scholarly journals Investments in Contemporary Russian Artwork as an Alternative Form of Investment

2020 ◽  
Vol 14 (3) ◽  
pp. 7-18
Author(s):  
Alexandra Galanova ◽  
Maria Lutsenko ◽  
Jorge Zamorano
Keyword(s):  
Real Estate ◽  
Alternative Form ◽  
Hedonic Price ◽  
Investment Performance ◽  
Real Estate Markets ◽  
Russian Art ◽  
The Usa ◽  
Capm Model ◽  
Investment Portfolios ◽  
Alternative Investment

In the last decades of the 20th century, various classes of alternative investments have become increasingly popular among investors. During this time, art as a form of alternative investment attracted attention not only from potential buyers but also from academic scholars. Unfortunately, only a few of the newly published papers contained any quantitative analysis with regard to art’s investment performance. Besides, even a smaller amount of research was devoted to the analysis of Russian art markets. Therefore, the purpose of this work is to evaluate the efficiency of investments in the artworks of contemporary Russian painters and to compare the effectiveness of these investments with the effectiveness of investments in stock, bond and real estate markets in Russia and the USA. For this research, we first conduct a hedonic regression analysis on the data available for 1950-2019 time period. After that, we build a hedonic price index for the canvases of contemporary Russian artists. According to the results, the trend of this index reiterates largely the price behavior for world contemporary art market. However, the results of this study indicate that investments in contemporary Russian art do not outperform investments in instruments of Russian and American capital and real estate markets. These results were derived by applying the CAPM model which demonstrated that Russian art as a form of alternative investment is not advisable for the purposes of diversification of investment portfolios. Based on these findings, contemporary Russian art in general can be considered an unattractive instrument for Russian and foreign investors.

scholarly journals Measuring European property investment performance: comparing different approaches

2014 ◽  
Vol 7 (1) ◽  
pp. 112-132 ◽  
Author(s):  
Steven Devaney
Keyword(s):  
Real Estate ◽  
Asset Allocation ◽  
Sample Selection ◽  
Real Estate Market ◽  
Commercial Real Estate ◽  
Investment Performance ◽  
Content Type ◽  
Real Estate Markets ◽  
Country Level ◽  
The Usa

Purpose – Price indices for commercial real estate markets are difficult to construct because assets are heterogeneous, they are spatially dispersed and they are infrequently traded. Appraisal-based indices are one response to these problems, but may understate volatility or fail to capture turning points in a timely manner. This paper estimates “transaction linked indices” for major European markets to see whether these offer a different perspective on market performance. The paper aims to discuss these issues. Design/methodology/approach – The assessed value method is used to construct the indices. This has been recently applied to commercial real estate datasets in the USA and UK. The underlying data comprise appraisals and sale prices for assets monitored by Investment Property Databank (IPD). The indices are compared to appraisal-based series for the countries concerned for Q4 2001 to Q4 2012. Findings – Transaction linked indices show stronger growth and sharper declines over the course of the cycle, but they do not notably lead their appraisal-based counterparts. They are typically two to four times more volatile. Research limitations/implications – Only country-level indicators can be constructed in many cases owing to low trading volumes in the period studied, and this same issue prevented sample selection bias from being analysed in depth. Originality/value – Discussion of the utility of transaction-based price indicators is extended to European commercial real estate markets. The indicators offer alternative estimates of real estate market volatility that may be useful in asset allocation and risk modelling, including in a regulatory context.

Return and co-movement of major public real estate markets during global financial crisis

2017 ◽  
Vol 35 (5) ◽  
pp. 489-508 ◽  
Author(s):  
Kim Hiang Liow ◽  
Shao Yue Angela
Keyword(s):  
Financial Crisis ◽  
Real Estate ◽  
Global Financial Crisis ◽  
Content Type ◽  
Real Estate Markets ◽  
The Public ◽  
Movement Dynamics ◽  
The Usa ◽  
Short Run ◽  
Practical Implications

