Best-Practices in Mortgage Default Risk Measurement and Economic Capital
Each of the major processes used by industry participants to measure
so-called “credit risk” for first mortgage products. The study has three
Section I provides a discussion of the general concept of Economic
Capital (“EC”), how EC is measured and used by best-practice banks,
and how EC concepts used by industry practitioners differ from
regulatory definitions of capital.
Section II discusses the various types of theoretical “credit risk
models” that are used by practitioners to measure EC for mortgages.
Section III conducts several empirical experiments in which large
historical databases are used to estimate the credit risk models
described in Section II. The empirical work is aimed at helping
the practitioner and the regulator to evaluate the results of
David Kaskowitz, LoanPerformance
Kyle Lundstedt, LoanPerformance
Alexander Kipkalov, Washington Mutual Inc.
John Mingo, Mingo & Co.
Time Dependent Data Exploration And Preprocessing:
Doing It All by SAS.
Exploration and preprocessing methodology of transactional data,
transform the data into a multivariate time series and select an
adequate model for analysis.
Unlike time series data, where observations are equally spaced by
a specific time interval, in transactional data, observations are not
spaced with respect to any particular time period. Our approach is
illustrated using observations of length of stay (LOS) of a patient
at a hospital Emergency Department (ED). The challenges of analyzing
these data include autocorrelations of the observations, non-linearity,
and the fact that observations were not recoded at regular time
First, using the SAS procedure, PROC HPF, we transformed the
transactional data set into multivariate time series data. Next, a
series of specialized plots such as histograms, kernel density plots,
boxplots, time series plots, and correlograms were produced using
the SAS procedure PROC GPLOT to capture the essentials of the
data to discover relationships in the variables, and to select an
optimal model of analysis. As a result of this step by step
preprocessing methodology, adequate models of analysis of
LOS were identified and the dimension of the data set was
reduced from 3345 observations to only 256 observations.
Joseph Twagilimana, University of Louisville, Louisville, KY [PDF]
Cointegration and Error Correction Mechanism Approaches:
Estimating a Capital Asset Pricing Model (CAPM) for House
Price Index Returns with SAS
Many researchers erroneously use the framework of linear
regression models to analyze time series data when predicting
changes over time or when extrapolating from present conditions
to future conditions. Caution is needed when interpreting the results
of these regression models. Granger and Newbold (1974) discovered
the existence of ‘spurious regressions’ that can occur when the
variables in a regression are nonstationary. While these regressions
appear to look good in terms of having a high R2 and significant
t-statistics, the results are meaningless. Both analysis and modeling
of time series data require knowledge about the mathematical model
of the process.
This paper introduces a methodology that utilizes the power
of the SAS DATA STEP, and PROC X12
and REG procedures. The DATA STEP uses the SAS LAG and
DIF functions to manipulate the data and create an additional
set of variables including Home Price Index Returns (HPI_R1), first
differenced, and lagged first differenced. PROC X12 seasonally
adjusts the time series. Resulting variables are manipulated
further (1) to create additional variables that are tested for
stationarity, (2) to develop a cointegration model, and (3) to
develop an error correction mechanism modeled to determine
the short-run deviations from long-run equilibrium. The relevancy
of each variable created in the data step to time series analysis is
discussed. Of particular interest is the coefficient of the error
correction term that can be modeled in an error correction mechanism
to determine the speed at which the series returns to equilibrium. The
main finding is that Metropolitan Statistical Areas (MSAs) with very
slow shortrun acceleration paths to the equilibrium have higher
returns and risk associated with house price returns than
MSAs with very rapid speed-of-adjustment coefficients.
-- Ismail Mohamed and Theresa R. DiVenti, PDF.
Underlying model and several of the features of Proc UCM, new in the
Econometrics and Time Series (ETS) module of SAS .
Time series data is generated by marketers as they monitor “sales by month”
and by medical researchers who collect vital sign information over time. This
technique is well suited to modeling the effect of interventions (drug administration
or a change in a marketing plan). This new procedure combines the flexibility of
Proc ARIMA with the ease of use and interpretability of Smoothing models.
UCM does not have the capability to easily model transfer functions, a useful
ARIMA function that is planned for Proc UCM.
An Animated Guide©: Proc UCM (Unobserved Components Model)
Russ Lavery, Contractor for ASG, Inc., PDF
Econometric course notes by John Aldrich.
Seemingly unrelated regressions and simulateous equations: PDF
The STATESPACE procedure analyzes and forecasts multivariate
time series using the state space model. The STATESPACE procedure
is appropriate for jointly forecasting several related time series that
have dynamic interactions. By taking into account the autocorrelations
among the whole set of variables, the STATESPACE procedure may
give better forecasts than methods that model each series separately.
Check the service contract: An internet without uploading or downloading.
Verizon's contract, for example, says its service cannot be used for uploading,
downloading or streaming of movies, music or games; it also prohibits peer-to-
peer file sharing and Internet phone calling, known also as VoIP.)
Random Roger invests his portfolio,
and explains how, in the WSJ.
Spreadsheets put on the web by NumSum.
Like Flickr for accountants.
[via Altos Research]
Governance could be worse. Draft Gore 2008.
Also: Ozone Man's Climate Crisis and SNL address
-- YouTube (Flash), C & L (QuickTime).
As for immigration, solving that came at a heavy cost, and I
personally regret the loss of California.
Previously: Al Gore's heart and soul, protecting our children
from the dangers of smoking.
Footnoted reads SEC filings, Edgar's fine print.
Mortgage Payment Reset: The Rumor and the Reality.
Our nation is a $10 trillion-per-year economy currently possessing
$19 trillion in household asset value and $11 trillion in homeowner’s
equity. Losses of $110 billion – spread over several years – would
come to only about one percent of the total national homeowners’
adding about $300 billion per year to our national income. Losses
of $30 billion in a year would consume only one-tenth of this
increase, the equivalent of slowing the growth rate from 3% to 2.7%.
According to the Mortgage Bankers Association of America, mortgage
lending totals from $2 trillion to $3 trillion per year. The yearly reset
losses anticipated by this paper would constitute only about one
percent of the total annual lending amount.
Dilbert's war for money.
Mortgage Valuation and Optimal Refinancing, Pliska (2006)
Landholders, Residential Land Conversion, and
Market Signals, Margulis (2006)
Mortgage Payment Reset: The Rumor and the Reality,
Christopher Cagan (2006)
Option-Theoretic Prepayment Model for Mortgages,
Fabozzi, Kalotay and Yang. (2004)
The Complexities of Mortgage Options,
Best-Practices in Mortgage Default Risk Measurement and
Economic Capital, Kaskowitz, Lundstedt (2002)
Residential Mortgage Termination and Severity,
De Franco. (1994)
Hockey playoff season.