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    Seed Weekly - Portfolio Construction and Optimisation

    It is one thing for a fund manager to have an investment philosophy and process that selects shares that typically outperform the market. But often “gains” made at the stock picking level are mitigated using poor portfolio construction methodologies. Increasingly we are looking more closely at specific methodologies that managers use in constructing their portfolios.

    Unless the stock picking ability is taken all the way through to the portfolio construction, total portfolio returns can be dramatically reduced where the manager has too low a weight to a winning position, or conversely too high a weight to a high conviction but high risk position. Or a fund manager may have what appears to be a well-diversified portfolio, but this could include a concentration in a range of shares with the same return driver – i.e. they may all be local importing companies that come under pressure as the rand weakens.

    So just what is portfolio construction and optimisation? It is a method of determining the allocation of selected shares (or asset classes, or funds) in a portfolio, so that they work together to maximise the overall returns and / or minimise the risk.

    Some of the various methodologies used to construct a portfolio include the following:

    • Benchmarking against an index. Many equity fund managers start the process of construction with the weights as determined in the index – for example the JSE Top 40 weights. Preferable shares are overweighed and vice versa, those that do not meet certain investment criteria are underweighted relative to the index.

    • Equally weighted. This is a methodology often used as an alternative to an index tracking portfolio, where the weights to the shares in the index are equally weighted, instead of the traditional highest weight to the largest market cap share on the stock market.

    • Many active fund managers adopt what is known as a Barbell strategy to portfolio construction. This strategy has its origins in constructing a bond portfolio, but can be loosely defined as allocating a portion of the portfolio, say 60%, to relatively low risk, but low yielding assets, example, money market. The remaining 40% is then allocated to higher risk and higher return expectation assets. An example being a range of small cap shares.

    • Increasingly, fund managers are looking at optimising portfolios for various risk measures. These risk metrics may include allocating the biggest weight to the shares with the lowest volatility and vice versa. There is investment merit in this approach, because the performance of shares that display lower than market volatility is often superior to the market.

    Investors may come across the term, modern portfolio theory, which was developed in the 1950’s and is a method of constructing a portfolio, which will maximise the expected return, for any given level of risk assumed; where risk is defined as volatility of the portfolio’s return.

    Where individual investments have similar return characteristics, but these returns are not perfectly correlated then combining them in a portfolio can reduce the overall portfolio’s volatility (i.e. risk measurement), without detracting from the performance. I.e. a more efficient portfolio can be constructed.

    Using a portfolio optimiser

    This can also extend to combining different types of unit trusts that have different risk and return characteristics. At Seed Investments we have developed a portfolio optimiser that assists us in determining the percentage mix that we allocate to different funds, when combining these into a portfolio.

    The optimiser works by allocating the selected range of fund’s historical performance into the mix. It then runs through all the various combinations and provides an ideal output across different risk criteria. An investor does not need an optimiser to determine which combination of funds gave the highest return over a period of time – that is straightforward.

    However when trying to optimise for downside standard deviation, minimised drawdowns, maximising Sharpe and Sortino ratio’s, then an optimiser tool is essential. The output is then used as a guide as to the final portfolio outcome, knowing that the past cannot be fully replicated into the future.

    As with so many aspects on investing, there is no one “magic bullet” even for portfolio construction. Very often the best is for a manager to have a defined process that makes sense and for that manager to then remain diligent to that process without unnecessary wavering, which too often results in increased uncertainty and underperformance.

    Kind regards,

    Ian de Lange

    Tel +27 21 914 4966
    Fax +27 21 914 4912
    Email info@seedinvestments.co.za

    Seed is hiring: Visit the Seed Analytics LinkedIn profile to view vacancies.


    Permalink2016-04-28, 14:46:21, by Mike Email , Leave a comment

    Seed Weekly - Index Reconstitution Effects

    Over the past year, we’ve seen some small movements in the JSE Top 40 index, with one or two shares moving in and out of the index at each rebalance. The bulk of the shares in the index remains the same, with only their weighting to the index changing as the index is reweighted by market capitalisation.