Purpose The purpose of this paper is to investigate the volatility spectral of five major public real estate markets, namely, the USA, the UK, Japan (JP), Hong Kong (HK), and Singapore (SG), during the pre- and post-global financial crisis (GFC) periods. Design/methodology/approach First, univariate spectral analysis is concerned with discovering price cycles for the respective real estate markets. Second, bivariate cross-spectral analysis seeks to uncover whether any two real estate price series share common cycles with regard to their relative magnitudes and lead-lag patterns of the cyclical variations. Finally, to test the contagion effects, the authors estimate the exact percentage change in co-spectral density (cyclical covariance) due to high frequencies (short run) after the GFC. Findings The authors find that whilst none of the public real estate markets examined are spared from the crisis, the three Asian markets were less severely affected by the GFC and were accompanied by a reversal in volatility increase three years post-global financial crisis. Additionally, the public real estate markets studied have become more cyclically linked in recent years. This is particularly true at longer frequencies. Finally, these increased cyclical co-movements measure the outcomes of contagion and indicate fairly strong contagious effects between the public real estate markets examined due to the crisis. Research limitations/implications The implication of this research is that benefits to investors from international real estate diversification may not be as great during the present time compared to previous periods because national public real estate markets have become more correlated. Nevertheless, the findings do not imply the complete absence of diversification benefits. This is because although cyclical correlations increase in the short run, many of the correlation values are still between low and moderate range, indicating that some diversification benefits may still be realized. Practical implications Given the significant market share and the highest levels of securitization in Asia-Pacific markets including JP, HK/China, and SG, this cyclical research including major public real estate markets has practical implications for ongoing international real estate investment strategies, particularly for the USA/UK and Asian portfolio managers. Originality/value This paper contributes to the limited research on the cyclical return and co-movement dynamics among major public real estate markets during financial/economic crisis in international finance. Moreover, the frequency-domain analysis conducted in this paper adds to better understanding regarding the impact of GFC on the cyclical return volatility and co-movement dynamics of major developed public real estate markets in international investing.

Housing Market Hedonic Price Study Based on Boosting Regression Tree

2017 ◽  
Vol 21 (6) ◽  
pp. 1040-1047 ◽  
Author(s):  
Guangtong Gu ◽  
Bing Xu ◽  
◽  
◽  
Keyword(s):  
Real Estate ◽  
Housing Prices ◽  
Regression Tree ◽  
Gradient Boosting ◽  
Hedonic Price ◽  
Tree Model ◽  
Policy Makers ◽  
Real Estate Markets ◽  
Architectural Features ◽  
Real Estate Prices

Based on the purchase price data of new real estate markets three cities in China, Beijing, Shanghai, and Guangzhou, including architectural features, neighborhood property features, and location features, in this study a boosting regression tree model was built to study the factors and the influence path of housing prices from the microcosmic perspective. First, a classical hedonic price model was constructed to analyze and compare the significant effect factors on housing prices in the market segments of the three cities. Second, the gradient boosting regression tree method that is proposed in this paper was applied to the three markets in combination to analyze the influence paths and factors and the importance of the type of housing hedonic price. The influence paths of housing hedonic prices and decision tree rules are visualized. The significant housing features are effectively extracted. Finally, we present three main conclusions and several suggestions for policy makers to improve urban functions while stabilizing real estate prices.

Transparency in the German real estate market

2005 ◽  
Vol 23 (1) ◽  
pp. 90-108 ◽  
Author(s):  
Karl‐Werner Schulte ◽  
Nico Rottke ◽  
Christoph Pitschke
Keyword(s):  
Real Estate ◽  
Real Estate Market ◽  
International Standards ◽  
Real Estate Industry ◽  
Content Type ◽  
Real Estate Markets ◽  
Current State ◽  
The Usa ◽  
Private And Public ◽  
The Uk

