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The main purpose of this paper is to study the effect of consumer expertise on mortgage loan prices. We argue that consumer expertise should affect price due to two reasons: (1) loan mortgage prices in non-price-regulated settings are usually the result of a bank-customer negotiation process; and (2) a mortgage loan is a complex product.

Data on mortgage loan prices were used for a sample of 1,055 households for 2005 (Bank of Spain Survey of Household Finances, EFF-2005).

The regression results indicate that consumer expertise-related metrics are highly significant as predictors of mortgage loan prices. Findings also indicate that cost-related variables and a measure of risk with low discrimination power (i.e. having a permanent employment contract, which accounts for 70 per cent of contracts in Spain) affect price. Surprisingly, more sophisticated measures of credit risk do not have such a significant impact on mortgage prices.

Empirical results refer to the credit conditions prior to the financial crisis and could shed some light on the factors that led to it.

Findings seem to indicate that, in the period under study, bank managers prioritized capturing new business in the short-term against normative prescriptions, which suggest that price should be credit-risk adjusted (financial literature) and long-term consumer potential adjusted (marketing literature). The post-2008 difficult economic situation of Spanish banks (linked to an excessive portfolio of mortgage loans granted at very low prices) shows that these strategies were wrong.

An uncommon perspective was adopted. The importance of consumer expertise-related variables on price has been underemphasized by prior research. The effect of consumer expertise is assessed by using a large and comprehensive database.

This study identifies the factors that affect the knowledge of mortgage loans' total cost.

Empirical research utilizing a survey administered through in-home interviews was conducted. This study adopts the elaboration likelihood model (ELM) theory to analyze the influence of information shortcuts and borrowers' abilities and motivations on the knowledge of mortgage loans' total cost.

The results support that the use of the price–quality cue and brand credibility have negative and positive effects, respectively, on the knowledge of mortgage loans' total cost. Households' primary income earners have a higher knowledge of mortgage loans' total cost. The results also show that the household's primary income earners who are price conscious and brand nonbelievers have more knowledge of mortgage loans' total cost.

Price knowledge studies in financial services, especially in the mortgage loan industry, are scarce. Consequently, understanding the price knowledge level for mortgage loans and its potential antecedents has been insufficient.

This paper offers empirical evidence on factors influencing credit spreads on commercial mortgage loans. It extends existing work on the pricing of commercial mortgage loans. The authors examine the relative significance of a range of factors on loan pricing that are lender, asset and loan specific. The research explores and quantifies the sources of spread differentials among commercial mortgage loans. The paper contributes to a limited literature on the subject and serves the purpose of price discovery in commercial property lending. It offers a framework to compare actual pricing with fundamental-based estimates of loan spreads.

Panel analysis is deployed to examine the cross-section and time-series determinants of commercial mortgage loan margins and credit spreads. Using an exclusive database of loan portfolios in the United Kingdom (UK), the panel analysis enables the authors to analyse and quantify the impact of a number of theory-consistent and plausible factors determining the cost of lending to commercial real estate (CRE), including type and origin of lender, loan size, loan to value (LTV) and characteristics of asset financed – type, location and grade.

Spreads on commercial mortgages and, therefore, loan pricing differ by the type of lender – bank, insurance company and debt fund. The property sector is another significant risk factor lenders price in. The LTV ratio has increased in importance since 2012. Prior to global financial crisis (GFC), lenders made little distinction in pricing different LTVs. Loans secured in secondary assets command a higher premium of 50–60bps. The analysis establishes an average premium of 35bps for loans advanced in regions compared to London. London is particularly seen a less risky region for loan advancements in the post-GFC era.

The study considers the role of lender characteristics and the changing regulation in the pricing of commercial mortgage loans and provides a framework to study spreads or pricing in this market that can include additional fundamental influences, such as terms of individual loans. The ultimate aim of such research is to assess whether mortgage loans are correctly priced and spotting risks emanating from actual loan spreads being lower than fundamental-based spreads pointing to tight pricing and over-lending.

The analysis provides evidence on lender criteria that determine the cost of loans. The study confirms that differences in regulation affect loan pricing. The regulatory impact is most visible in the increased significance of LTV. In that sense, regulation has been effective in restricting lending at high LTV levels.

The paper exploits a database of a commercial mortgage loan portfolio to make loan pricing more transparent to the different types of lender and borrowers. Lenders can use the estimates to assess whether commercial loans are fairly priced. Borrowers better understand the relative significance of risk factors affecting margins and the price they are charged. The results of this paper are of value to regulators as they can assist to understand the determinants of loan margins and gauge conditions in the lending market.