    The change in the composition of the JSE Top 40 index got me thinking on the possible effects that index tracker funds, such as the Satrix Top 40, can have on the price of these shares moving in and out of the index. The Satrix Top 40 fund needs to rebalanced quarterly to remain in line with its benchmark. Let’s look at a practical example and take the adjustment in the JSE Top 40 index at the end of the last quarter, when PSG was replaced by AngloGold Ashanti (ANG) at the end of March 2016. This meant that the Satrix Top 40 would have had to sell all its shares in PSG and buy ANG to remain in line with its benchmark. Using only supply and demand factors and keeping all other variables constant, we would expect to see the price of ANG increase and the price of PSG decrease on the effective rebalance date. Using this hypothesis, below are the results of the last three re-weightings of the Satrix Top 40 portfolio:

    Source: Seed Investments

    The results for March 2016 indicates an increase in the share price of 2.69% for ANG, with a decrease in the price of -2.44% for PSG on the effective rebalance date of the Satrix Top 40 portfolio. However, this is not the case for the previous two quarters, where an increase in the price of the share moving out of the Satrix 40 portfolio can be seen, instead of the expected decrease in share price.

    This is obviously a very small universe of test cases, but initially my hypothesis does not seem to have any credibility, or justifies a more thorough research process. In the US, some observers have suggested that indexing and benchmarking have distorting effects on share prices. I will briefly look at some of the price distortion effects which have been identified below.

    The S&P 500 Index Reconstitution Effect

    Shares added to the S&P 500 rise in price radically upon announcement of their addition to the index. Shares deleted from the index suffer a corresponding price decline. The reason for the inclusion and deletion effects (classified together as a reconstitution effect) is obvious: an increase in the demand for a stock caused by the need for index funds to hold that stock is not met by any change in supply. Thus, the price rises. The deletion effect is simply the mirror image of the inclusion effect.

    Russell Mania

    A market microstructure effect that is closely related to, but somewhat different in character, from the S&P reconstitution effect is what has come to be called “Russell Mania”. Stocks being added to the Russell 2000 (which includes 98% of the U.S. equity market value) are very small in market cap, so they are excessively affected by either temporary or permanent changes in demand. A large portion of small-cap portfolios are indexed or benchmarked to the Russell 2000 index. Thus, when a share moves from the Russell 1000 to the Russell 2000, because its relative market cap has declined, the demand for the stock increases which in effect cause an increase in the share price.

    Free-Float Mismatch: The “Yahoo! Effect”

    The most significant S&P 500 inclusion effect in history occurred in 1999, when Yahoo! was added to the index, and the price rose by 24%. The cause was the fact that Yahoo! had been added to the S&P 500 at its full market-cap weight without any adjustment for the free float of shares. Because most shares were held by employees, venture capital firms, and other investors who were restricted from selling, the accurate supply of Yahoo! shares was only about 10% of the full market cap. This resulted in a significant imbalance in the supply-demand dynamic of Yahoo! Shares, which was apparent in the sharp rise in the price.

    The US market is by far the largest ETF market in the world, with 73% of worldwide ETF assets under management and a high proportion of passive funds vs. active funds.

    Sources: Investment Company Institute and ETFGI

    SA’s smaller ETF funds will not have the same impact on share prices as the larger U.S. funds have, and to identify and examine these price distortion effects in our market would be a much more difficult exercise. It was an interesting exploration nonetheless.

    Kind regards,

    Stephan van der Merwe

    Tel +27 21 914 4966
    Fax +27 21 914 4912
    Email info@seedinvestments.co.za

    Seed is hiring: Visit the Seed Analytics LinkedIn profile to view vacancies.


    Source: SeedInvest

    Permalink2016-04-20, 08:17:47, by Mike Email , Leave a comment