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Financial engineering  the nuclear option
 

Financial engineering the nuclear option

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    Financial engineering  the nuclear option Financial engineering the nuclear option Presentation Transcript

    • Financial Engineering : 
Is it a nuclear option?"Stavros A. Zenios"University of Cyprus"The Wharton Financial Institutions Center"MIE Distinguished Seminar Series!University of Toronto!April 2013!
    • 2OUTLINE"•  The issue!•  Three applications:!– Products with Guarantees and Personal FinancialPlanning!– Collateralized Mortgage Obligations !– European Stability Bonds!•  Reflexivity of financial engineering!
    • When does financial engineering backfire
"– Errors are magnified through optimization!•  Constraints ignored or mis-specified!•  Data errors!– Response!•  robust optimization, stochastic programming, 
scenario optimization!!– Create a reflexive world!•  When successful and large-scale!•  Success and large-scale may hurt you!– Response!•  ???!3
    • 4Products with guarantees"•  Financial innovation: insurance + investment!•  Minimum guaranteed return: “Smoothing”!–  Pension funds!–  Life insurance policies and mutual funds !–  Investment side of commercial Banks!–  Personal financial planning!•  Fixed income securities can hardly yield the guarantee!•  Regulatory restrictions!
    • 5Participating policies"•  Sum insured payable if event occurs!•  Otherwise the insured sum capitalized at therate of an asset portfolio!– bonus policy"•  Minimum guaranteed rate of return!•  Lapse option to surrender the policy!
    • 600.020.040.060.080.10.121 2 3 4 5 6 7 8 9 10 11 12Portfolio Retuns Policy ReturnsSuffer shortfallBuild buffer
    • 70.511.522.531 2 3 4 5 6 7 8 9 10 11Time periodCumulativereturnsFloor Asset returns Policy returns Lifted floor
    • 8Bonus Policies"•  Italian firms:!–  Bonuses are contractually specified!–  Policyholders receive a fixed percentage of excess returns!•  UK firms:!–  Flexibility in determining the bonus policies!–  Can reduce bonuses if asset portfolio performs poorly!–  Policyholders’ Reasonable Expectations (PRE)!
    • 9Modeling issues"•  Pricing the options!– guarantee (bond)!– bonus (European option)!– lapse (American option)
!•  Brennan and Schwartz (1976), Boyle and Schwartz (1977)!•  Grosen and Jorgensen (1999), Bacinello (1999)
Giraldi et al. (2000), Siglienti (2000)!
    • 10Further modeling issues"•  Capitalizing the product!•  Satisfy regulatory requirements!•  Design competitive policies
!
    • 11Enterprise Wide Risk Management"•  Design new product!•  Integrate disparate sources of risk!•  Financial risks and business risks!Simulation + Optimization!!Holmer and Zenios, Integrated financial product management,Operations Research, Vol. 43, 1995. !
    • 12Stochastic Programming"•  Optimization under uncertainty !•  Dynamic: decisions are revised with time 
as more information is received!•  Anticipate uncertainty and adapt with it

G.B. Dantzig (1955), R. J-B. Wets (1966)
J.R. Birge and F. Louveaux (1997) 

Y. Censor and S.A. Zenios (1997)
Parallel Optimization: Theory, Algorithms and Applications,
Oxford University Press.

S.A. Zenios and W.T. Ziemba (2006)
Handbook of Asset and Liability Modeling, 
North-Holland.!
    • 13Scenario tree"0.0130.0150.0170.0190.0210.0230.0250.0270.0290 2 4 6 8 10 12 14MonthInterestrate0.000.020.040.060.080.100.120.140.160.51 0.52 0.53 0.54 0.55 0.56 0.57 0.57 0.58 0.59 0.60 0.61 0.62 0.63 0.64 0.65 0.66 0.66 0.67 0.68 0.69 0.Exchange rateProbability0.0130.0150.0170.0190.0210.0230.0250.0270.0290 2 4 6 8 10 12 14MonthInterestrate0 T1
    • April 19, 201314The PROMETEIA model:
Integrate option pricing problem with asset allocation problem
"
    • 15The PROMETEIA model"
    • 16The PROMETEIA model"
    • April 19, 201317Bonus Policies"•  Italian policies:

!•  UK policies:!