The questions of loan availability and pricing were considered from the perspectives of financial economic theory and practice as well as a survey of lenders capable of financing a one-year bridge loan to determine the market's willingness to make such a loan and what rate of interest would be charged. Utilizing the sources above, in conjunction with professional knowledge and industry contacts, 101 lenders were selected as representative of the universe of lenders who had the capacity to make directly or otherwise to arrange, a $192 million bridge loan. The survey of lenders involved interviews with 67 of the 86 selected lenders from 59 firms. The paper aims to discuss these issues.

Loan availability and pricing were considered from perspectives of financial economic theory and practice plus a survey to determine market's willingness to make a loan at what price. Utilizing professional knowledge and industry contacts, 101 lenders were selected as representative of those which had the capacity to make a $192 million bridge loan. When lenders were evaluated against criteria of size, product type, geographic territory, and willingness/capability to provide nonstandard loans, list selected for telephone interviews was narrowed, then subsequently expanded with referrals that led to identification of new potential lenders to be contacted.

Nine lenders offered conceptualized deal structures to provide the required financing. Though the price may be expensive, especially relative to what borrowers may wish to pay, financing is available. Developers’ and deal-makers’ protestations that “it's impossible,” should be discounted and rejected. Because the subject property is characterized by high-risk, it is logical conclusion that the lenders expressing a desire to provide the bridge loan would expect to earn a high return, meaning that the interest rate would approach, if not exceed, 20 percent.

Because the nature of the research required that the specific identities of the building and the parties were not revealed, some lenders might decline to consider this financing opportunity. And, real world negotiation of financing terms could result in higher rates than quoted and/or disinclination of lenders to proceed. Because of very specialized circumstances surrounding this proprietary research, conducted subject to nondisclosure agreement, publication had to be deferred until those constraints no longer applied. Though the data are more than a decade old, this consideration does not compromise the relevance, validity, or generalizability of the findings.

Markets can accommodate transactions that might be perceived as improbable. Investors which approach opportunities with creativity and open mind, can make deals that would not be possible, were strict, rigid, unbending eligible deal preference parameters to be employed. Strategists establishing policies for real estate enterprises should insist on progressive, expansive thinking in turning the scope of their potential venture involvements. Real estate education and training should address more attention to financial economic theory, strategic initiative, and creative deal making, which priority topics are too seldom prioritized, with the consequence that too many in real estate think narrowly rather than expansively.

This research substantiates a fundamental theory of financial economics and refutes conventional applied wisdom. Seldom do researchers and investors have the opportunity to “get inside” the lending decision process for a large scale commercial property, especially one characterized by daunting circumstances and considerable complexity, such as studied here. A unique real world date set – not normally accessible to property scholars – enables study of the proposition that every commodity has a price, no matter how severe or difficult the circumstances, in a manner fully congruent with the new AACSB Business School Deans policy emphasis on relevance in addition to rigor.

As commercial mortgages much less studied than residential mortgages, this paper is significant addition to undeveloped segment of literature. As the majority of mortgage finance research, estimated to be in the range of 90 percent, has been limited to single family residential financing, the study of commercial mortgage financing is relatively under-researched. Further, the studies of commercial mortgage finance tend to be illustrative case studies with stylized facts rather than explorations of empiricism-based investigations. As most researchers engaged in exploring real estate topics limit themselves to public information, research that provides access to real world private transactions is especially important.

This paper aims to answer how effective the loan-to-value (LTV) regulation has been since 2011 for conventional and Islamic (participation) banks in Turkey in terms of curbing mortgage loan growth and delinquency[1].

The authors first use unit root tests and tests of difference in loan and property price data in pre-LTV and post-LTV period. Second, the authors follow Chow test and ordinary least squares regression analyses to test for a structural break when sensitivity of mortgage loan and delinquency growth changes to property price changes considered.

The authors find that two periods are statistically different, while the significance level is lower for Islamic banks. Moreover, loan growth has become less responsive to property price increases; delinquency sensitivity to property price changes has significantly increased in the post-LTV period for conventional banks, while this is not the case for Islamic (participation) banks.

This paper not only increases empirical evidence regarding the effectiveness of LTV ratio policy but also fills the gap in the literature by providing a comparison between conventional banks and Islamic (participation) banks.

The design of a macro-prudential framework and its interaction with monetary policy has been at the forefront of the policy agenda since the global financial crisis. However, most advanced economies (AEs) have little experience using macroprudential policies. As a result, relatively little is known empirically about macroprudential instruments’ effectiveness in mitigating systemic risks in these countries, about their channels of transmission, and about how these instruments would interact with monetary policy. This paper aims to fill in the gap.

The authors develop a new approach using the euro area bank lending survey to assess the effectiveness of macro-prudential policies in containing credit growth and house price appreciation in mortgage markets. Estimation is performed under the panel regressions (OLS, GLS) and panel VAR setup. Endogeneity issues arising from measures of macro-prudential policies are addressed by introducing GMM estimation and various instruments.