PurposeGerman real estate markets used to show little transparency in the past. This has changed over the last 15 years. The purpose of this study therefore is to examine the current state of transparency.Design/methodology/approachThe study investigates and discusses the concept of transparency in general, availability of private and public market data, major real estate investment products, performance measurement, changes in the regulatory environment and the emergence of organizations and publications. The findings of this study are obtained in a comparative manner: The transparency status of the 1990s in the different areas researched is compared to the current German and other international standards. The authors describe the relatively opaque German real estate market as it was at the beginning of the 1990s and show how it has improved to date.FindingsThe results show that transparency in the German real estate market has noticeably improved in all researched areas. But still, compared with the USA or the UK, the German real estate industry and real estate market still lack transparency and are characterized by information asymmetries and opaqueness.Originality/valueThe results indicate that the German real estate market and industry become more mature and bit by bit converge with their US and UK archetype.

scholarly journals Multivariate modelling of 10-day-ahead VaR and dynamic correlation for worldwide real estate and stock indices

2014 ◽  
Vol 41 (2) ◽  
pp. 216-232 ◽  
Author(s):  
Stavros Degiannakis ◽  
Apostolos Kiohos
Keyword(s):  
Real Estate ◽  
Confidence Level ◽  
Content Type ◽  
Real Estate Markets ◽  
Dynamic Correlation ◽  
Basel Committee ◽  
Percent Confidence Level ◽  
Multivariate Modelling ◽  
The Usa ◽  
Risk Managers

Purpose – The Basel Committee regulations require the estimation of value-at-risk (VaR) at 99 percent confidence level for a ten-trading-day-ahead forecasting horizon. The paper provides a multivariate modelling framework for multi-period VaR estimates for leptokurtic and asymmetrically distributed real estate portfolio returns. The purpose of the paper is to estimate accurate ten-day-ahead 99%VaR forecasts for real estate markets along with stock markets for seven countries across the world (the USA, the UK, Germany, Japan, Australia, Hong Kong and Singapore) following the Basel Committee requirements for financial regulation. Design/methodology/approach – A 14-dimensional multivariate Diag-VECH model for seven equity indices and their relative real estate indices is estimated. The authors evaluate the VaR forecasts over a period of two weeks in calendar time, or ten-trading-days, and at 99 percent confidence level based on the Basle Committee on Banking Supervision requirements. Findings – The Basel regulations require ten-day-ahead 99%VaR forecasts. This is the first study that provides successful evidence for ten-day-ahead 99%VaR estimations for real estate markets. Additionally, the authors provide evidence that there is a statistically significant relationship between the magnitude of the ten-day-ahead 99%VaR and the level of dynamic correlation for real estate and stock market indices; a valuable recommendation for risk managers who forecast risk across markets. Practical implications – Risk managers, investors and financial institutions require dynamic multi-period VaR forecasts that will take into account properties of financial time series. Such accurate dynamic forecasts lead to successful decisions for controlling market risks. Originality/value – This paper is the first approach which models simultaneously the volatility and VaR estimates for real estate and stock markets from the USA, Europe and Asia-Pacific over a period of more than 20 years. Additionally, the local correlation between stock and real estate indices has statistically significant explanatory power in estimating the ten-day-ahead 99%VaR.

Co-movement and Forecasting Analysis of Major Real Estate Markets by Wavelet Coherence and Multiple Wavelet Coherence

2017 ◽  
Vol 05 (02) ◽  
pp. 1750010 ◽  
Author(s):  
Cengiz KARATAS ◽  
Gazanfer UNAL ◽  
Adil YILMAZ
Keyword(s):  
Time Series ◽  
Real Estate ◽  
Real Estate Market ◽  
Wavelet Coherence ◽  
Real Estate Markets ◽  
Frequency Space ◽  
Time Frequency ◽  
Dynamic Correlation ◽  
The Usa ◽  
Multiple Wavelet Coherence

Wavelet coherence of time series provides valuable information about dynamic correlation and its impact on time scales. Here, the authors analyze the wavelet coherence of major real estate markets data, and take the USA, Hong Kong of China, Canada, Japan, and Developed Europe real estate market prices as time series. The wavelet coherence results show relationships among these markets, the correlations between the two and three markets (by multiple wavelet coherence) and how these relationships vary in the time-frequency space. These relationships allow the authors to build VARMA models of real estate data which produce forecasts with small errors.

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