model (Quercia, 1997). o explore he impac of he housing price uncerainy, we likewise assume ha he housing price follows a geomeric Brownian moion process as follows: dp = µ Pd + σpdw, (1) where µ is he expeced percenage growh in house price, σ is he volailiy parameer of house price, and W is a sandard Brownian moion. 6 However, we will exend our model o allow for he effecs of changes in wo caegories of ineres raes in he numerical analysis, such as loan ineres rae and riskfree ineres rae. his will provide addiional insighs ino he usefulness of our valuaion model. 8
10 Longeviy risk is anoher crucial deerminan of he crossover risk of reverse morgages. o capure he impac of his risk facor, le be he ime insan a which he deah of he homeowner occurs. For any given ime > 0, he cumulaive disribuion funcion and he probabiliy densiy funcion of he random deah ime can be defined, respecively, as follows F ( ) = Pr( ), () f() = F'(). (3) Correspondingly, he survival funcion specifies he probabiliy a which he homeowner can live beyond ime S ( ) = 1 F ( ) = Pr( > ). (4) In addiion, o describe he insananeous deah rae, acuaries define he force of moraliy by S'( ) λ () =. (5) S () In his analysis we allow he homeowner o wihdraw his house equiy by choosing eiher of wo ypical caegories of reverse morgage schemes, namely a lump sum paymen and a lifeime annuiy. In hese wo schemes, we will develop a breakeven framework o deermine boh he maximum morgage loan amouns offered by he lender and he minimum loan amouns accepable for he homeowner. Our model differeniaes wo caegories of ineres raes. he firs one, R, is he rae a which he lender is going o charge he elderly homeowner, and which is used o calculae he ousanding loan balance. he second one, r, is he riskfree ineres rae 9
11 or he opporuniy cos, which is uilized o calculae he presen value of he morgage loan. Since his model is developed in he coninuous ime conex, he ineres raes are compounded coninuously. 7. Porfolio Diversificaion he operaion of insurance indusry largely relies on he Law of Large Numbers and he Cenral Limi heorem,and his principle is likewise applicable o he reverse morgage secor. According o hese heories and modern porfolio heory, if he number of pooled reverse morgages is sufficienly large, he house price risk in he morgage pool can be, o a large exen, diversified away. In order o allow for he imporan implicaion of morgage porfolios in his analysis, we relax he previous assumpion by allowing he lender o provide reverse morgage loans o N elderly homeowners. For simpliciy, suppose ha all he morgage borrowers have he same age x, and ha boh he lender and hese borrowers hold he homogeneous belief on he expeced growh and volailiy of he price of any individual housing uni. As a resul, he prices of N underlying houses can be expressed as an Ndimensional vecor ha follows a sysem of geomeric Brownian processes dp = µ P d + σp dw for i = 1,,3... N (6) () i () i () i () i, where ( i) W represens a sandard Brownian moion driving he sochasic evoluion of underlying propery i price. Miao and Wang (007) show ha he oal volailiy of real esae value can be decomposed ino sysemaic volailiy and idiosyncraic volailiy. his suggess ha he value of a propery is influenced by idiosyncraic risk 7 For exposiional convenience, boh R and r are specified o be deerminisic variables in our analysis and are herefore independen of each oher. An exension of allowing hese wo variables o be correlaed wih each oher will complicae our analysis subsanially, while i does no provide addiional insighs ino our research quesion. Despie such specificaion, however, we will show in Figure 4 ha when hese wo raes are becoming closer o each oher, he annuiy paymen will decline. 10
