This document describes the CLEANTM model for valuing mortgage-backed securities (MBS). The CLEANTM model treats mortgages as callable amortizing bonds and models prepayments by dividing mortgage pools into buckets based on borrower behavior. The key risk factors in the model are interest rates, volatility, and homeowner credit spreads. The model calibrates quickly and intuitively based on observable market data. It provides realistic valuations, risk measurements, and trading opportunities without the limitations of other prepayment models.
Interest rate risk management what regulators want in 2015 7.15.2015Craig Taggart MBA
Areas covered in this section
Why Interest Rate Risk (IRR) should not be ignored
• Forward Rate Agreements (FRA’s) Forwards, Futures
• Swaps, Options
Why Bank Regulators continue to have a poor handle on interest rate risk
• Interest Rate Caps, floors, Collars
• LIBOR and UBS & Barclays rigging rates
• How should Financial Institutions determine which IRR vendor models are appropriate?
IRR Measurement methodologies are institutions
Interest rate risk management for banks under Basel II, presentation by Christine Brown, Department of Finance , The University of Melbourne, Shanghai, December 8-12, 2008
Presentation about interest rate risk
We start with a simple example about deposit rates. We pursue with bondmarkets and turn to the yieldcurve. Than we derive information about future rates with help of zerorates. Finally we discuss how to invest in a matching example for an early retirement scheme
Interest rate risk management what regulators want in 2015 7.15.2015Craig Taggart MBA
Areas covered in this section
Why Interest Rate Risk (IRR) should not be ignored
• Forward Rate Agreements (FRA’s) Forwards, Futures
• Swaps, Options
Why Bank Regulators continue to have a poor handle on interest rate risk
• Interest Rate Caps, floors, Collars
• LIBOR and UBS & Barclays rigging rates
• How should Financial Institutions determine which IRR vendor models are appropriate?
IRR Measurement methodologies are institutions
Interest rate risk management for banks under Basel II, presentation by Christine Brown, Department of Finance , The University of Melbourne, Shanghai, December 8-12, 2008
Presentation about interest rate risk
We start with a simple example about deposit rates. We pursue with bondmarkets and turn to the yieldcurve. Than we derive information about future rates with help of zerorates. Finally we discuss how to invest in a matching example for an early retirement scheme
Interest-rate risk substantially affect the values of the assets and liabilities of most corporations and is often a dominant factor affecting the values of pension funds, banks and many other financial intermediaries.
Interest-rate risk substantially affect the values of the assets and liabilities of most corporations and is often a dominant factor affecting the values of pension funds, banks and many other financial intermediaries.
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Counterparty Credit Risk | Evolution of
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Retail media wordt gezien als het nieuwe advertising-medium en ook mediabureaus richten massaal retail media-afdelingen op. Merken die niet in de betreffende winkel liggen staan ook nog niet in de rij om op de retail media netwerken te adverteren. Marvin belicht de uitdagingen die er zijn om echt aansluiting te vinden op die markt van non-endemic advertising.
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Enterprise excellence and inclusive excellence are closely linked, and real-world challenges have shown that both are essential to the success of any organization. To achieve enterprise excellence, organizations must focus on improving their operations and processes while creating an inclusive environment that engages everyone. In this interactive session, the facilitator will highlight commonly established business practices and how they limit our ability to engage everyone every day. More importantly, though, participants will likely gain increased awareness of what we can do differently to maximize enterprise excellence through deliberate inclusion.
What is Enterprise Excellence?
Enterprise Excellence is a holistic approach that's aimed at achieving world-class performance across all aspects of the organization.
What might I learn?
A way to engage all in creating Inclusive Excellence. Lessons from the US military and their parallels to the story of Harry Potter. How belt systems and CI teams can destroy inclusive practices. How leadership language invites people to the party. There are three things leaders can do to engage everyone every day: maximizing psychological safety to create environments where folks learn, contribute, and challenge the status quo.
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Dr. William Harvey is a seasoned Operations Leader with extensive experience in chemical processing, manufacturing, and operations management. At Michelman, he currently oversees multiple sites, leading teams in strategic planning and coaching/practicing continuous improvement. William is set to start his eighth year of teaching at the University of Cincinnati where he teaches marketing, finance, and management. William holds various certifications in change management, quality, leadership, operational excellence, team building, and DiSC, among others.
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Cracking the Workplace Discipline Code Main.pptxWorkforce Group
Cultivating and maintaining discipline within teams is a critical differentiator for successful organisations.
Forward-thinking leaders and business managers understand the impact that discipline has on organisational success. A disciplined workforce operates with clarity, focus, and a shared understanding of expectations, ultimately driving better results, optimising productivity, and facilitating seamless collaboration.
Although discipline is not a one-size-fits-all approach, it can help create a work environment that encourages personal growth and accountability rather than solely relying on punitive measures.
In this deck, you will learn the significance of workplace discipline for organisational success. You’ll also learn
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CLEAN: A Patented Risk-Neutral Approach to MBS Valuation
1. 61 Broadway New York, NY 10006 212.482.0900 www.kalotay.com
CLEAN™: A Risk-Neutral
Approach to MBS Valuation
2. 2
What Is an Ideal MBS Valuation Model?
