Home / Peter Elston’s Investment Letter – Issue 31: December 2017

Peter Elston’s Investment Letter – Issue 31: December 2017

A new, simple, comprehensive measure of fund ‘active-ness’

In the spirit of Christmas, I present in this final letter of the year some truly psychedelic charts!

2017 saw the debate (ok, it’s a war) between active and passive intensify further, with flows into passive funds, ETFs and smart beta products reaching unprecedented levels. In this letter I put forward a suggestion for a comprehensive but simple measure of the ‘activeness’ of a fund. This I hope might provide an easy way to distinguish between ‘good active’ and ‘bad active’ and thus determine which active funds stack up well against their passive equivalents.


The ‘activeness’ of an active fund tends to get measured in various ways. It has also at times been ill defined, and by those who should know better. Nobel laureate William Sharpe said, “An active investor is one who is not passive. His or her portfolio will differ from that of the passive managers at some or all times. Because active managers usually act on perception of mispricing, and because such misperceptions change relatively frequently, such managers tend to trade fairly frequently – hence the term ‘active’”. Trade frequently? I guess he’d never heard of Warren Buffett and the many other great long-term investors.

Yale CIO David Swensen on the other hand got it right. He wrote that, “There is no way to succeed in active management if you try to control for benchmark risk. You must be willing to deviate from the benchmark if you want to earn returns commensurate with the risk of owning equities. And you must be patient.”

Here then in Swensen’s simple words are the two key requirements for active management: deviating from the benchmark and patience. Put another way, good actively managed funds must be concentrated and long term.

This proposition is both logical and empirically well supported (I will not elaborate here but I have written about both concentration and time horizon in relation to investment returns on previous occasions). However, I have yet to see a study either by an academic or practitioner that combines both portfolio concentration and portfolio time horizon into one score or measure. The two always seemed to be considered separately.

And that may be because many do not see the link between concentration and time horizon. I suggest there is a clear, logical link between the two and also that there is a way to measure both at the same time.

Chart 1 below is a so-called soil chart, depicting the positioning over time of an actual investment trust (psychedelic man!) Note that totals in excess of 100% imply net gearing, while totals less than 100% imply net cash. The large mauve band represents the introduction of a fund to gain exposure to a particular country. The rest are individual equities.

Chart 1: holding weights over time of an actual investment trust

Chart 1

It should be clear that the portfolio concentration of the fund can be understood in terms of the width of the lines while portfolio time horizon in terms of the length of the lines. The point is that both concentration and time horizon measure the exposure of a fund to a particular holding, one in terms of ‘how long’ and the other in terms of ‘how big’. Being active is not just about being high conviction but also about how long you hold something.

Both concentration and time horizon can be measured at the same time by considering the area of each line, then calculating the average line area. The area of each line would be the length of the line multiplied by the average width. All the data required for this calculation is readily available in the chart data, which is available within our annual reports.

Funds with a low average line area are thus lowly concentrated, or short-term, or both, while those with a high average are highly concentrated, long term, or both.

The units for this measurement would be % times ‘time’ since the x-axis is ‘time’ while the y-axis is ‘percentage’. A standard unit could be ‘% months’ (if data is monthly) or ‘% quarters’ etc. The higher the score, the more active the fund.

The charts below are highly stylised representations of funds that would fit into various categories, starting with the two extremes (low concentration/short term and high concentration/long term).

Chart 2: Low concentration/short term

Chart 2

Chart 3: Ultra high concentration/very long term

Chart 3

Chart 4: Very high concentration/very long term

Chart 4

Chart 5: Low concentration/very long term

Chart 5

Chart 6: Ultra high concentration/short term

Chart 6

Chart 7: Very high concentration/short term

Chart 7

Chart 8: Very high concentration/medium term

Chart 8

Chart 9 Very high concentration/long term

Chart 9

Chart 10: High concentration/long term

Chart 10

Now, I bet you never realised that funds could be so beautiful!
More seriously, we can calculate the average area of each “line” in ‘% quarters’ as per the below table.

Table 1: Combining holding sizes and holding periods for 9 hypothetical funds

Table 1

Interestingly, there are three configurations that deliver a score of 100 (charts 5, 6 and 8). Clearly, the fund that has just one holding but changes it every quarter should not be  awarded the same score as a fund that more sensibly has 10 holdings and changes them on average every 10 quarters (2 and a half years). The same goes for chart 3.

In other words, there must be an optimal holding size which should be rewarded more than holding sizes that are either bigger or smaller. This can be achieved by normalisation of the data.

As for average holding period, let us propose that the optimal average holding period is 20 quarters (or 5 years).

So, if we can agree that chart 10 has the optimal mix of concentration and holding period (academic evidence supports such a suggestion), this then is the chart that should receive the highest aggregate score after data normalisation.