!!)))(,0max(1(1gRgLL Pttt−++= −α)1)(1( 11 −− ++= ttt RBgLLreversionary bonus 
set at the discretion of the firm"
    • 18Results for the Italian insurance industry"•  Does it pay to integrate risk decisions?
!•  How far can the industry push its policies?!•  Design competitive policies
!•  23 stock indices and 3 bond indices (IT)!•  Stock and bond indices (UK, USA, JP)!•  Corporates (USA)!
    • 19Are mean-variance portfolios efficient?"0.0040.0050.0060.0070.0080.0090.010.0110.0120.0130.006 0.011 0.016 0.021 0.026 0.031Standard deviationExpetedreturnABG
    • 20Cost of guarantee and CEexROE of mean-variance portfolios"0.060.0650.070.0750.080.035 0.037 0.039 0.041 0.043 0.045 0.047 0.049 0.051 0.053 0.055Cost of min. guaranteeNetCEexROEGABH
    • 21How far can the industry push its policies?
Cost of min. guarantee vs net CEexROE "00,020,040,060,080,10,120,140,160 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1Cost of minimum guaranteeNetCEexROEm.g. = 0.01m.g. = 0.04m.g. = 0.07m.g. = 0.12Mean-variance efficient portfoliosfor 4% minimum guarantee productsHThe value of the integrative modelfor 4% minimum guarantee products
    • 22Comparisons with benchmark portfolios"00.020.040.060.080.10.120 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.1680/20
    • 23How far can the industry push its policies?
Net CEexROE vs min. guarantee"00.020.040.060.080.10.120.1400.010.020.030.040.050.060.070.080.090.10.110.120.13Minimum GuaranteeNetCEexROEUKItaly
    • 24Shareholders vs Policyholders "00.020.040.060.080.10.120.140 0.1 0.2 0.3 0.4 0.5 0.6Cost of the GuaranteeNetCEexROEUKItaly00.050.10.150.20.250.30 0.02 0.04 0.06 0.08 0.1Standard DeviationMeanReturnUKItalyShareholders"Policyholders"
    • April 19, 201325Web based financial services
    • 26
    • 27
    • 28Argentinean 2001 debt restructuring!$81.8 billion!!!100,000 Italian pensioners!loose their pension!
    • 29Collateralized Mortgage Obligations"BAAAAAAA DebtFirst LossPositionCDO
    • NINJA loansRegion Total 3Q08 2Q08 1Q08 4Q07 3Q07Worldwide 516,3 18,1 115,1 168,0 167,9 47,2America 263,0 18,1 70,3 69,3 75,9 29,4Europe 229,5 0,0 41,3 89,3 81,3 17,6Asia 23,9 0,0 3,4 9,4 10,7 0,4Loan write-offs in billions (DZ Bank research publication, 2008)Total MortgageOriginations(Billions)SubprimeOriginations(Billions)Subprime Sharein TotalOriginations (%of dollar value)SubprimeMortgageBackedSecurities(Billions)PercentSubprimeSecuritized (%of dollar value)2001 $2 ,215 $190 8.6% $95 50.4%2002 $2,885 $231 8.0% $121 52.7%2003 $3,945 $335 8.5% $202 60.5%2004 $2,920 $540 18.5% $401 74.3%2005 $3,120 $625 20.0% $507 81.2%2006 $2,980 $600 20.1% $483 80.5%
    • The bubble!S&P/Case-Schiller Home Price Index
    • European Stability Bonds"•  Blue bonds-red bonds!•  Debt redemption fund!!!!!!32Debt/GDP ratio" Debt/GDP ratio"Borrowing rate" Borrowing rate"
    • European Stability Bonds"•  Pool sovereign bonds and collateralize!– European Safe Bonds –ESBies!– European Junior Bonds –EJBies!•  ESBies have no country risk!•  ESBies create reserve currency!•  Flight from EJBies to ESBies!•  No EU institutional or Treaty arrangements!33
    • European Stability Bonds"Suspiciously similar to CMOs!!!!!! 34
    • 35Discussion: can financial engineering destroythe financial system"•  Ulrich Beck, 1992 -Risk society. !•  Anthony Giddens -Duality of structure !•  George Soros, 2008 -reflexivity of the markets!•  Peter Bernstein 1996–Against the gods!
    • •  Modeling errors –Fallibility!– Know within limits!– Uncertainty in data!•  Modeling uncertainty in data!•  Modeling success –Reflexivity!– Model creates uncertainty!– Uncertainty reflects back on model!Discussion: can financial engineeringdestroy the financial system"
    • •  Use reflexivity to make money!•  Can destroy the system:!– LTCM!– Equitable Insurance!– Sub-prime crisis!•  Reinhart and Rogoff excel error!Discussion: can financial engineeringdestroy the financial system"
    • Conclusion"Financial engineering:""Fertile Fallacy"38
    • •  Karl Marx 
!“Society poses itself only such problems 
as it can solve” !•  John F. Kennedy
!“Our problems are man-made, 
! therefore they can be solved by men”!•  Stavros A. Zenios amendment 
!“Our problems are man-made, 
! therefore they can be solved by women”!Conclusion"