12 as well as sysemaic risk. Accordingly, we may decompose each W according o () i he following expression dw = ρdz + 1 ρ db, i = 1,,3,..., N (7) () i () i i i where ρ i can be explained as he correlaion coefficien beween he sysemaic reurn and he reurn on underlying propery i, Z is a sandard Brownian moion sanding for he sysemaic shock, B is a sandard Brownian moion represening () i he idiosyncraic shock and is independen of Z and B for j i and j = 1,,3,..., N. In addiion, ρσ i can be explained as he sysemaic componen of ( j ) house price volailiy, while ρ σ represens he idiosyncraic componen. I is 1 i noeworhy ha even hough he parameer ρ i is of he same value across he underlying propery pool, he Brownian moions W migh be differen in ha () i are independen of he sysemaic shock and of each oher. () i B Le P N = P be he oal value of hese N homes. By adding he sochasic i= 1 () i differenial equaions by each P () i, we obain N N N () i () i () i () i dp = µ P d + σ P dw i= 1 i= 1 i= 1. (8) o simplify he analysis, we assume ha he correlaion coefficien ρ i = ρ is consan across he underlying propery pool. his is similar o considering he equally weighed porfolio in modern porfolio heory, and such assumpion can, o a large exen, simplify our model in order o shed new ligh on he deerminaion of he maximum loan amouns. An exension of relaxing his assumpion will complicae our analysis and resul in he inracabiliy in mahemaical reasoning, and he resulan model can only be solved numerically using MoneCarlo simulaion. Also, such 11
13 relaxaion canno produce addiional insighs ino our main issues of ineres. As a resul, subsiuing (7) ino (8), we direcly obain P dp Pd P ( dz 1 db ). (9a) N () i () i = µ + σ ρ + ρ i= 1 P P where P () i can be inerpreed as he weigh of house i value in he underlying house porfolio. Wihou loss of generaliy, suppose ha he weigh can be expressed as π = i P P () i, where N i i π = 1 and 0< π < 1 for each i. Subsiuing his weigh ino i= 1 (9a) produces he following equaion N i () i = µ + σ ( ρ + π 1 ρ ) i= 1 dp Pd P dz db. (9b) Define N 1 i () i W = ρz π 1 ρ B θ + (10) i= 1 θ = ρ + (1 ρ ) π. I is easy o verify ha W is also a sandard i where ( ) N i= 1 Brownian moion. herefore, from a porfolio perspecive, he oal value of hese pooled properies saisfies he following sochasic differenial equaion N () i 0 0 i= 1 dp = µ Pd + σpdw, P = P, (11) 1
14 where σ = θσ, and P is he iniial price of underlying propery i. Given () i 0 N N i i ( π ) < π = 1, one may easily find ha when N >1, 1 i= 1 i= 1 θ < always holds. his indicaes ha θ is sricly less han uniy such ha he volailiy of he underlying propery porfolio is less han ha of any individual house due o he diversificaion impac of propery porfolio. For exposiional convenience, suppose ha all he underlying homes have he same i 1 weigh a a given ime, ha is π =. In his case, equaion (10) can rewrien as N N 1 1 () i W = ρz 1 ρ B θ + N (1) i= 1 1 whereθ = ρ + (1 ρ ). By equaions (11) and (1), when he lender provides N reverse morgage loans o more han one elderly homeowners, he expeced price growh of he underlying propery pool is sill kep he same as ha of any individual home, bu is volailiy would be reduced compared wih hose of any individual home. his implies ha boh he lender and he elderly borrowers always have a common expecaion on he percenage price growh of he underlying houses bu could have heerogeneous perspecives on heir volailiy magniudes. As he number of reverse morgage loans in he morgage pool increases, we find lim θ = ρ N. his means ha boh he number N and he correlaion coefficien ρ could have imporan implicaion for he deerminaion of reverse morgage loan limis. If here are a sufficienly grea number of elderly homeowners who have obained reverse morgage loans, he lender would be only exposed o sysemaic risk in he housing 13
15 marke due o he diversificaion effec of propery porfolio. However, he individual elderly homeowners are sill exposed o he idiosyncraic risk as well as he sysemaic risk in he marke if hey plan o sell ou heir homes, in ha hey canno diversify away he idiosyncraic risks of heir houses via developing a similar porfolio sraegy. his is analogous o he insurance indusry. Alhough an individual policy holder has a considerable probabiliy o experience a large damage even, insurance companies can largely decrease he uncerainy via selling a grea number of insurance policies according o he Law of Large Numbers. hese companies make full use of his advanage o charge he insurance premiums which are profiable for hem while being also accepable o each policy holder. Furher, we also allow for wo exreme cases: ρ = 1 and ρ = 0. If ρ = 1, one may easily find ha θ = 1 and σ = σ. 8 his indicaes ha if he reurns on he pooled