Collateral Misreporting in the Residential Mortgage-Backed Security Market

2020 ◽  
Author(s):  
Samuel Kruger ◽  
Gonzalo Maturana
Keyword(s):  
Interest Rates ◽  
Selection Bias ◽  
Security Market ◽  
Residential Mortgage ◽  
Valuation Model ◽  
Loan Officers ◽  
Automated Valuation

Securitized mortgage appraisals routinely target pre-specified valuations, 45% of purchase loan appraisals exactly equal purchase prices, and appraisals virtually never fall below purchase prices. As a result, appraisals exceed automated valuation model (AVM) valuations 60% of the time and are 5% higher than AVM valuations on average. High appraisals and indicators of appraisal targeting predict loan delinquency and residential mortgage-backed security (RMBS) losses and are priced at the loan level through higher interest rates, but have essentially no impact on RMBS pricing. Selection bias simulations and unfunded loan application appraisals indicate that high appraisals are intentional. The extent to which appraisals exceed AVM valuations varies across loan officers, mortgage brokers, and appraisers, and high appraisals are associated with more repeat business for appraisers, potentially incentivizing appraisers to inflate their appraisals. This paper was accepted by Tomasz Piskorski, finance.

scholarly journals International Real Estate Review

2021 ◽  
Vol 24 (2) ◽  
pp. 139-183
Author(s):  
Kristoffer B. Birkeland ◽  
◽  
Allan D. D’Silva ◽  
Roland Füss ◽  
Are Oust ◽  
...  
Keyword(s):  
Real Estate ◽  
Real Estate Market ◽  
Percentage Error ◽  
Residential Real Estate ◽  
Valuation Model ◽  
Stacked Generalization ◽  
Novel Approach ◽  
Out Of Sample ◽  
Selection For ◽  
Automated Valuation

We develop an automated valuation model (AVM) for the residential real estate market by leveraging stacked generalization and a comparable market analysis. Specifically, we combine four novel ensemble learning methods with a repeat sales method and tailor the data selection for each value estimate. We calibrate and evaluate the model for the residential real estate market in Oslo by producing out-of-sample estimates for the value of 1,979 dwellings sold in the first quarter of 2018. Our novel approach of using stacked generalization achieves a median absolute percentage error of 5.4%, and more than 96% of the dwellings are estimated within 20% of their actual sales price. A comparison of the valuation accuracy of our AVM to that of the local estate agents in Oslo generally demonstrates its viability as a valuation tool. However, in stable market phases, the machine falls short of human capability.

scholarly journals An Investigation into the Fundamental Drivers of Pricing of Residential Mortgage Products – A Risk Pricing Viewpoint

2010 ◽  
Vol 10 (4) ◽  
pp. 60-72
Author(s):  
Harry M Karamujic
Keyword(s):  
Financial Crisis ◽  
Interest Rates ◽  
Financial Institutions ◽  
Global Financial Crisis ◽  
Exact Science ◽  
Residential Mortgage ◽  
Risk Pricing ◽  
Price Risks ◽  
The Global Financial Crisis ◽  
Underlying Theme

Residential mortgage products (also known as home loans) pricing has been long understood to be something of a ‘dark art’, requiring judgment and experience, rather than being an exact science. In the last decade, a lot has changed in this field and more and more lenders, primarily the larger lenders, are increasingly looking to make their pricing as exact as possible. Even so, inadequate pricing of residential mortgage products (in particular its substandard risk pricing) has been seen as one of major causes of the global financial crisis (GFC) and subsequent spectacular banking collapses. The underlying theme of the paper is to exhibit how contemporary lenders, in practice, price their residential mortgage products. While discussing elements of the pricing calculation particular attention was given to the exposition of how contemporary lenders price risks involved in providing home loans. Because of the importance of Basel capital accords to how financial institutions assess and quantify their risks, the paper provides an overview of Basel capital accords. The author envisages that the paper will (i) help enhance comprehension of the underlying elements of the pricing calculation and the ways in which these elements relate to each other, (ii) scrutinize how contemporary lenders identify and quantify risks and (iii) improve consciousness of future changes in interest rates

scholarly journals Contextualized Property Market Models vs. Generalized Mass Appraisals: An Innovative Approach

2019 ◽  
Vol 11 (18) ◽  
pp. 4896 ◽  
Author(s):  
Morano ◽  
Rosato ◽  
Tajani ◽  
Manganelli ◽  
Liddo
Keyword(s):  
Urban Planning ◽  
Functional Form ◽  
Property Market ◽  
Market Models ◽  
Italian Study ◽  
The Public ◽  
Valuation Model ◽  
Residential Units ◽  
Automated Valuation

The present research takes into account the current and widespread need for rational valuation methodologies, able to correctly interpret the available market data. An innovative automated valuation model has been simultaneously implemented to three Italian study samples, each one constituted by two-hundred residential units sold in the years 2016–2017. The ability to generate a “unique” functional form for the three different territorial contexts considered, in which the relationships between the influencing factors and the selling prices are specified by different multiplicative coefficients that appropriately represent the market phenomena of each case study analyzed, is the main contribution of the proposed methodology. The method can provide support for private operators in the assessment of the territorial investment conveniences and for the public entities in the decisional phases regarding future tax and urban planning policies.

