Financial Modelling for Mortgages

2017 ◽  
Author(s):  
Radu S. Tunaru
Keyword(s):  
Risk Management ◽  
Real Estate ◽  
The Other ◽  
Single Model ◽  
Mortgage Loans ◽  
Real Estate Markets ◽  
The Real Estate ◽  
Financial Modelling ◽  
Asset Class ◽  
Behavioural Factors

The purpose of this chapter is to familiarize the reader with the concept of mortgages and to describe the behavioural factors behind decisions to prepay and default on mortgages that ultimately influence the evolution of real-estate markets. The other scope of this chapter is to highlight the complexity of the financial modelling related to the real-estate area, and to mortgages in general. Mortgage loans are contracts carrying real-estate risk. They represent a large part of the assets in the banking systemsworldwide and banks find it difficult to hedge this asset class against real-estate risk. Prepayments and default models are essential to any risk management enterprise looking to contain this type of risk, and they are reviewed in this chapter. There are many models proposed in the academic and practitioner literature, but there is not a single model that is widely accepted.

scholarly journals The Role of Macroprudential Policy in Bank Housing Loans Portfolio Quality Assurance

2021 ◽  
Vol 59 (2) ◽  
pp. 281-296
Author(s):  
Mirela Mitrašević
Keyword(s):  
Real Estate ◽  
Real Estate Market ◽  
Residential Real Estate ◽  
Macroprudential Policy ◽  
Mortgage Loans ◽  
Real Estate Markets ◽  
The Real Estate ◽  
Business Conditions ◽  
Policy Measures ◽  
The Impact

Abstract The subject of this paper is the contemporary trend in residential real estate markets in European countries and their impact on the quality of banks’ housing loan portfolios. Due to the fact that these are the markets that still have not fully recovered from the previous financial crisis, and at the time of writing were exposed to significant uncertainty related to the effects of specific business conditions caused by COVID-19, the research on the risks related to these markets and tools which can mitigate their consequences are of paramount importance. Given the fact that the importance of monitoring the emergence of systemic risks in the financial system and the design of macroprudential tools for Bosnia and Herzegovina is yet to come, one of the aims of the paper is to present the results of the research on the effectiveness of certain macroprudential policy measures for mitigating the impact of price fluctuations in residential real estate markets. A special attention is paid to the challenges that the real estate market and mortgage loans have been facing during the crisis caused by the COVID-19 pandemic. The paper provides a basis for future researches examining to which extent the applied macroprudential policy measures in some countries have been effective in hitherto unprecedented business conditions

Mortgage Securitization; Pricing and Risk Management

2017 ◽  
Author(s):  
Radu S. Tunaru
Keyword(s):  
Risk Management ◽  
Real Estate ◽  
Cash Flows ◽  
Mortgage Loans ◽  
Financial Instrument ◽  
Mortgage Securitization ◽  
Period Derivative

This chapter captures an overview of how real-estate risk is transferred to investors through securitization channels. A large part is dedicated to a less known financial instrument called balance guaranteed swap, which is a type of multi-period derivative contingent on cash-flows generated by a pool of mortgage loans. Emphasis is placed on the problems arising from modelling cash-flows and also revealed is the difficult task of dynamically managing the risk of the balance guaranteed swaps.

scholarly journals Information Spillover Effects of Real Estate Markets: Evidence from Ten Metropolitan Cities in China

2021 ◽  
Vol 14 (6) ◽  
pp. 244
Author(s):  
Junjie Li ◽  
Li Zheng ◽  
Chunlu Liu ◽  
Zhifeng Shen
Keyword(s):  
Real Estate ◽  
Rapid Development ◽  
House Price ◽  
Principal Component ◽  
Spillover Effects ◽  
Real Estate Markets ◽  
The Real ◽  
The Real Estate ◽  
Information Interaction ◽  
Information Spillover

With the rapid development of information communication technology and the Internet, information spillover between cities in real estate markets is becoming more frequent. The influence of information spillover in real estate markets is becoming more and more prominent. However, the current research of information spillover between cities is still relatively insufficient. In view of this research gap, this paper builds a research framework on the information conduction effect in the real estate markets of 10 Chinese cities by using Baidu search data, text mining and principal component analysis and analyzes the information interaction and dynamic influence of the real estate markets in each city by using the vector autoregressive model empirically. The results show that the information interaction among the real estate markets in each city has a network pattern and there is a significant two-way information spillover effect in most cities. When the “information distance” becomes closer, the information interaction between the markets of the cities becomes closer and it is easier for cities to influence each other. The results help to explain the information spillover mechanism behind the house price spillover and to improve the ability to predict and analyze the information spillover process in real estate markets.

Information security in the South Australian real estate industry

2014 ◽  
Vol 22 (1) ◽  
pp. 24-41 ◽  
Author(s):  
Deepa Mani ◽  
Kim-Kwang Raymond Choo ◽  
Sameera Mubarak
Keyword(s):  
Risk Management ◽  
Information Security ◽  
Real Estate ◽  
South Australia ◽  
Security Threats ◽  
The South ◽  
Content Type ◽  
The Real ◽  
The Real Estate ◽  
Real Estate Sector