The authors find instruments targeting the cost of bank capital most effective in slowing down mortgage credit growth, and that the impact is transmitted mainly through price margins, the same banking channel as monetary policy. Limits on loan-to-value ratios are also effective, especially when monetary policy is excessively loose.

With limited data on macroprudential policy measures in the AEs, this paper proposed a new methodology of using answers from bank lending survey as proxies to assess the effectiveness of specific macroprudential measures and their transmission channels.

This article proposes a new approach to bundling for both the marketing of services and relationship marketing. Reviews the literature on both bundling and relationship marketing and puts forward a new theoretical approach. Uses the case method as a means of defending the argument and justifies its use in this specific research project. Demonstrates that collaborative relationship bundling can constitute the strategic core of a company; at least, if the firm's primary goal is to maximise the opportunities of attracting valuable customers within competitive markets. Research bears out some results from previous studies, while it finds other results to be questionable. Shows that the strategic implications of bundling are only partially explained in terms of a price or product focus, which was what previous research had concentrated on. A specific price bundle can have more strategic implications than a different specific product bundle, due to the associative power of bundling and its interactive capacity. As an essential part of this approach, a company must define bundling through an in‐depth appraisal of the actual contextual experience of the customer, rather than focusing solely on reservation prices, which is where previous literature had laid its main emphasis. Calculates the lifetime value of the average customer attracted through bundling as compared to that of the average customer in the sector studied, and thus is able to demonstrate that the customer attracted through bundling is of greater value. The case method provides an in‐depth explanation but the results it provides may not necessarily be generalised into other contexts. Develops therefore a model to identify the factors that explain the success registered in the case selected for analysis. Puts forward 11 propositions suitable for comparative application in other contexts.

The main scope of the paper is to demonstrate the capabilities of PYTHIA forecasting platform, to compare time series forecasting techniques, which were used to forecast mortgage loans in UK, and to show how PYTHIA can be useful for a bank.

The paper outlines the methods used to forecast the time series data, which are included in PYTHIA. Theta, the time‐series used to forecast average mortgage loan prices, were grouped in: all buyers – average loan prices in UK; first‐time buyers – average loan prices in UK; and home‐movers – average loan prices in UK. The case of all buyers – average loan prices in UK, was presented in detail.

After the comparison of the methods, the best forecasts are produced by WINTERS and this is maybe due to the fact that there is seasonality in the data. The Theta method comes next in the row and generally produces good forecasts with small mean absolute percentage errors. In order to tell with grater certainty which method produces the most accurate forecasts we could compare the rest error statistics provided by PYTHIA too.

The paper presents the PYTHIA forecasting platform and shows how it can be used by the managers of a Bank to forecast mortgage loan values. PYTHIA can provide the forecasts required by practically all business situations demanding accurate predictions. It is designed and developed with the purpose of making the task of managerial forecasting straightforward, user‐friendly and practical. It incorporates a lot of knowledge and experience in the field of forecasting, modeling and monitoring while fully utilizing new capabilities of computers and software.

Foreclosure risk is a key concern to lenders of real estate mortgages. Using auction data, this study provides the first analysis of mortgage foreclosure in Singapore by examining how macro‐economic variables affect the probability of foreclosure. The foreclosure rate for properties is found to be increasing in the first five years of purchase and decreases as the holding period lengthens. The likelihood of foreclosure increases with unemployment rate, mortgage rate and expenditure and decreases with equity, dividend yield and lending volume at fourth and twentieth quarters lag. Further analysis shows considerable differences between residential and non‐residential properties. However, when the analysis on non‐residential properties is further separated into office, retail and industrial sub‐sectors, the results are relatively similar among the three sub‐sectors. This implies that banks and financial institutions should apply different underwriting standards for residential properties, mainly for owner‐occupation and non‐residential properties for the purpose of businesses and rental income.

Beijing and Shanghai have been the leading housing markets in urban China. In the late half of the 2000s, both metropolises experienced a pronounced process of housing price appreciation. The purpose of this paper is to examine whether there exist housing price bubbles in the two largest cities in China.

The study is based on a combination of different quantitative indicators: a comparison of housing market prices with the rational expectation price, mortgage loans, and the ratios of price to income and to rent. Moreover, the statistical tool of control chart is introduced to quantify housing bubbles.

The study shows that Beijing appears to have been on the way of forming a housing price bubble between 2005 and 2008, and that there perhaps existed a housing bubble in Shanghai from 2003 to 2004. It appears that the housing market cycle in Beijing may be divided into three stages: the cycle peak stage (1991‐1997), the cycle trough stage (1998‐2003) and the second cycle peak stage (2004‐2008).

In an attempt to explain the possible existence of housing bubbles in Beijing and Shanghai, this paper uses an integrated strategy involved with such fundamentals as interest rates, rent, income and GDP. In particular, the control chart, based on per capita GDP, is introduced to identify a housing bubble.