Performance evaluation is key to a fund manager’s skills
When we invest in a mutual fund scheme, we expect it to not only give good returns but also outperform its benchmark. Else we would have been better off investing in the index itself. The skill of a fund manager lies in generating superior returns compared with the benchmark, which is also termed as alpha or active return.
The skill to generate alpha is scrutinized by fund managers to ensure that they are on the right path.
How is alpha generated?
Let’s take an example of a large-cap fund that is benchmarked to CNX Nifty (large-cap index). Nifty is a collection of 50 stocks and each of these stocks contribute to the index’s return. The total Nifty return is the weighted average return of these 50 stocks.
Nifty would constitute a few stocks that would have given higher return than the Nifty total return (outperformers) and the remaining would have given lesser return than the Nifty (underperformers).
To generate alpha, the fund manager must put more weight of the portfolio in outperformers and lesser weight in underperformers.
Note that it’s not about selecting stocks with positive returns, it’s about picking stocks that will outperform the Nifty.
In a typical top-down approach of portfolio construction, a fund manager has to first identify sectors that might outperform the index and then identify best stocks in the sector that will outperform peers and accordingly place her bets. Easier said than done, this translates into taking a decision of appropriately weighting each sector and stock.
Evaluating the drivers of performance
It is these skills of the fund manager, that is picking the right sectors (sector allocation) and picking outperforming stocks (security selection), that drives a fund’s alpha. While fund managers evaluate fund performance, they evaluate if the decisions taken by them have been right or not and how much alpha each decision has generated.
The process of attributing the portfolio alpha to individual decisions is called performance attribution. Say for investments across 15 or more sectors and 50 securities in Nifty, performance attribution breaks down the outperformance (alpha) to each sector allocation and security selection decision (total 15 + 50 = 65 decisions).
Sources of alpha
The first cut attribution segregates the alpha into the constituent sectors. It can be easily deduced if the alpha has been generated from only a few sectors or a wide range of sectors. A good fund manager would be skilled enough to drive alpha from across various sectors and this demonstrates the diversification of her skills. On the contrary, if the alpha is sourced from a few sectors, it might signify luck.
The alpha at sector level is then segregated into alpha from sector allocation and stock selection.
The fund management team keeps an eye on macroeconomic scenarios including gross domestic product growth, interest rate cycles, inflation, exchange regimes and other parameters to determine the sectors that would be positively affected in the given regime and the sectors that would be negatively affected.
Accordingly, they decide on which sectors to be termed as overweight and which ones to be termed as underweight. A positive sector allocation is achieved if the fund manager has an overweight view on a sector that has “outperformed” or if she has an underweight view on a sector that has “underperformed”.
This analysis of allocation alpha across sectors signifies the strength in understanding of sectors with economic cycles.
Even if a sector is doing well, all stocks in the sector don’t behave alike. Once a weight has been assigned to a sector, stock analysts shortlist the companies that they are bullish on and expect to outperform the sector. If they are able to pick the right stocks, it shows in the stock selection of the sector.
Irrespective of whether the sector is overweighted or underweighted, this decision relates to picking outperformers within that sector and betting appropriately on them.
Fund managers might review their sector allocation and stock selection models if they see that either of the decisions is going wrong. Negative numbers for short-term might be acceptable as the portfolio might be designed for the long term. However, if it is observed that a particular decision is consistently detracting the alpha, the fund manager may tighten a few screws.
It might happen that the entire alpha is contributed by stock selection with allocation playing a very small part. This can be the case with funds that focus on stock picking and don’t deviate from index in terms of sector allocations. However, if such outcome is not because of the fund style then it demands further analysis and corrective measures.
Fund managers work with their teams of sector and stock analysts who contribute to the entire decision-making process. Performance attribution analysis easily helps them to identify the sources of positive and negative alpha and provide a quantified effectiveness of decision making. With that information and regular feedback from powerful attribution analytics, fund managers can iron out the weak links to deliver better performance. Large wealth managers also use attribution extensively to analyse and select mutual funds for their clients.
Sharad Singh is chief executive officer, Valuefy Solutions Pvt. Ltd.