Do real estate mutual funds enhance portfolio returns and reduce portfolio risk?

2005 ◽  
Vol 5 (1-2) ◽  
pp. 51-66 ◽  
Author(s):  
Nell S. Gullett ◽  
Arnold L. Redman
Keyword(s):  
Real Estate ◽  
Mutual Funds ◽  
Portfolio Risk ◽  
Portfolio Returns

A Study on Investment Decision of Investors With Reference to Penetration of Mutual Funds in India

2016 ◽  
Vol 5 (2) ◽  
Author(s):  
Ratish C Gupta ◽  
Dr. Manish Mittal
Keyword(s):  
Decision Making ◽  
Real Estate ◽  
Mutual Funds ◽  
Capital Markets ◽  
Mutual Fund ◽  
Financial Services ◽  
Investment Decision ◽  
Fund Industry ◽  
Mutual Fund Industry ◽  
The Impact

The Indian mutual fund industry is one of the fastest growing and most competitive segments of the financial sector. The extent of under-penetration in the market is a sore point with the financial services industry, with a large amount of savings being channelized into fixed deposits, gold and real estate rather than the capital markets. The mutual fund industry is yet to spread its reach beyond Tier I cities. The top fifteen cities contribute to 85% of the pie, with the remaining 15% distributed among other cities. The study seeks to determine the impact of decision making of investors on current situation of mutual fund industry.

The performance of Italian real estate mutual funds

2009 ◽  
Vol 2 (2) ◽  
pp. 170-185 ◽  
Author(s):  
Giacomo Morri ◽  
Stephen L. Lee
Keyword(s):  
Real Estate ◽  
Mutual Funds

scholarly journals Real estate as a portfolio risk diversifier

2016 ◽  
Vol 13 (2) ◽  
pp. 45-52
Author(s):  
Ahmad Etebari
Keyword(s):  
Real Estate ◽  
Portfolio Risk ◽  
Optimal Portfolios ◽  
Investment Performance ◽  
Optimization Framework ◽  
Expected Inflation ◽  
Common Stocks ◽  
Asset Class ◽  
The U.S ◽  
Return Data

This study provides evidence on the investment performance of real estate relative to bonds and common stocks in the U.S. Using quarterly total return data over the years 1978-2012, the analyses show that, over this period, on a risk-adjusted basis real estate was the top performing asset class, outperformed both bonds and stocks. Real estate, in the Eastern U.S., was the top performer, outperforming both bonds and stocks. The results also show that real estate provided a partial hedge against actual and expected inflation, and that, in combinations with bonds and stocks, it made up a major share of optimal portfolios constructed for various target returns within the Markowitz optimization framework

Long-term dependency between sovereign bonds and sectoral indices of India: evidence using Hurst exponent and wavelet analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Santanu Das ◽  
Ashish Kumar
Keyword(s):  
Wavelet Analysis ◽  
Hurst Exponent ◽  
Minimum Variance ◽  
Portfolio Risk ◽  
Content Type ◽  
Sovereign Bonds ◽  
Portfolio Returns ◽  
Portfolio Managers ◽  
Practical Implications

PurposeThe purpose of this study is to provide a new way to optimize a portfolio and to show that combining the Hurst exponent and wavelet analysis may help to increase portfolio returns.Design/methodology/approachThe authors use the Hurst exponent and wavelet analysis to study the long-term dependencies between sovereign bonds and sectoral indices of India. The authors further construct and evaluate the performance of three portfolios constructed on the basis of Hurst standard deviation (SD) – global minimum variance (GMV), most diversified portfolio (MDP) and equal risk contribution (ERC).FindingsThe authors find that an ERC portfolio generates positive superior return as compared other two. Since our sample includes periods of two crisis – post-2007 financial crisis and the ongoing pandemic, this study reveals that combining government bond with equities and gold provides a higher returns when the portfolios are constructed using the risk exposures of each asset in the overall portfolio risk.Practical implicationsThe findings provide guidance to portfolio managers by helping them to select assets using the Hurst approach and wavelet analysis thereby increasing the portfolio returns.Originality/valueIn this study, the authors use a combination of Hurst exponent and wavelet analysis to understand the long-term dependencies among various assets and provide a new methodology to optimize a portfolio. As far as the authors’ knowledge, no study in the past has attempted to provide a joint framework for portfolio optimization and therefore this study is the first to apply this methodology.

Real Estate Portfolio Risk Reduction through Intracity Diversification

1998 ◽  
Vol 4 (1) ◽  
pp. 35-41 ◽  
Author(s):  
Marvin Wolverton ◽  
Ping Cheng ◽  
William Hardin
Keyword(s):  
Real Estate ◽  
Risk Reduction ◽  
Portfolio Risk

The predictive abilities and persistence of Morningstar ratings: an examination of real estate mutual funds

2011 ◽  
Vol 28 (3) ◽  
pp. 249-267 ◽  
Author(s):  
Vivek Sah ◽  
Owen Alan Tidwell ◽  
Alan James Ziobrowski
Keyword(s):  
Real Estate ◽  
Mutual Funds

Gains From Diversifying Into Real Estate: Three Decades of Portfolio Returns Based on the Dynamic Investment Model

1995 ◽  
Vol 23 (2) ◽  
pp. 117-159 ◽  
Author(s):  
Robert R. Grauer ◽  
Nils H. Hakansson
Keyword(s):  
Real Estate ◽  
Investment Model ◽  
Portfolio Returns ◽  
Dynamic Investment

Analyzing Real Estate Portfolio Returns

2005 ◽  
Vol 31 (5) ◽  
pp. 134-142 ◽  
Author(s):  
Ronald W. Kaiser
Keyword(s):  
Real Estate ◽  
Portfolio Returns

scholarly journals Mutual funds behavior and risk-adjusted performance in Nigeria

2021 ◽  
Vol 18 (3) ◽  
pp. 277-294
Author(s):  
Joshua Odutola Omokehinde
Keyword(s):  
Mutual Funds ◽  
Portfolio Performance ◽  
Average Risk ◽  
Negative Effects ◽  
Market Returns ◽  
Significance Level ◽  
Fund Managers ◽  
Portfolio Returns ◽  
Normality Test ◽  
Risk Free Rate

The paper investigates the behavior of mutual funds and their risk-adjusted performance in the financial markets of Nigeria between April 2016 and May 31, 2019, using descriptive statistics, as well as CAPM, Jensen’s alpha, and other risk-adjusted portfolio performance measures such as Sharpe and Treynor ratios, as well as Fama decomposition of return. The descriptive tests revealed that 80.77% of the funds were superior to market returns, while 13.46% were riskier. The market and the fund returns behaved abnormally with asymptotic and leptokurtic characteristics as their skewness and kurtosis varied from the normal requirements. Diagnostically, the normality test by Jacque-Berra showed that the return was not normally distributed at a 1% significance level. The market was more aggressive relative to the funds. The average risk-free rate was 6.75% above the market’s return. The risk-adjusted portfolio returns measured by Sharpe and Treynor ratios showed that 67.31% of the funds underperformed the market compared to 40.38% that outperformed the market using Jensen’s alpha. Fama decomposition of return revealed that the fund managers are risk-averse with 48% superior selection ability and rationally invested over 85% of investors’ funds in schemes with fixed income securities at a given risk-free return that cushioned the negative effects of the systematic and idiosyncratic risks and consequently threw the total returns into positive territories. Overall, the fund managers possessed 52% of inferior selection abilities that only earned 33% of superior risk-adjusted returns and hence, failed to achieve the desired diversification in the relevant period.

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