Purpose – Opportunities for malicious cyber activities have expanded with the globalisation and advancements in information and communication technology. Such activities will increasingly affect the security of businesses with online presence and/or connected to the internet. Although the real estate sector is a potential attack vector for and target of malicious cyber activities, it is an understudied industry. This paper aims to contribute to a better understanding of the information security threats, awareness, and risk management standards currently employed by the real estate sector in South Australia. Design/methodology/approach – The current study comprises both quantitative and qualitative methodologies, which include 20 survey questionnaires and 20 face-to-face interviews conducted in South Australia. Findings – There is a lack of understanding about the true magnitude of malicious cyber activities and its impact on the real estate sector, as illustrated in the findings of 40 real estate organisations in South Australia. The findings and the escalating complexities of the online environment underscore the need for regular ongoing training programs for basic online security (including new cybercrime trends) and the promotion of a culture of information security (e.g. when using smart mobile devices to store and access sensitive data) among staff. Such initiatives will enable staff employed in the (South Australian) real estate sector to maintain the current knowledge of the latest cybercrime activities and the best cyber security protection measures available. Originality/value – This is the first academic study focusing on the real estate organisations in South Australia. The findings will contribute to the evidence on the information security threats faced by the sector as well as in develop sector-specific information security risk management guidelines.

scholarly journals Predicting real estate market trends and value using pre-processing and sentiment text mining analysis

2021 ◽  
pp. 35-43
Author(s):  
Nikolay Sinyak ◽  
Singh Tajinder ◽  
Jaglan Madhu Kumari ◽  
Vitaliy Kozlovskiy
Keyword(s):  
Social Media ◽  
Text Mining ◽  
Real Estate ◽  
Real Estate Market ◽  
Media Analysis ◽  
Market Information ◽  
Real Estate Markets ◽  
The Real Estate ◽  
Crowd Wisdom ◽  
Market Trends

Ubiquitous growth in the text mining field is unprecedented, where social media mining is playing a significant role. Gigantic growth of text mining is becoming a potential source of crowd wisdom extraction and analysis especially in terms of text pre-processing and sentiment analysis. The analysis of a potential influence of sentiment on real estate markets controversially discussed by scholars of finance, valuation and market efficiency supporters. Therefore, it’s a significant task of current research purview which not only provide an appropriate platform for the contributors but also for active real estate market information seekers. Text mining has gained the widespread attention of real estate market information users which is almost on explosion level. Accessibility of data on such behemoth scale mandates regular and critical analysis of this information for various perspectives’ plausibility. Rich patterns of online social text can be exploited to extract the relevant real estate information effectively. As text mining plays a significant and crucial role in discovery of these insights therefore its challenges and contribution in social media analysis must be explored extensively. In this paper, we provide a brief about the current summary of the modern state of text mining in pre-processing and sentiment for the real estate market analysis. Empha-sis is placed on the resources and learning mechanism available to real estate researchers and practitioners, as well as the major text mining tasks of interest to the community. Thus, the main aim of this chapter is to expound and intellectualize the domains of social media which are accessible on an extraordinary range in the field of text mining real estate for predicting real estate market trends and value.

scholarly journals COVID-19 Infects Real Estate Markets: Short and Mid-Run Effects on Housing Prices in Campania Region (Italy)

2020 ◽  
Vol 9 (7) ◽  
pp. 114 ◽  
Author(s):  
Vincenzo Del Giudice ◽  
Pierfrancesco De Paola ◽  
Francesco Paolo Del Giudice
Keyword(s):  
Real Estate ◽  
Housing Prices ◽  
Real Estate Market ◽  
Campania Region ◽  
Real Estate Markets ◽  
The Real ◽  
The Real Estate ◽  
Short Run ◽  
Predator Model ◽  
Real Estate Prices

The COVID-19 (also called “SARS-CoV-2”) pandemic is causing a dramatic reduction in consumption, with a further drop in prices and a decrease in workers’ per capita income. To this will be added an increase in unemployment, which will further depress consumption. The real estate market, as for other productive and commercial sectors, in the short and mid-run, will not tend to move independently from the context of the aforementioned economic variables. The effect of pandemics or health emergencies on housing markets is an unexplored topic in international literature. For this reason, firstly, the few specific studies found are reported and, by analogy, studies on the effects of terrorism attacks and natural disasters on real estate prices are examined too. Subsequently, beginning from the real estate dynamics and economic indicators of the Campania region before the COVID-19 emergency, the current COVID-19 scenario is defined (focusing on unemployment, personal and household income, real estate judicial execution, real estate dynamics). Finally, a real estate pricing model is developed, evaluating the short and mid-run COVID-19 effects on housing prices. To predict possible changes in the mid-run of real estate judicial execution and real estate dynamics, the economic model of Lotka–Volterra (also known as the “prey–predator” model) was applied. Results of the model indicate a housing prices drop of 4.16% in the short-run and 6.49% in the mid-run (late 2020–early 2021).

scholarly journals Crowdfunding REITs: a new asset class for the real estate industry?

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lucia Gibilaro ◽  
Gianluca Mattarocci
Keyword(s):  
Real Estate ◽  
The United States ◽  
Individual Investors ◽  
Diversification Strategy ◽  
Content Type ◽  
The Real ◽  
The Real Estate ◽  
Real Estate Sector ◽  
Real Estate Investments ◽  
Asset Class

PurposeThe paper aims to study the performance of crowdfunding REITs with respect to traditional REITs in order to evaluate the differences in the risk–return profile and their usefulness for a diversification strategy within the indirect real estate investments.Design/methodology/approachThe paper considers the crowdfunding REITs introduced after the JOBS act in the United States and evaluates their performance and risk during the time period 2016–2018. Performance achieved by crowdfunding REITs is compared with other types of REITs in order to evaluate their usefulness for constructing an optimal portfolio strategy based on a standard mean variance approach.FindingsResults show that the performance of crowdfunding REITs is more stable over time with respect to other REITs and the lack of correlation with traditional REITs may be exploited for constructing a more efficient diversified portfolio of indirect real estate investments.Practical implicationsCrowdfunding REITs have different performance with respect to standard REITs and, especially individual investors, may benefit from including this new investment opportunity in their portfolio.Originality/valueThe paper is the first study on the performance of the crowdfunding REITs that is evaluating their usefulness for a diversification strategy within the real estate sector.

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