Risk Characteristics of Real Estate Related Securities--An Extension of Liu and Mei (1992)

This study extends from Liu and Mei (1992) by further investigation of assets, real estate related securities, which includes both equity and mortgage real estate investment trusts (REITs), the stocks of builder- and owner-companies, and mortgage-backed securities (MBSs). There are five major findings. First, expected excess returns of real estate related securities are more predictable than the expected excess returns of value-weighted stocks and bonds. Second, right market timing is important to investors since evidence shows that the risk premiums of real estate related securities vary substantially over time. Third, real estate market conditions significantly influence bonds and MBSs. Fourth, MBSs are more similar to bonds than mortgage REITs. In addition, returns on mortgage REITs resemble both stocks and bonds. Finally, real estate stocks have a very high sensitivity toward stock market portfolio. This suggests that real estate stocks are not good instruments to help diversify stock risk.

Institutional Factors and Real Estate Returns - A Cross Country Study

This study provides an empirical study on the relationship between institutional factors and real estate returns. Using data from both developed and emerging market countries, our empirical results show that institutional factors do influence real estate returns and these factors may not be fully priced. We find that when controlling return volatility and level of economic growth, a higher property return is expected in countries where the economy is more efficient and has more economic freedom. Our results support the view that the combination of "lumpiness" of real estate investment and the volatile nature of international capital flows may expose property investors to extra investment risk, which needs to be compensated. Our results also indicate that an improvement in a country's economic efficiency and economic freedom may reduce property variance risk thus enhancing property returns.Economic Freedom index, Institutional Investors' Country Credit Ratings

Bounded-Distortion Metric Learning

Metric learning aims to embed one metric space into another to benefit tasks like classification and clustering. Although a greatly distorted metric space has a high degree of freedom to fit training data, it is prone to overfitting and numerical inaccuracy. This paper presents {\it bounded-distortion metric learning} (BDML), a new metric learning framework which amounts to finding an optimal Mahalanobis metric space with a bounded-distortion constraint. An efficient solver based on the multiplicative weights update method is proposed. Moreover, we generalize BDML to pseudo-metric learning and devise the semidefinite relaxation and a randomized algorithm to approximately solve it. We further provide theoretical analysis to show that distortion is a key ingredient for stability and generalization ability of our BDML algorithm. Extensive experiments on several benchmark datasets yield promising results

Dust-wind interactions can intensify aerosol pollution over eastern China.

Eastern China has experienced severe and persistent winter haze episodes in recent years due to intensification of aerosol pollution. In addition to anthropogenic emissions, the winter aerosol pollution over eastern China is associated with unusual meteorological conditions, including weaker wind speeds. Here we show, based on model simulations, that during years with decreased wind speed, large decreases in dust emissions (29%) moderate the wintertime land-sea surface air temperature difference and further decrease winds by -0.06 (±0.05) m s-1 averaged over eastern China. The dust-induced lower winds enhance stagnation of air and account for about 13% of increasing aerosol concentrations over eastern China. Although recent increases in anthropogenic emissions are the main factor causing haze over eastern China, we conclude that natural emissions also exert a significant influence on the increases in wintertime aerosol concentrations, with important implications that need to be taken into account by air quality studies

An integral gated mode single photon detector at telecom wavelengths

We demonstrate an integral gated mode single photon detector at telecom wavelengths. The charge number of an avalanche pulse rather than the peak current is monitored for single-photon detection. The transient spikes in conventional gated mode operation are canceled completely by integrating, which enables one to improve the performance of single photon detector greatly with the same avalanche photodiode. This method has achieved a detection efficiency of 29.9% at the dark count probability per gate equal to 5.57E-6/gate (1.11E-6/ns) at 1550nm.Comment: word to PDF, 3 pages with 4 figure