Housing Mortgage Loans Research Articles

Housing Market in Russia in 2016

According to the data released by the Bank of Russia, as of July 1, 2016, the number of credit institutions issuing residential loans (RL) and housing mortgage loans (HNL) fell to 680 and constituted 85.3% of their number as of July 1, 2015 (Table 16). Herewith, the number of credit institutions issuing RL came to 522 and those extending HML – 499, and those attracting refinancing on the HML secondary market – 34. Moreover, the number of credit institutions extending housing mortgage loans secured by the right of foreclosure on agreements of participation in shared construction came to 212 as of July 1, 2016.

以房抵债业务的增值税筹划政策依据及要点

针对企业商事交往中经常发生以房抵债业务的客观现实，结合国家“营改增”有关不动产销售和固定资产处置等相关政策规定，阐述了不动产抵债业务应纳相关税种的法律依据，并分析指出增值税纳税筹划的重要性；继而分析介绍了开展增值税筹划的政策依据，重点探讨了房地产抵债业务增值税筹划的关键环节、内容及技术方法，期能为企业财会人员精细核算与巧妙筹划以房抵债的增值税业务。 In view of the objective reality that housing mortgage loans often occur in business transactions, this article combines the state “Business Tax Reform VAT” related to real estate sales and disposal of fixed assets and other relevant policies and regulations, elaborates the legal basis that the real estate debt service should pay the related taxes, and points out the importance of VAT tax planning and analysis. Then it analyzes and introduces the policy basis for carrying out VAT planning. This paper focuses on the key links, contents and technical methods of the value-added tax planning of real estate debt paying business, in order to make fine accounting for enterprise accounting personnel and skillfully plan value-added tax business with house debts.

Pricing for a basket of LCDS under fuzzy environments

This paper looks at both the prepayment risks of housing mortgage loan credit default swaps (LCDS) as well as the fuzziness and hesitation of investors as regards prepayments by borrowers. It further discusses the first default pricing of a basket of LCDS in a fuzzy environment by using stochastic analysis and triangular intuition-based fuzzy set theory. Through the ‘fuzzification’ of the sensitivity coefficient in the prepayment intensity, this paper describes the dynamic features of mortgage housing values using the One-factor copula function and concludes with a formula for ‘fuzzy’ pricing the first default of a basket of LCDS. Using analog simulation to analyze the sensitivity of hesitation, we derive a model that considers what the LCDS fair premium is in a fuzzy environment, including a pure random environment. In addition, the model also shows that a suitable pricing range will give investors more flexible choices and make the predictions of the model closer to real market values.

Mortgage in the Russian Federation in December 2015

In 2015, 691,943 housing mortgage loans (HML) were originated totaling to Rb 1.15 trillion, which demonstrate a reduction against 2014 in quantitative terms by 31.68% and in value terms – by 34.96%. The HML portfolio quality deteriorate. In 2015 against 2014, outstanding debt denominated in rubles as a share of residual debt went up by 0.19 p.p. to 1.04% and in foreign currency – by 7.81 p.p. to 20.37%. In 2015, weighted average ruble rate on HML for the year against 2014 moved up by 0.88 p.p. to 13.33%, and weighted average rate in foreign currency moved up by 0.57 p.p. to 9.82%.

The Real Estate Market in the Russian Federation in H1 2016

126,100 apartments covering a total of 10.4 million square meters floor space were constructed in Q1 2013, accounting for 106.5% against Q1 2012. Average actual cost of construction of 1 square meter in the housing total floor space increased 7.89% in Q1 2013 vs. Q1 2012 and amounted to Rb 34,920. The ratio of the price of 1 square meter of residential floor space in the total floor space in the primary housing market to the cost of construction of 1 square meter of the residential floor space increased by 0.85 p.p. over the same period and stood at 139.75%. State registration of land title for individuals (1,243m title deeds) increased 6.24% in volumes in Q1 2013 vs. Q1 2012. 211480 housing mortgage loans (HMLs), Rb 341,0bn, were issued from January to April 2013, showing an increase of 27.52% vs. April 2012. In April 2013, monthly growth in the weighted average interest rate on ruble HMLs gave way to a decline for the first time since November 2011. The interest rate decreased 0.3 p.p., falling to 12.6%.

Housing Mortgage in the Russian Federation in H1 2013

In Q2 2013, the monthly weighted average interest rate on ruble-denominated housing mortgage loans was no longer on the rise, after a more than year-long period of growth: the interest rate for June was 12.6% against its record high of 12.9% in March 2013. The volume of housing mortgage lending in Q2 2013 amounted to Rb 315.5bn, which is by 26.63% higher than the volume of similar loans granted over Q2 2012. The share of outstanding ruble-denominated debt against housing mortgage credits relative to the sum of residual debt continues to be on the decline (1.24% as of 1 July 2013 against 1.41% as of 1 April 2013); the same is true with regard to the corresponding share of outstanding debt denominated in foreign currencies (12.45% as of 1 July 2013 against 11.78% as of 1 April 2013). The share of debt against defaulted housing mortgage credits (HMC) (with payments overdue for periods over 180 days) in the sum of total debt denominated in all currencies shrank to 1.15%.

