Market Downturns Research Articles

Value capitalization effects of green buildings: A new insight through time trends and differences in various price levels

While many studies have explored green buildings, there remain many unsolved questions about how to expand this section of the housing market, such as how the capitalization effect of green buildings varies across time and location. This study investigates the price premiums of green buildings in Taipei City, the largest metropolis in Taiwan, to examine how they have changed over time, and assesses the magnitude of the capitalization effects under varying housing price levels. The empirical results indicate that Taipei residents are willing to pay higher prices for houses with green-label certification. The higher the certification level, the higher the price that residents are willing to pay. This study additionally identifies two characteristics of the capitalization effects in this market. The first is that the price premiums vary with the market condition. For example, during housing market downturns (e.g., 2014–2015), building green premiums may be unremarkable or non-existent. The second effect identified is that green buildings tend to exhibit an ‘aristocratic trend.’ This means that high-priced houses (i.e., houses priced above the 80% quantile) in the high-end label category attract the highest premiums, implying that the willingness to pay for green features tends to only exist among wealthy buyers. The result of this paper provides evidence to explain the heterogeneity of green build premiums. Regarding the specificity of these premiums, this paper provides recommendations for builders and managers.

The practice of Amoeba post-practice sustainable business model in real estate – taking zhongliang as example

This paper studies the practice of the amoeba model in China’s real estate industry, manage to analysis the advantages and disadvantages along the company’s development, taking the management case of Zhongliang as an example, which is a top 20th real estate development company, and considering the crisis in the post-epidemic market downturn environment. In conclusion, the article puts forward suggestions on the application of the amoeba model in the enterprise.Research aim. With the study of previous research, we leave questions. Is it possible to effectively implement the Amoeba model in China, given the circumstances of cultural differences between China and Japan? The motivation for the study in this paper is to schedule the Amoeba model in Zhongliang, China’s leading real estate company known for Amoeba’s management, to identify key factors in Amoeba’s widespread use and the impact of the system in the real estate industry during the pandemic.Results. What is Amoeba? The word amoeba originally refers to a single-celled amoeba whose body can protrude pseudopods in all directions, making the shape changeable, hence the name “amoeba”. The biggest characteristic of amoeba is that it can change with the changes of the external environment and constantly adjust itself to adapt to the living environment it faces. Kazuo Inamori introduced this idea into enterprise management, dividing the enterprise into several independent and tiny business units, each business unit realizes revenue independently, and conducts corresponding cost accounting, and then develops independent performance on this basis. Assessment. This advanced business model not only made the second electric power company he founded to become a Fortune 500 company, but also brought JAL back to life. Amoeba’s business model is not only refined management, but also enables enterprises to cultivate their own management talents. This model transforms large enterprises into small operations, which enables enterprises to maintain the advantages of large enterprises in scale and at the same time have the flexibility of small enterprises; at the same time, it improves the enthusiasm of employees to participate in operation, enhances the motivation of employees, and quickly cultivates talents for enterprises; through perfect accounting The mechanism enables enterprise leaders to grasp the actual situation of enterprise operation at all times, make correct decisions in time, and reduce the risk of enterprise operation.With the development of the economy, the requirements for management methods are gradually increasing, and the extensive management model is no longer suitable for the management requirements of modern enterprises. The amoeba management method proposed by Kazuo Inamori meets the requirements of modern enterprises and is increasingly favored by strategists. In an era of vigorous development of the real estate industry and fierce competition, after introducing the Amoeba business model in 2015, Zhongliang has reached a rapid growth from 3.5 billion to 100 billion by 2018.Conclusion. Zhongliang has been able to solve three main factors that could be the obstacles within its rapid growth path – structure, responsibility division and incentives for staffs. Firstly, with the rapid expansion of business and a large number of projects, the scope, difficulty and cost of group management and control have increased significantly. The headquarters has slow decision-making and low efficiency, and each functional department has a high degree of professional control and approval of everything; the service capacity is limited, and it cannot form a strong support for the project. Secondly, the project management team has unconsummated rights and responsibilities, lack of business awareness, and extensive project management leads to higher and higher project development costs, lower and lower project profit margins, and serious delay in the project development process. Last and the most important, with the introduction of a large number of excellent management talents, it is urgent to establish a corresponding talent development and incentive mechanism, to give all kinds of talents opportunities and platforms to fully display their talents, to fully stimulate their wisdom and potential, and to turn them into the driving force of enterprise development. Instead of a large inflow and outflow of staffs, human resources are wasted in the handover.