Credit Solicitations as Market Experiments in the U.S. Credit Card Industry

2017 ◽  
pp. 1-5
Author(s):  
Nabil Al-Najjar ◽  
David Besanko ◽  
Roberto Uchoa
Keyword(s):  
Interest Rates ◽  
Selection Bias ◽  
Credit Card ◽  
Risk Profile ◽  
Average Risk ◽  
Credit Reporting ◽  
Credit Score ◽  
Typical Experiment ◽  
Market Experiments ◽  
The U.S

Describes market experiments conducted by a major credit card issuer. In a typical experiment, the issuer sends out hundreds of thousands of solicitations based on information received from credit reporting agencies (e.g., credit score, past delinquencies, etc.). Selection bias is striking: the average risk profile of those responding to higher interest rates is significantly worse than that of respondents to lower rates. Tracking respondents for 27 months after the experiment, respondents to higher rates displayed significantly higher delinquency and bankruptcy rates. Based on a research paper by Larry Ausubel.

scholarly journals Automated valuation model for livestock appraisal in loaning practice

2014 ◽  
Vol 8 (1) ◽  
pp. 37-42
Author(s):  
Ferenc Buzás ◽  
Sándor Kiss
Keyword(s):  
Point Of View ◽  
Valuation Model ◽  
Stock Value ◽  
Appraisal Method ◽  
Set Up ◽  
Automated Valuation ◽  
Professional Guidance

Actualization of loan security (mortgage) value is of major importance in Hungarian loaning practice. Due to the recession in economics, the value of agricultural portfolio of banks has decreased a great deal, though not to such a great extent as other branches of the economy. Depreciation of estate stock is compensated with additional collateral security. Besides other stock, often temporarily and out of necessity, livestock is presented as additional collateral security. From the loaners’ point of view, however, the registered inventory value does not guarantee security. The authors have set up an appraisal method giving professional guidance through automated valuation as to how dairy stock can be used as mortgage for loan security. Hereby we are to present the details of both the theory and the methodology of a model that is appropriate for the valuation of dairy livestock on an MS Excel basis. Thus, the process is fast and has more prospects for all parties in the loaning or leasing business. The method involves the features of livestock technology, the expected realized profit, and breed stock value. By the implementation of this method, the loaners can calculate the value of loan recovery (loan to value) with acceptable security.

Automated valuation model: an application to the public housing resale market in Singapore

2005 ◽  
Vol 23 (5) ◽  
pp. 357-373 ◽  
Author(s):  
Muhammad Faishal Ibrahim ◽  
Fook Jam Cheng ◽  
Kheng How Eng
Keyword(s):  
Public Housing ◽  
The Public ◽  
Valuation Model ◽  
Automated Valuation ◽  
Resale Market

scholarly journals Valuing Time-Dependent CEV Barrier Options

2009 ◽  
Vol 2009 ◽  
pp. 1-17 ◽  
Author(s):  
C. F. Lo ◽  
H. M. Tang ◽  
K. C. Ku ◽  
C. H. Hui
Keyword(s):  
Interest Rates ◽  
Lower Bounds ◽  
Time Dependent ◽  
Upper And Lower Bounds ◽  
Model Parameters ◽  
Option Prices ◽  
Barrier Option ◽  
Cev Model ◽  
Valuation Model ◽  
Similarity Transformations

We have derived the analytical kernels of the pricing formulae of the CEV knockout options with time-dependent parameters for a parametric class of moving barriers. By a series of similarity transformations and changing variables, we are able to reduce the pricing equation to one which is reducible to the Bessel equation with constant parameters. These results enable us to develop a simple and efficient method for computing accurate estimates of the CEV single-barrier option prices as well as their upper and lower bounds when the model parameters are time-dependent. By means of the multistage approximation scheme, the upper and lower bounds for the exact barrier option prices can be efficiently improved in a systematic manner. It is also natural that this new approach can be easily applied to capture the valuation of other standard CEV options with specified moving knockout barriers. In view of the CEV model being empirically considered to be a better candidate in equity option pricing than the traditional Black-Scholes model, more comparative pricing and precise risk management in equity options can be achieved by incorporating term structures of interest rates, volatility, and dividend into the CEV option valuation model.

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