Housing Mortgage in the Russian Federation in Q2 2015

In Q2 2015, housing mortgage loans (HML) totaling to Rb 242.53bn were originated which was 44.23% lower than the same index for Q2 2014. The volume of residual debt on HML as of 1 July 2015 constituted Rb 3.608 trillion. The share the ruble stale debt on HML in the residual debt came to 0.98% as of 1 July 2015 against 0.92% as of 1 April 2015. As of 1 July 2015, the share of debt on default HML with past-due payments of 180 days and more went up to 2.08% of the total debt amount. The weighted average interest rate on ruble-denominated HML issued in June 2015 constituted 13.29% and the weighted average interest rate for half year – 14.4%. In the course of Q2 2015, in the framework of the state program of subsidizing interest rates of the residential mortgage loans extended for purchasing accommodation in the new housing construction sector (interest rate not more than 12%) a total number of 52 thousand loans were originated totaling to Rb 90bn which constitute 38% of the total HML amount originated over this period.

Application of Discriminant Analysis of Home Mortgage Loan Prepayment Risk

Whether the borrower is engaging in default risk behavior is bound to be driven by some incentives as judged by internal and external observable variables; or it can be observed from some of the characteristics of the borrower. Which type of borrowers is less reliable in credit and may prepayment is an issue of great concern to asset risk management of financial institutions holding the housing mortgage loans. Therefore, the study of the tracking and forecasting of changes in relevant factors during the loan period of each borrower is very valuable. For example, the prediction and evaluation of financial institution prepayment risk probability by changes in borrowers’ income can help prevent the borrowers’ prepayment risk behavior in advance.

Impact of Regulation on Collateralization Policies of Banks - Evidence from India

Housing satisfies investment and consumption needs for households - about 11% of Indian households purchase homes through home mortgages loan from Banks and Housing Finance Companies (HFCs). Lending norms by banks and HFCs for housing mortgage loans are largely determined by two factors: Loan-to-value ratio (LTV) and Interest-to-Income (Debt-to-income, or DTI) ratio. From a macro-economic perspective regulations set by the Central Bank, the money supply available in the market and the competitiveness of home loan sector influence the collateralization policies of Banks and HFCs.Using data for one of the largest mortgage providers in India for multiple cities, patterns in LTV and Interest-to-Income ratio are identified over a time period of ten years from 1995 to 2005. Banks have opposing interests in settling LTV and DTI targets, where they balance the competitiveness of expansionary LTV vis-a-vis the risk of overvaluation of collateral. The study expects to analyse whether collateralization requirements of banks and HFC’s change with reference to property prices, and if so, to quantify the direction and magnitude of such change.

Потенціал і обмеження посткризового відновлення іпотечного ринку України

The article analyzes the structural characteristics of the mortgage lending market caused by the impact of financial and economic crisis. The evaluation of government programs to support housing mortgage loans is conducted,conclusions and recommendations are made on future actions for the resumption of bank mortgage lending through improving institutional structure, legal support and government programs.

Does large volatility help?—stochastic population forecasting technology in explaining real estate price process

This paper investigates the association between real estate demand and the volatility of population changes. In a financial liberalized housing market, the housing mortgage loan implies insurance function to homeowners through the default option. Larger expected volatilities in the population imply a higher value of the default option. When analyzing the impact of the long-term population development on housing prices, the traditional deterministic population forecasting employed by previous research provides limited credibility. By means of the newly developed stochastic population forecasting methodology and counterfactual numerical simulations, we found a huge volatility associated with long-term population forecasting. A positive correlation between the expected volatility of population changes and real estate demand is ascertained.

Mathematical Model of Housing Loans

Currently, that individual use housing mortgage loans to buy houses has become a hot topic, and residents are very concerned about the debt repayment ways of individual housing mortgage loans. In this paper, using the time value of money principle, we establish equal principal and interest repayment model. Furthermore we test its validation and illustrate its specific application with an example in the economic life.

On the Securitization of Housing Mortgage Loans

It is important for the Chinese commercial banks to systematically identify and measure their credit risk concentrations and reduce the detected concentrations through financial innovation. This paper probes the significance and obstacles of housing mortgage loans the securitization and put forward some measures to facilitate the introduction of securitization. Keywords: Housing mortgage loans, Securitization, Special purpose vehicle (SPV) Resume: Il est important pour les banques commerciales chinoises d’identifier systematiquement , de mesurer leur risque de concentration de credit , de reduire la concentration detectee par l’innovation financiere . Ce texte cherche a decouvrir la signification et les obstacles d’emprunt-logement , et propose quelques mesures pour faciliter l’introduction de la securisation . Mots-cles: emprunt-logement, securisation, vehicule a l’usage special