The Effect of Covid-19 on the Real Estate Industry in India

Sanchaniya, Rashmi Jaymin

doi:10.2478/bjreecm-2021-0010

Cited by 7 publications

(7 citation statements)

References 8 publications

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“…This results in an even greater increase in the precision of the forecast. From the vantage point of the global economy, Jaymin [39] investigated the effects of the coronavirus epidemic on India's real estate market, as well as the risks and opportunities posed by those involved in the real estate market. She also looked at the risks and opportunities posed by those involved in the real estate market.…”

Section: Background Of the Studymentioning

confidence: 99%

Application of Artificial Intelligence for Predicting Real Estate Prices: The Case of Saudi Arabia

et al. 2022

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The housing market is a crucial economic indicator to which the government must pay special attention because of its impact on the lives of freshly minted city inhabitants. As a guide for government regulation, individual property purchases, third-party evaluation, and understanding how housing prices are distributed geographically may be of great practical use. Therefore, much research has been conducted on how to arrive at a more accurate and efficient way of calculating housing prices in the current market. The goal of this study was to use the artificial neural network (ANN) technique to correctly identify real estate prices. The novelty of the proposed research is to build a prediction model based on ANN for predicting future house prices in Saudi Arabia. The dataset was collected from Aqar in four main Saudi Arabian cities: Riyadh, Jeddah, Dammam, and Al-Khobar. The results showed that the experimental and predicted values were very close. The results of the proposed system were compared with different existing prediction systems, and the developed model achieved high performance. This forecasting system can also help increase investment in the real estate sector. The ANN model could appropriately estimate the housing prices currently available on the market, according to the findings of the assessments of the model. Thus, this study provides a suitable decision support or adaptive suggestion approach for estimating the ideal sales prices of residential properties. This solution is urgently required by both investors and the general population as a whole.

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Section: Background Of the Studymentioning

confidence: 99%

Application of Artificial Intelligence for Predicting Real Estate Prices: The Case of Saudi Arabia

et al. 2022

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“…Tenants were moving from properties considered expensive to less expensive ones. In India, for example, the market value of real estate increased during the COVID-19 era due to the constrained job market as developers were unable to satisfy demand (Sanchaniya, 2021). While there appears to be a consensus about the effect of COVID-19 on the real estate sector, the nature of the effect has proved to be different from one region to another.…”

Section: Covid-19 and The Real Estate Sectormentioning

confidence: 99%

Managing Risk in a Post-COVID-19 Economy: Investors’ Perception of Lagos State Real Estate Sector

Ogiri¹,

Nosiri²,

Igoni³

2022

AJF

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Purpose: As the global community continues to grapple with the effect of the COVID-19 pandemic, there is a prospect of negative/undesirable business outcomes in Nigeria. The scourge has been a regular topic of discussion in businesses, policy-making, and the academic community in many countries around the world. The pandemic has introduced a novel systematic risk class in the real estate sector. This study investigated how real estate investors in Lagos State perceive the emerging business climate following the pandemic. Methodology: The study had a population of 2,400 while a sample size of 240 was drawn using a 10% rate. The study adopted a descriptive survey design. The statistical Package for Social Sciences (SPSS) was used to analyze data collected through questionnaires. Findings: The findings showed that COVID-19 had a significant relationship with the level of investment in real estate in Lagos State though at a weak linear associative level. Secondly, while risk managers in these sectors have adopted different strategies to minimize their risk exposures, the study revealed that funds providers are placing a higher risk premium on investible capital as a result of uncertainties in the economic outlook occasioned by the COVID-19 pandemic. However, the study shows that the demand for real estate property in Lagos State was not negatively affected to a significant extent as a result of the pandemic, but rather a shift in preferences by property owners and occupiers. The study has implications for taxation and housing policy as well as business planning decisions. Recommendation: The study recommends that government should create a favorable investment climate for real estate investors with appropriate risk mitigation measures that can reactivate the real estate sector while aiding its recovery from the COVID-19 debilitations.

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“…65,000 crores in 2024. Being the highest generator of employment, this sector was estimated to augment the country’s GDP by 13% in 2025 (Sanchaniya 2021 ). The GOI has made many reforms and policies to improve the real estate sector in India.…”

Section: Introductionmentioning

confidence: 99%

“…Commercial space rentals seem to be going downhill owing to the COVID-19 pandemic. There has been a tremendous reduction in the volume of commercial real estate investment by up to 29%, and inter-regional investment has declined by 69% (Sanchaniya 2021 ). A link between lowered cap rates, interest rates, and market fluctuations has been studied empirically (Sivitanides et al 2003 ).…”

Section: Introductionmentioning

confidence: 99%

An empirical investigation of investor sentiment and volatility of realty sector market in India: an application of the DCC–GARCH model

Pillada

Rangasamy

2023

SN Bus Econ

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Understanding how an irrational investors’ sentiment affects the realty market returns, especially during the pandemic, is imperative to take any financial decisions. The effect of investor sentiment on the movement of the realty market leading to market volatility is dynamically represented in a numerical form. The study incorporates daily market data and their implicit indices to construct a sector-specific investor sentiment index by using the principal component analysis method. To analyse the relationship between the variables, a quantitative approach is used by incorporating an econometric model—dynamic conditional correlation–generalized autoregressive conditional heteroskedasticity (DCC–GARCH). The directionality of the relationship between the variables is assessed by the Diebold–Yilmaz method. This study is done to investigate the return deviation in the realty sector due to sentiment impact during the pandemic in the Indian context. The findings indicate the existence of an asymmetric impact of the sentiment, leading to extreme volatility and returns in the realty sector. The results confirmed the presence of bi-directional relationship between asset returns and investor sentiment and quantified the relationship numerically. This study focused on the development, applicability, and validity of a sentiment index pertaining to the Indian realty sector. This study highlights the impact of a qualitative non-fundamental factor like sentiment as a measurable factor in determining the volatility on market returns.

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The Effect of Covid-19 on the Real Estate Industry in India

Cited by 7 publications

References 8 publications

Application of Artificial Intelligence for Predicting Real Estate Prices: The Case of Saudi Arabia

Application of Artificial Intelligence for Predicting Real Estate Prices: The Case of Saudi Arabia

Managing Risk in a Post-COVID-19 Economy: Investors’ Perception of Lagos State Real Estate Sector

An empirical investigation of investor sentiment and volatility of realty sector market in India: an application of the DCC–GARCH model

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