Tail risk dependence, co-movement and predictability between green bond and green stocks

ABSTRACT This paper examines the coherence of extreme returns between green bonds and a unique set of green stocks. We use the novel quantile cross-spectral coherence methodology of quantile spectral coherency model, cross-quantilogram correlation approach, windowed time-lagged cross-correlation, and windowed scalogram difference models as estimation techniques. The study period spans from 28 November 2008 to 23 September 2020. Our measure of green stocks comprises the constituents of the MSCI Global Environment Price Index: Alternative Energy, Green Building, Pollution Prevention or Clean Technology while our green bond market is proxied by S&P Green Bond Index. We find the dependency between Green Bonds and green stocks to be weak, and this is high during market downturn periods in the short- to medium-term dynamics. This suggests that Green Bonds do act as a hedge, diversifier, or safe-haven instrument for environment portfolio in the short-term, medium-term and long-term dynamics during bearish market conditions. We conclude that green bonds and green stocks are two distinct asset classes with a distinct risk-return profile despite their common climate-friendly nature.

The period effects of crisis and recovery on life course and residential mobility of owner-occupants

This study examines how the relationship between life course and mobility of owner-occupants is affected by periods of economic and housing market downturn and recovery. The impact of ‘period effects’ are largely unknown. Using Dutch register data, we compare the probabilities of moving in view of partnership, children and employment status for 2012–2014 and 2014–2016. We find that the downturn period is associated with lower mobility, yet the association is different for various household situations. Mobility to ownership in the crisis was particularly constrained for stable couples, employed owners and households with children. Moves to the rental sector were less period sensitive. Only owners who became unemployed were more likely to move into rental during crisis. ‘Delayed mobility’ has been found for moving in together, separation, households who had children, and job change. So, periods of crisis and recovery structure how home-owners adapt to life-course changes. Our findings imply that period effects should be accounted for in residential mobility studies.

Assessing the risks of a global housing market downturn

Economic OutlookVolume 46, Issue 3 p. 21-27 Feature article Assessing the risks of a global housing market downturn First published: 29 July 2022 https://doi.org/10.1111/1468-0319.12637Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Volume46, Issue3July 2022Pages 21-27 RelatedInformation

Analyzing The Covid-19 Pandemic of Volatility Spillover Influence the Collaboration of Foreign and Indian Stock Markets

One of the most crucial variables in investment selections is volatility. Unexpected information causes an investor to trade unusually in the market, which influences market volatility. Furthermore, various market sectors are affected differently by this type of trading behaviour. This research investigates the impact of COVID-19 on stock market volatility in India using a generalised autoregressive conditional model. The research was conducted using daily closing prices of stock indices include Nifty 50 and Nifty 500, from September 8, 2019, to July 9, 2021. In this article, the TGARCH model (1,1) was utilized to evaluate the volatility of NSE listed shares. The stock market's volatility has been calculated using the NSE's closing price. To reduce the skewness in the stock price data distribution, the natural logarithm of each price data is employed in the estimations. During the pre-COVID and COVID periods, the conditional volatility of the daily return series showed signs of volatility variations. Furthermore, the study aimed to compare stock price returns in pre-COVID19 and post-COVID19 scenarios to global indexes such as the NASDAQ, Nikkei 225, and FTSE. The stock market in India suffered volatility throughout the epidemic, according to the findings. Consequently, the study recommends NSE stock exchange bond indices to explore the volatility spillover influence between foreign exchange and the stock market in India. In this work, the positive definite covariance matrix is given, therefore a multivariate GARCH with BEKK model is used to estimate the covariance correlation and identify the consequences that stock market downturns can create. SPSS and Eviews software are used to analyze the data. The Augmented Dickey-Fuller (ADF) and KPSS unit root tests have been used to determine whether a time series is stationary or nonstationary. Whereas it corrects for heteroscedasticity and autocorrelation consistency in ADF test statistics, the study employed the KPSS unit root test to estimate the right result. In addition, to investigate the impact of COVID19 on stock market volatility in terms of negative and positive shocks in financial decisions, the TGARCH model captures asymmetry. The finding that the variable has a negative and statistically significant coefficient suggests that the COVID-19 outbreak lowered stock market volatility in India. In terms of historical errors, the coefficients represent the persistence of volatility for each nation. NIFTY and NASDAQ have the largest and longest-term spillover effect. According to the findings, India is the least sensitive to external shocks.