Table 2 below sets out scores for each of the nine funds after data normalisation (I am happy to share the details of the process of normalisation of data upon request, suffice to say it is purely systematic).

Table 2: Active-ness scores after data normalisation

Table 2

The two funds that only have one holding now score very lowly which has to be correct. The next lowest scores are the funds that have very high turnover. Chart 10 has the highest score of 9 which is also consistent. Charts 8 and 9 are not too far behind which feels about right.

There is no doubt that a trained statistician could do a better job of normalising the data and also of interpreting academic evidence with respect to the optimal holding sizes and holding periods that have tended to produce the best performance.

However, applying the above methodology to the actual investment trust data cited earlier provides an interesting insight. Average holding size is 1.7% and average holding period is 14.5 quarters. This generates a high “activeness” score of 8.7 which is thoroughly appropriate. The fund in question is Aberdeen New Dawn, and during the period in question it returned 1918% (1) compared with its benchmark, the MSCI AC Asia Pacific ex Japan index, which returned 1127%.

If there is a trained statistician out there who would like to collaborate on turning this into a more formal research paper, I would be delighted. The objective of course would be to determine if there is a correlation, presumably positive, between the activeness score and investment performance. If there is, that I think would certainly be interesting.

Happy Christmas everyone!

Macro and Markets Monthly


From an economic perspective, November was in many respects a repeat of October. On the whole, macro data supported our belief that economies in general are making good progress at the moment, in both the developed and the emerging world.

In the US, the ADP Employment Change (2), which precedes the official government numbers by a day or two, came in at 235,000. This was both stronger than expected and the previous month, though the latter was revised down slightly. As for the government numbers, the change in private payrolls was a strong 252,000 although expectations were for 302,000. The previous month however was revised up from a fall of 40,000 to an increase of 15,000, meaning that the amalgamated two-month number came in bang in line with expectations.

The unemployment rate declined further to 4.1% from 4.2% in October. Some of this decline will have been the result of the fall in the participation rate from 63.1% to 62.7%, meaning that some without jobs stopped looking, thus pushing down the number of unemployed. This effect may have shown up more in the underemployment rate, which fell from 8.3% to 7.9%. The substantial fall in the participation rate over the last few years has been one of the interesting features of this economic cycle. Part of this fall will have been due to the US’s aging population but not all. The prospect of disaffected workers returning to the workforce at some point, thus pushing up the participation rate, provides hope that this cycle has further to run without putting undue pressure on wages and thus the Fed to raise interest rates more quickly than is currently anticipated.

On the inflation front, core inflation in the US nudged up slightly, from 1.7% yoy to 1.8% yoy. This is a good thing, as some had worried that the decline earlier in the year was a sign of trouble to come. The Fed has said that they are still not sure why core inflation dipped, but it is possible that it was the delayed effect of the strong US dollar. Nevertheless, it is always a relief when a central bank can breathe a sigh of relief. The stronger employment conditions are not yet feeding through to wages. Average hourly earnings growth in October fell from 2.9% yoy to 2.4% yoy, while real average hourly earnings fell from 0.7% yoy to 0.4% yoy. This may be due to the fact that productivity growth is picking up, with non-farm productivity in the third quarter rising by 3.0% compared with 1.5% in the previous quarter. As with the participation rate, further gains in productivity would enable the cycle to progress further without inflation pressures intensifying.

In the UK, the Bank of England raised its base rate as expected from 0.25% to 0.5%. It thus joins the US as the only two major developed country central banks to increase interest rates this cycle. However, the case for raising interest rates in the UK appeared to be more about dealing with inflation pressures that were the result of the weak currency rather than a strong economy. That said, the economy did make progress during the month, with purchasing manager indices all much stronger than expected, whether in construction, manufacturing or services. The unemployment rate held steady at 4.3% while, encouragingly, core inflation came in below expectations at 2.7%.

Elsewhere, key data in Japan and Europe gave no cause for concern. The unemployment rate in Europe fell from 8.9% to 8.8%, and core inflation held steady at 0.9% yoy. As for Japan, joblessness held steady at 2.8% while CPI ex Fresh Food rose slightly from 0.7% to 0.8%.

There were further encouraging signs that growth in the emerging world has become healthier. For example, purchasing manager indices in China were both strong and stronger than expected, with a similar pattern in India.

As mentioned last month, the reason for focusing on employment and inflation is that these are the key indicators that central banks target when deciding on monetary policy. Thus, in November, there was nothing to suggest central banks needed to reconsider the monetary policy roadmaps that they had previously laid out.

As for financial markets, equity markets generally rose in October, though there was a bit of weakness in the UK and Europe which, at least in the case of Europe, can be put down to previous strength.