MBS price driven by parsimonious set of risk factors
Each factor is readily observed and measured
Risk factor values and sensitivities match reality
Leads to trading opportunities
Unhedged risk factors signal rich/cheap opportunities
Provides a robust basis for risk management
Probability distributions for risk factors imply probability distribution for the
MBS price
3. 3
Other Desirable Features
Minimal dependence on historical econometric data
No redesign required when market conditions change
Speed: fast calibration and valuation
4. 4
Initial Observations
Modeling prepayments is only a means to an end
The real goal is proper valuation and risk measurement
A mortgage is a callable amortizing bond
Prepayment models should be consistent with callable bond models
Bonds (mortgages) are called (refinanced) when the call (refinancing)
option is worth more dead than alive
Bond and MBS models should therefore respond similarly to changes in
interest rate levels and volatilities
5. 5
The CLEAN™ Way
Modeling prepayments
Turnover and defaults modeled using deterministic speeds
Refinancings modeled using stochastic interest rate model
Modeling a mortgage
As a callable amortizing bond
A financial engineer will refinance when the option is worth more dead than
alive
Others will refinance too early (never really happens) or too late
(“laggards”)
Modeling heterogeneous refinancing behavior
Divide mortgage pool into 10 buckets according to laggard parameter
Use a standard laggard distribution for a new pool
Modeling seasoned pools
Fastest refinancing buckets disappear first
Automatically accounts for ‘burnout’
6. 6
Risk Factors in the CLEAN™ MBS Model
Interest rate
USD swap curve
Swaption volatilities
Prepayment
Laggard distribution
Turnover speed
Default/buyout speed and recovery percentage
Refinancing cost
Homeowner credit spread
OAS (option-adjusted spread to swap curve)
7. 7
Calibration of CLEAN™:
Straightforward and Intuitive
Rarely adjusted
Laggard distribution
Default recovery percentage
Refinancing cost
Occasionally adjusted
Turnover speed
Default/buyout speed
Adjusted monthly
Homeowner credit spread
8. 8
CLEAN Uses Two Separate Credit Spreads
Homeowner credit spread
Specifies the homeowner’s borrowing curve
Determines when homeowner would refinance
Refinance if refinancing option is worth more dead than alive
OAS
Spread demanded by MBS investor
Used for discounting MBS cash flows
Reflects
Credit spread of guarantor
Plus market discount for unhedged uncertainty in price
9. 9
Homeowner Credit Spread:
Key Driver of Refinancing Speed
For current coupon pool
Conceptually the spread between a “par mortgage curve” and swap curve
Current primary mortgage rate minus volatility minus 10y swap rate
Implies refi option premium of approximately 40 bps
Comparable to single-A/BBB 10-year corporate credit
For higher coupon pool
Wider than current coupon spread due to credit impairment
Start with current coupon homeowner credit spread
Add difference between WAC minus primary mortgage rate
Fine-tune by matching duration and convexity to dealer consensus
16. 16
Why CLEAN™ Is Ideal for
Trading, Hedging, and Risk Management
Realistic transparent behavior
Based on well established financial and economic principles
Instead of ad hoc mathematical formulas and parameters
Consistent with valuation models for callable bonds and
cancelable swaps
Calibration is straightforward and intuitive
Concretely defined model parameters
Easier to simulate
Model behavior always realistic
Based on fundamental financial and economic principles
Not on statistical fitting of historical behavior
And ridiculously fast
Critical for simulation
17. 17
Challenges Faced by Other Prepayment
Models But Not by CLEAN
Burnout
As pool ages, refinancing speed decreases
Model parameters are mathematical and not economic
Need to be estimated using fit to historical data
Rather than direct observation
Ongoing need to update not just parameters but the model itself
Estimating a future primary mortgage rate
Many models assume a fixed formula using spread to an interpolated
Treasury yield
But mortgage rate contains premium for refinancing option, which depends
on volatility
Computation speed
Use of Monte Carlo forces tradeoff between speed and precision
18. 18
Heard It Through The Grapevine
"The actual sensitivity of MSRs to implied volatility is complex and
somewhat controversial”
Ben Golub in “Mark-to-Market Methodology, Mortgage Servicing Rights,
and Hedging Effectiveness”
“The model we use doesn’t even get the sign right for volatility
hedging of MSRs”
A/L management advisor
“The price response to skew adjustment seems exaggerated”
Hedge fund manager
Why do intuition and model disagree
when it comes to volatility?
19. 19
Other Prepayment Models
Are Overly Sensitive to Volatility
-2
-1
0
1
2
20 30 40
Changeinprice(%ofpar)
Volatility (%)
30-yr 4.5% MBS
Price: 101 2/32
Base Volatility 30%
CLEAN
Bloomberg
20. 20
Why Other Prepayment Models
Struggle with Interest Rate Volatility
Others model future mortgage rate as a formula
Say a function of 2-yr and 10-yr Treasuries plus a fixed spread
Where fixed spread is refinancing option premium
Does not widen when volatility increases
So prepayments overreact to change in volatility
For example, if volatility increase
Option premium spread underestimated
Future mortgage rates underestimated
Refinancing speed overestimated
Higher-coupon MBS prices decline too much
21. 21
References
Andrew Kalotay & Qi Fu (June 2009), A Financial Analysis of
Consumer Mortgage Decisions, Mortgage Bankers Association.
Andrew Kalotay & Qi Fu (May 2008), Mortgage servicing rights and
interest rate volatility, Mortgage Risk.
Andrew Kalotay, Deane Yang, & Frank Fabozzi (Vol. 1, 2008), Optimum
refinancing: bringing professional discipline to household
finance, Applied Financial Economics Letters.
Andrew Kalotay, Deane Yang, & Frank Fabozzi (Vol. 3, 2007), Refunding
efficiency: a generalized approach, Applied Financial Economics
Letters.
Andrew Kalotay, Deane Yang, & Frank Fabozzi (December 2004), An
option-theoretic prepayment model for mortgages and
mortgage-backed securities, International Journal of Theoretical
and Applied Finance.
Available from http://www.kalotay.com/research