properies are compleely correlaed and heir sochasic evoluions will be driven only by a single sysemaic Brownian moion. In his case, any risk in he underlying propery pool canno be diversified away, and boh he lender and he homeowners herefore have he idenical perspecive on he house volailiy. As a resul, here are no bidask spreads of morgage loan amouns generaed by heir marke beliefs on house risk (see Figure 10). Similarly, in he insurance indusry insurance companies are usually no willing o insure hose damages ha are highly correlaed. For example, propery insurance policies usually exemp he insurance companies from he coverage for damages caused by earhquakes. On he oher hand, if ρ = 0, he reurns on he pooled properies are pair wise independen of each oher. In his scenario, we have θ = 1 N, which is he minimum 8 When ρ = 1 and ρ = 1, we can readily find ha boh of hem will produce he same effec on he loan limis from he lender s perspecive. If ρ = 1, we only need o replace moion Z, and hen we can obain he same resul on he limis as in he case of ρ = 1. Z by a new sandard Brownian 14
16 θ value for fixed N, and he idiosyncraic risk of he underlying propery porfolio can be diversified o he larges exen. he lump sum or he annuiy paymen offered by he lender is herefore highes in his case, and he bidask spread of morgage loan amouns is larges (see Figure 10). One may also noice ha if N approximaes infiniy in his case, we have lim θ = 0. ha is, as he number of he pooled morgages N approaches infiniy, he price of he underlying propery porfolio in he lender s viewpoin evolves in a deerminisic manner, while hose morgage borrowers sill hink ha housing prices are governed by he sochasic processes specified above..3 Lump Sum Paymen and Bid/Ask Amouns In his secion, we discuss he deerminaion of he breakeven paymens of reverse morgage loans if he morgage borrowers choose o receive a lump sum paymen a = 0. Since all he elderly morgage borrowers are homogeneous, for exposiional convenience we look a his issue from an individual morgage borrower s and a lender s perspecive. As we have menioned above, hese wo marke paricipans hold he homogeneous belief on he expeced growh of he housing prices, whereas hey could have differen beliefs on housing volailiy due o he diversificaion impac of propery porfolio. Under our model framework, we specify ha he acuarial presen value of he loan amoun provided by he lender o he elderly borrower should be equal o he acuarial presen value of he payoff received by he lender a he mauriy dae such ha he breakeven loan amoun can be deermined endogenously. We can find ha because of he heerogeneous beliefs on housing volailiy, hese wo paricipans can hold differen viewpoins abou he breakeven loan amoun such ha a bidask amoun spread is generaed. Suppose ha he lender makes a lump sum paymen o he homeowner a he beginning of he conrac, = 0. We iniially fix he homeowner s deah ime a ime = and only allow for uncerainy on housing price. Condiional on his assumpion, he breakeven lumpsum paymen of he loan can be deermined according o he 15
17 following breakeven condiion ( ) max,0 r r R L = e E P e E P Le (13) where he lefhand side erm represens he breakeven loan amoun received by he homeowner a ime 0, while he righhand side represens he presen value of he payoff which he lender will receive a he mauriy dae. Since he soluion o equaion (1) can be expressed as 1 P = P0 exp[( µ σ ) + σw], (14) We can obain he following expression regarding he firs erm of he righhand side in (13) r r 1 e E[ P ] = Pe 0 E exp ( µ σ ) + σw ( µ r ) 1 = Pe 0 E exp σ + σw. (15) 1 According o Io s Lemma, we may readily verify ha Z = exp( σ + σw) is a maringale, so is expecaion is EZ = EZ0 = 1. Hence, we have ( ) [ ] r r e E P Pe µ 0 = (16) he second erm of he righhand side in (13) may be viewed as he payoff of a European call opion, while is srike price R Le is a funcion of he given deah ime. As a consequence, for he given deah ime we may calculae he second erm using he echnique similar o ha of obaining he value of he European call opion [see Shreve (004, p.190)]. he proof deails are given in Appendix A 16