We continue to believe the global economy as a whole is moving from recovery phase to expansion phase (some like the US are firmly in the latter while others such as the Eurozone are still in the former). Thus we expect equity market returns to continue to fall slightly, but remain positive for the two or so years up to the point at which monetary policy becomes much tighter and when economies are likely to start peaking.

Inflation we think will continue to rise and we thus remain negative on safe haven bonds which anyway are very expensive in light of low or negative real yields.

(1) Bloomberg

(2) A report that measures levels of non-farm private employment based on payroll data from over half of ADP’s U.S. business clients. The data represents about 24 million employees from all 19 of the major North American Industrial Classification (NAICS) private industrial sectors.

Current fund targets

The target weights in the table below are where funds should be positioned currently. Actual positions may deviate slightly from these target weights as a result of market movements or ongoing trades for example.

Table 3: Current fund tactical asset allocation (TAA) target weights as of 30th November 2017 (prior month’s targets in brackets)

(from 18 December 2017 the funds names will change to LF Seneca Diversified Income Fund & LF Seneca Diversified Growth Fund)

Table 3


  • Economic news was generally good during the month, with employment and inflation conditions improving in key jurisdictions.
  • The Bank of England raised its base rate from 0.25% to 0.5% as expected, though this was as much a response to high inflation
    induced by the weak currency as to broad economic strength
  • Conviviality was exited on valuation grounds and because we had some concerns regarding two accounting errors. Having
    yielded close to 6% back in January, the yield had fallen closer to 3% when we exited following strong performance
  • A good update from Bovis Homes in which net cash was guided to be higher by the year end than previously forecast,
    supporting substantial shareholder returns by way of special dividends.
  • Due to the successful deployment of initial capital proceeds through 2017 by Civitas Social Housing REIT, we participated in the
    C share offer.
  • Fair Oaks Income Fund announced further equity issuance in order to finance additional investments into new Collaterialised
    Loan Obligations where they are taking a controlling equity stake.


  • Equity target reduced from 57% to 55%. This was related to decision to exit one of our UK companies (see below) but is
    consistent with gradual reduction in risk as business cycle matures.
  • After good performance across the Fund’s Japanese holdings, reductions were made in order to bring weights back towards
    target size


  • Equity target reduced from 38% to 37%. This was related to decision to exit one of our UK companies (see below) but is
    consistent with gradual reduction in risk as business cycle matures.
  • Schroder Asian Income Maximiser Fund was added to in order to bring the position to target weight
  • Small additions to three existing holdings to maintain weightings following cash inflows early in the month


  • Equity target reduced from 58% to 57%. This was related to decision to exit one of our UK companies (see below) but is
    consistent with gradual reduction in risk as business cycle matures.
  • Schroder Asian Income Maximiser Fund was added to in order to bring the position to target weight
  • Goodhart Michinori Japan Equity Fund was exited, with proceeds reinvested into the CC Japan Income & Growth Trust, an
    existing holding which is delivering a growing dividend to shareholders
  • Small additions to Royal London Short Duration Global High Yield Bond Fund and Templeton EM Bond Fund to invest share
    issuance proceeds

Download this investment letter as a PDF

Important Information

Past performance is not a guide to future returns. The value of investments and any income may fluctuate and investors may not get back the full amount invested. This document is provided for the purpose of information only and if you are unsure of the suitability of these investments you should take independent advice.

The views expressed are those of Peter Elston at the time of writing and are subject to change without notice. They are not necessarily the views of Seneca and do not constitute investment advice. Whilst Seneca has used all reasonable efforts to ensure the accuracy of the information contained in this communication, we cannot guarantee the reliability, completeness or accuracy of the content.

LF Seneca Funds
These funds may experience high volatility due to the composition of the portfolio or the portfolio management techniques used. Before investing you must read the key investor information document (KIID) as it contains important information regarding the funds, including charges, tax and fund specific risk warnings and will form the basis of any investment. The prospectus, KIID and application forms are available from Link Fund Solutions, the Authorised Corporate Director of the funds (0345 608 1497).

Seneca Global Income & Growth Trust plc
Before investing you should read the latest Annual Report for details of the principle risks and information on the trust fees and expenses. Net Asset Value (NAV) performance may not be linked to share price performance, and shareholders could realise returns that are lower or higher in performance. The annual investment management charge and other charges are deducted from income and capital.

Seneca Investment Managers Limited is the Investment Manager of the Funds (0151 906 2450) and is authorised and regulated by the Financial Conduct Authority and is registered in England No. 4325961 with its registered office at Tenth Floor, Horton House, Exchange Flags, Liverpool, L2 3YL. FP17/490