FORECASTING STOCK MARKET CRASHES VIA REAL-TIME RECESSION PROBABILITIES: A QUANTUM COMPUTING APPROACH

A fast and precise prediction of stock market crashes is an important aspect of economic growth, fiscal and monetary systems because it facilitates the government in the application of suitable policies. Many works have examined the behavior of the fall of stock markets and have built models to predict them. Nevertheless, there are limitations to the available research, and the literature calls for more investigation on the topic, as currently the accuracy of the models remains low and they have only been extended for the largest economies. This study provides a comparison of quantum forecast methods and stock market declines and, therefore, a new prediction model of stock market crashes via real-time recession probabilities with the power to accurately estimate future global stock market downturn scenarios is achieved. A 104-country sample has been used, allowing the sample compositions to take into account the regional diversity of the alert warning indicators. To obtain a robust model, several alternative techniques have been employed on the sample under study, being Quantum Boltzmann Machines, which have obtained very good prediction results due to their ability to remember features and develop long-term dependencies from time series and sequential data. Our model has large policy implications for the appropriate macroeconomic policy response to downside risks, offering tools to help achieve financial stability at the international level.

What drives individual investors in the bear market?

This study uses a unique dataset from a large anonymous brokerage firm to examine the net investment of individual investors during a bear market. The study's empirical evidence reveals that individual investors provide liquidity by acting as net buyers. Particularly, male and younger investors tend to have a higher buying intensity than the others during the market downturn. Besides, better performances when the market crashed encourage investors to be overconfident, thus exhibiting self-attribution bias since we do not find similar results in the bull-market subsample. Results from the stock-level analysis imply that investors tend to buy stocks with worse short-term past performance, higher liquidity, and larger market capitalization. Our findings on the individual investor trading behaviour cannot be explained by either a superior stock-picking ability or a higher tendency to gamble during the market downswing.

A perfect storm in the financial market

This study provides a model explaining how small changes in asset prices may disrupt an entire financial market. Based on the capital asset pricing model (CAPM), our model implies that during a market crash, asset price changes affect the relative distribution of the CAPM betas of individual assets and force all tradable assets to co-move. Using US stock market data, our empirical results are consistent with the model’s predictions. Overall, the study aids understanding of the price patterns of assets during substantial market downturns, such as financial crises.

In Through the Out Door: Editas' CEOs Grasp Opportunities Amidst Challenges

In Through the Out Door: Editas' CEOs Grasp Opportunities Amidst Challenges

Tail risk, systemic risk and spillover risk of crude oil and precious metals

The relationship between oil prices and metal prices has been extensively investigated. However, the tail risk, systemic risk and spillover risk of oil prices have not been investigated via extreme value theory (EVT). We use this novel approach to determine the tail risk of oil, precious metals, how much risk they pose to the financial system and to what extent a shock in oil prices spill over to other precious metals as well as from the financial system. We use long time series of daily data from 1st January 1987 to 31st December 2021 as long time series is required for the EVT. The data is based on the total return index (RI) of four precious metals including gold, platinum, palladium and silver. Our results show that the tail risk of these metals is lower during the crisis period except the Covid-19 pandemic crisis. Most importantly, gold is a safer asset due to the lowest tail risk among four precious metals, indicating the claim that gold is a precious asset to mitigate the returns during market downturns and acts as a ‘safe haven’. Moreover, we also find that extreme systemic risk (tail-β) for crude oil and selected precious metals reduces during crisis period. This is also recognising the fact that these commodities act as a prospective asset for portfolio diversification to hedge against financial assets' volatility. Finally, the spillover risk among crude oil and selected precious metals varies over time, especially during the crisis period and crude oil is an important stimulator of the spillover risk for precious metals. By using our findings, financial market investors can improve their investment planning to attain the maximum advantage of portfolio diversification. Financial managers can further apply these results in forecasting to estimate future global oil market trends for improving their hedging skills and portfolio performance.