18 while he resulan expression is direcly given by E e P Le Pe Nb L Le Nb L r R ( m r ) ( R r ) max(,0) = 0 ( 1( )) ( ( )) (17) where 1 P 0 1 b1( L) = b( L) + σ = log ( r σ ) R + + σ Le Proposiion 1: Given ha he price of he collaeralized home is governed by a geomeric Brownian moion process and he homeowner s deah ime is fixed a, he breakeven lumpsum paymen of he reverse morgage loan saisfies he following equaion ( µ r ) ( µ r ) r R L = Pe 0 Pe 0 N( b1( L)) + e Le N( b( L)) (18) Proof: his proof is sraighforward by subsiuing (16) and (17) ino (13). I is worh noing ha he derivaion of equaions (17) and (18) is differen from he process of obaining he classic BlackScholes opion formula. We do no assume he compleeness of he marke such ha he convenional noarbirage argumen does no work here anymore. Insead, we calculae he breakeven paymen by equaing he acuarial presen value of he cash flow from he lender o he borrower wih ha from he borrower o he lender. Based on he principle, we can derive equaions (17) and (18). he soluion of (18) wih regard o L does no have a closedform expression, bu we may solve i numerically. I is also noeworhy ha o derive L we have assumed ha he deah of he morgage borrower occurs a a fixed ime, while he individual life span could change a random in acuarial pracice. If he uncerainy of moraliy is aken ino consideraion, hen he breakeven lumpsum paymen is given 17
19 by L = L f () d. (19) 0 We may uilize (18) and (19) o deermine he breakeven loan amoun. I can be shown ha he breakeven paymen always decreases in he housing volailiy. If we exend his model o allow for a grea number of elderly morgage borrowers, his suggess ha he volailiy for he lender be smaller han any one of he elderly borrowers believes due o he diversificaion effec of propery porfolio. As a resul, he lender is acually willing o offer higher breakeven paymens han he elderly borrowers expec. Proposiion : Suppose ha all he N collaeralized homes are homogenous, while heir prices are governed by he respecive geomeric Brownian processes. Given i 1 N > 1and π = a a ime, he bid and ask amouns of lumpsum paymen of a N reverse morgage are deermined by (18), whereas heir volailiy parameers are σ andσ, respecively. Proof: his proof is sraighforward by subsiuing (6) and (1) ino (18). his proposiion suggess ha he volailiy σ of he underlying propery pool can, o a cerain exen, be diversified hrough he porfolio sraegy such ha he bid and ask amouns of lumpsum paymen of a reverse morgage migh be disinc for he lender and he elderly borrower. his is because σ = θσ and θ < 1for N >1, such ha σ < σ holds. Also, one can readily find ha θ ρ > 0, herefore implying ha an drop in he absolue value of he correlaion ρ reduces he value of θ and in urn he value of σ. We may also idenify θ N < 0, which suggess ha an increase in he number N of he pooled reverse morgages decreases he value of σ. 18
20 For he reason, his proposiion can provide imporan implicaion for he bargaining process beween he lender and he elderly borrowers. his proposiion also means ha he lender s marke power plays an imporan role in deermining he markeclearing amoun of lumpsum paymen of a reverse morgage. Le Q [ 0,1] denoe he lender s deerminisic marke power, ha is, her abiliy o deermine he reverse morgage loan amoun independenly. hen he markeclearing reverse morgage amoun is given by L = QL + (1 Q) L clear bid ask where bid L respecively. and ask L represen he bid and ask amouns of lumpsum paymens,.4 Annuiy Paymen In his secion, we assume ha insead of a lumpsum paymen, he elderly borrower chooses a lifeime annuiylike scheme wih coninuous paymens. We will invesigae his caegory of reverse morgages by he similar argumen: we firs fix he elderly borrower s deah ime a and allow for uncerainy in he housing price. Nex, we furher ake longeviy risk ino consideraion. Under his assumpion, upon he deah of he elderly borrower he ousanding loan balance is given by 0 R ( e 1) Rs B( A, R, ) = e Ads = A (0) R where R is he coninuously compounded rae, and A sands for he coninuous rae of morgage loan paymen he lender makes. If he value of he collaeralized house exceeds he ousanding loan balance, his loan canno be repaid unil he deah or moveou of he homeowner; oherwise, he lender can only receive he proceeds from 19
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