Portfolio Management - Summary Paper

Royal Melbourne Institute of Technology **We aren't endorsed by this school
BFF 3121
Oct 16, 2023
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Portfolio Management Summary paper on The Smart Beta Mirage RMIT UNIVERSITY Prepared by Rutuja Bodhe - S3930752 Suhas Reddy - S3961901 Vipul Dhakate - S3954369
Summary Paper What are Smart Beta ETF's? Smart beta is a broad phrase that refers to non-market weighted indexes in stock markets and, progressively, various other kinds of assets. Smart beta indexes, in general, deviate from the usual practice of weighting members by market capitalization to represent a number of distinct goals. Smart beta ETFs employ different weighting systems based on criteria such as value, momentum, quality, volatility, and size to construct a portfolio of stocks tailored to meet certain investing goals. Despite capitalization-weighted indexes are widely used as performance standards along with the foundation for index-tracking investment products, they are susceptible to times of significant focus in certain sectors or stocks, indicating very brief market patterns. This paper's key findings are as follows: The dramatic decline in performance of smart beta indexes following the listing of smart beta ETFs for investment. Adjusted for aggregate market return, smart beta indexes' average return falls from 3% per year "on paper" before ETF listing to 0.50 to -1% per year after ETF listing. This decline in performance cannot be explained by intentional timing in ETF launching or by a temporal trend in factor premia. We uncover evidence of data mining in smart beta index construction because the post-ETF-listing performance decrease is substantially steeper for indexes that are more sensitive to data mining in back tests. (Huang, Song and Xiang, 2023) Smart beta tactics are neither passive nor diverse. They also cannot be expected to function consistently in all market conditions. Especially because they concentrate on a small number of variables, smart beta strategies miss out on several possible profit chances. Smart beta techniques may be a beneficial addition to the spectrum of investing strategies accessible to investors, however they're certainly not a miracle code for raising returns whilst decreasing risks. A more accurate assessment of the benefits and drawbacks of smart beta investing would benefit investors more. Jacobs and Levy (2015)
As for the working, the Smart Beta ETF only seems smart on paper, as the paper mentions it's a 'mirage' that showcases the results through past data. We discover that it is not due to ETF sponsors' deliberate placement in ETF listings or factor return changes. Rather, we find significant support for data mining in index development, implying that good performance occurs only in back tests and has little predictive potential for "real" output. This document serves two purposes. Firstly, we add to the body of work that examines if traditional asset pricing determinants have any predictive value for the cross-section of (REIT) returns. It specifically studies the presence of a premium connected with the Value, Size, Momentum, as well Investment, and Profitability aspects from 2000 to 2018. This provides evidence across all price criteria except Profitability. Furthermore, it will look at if a set of smart beta methods centered around a mix of the discovered factors could beat equivalent allocation approaches that do not use factors. They discover that all the suggested factor-based strategies outperform a basic buy-and-hold investment in the real estate market in terms of risk-adjusted out-of-sample performance. Additionally, when factor-based methods are used, REIT-only portfolios have risk-adjusted returns equivalent to that of portfolios with diversification that include equities, bond, and commodities. Possible explanations related to smart beta in the paper: Smart beta investment strategy emphasizes on use of alternative index to exploit performance factors so as to outperform benchmark index. The given paper described that smart beta ETFs are launched in the market to provide extra exports for investors to receive excessive returns. (Huang, Song and Xiang, 2023) highlighted that ETFs are growing remarkably and now the "smart beta" segment is even more popular financial innovation that appeared firstly in 200 in the US and by 2018, the volume of smart beta ETFs will increase over $700 billion in 2018. Smart beta ETF are exchange traded funds which use a rule-based system in order to select the best investment for a portfolio and this is the main attribute of this investment. However, it requires large scale availability of data and strong computing power so that the certain behaviors of stocks can be analyzed for investments (Bowes and Ausloos, 2021). The paper also presented another important explanation that when the smart beta indexes become accessible to all investors most smart beta ETFs do not add much value to investors and only the proliferation of such ETFs could be valuable to investors in terms of cheaper exposure to asset pricing factors .
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