Dynamics of the sheltering role of Bitcoin against crude oil market crash with varying severity of the COVID-19: A comparison with gold

This paper studies evolution of the asymmetric sheltering role of Bitcoin compared to gold against oil-related uncertainties with varying severity of the COVID-19 pandemic. Using a varying-coefficient quantile approach, we find a safe haven role of Bitcoin, and it becomes gradually stronger when the pandemic intensifies. The relationship between gold and oil markets is shown to vary with changing severity of the pandemic. We find that gold acts as an increasingly weakened diversifier as the pandemic intensifies until a level, above which its diversification gains would dissipate then. In normal market conditions, both Bitcoin and gold perform as weak hedges for oil portfolios. Our findings demonstrate that interpretation of the sheltering role of Bitcoin and gold against oil market downturns would be biased unless the role dynamics in different market conditions and pandemic severity are considered. Additional analyses reassure robustness of our findings.

Asset prices, financial amplification and monetary policy: Structural evidence from an identified multivariate GARCH model

We investigate feedback relations among asset prices and financial institutions and identify associated monetary policy effects within a system of US nonfinancial firms, real estate, banks and treasury bonds between January 1997 and April 2019. For this purpose, we propose a novel ‘economic’ identification approach to the contemporaneous modeling of conditionally heteroscedastic financial data. While financial amplification characterizes the relation between real estate and banks during the great financial crisis, such effects have been absent among stocks and financial institutions during the dotcom crisis. Interestingly, policy effects are especially strong during most intense market downturns. Moreover, policy sensitivity of asset prices starts increasing long before the actual burst of the bubble.

Does judicial foreclosure procedure help delinquent subprime mortgage borrowers?

AbstractWe conduct comprehensive analyses on whether and how the judicial foreclosure procedure helps subprime mortgage borrowers to reinstate their delinquent loans outside foreclosure liquidation. Even though the transition rates of various exit types are all higher in non‐judicial states, we argue such higher rates can be mechanically driven by the faster shrinking pool of delinquent mortgages in non‐judicial states over time. Based on the cumulative proportions of various exit types during a period of up to 5 years post the mortgage first become 90 days past due, we find that judicial states offer more opportunities for delinquent borrowers to reinstate their loans outside foreclosure liquidation, especially during a housing market downturn. Cures, modifications, and paid‐offs were all important alternative ways to resolve serious delinquencies during 2007–2008. After modifications became widely available in 2009, loan modifications became the most important alternative for subprime borrowers to reinstate their delinquent mortgages outside foreclosure liquidation. The lion's share of the judicial foreclosure benefit shows up after the start of the foreclosure process.

DISRUPTION OF CONTINUITY OR BUSINESS AS USUAL?: A SECTORAL ANALYSIS OF THE IMPACT OF COVID-19 ON EQUITY MARKETS IN BANGLADESH

The present paper analyses the impact of the COVID-19 breakout on the frontier stock market Dhaka Stock Exchange (DSE), exemplified by the case of Bangladesh. This study is based on secondary data from the official website of the Dhaka Stock Exchange. The sampling period extends across two sub-periods, referred to as the pre-lockdown period, extending from March 19, 2019, to March 25, 2020, and the re-opening period stretching from May 31, 2020, to March 11, 2021. Taken together, both sub-periods include a maximum of 442 data points. Our dataset consists of 106 listed companies from the Pharmaceutical, Engineering, and Insurance sectors in DSE. A classical Chow test was used to detect structural breaks. In a vast majority of cases, our results confirm the presence of structural breaks as an effect of Covid-19 by rejecting the null hypothesis. Our analysis of the statistical risk-return profiles of the companies under investigation indicates that the temporary interruption of stock trading in DSE was indeed a “game-changer”. Moreover, our findings support the view that pairwise return correlations tend to be larger during rapid market downturns than they are under “normal” or “positive” market conditions.

