Mean-ETL Portfolio Construction in US Equity Market

South Afric's Equity market provides a large (in terms of volume) but concentrated investment environment. Domestic pension funds are restricted from diversifying globally and are thus faced with a restricted set of investment opportunities. This article describes and quantifies the extent of the concentration on the JSE historically and at present. The article describes the consequent limitations on long-only equity portfolio construction and the implications for the domestic long-only fund manager subject to various active weight limits. The analysis shows that the higher the allowable active bet sizes, the less consistently asset managers are able to implement their views and the less symmetric their response to forecasted excess returns can be. Consequently, the less competitive a long-only fund manager can be alongside hedge funds and similarly constrained long-short managers.

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The volatility effect across size buckets: evidence from the Indian stock market

Investment Management and Financial Innovations ◽

10.21511/imfi.16(3).2019.07 ◽

2019 ◽

Vol 16 (3) ◽

pp. 62-75 ◽

Cited By ~ 1

Author(s):

Shilpa Peswani ◽

Mayank Joshipura

Keyword(s):

High Risk ◽

Stock Market ◽

Significant Risk ◽

Equity Market ◽

Sharpe Ratio ◽

Portfolio Construction ◽

Market Capitalization ◽

Value Stocks ◽

High Volatility ◽

Indian Stock Market

The portfolio of low-volatility stocks earns high risk-adjusted returns over a full market cycle. The annual alpha spread of low versus high-volatility quintile portfolios is 25.53% in the Indian equity market for the period from January 2000 to September 2018. The low-volatility (LV) effect is not an overlap of other established factors such as size, value or momentum. The effect persists across various size buckets (market capitalization). The performance of the low-volatility effect within various size buckets is analyzed using three different portfolio formation methods. Irrespective of the method of portfolio construction, the low-volatility effect exists and it also generates economically and statistically significant risk-adjusted returns. The long-short portfolios across the study deliver exceptionally high and statistically significant returns accompanied by negative beta. The low-volatility effect is not restricted to small or illiquid stocks. The effect delivers the highest risk-adjusted returns for the portfolio consisting of largecap stocks. Though the returns of the portfolio comprising of large-cap LV stocks are lower than the returns of the portfolio comprising of small-cap LV stocks, its Sharpe ratio is higher because of less risky nature of large-cap stocks as compared to small-cap stocks. The LV portfolio majorly comprises of large-cap, growth and winner stocks. But within size buckets, large-cap and mid-cap low LV picks growth and winner stocks, while small-cap LV picks value stocks.

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The impact of sectorial and geographical segmentation on risk-based asset allocation techniques

Investment Management and Financial Innovations ◽

10.21511/imfi.16(3).2019.24 ◽

2019 ◽

Vol 16 (3) ◽

pp. 260-274

Author(s):

Ignazio Basile ◽

Pierpaolo Ferrari ◽

Guido Abate

Keyword(s):

Asset Allocation ◽

Equity Market ◽

Portfolio Construction ◽

Financial Evaluation ◽

Significant Preference ◽

Construction Techniques ◽

Internal Coherence ◽

Stock Market Investment ◽

The Impact ◽

Made In

In the last decades, risk-based portfolio construction techniques have enjoyed a widespread diffusion in the financial community. This study aims at evaluating how these portfolio construction techniques produce different results depending on whether the segmentation of the stock market investment universe is based on sectorial or geographical criteria. An empirical analysis, applied on the global equity market, is carried out by making use of the typical and most advanced statistical and financial evaluation measures. Geographical segmentation is carried out in relation to the listing market, while sectorial segmentation is made in relation to the productive sectors to which individual companies belong. Our comparative analysis provides substantially coherent results, demonstrating a significant preference for the sectorial criterion compared to the geographic one. In conclusion, this result can be attributed to the subdivision of the investment universe into sectorial indices characterized by greater internal coherence and better external differentiation, in addition to the lower concentration of sectorial segmentation compared to the geographical one.

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