Cyclical labor market sorting

We consider sorting in the labor market, that is, whether high- or low-productivity workers and firms tend to match with each other, and how this varies over time using U.S. linked employer–employee data. Composition changes of workers and firms move in opposite directions over the business cycle. During and after recessions, low-rank workers are less likely to work, while the employment share of low-rank firms increases. The agreement between worker and firm ranks increases in the early stages of labor market downturns.

Dependence Structures between Sovereign Credit Default Swaps and Global Risk Factors in BRICS Countries

This study investigates the tail dependence structures of sovereign credit default swaps (CDSs) and three global risk factors in BRICS countries using a copula approach, which is popular for capturing the “true” tail dependence based on the “distribution-adjusted” joint marginals. The empirical results show that global market risk sentiment comoves with sovereign CDS spreads across BRICS countries under extreme market events such as the pandemic-induced crash of 2020, with Brazil reporting the highest bilateral convergence followed by China, Russia, and South Africa. Furthermore, oil price volatility is the second biggest risk factor correlated with CDS spreads for Brazil and South Africa, while exchange rate risk exhibits very low co-dependence with CDS spreads during extreme market downturns. On the contrary, exchange rate risk is the second largest risk factor co-moving with China and Russia’s CDS spreads, while oil price volatility exhibits the lowest co-dependence with CDS in these countries. Between oil price and currency risk, evidence of single risk factor dominance is found for Russia, where exchange rate risk is largely dominant, and policymakers could promulgate financial sector regulations that mitigate spill-over risks such as targeted capital controls when markets are distressed.

Design and Evaluation of Robo-Advisors Using Index Fund and Alternative Assets of Cryptocurrency and Gold: Case of Indonesian Capital Market

Robo-advisor is one of the most prominent innovation in the wealth management industry, and its success in Indonesia has been evident in the case of Bibit. Therefore, wealth management companies need to employ Robo-Advisor to overcome their competition. This research aims to give recommendation on asset allocation method and asset class selection for Robo-Advisors in Indonesia using Sharpe Ratio Analysis. Then, the author will analyze the robo-advisor’s performance during equity market downturn. Finally, The Robo-Advisor’s actual performance will be tested in 2018, 2019, and 2020. The Sharpe ratio analysis result showed that Robo-Advisors seeking higher risk-adjusted return should choose mean-variance optimization over risk parity for asset allocation method, and the inclusion of gold and bitcoin in a portfolio of stock mutual fund and bond mutual fund increases the risk-adjusted return of the portfolio. The proposed robo-advisor’s portfolio protected investors from equity market downturn in 2011-2010 in 83,3% of the case. Finally, the proposed robo-advisor’s portfolio generated better return for the conservative, moderate and aggressive investor during 2018, 2019, and 2020 when compared to LQ45.

Managing Editor’s Letter

1. Francesco A. Fabozzi 1. Managing Editor When facing periods of sharp market downturns, the recommendation typically offered to investors by financial advisors is to remain calm and not sell off their positions. A large percentage of investors ignore this advice, selling off a large portion

Foreclosure Sales Under the UCC During the Covid-19 Pandemic

Under the Uniform Commercial Code (UCC), “every aspect” of a foreclosure sale must be commercially reasonable. The traditional commercial reasonableness standard was tested during the first year of the COVID-19 pandemic, as the unprecedented circumstances imposed by state restrictions prompted increased judicial scrutiny of UCC foreclosure sales. This occurred most prominently in the context of commercial property mezzanine loan foreclosures. A mezzanine loan is a property loan secured by a pledge of equity interests in the property-owning entity rather than a security interest in the property itself. As state mortgage foreclosure moratoriums restricted lenders’ abilities to foreclose on commercial property, mezzanine lenders initiated UCC foreclosures to circumvent this barrier and take control of their collateral. 
 This Note argues that courts adopted a more probing and holistic analytical approach to commercial reasonableness analyses during the first year of the pandemic. This approach more closely analyzed the procedures employed by foreclosing lenders and contextualized fair price considerations within wider market and societal concerns. This Note then proposes ways for secured creditors to protect their foreclosure sales during future periods of market uncertainty. Although secured creditors cannot fully insulate their foreclosure sales from fair price challenges in a market downturn, they should employ additional procedural safeguards to deflect commercial reasonableness challenges aimed at the alleged procedural irregularities of such sales.