Update: There are some concerns about the reliability or our reading of the data source we’ve used to compile this feature, which it’s being suggested does not always take account of dividends in its returns. We have modified this copy to reflect this, and will investigate further.

Despite claims that the Total Expense Ratio (TER)1 is the best predictor of returns from passive index funds, it often only does half a job when pinpointing the real costs of a tracker.

Just as nature selects for big brains, sharp teeth, and the ability to waggle your dangly bits in an amusing fashion, smart passive investors look for low tracking error as a highly desirable trait when choosing the fittest index funds in the investment jungle.

But reliable tracking error data is devilishly hard to find. And summoning the will to trawl the internet can be harder still for investors of the couch potato kind.

Help is at hand

Never fear, the alarm has been sounded. Monevator’s sleeper agents have once again been activated and prodded into action to fill the yawning gaps on the ‘to do’ lists of Britain’s passive investors.

Our plan this time is to host a regular performance review of the main FTSE All Share trackers versus their index.

Hopefully this survey will:

• Highlight that TER or the Ongoing Charge Figure (OCF) isn’t automatically the best guide to your fund’s peer group performance.

• Expose shoddy tracker construction – we want to find out which funds are more costly than they look.

• Demonstrate how you can build up a better picture of the available index trackers with just a little extra effort.

Tracking error comparison table

The following table shows the returns from a variety of All Share index tracker funds, plus the index itself, marked in blue.

I’ve ranked the entries by order of their 3-year returns. Funds placed higher than the All Share index returned slightly more than it over three years. Funds placed below it lagged the returns from the index over that period.

Note: The db X-trackers data may not be representative — we’re investigating. Annualised performance figures

The tracking error calculation is simple. Just subtract the fund’s performance figure from the return of the index. (Some call this tracking difference).

For example, the tracking error figure for the M&G Index Tracker A fund over one year is:

Tracking error = (15.9-15.4) = 0.5%

The science bit

There are a few technicalities to note if you want a fully rounded picture of what I’m doing to get my table. (This section is eminently skippable if you just want to get straight to the point).

• The performance figures shown are annualised returns. They are brought to you by Trustnet’s excellent charting tool, which also shows discrete annual returns and cumulative returns.

• The OCF is the explicit cost of owning the fund now. The tracking error reveals the total cost including hidden charges such as turnover, taxes, and index replication deviancy.

• The OCF will have been higher for many funds in previous years.

• All funds are index trackers with the exception of the Dimensional Fund Advisors’ (DFA) UK Core Equity. It is formulated according to Fama and French’s special preparation H and is designed for passive investors.

• Most of the funds are accumulation flavour index funds with the exception of the db X-tracker ETF, and the Edinburgh investment trust tracker.

• All funds track the FTSE All Share index with the exception of the DFA fund and Royal London FTSE 350 tracker. There is a Royal London FTSE All Share fund, but Trustnet’s charting tool refused to recognise it. The 350 fund is very similar.

• Certain funds were excluded because they haven’t collected at least three years of data, namely: the BlackRock CIF UK Equity Tracker, new clean class funds, the SPDR FTSE UK All Share ETF, and SWIP Foundation Growth B.

• Chart options chosen: income reinvested and offer-to-bid. If you take advantage of Trustnet’s tool, beware the quirk: every time I added a fund, the numbers for the index went loopy. Just change your radio button selection to fix it e.g. % return to £ return and back again.

Analysis

The most important point this table makes is that time is a great leveller. The chart-topping DFA fund shoots the lights out over one year, but over five it’s settling back into the pack. Which is especially important to know as you have to pay expensive advisor fees to access DFA funds.

The same goes for the Edinburgh Tracker Trust that’s in a photo-finish with the index over five years but is deeply average over ten. If this fund was on my hotlist then my next step would be to find out whether its TER had been slashed, which may account for its recent rocketry, or whether there is some peculiarity in its index replication recipe.

On the face of it the stark underperformer amongst this lot is the db-X tracker ETF, though its OCF is reasonably competitive. (Update: This may be due to inaccurate or misread source data. We’re looking into this).

The Virgin tracker looks nowhere near as bad as its market-lagging OCF would suggest. Fidelity has a headline grabbing 0.3% charge but has somehow conspired to underperform Virgin’s 1% fund over the last three years.

Over ten years the best-performing fund we have data for is the M&G Index Tracker. Although, in the last three years it’s fallen behind the HSBC fund which aggressively cut its price in 2009 to combat Vanguard.

Intriguingly, Vanguard is flattered by a tracking error comparison because it charges a 0.5% initial fee to cover stamp duty. That means stamp duty doesn’t swell Vanguard’s tracking error whereas the other funds excrete the share-dealing tax directly via this route.

You can account for all these nuances by squaring up your favourite funds against each other using a fund cost comparison calculator. Use your tracking error figures as the annual charge to find out the real cost of the fund.

Perfect is the enemy of good

Over 10 years I wouldn’t worry about the differences between the funds in the table we have data for. The gap between top and bottom is a piffling 0.3%.

But I’d want to avoid the gulf that’s opened up between a very poorly performing fund and the top funds over five years. I’d worry that a fund that can miss its benchmark by over 4% isn’t doing its job properly, and would dig deeper into the data to try to find an explanation.

Avoiding a straggly bottom shouldn’t find its mirror in an obsession to own the top. Don’t waste time hunting down the very best fund and then lash yourself with the cat if it doesn’t ‘win’ one year.

Look for a fund that habitually hugs its index tight, has a low OCF, and check that its tracking error is reasonably low and consistent with its peer group over as many years as possible. That should do you nicely.

Take it steady,

The Accumulator

1. Or OCF to use the contemporary term [↩]
2. + 0.5% initial charge [↩]
3. + 0.5% initial charge [↩]

Good reads from around the Web.

When I was growing up, Margaret Thatcher and Ronald Reagan championed the power of capitalism to change the world.

There was a clear alternative back then – making tractors in some Soviet gulag wearing ill-fitting overalls while being lorded over by sanctified hypocrites who hunted bears from private lodges on the Kamchatka peninsula before stuffing their faces with Beluga caviar.

I was happy to sides with Thatcher and Reagan over a Labour party that risked taking us one step in that direction.

But by the 1990s, the communist threat had gone. Plenty of us, including me, indulged our more socialist side – both in our thinking, and at the ballot box. Dotcom moguls made money almost as a by-product of their desire to change the world, and before long even Bill Gates had pledged to give away his fortune.

Now, today, we’re shaking off the credit crisis, inequality is rising out of control, and old arguments of Left Vs Right are being reborn in new guises.

So far I’ve come down on the side of the 99%. I think extremes of wealth need curbing – especially because the threat of the Siberian tractor factory is no longer there to encourage the richest to keep everyone on side.

But I don’t think we should do that simply by taxing and redistributing more money. I think the incentives can begin to act in perverse ways, locking some of the poor in dependency and dead-end thinking.

Instead I think we should boost pre-university training, give massive tax breaks to companies for taking on young and unskilled workers, create more start-up funds for new entrepreneurs, raise the income tax personal allowance to at least £10,000, think of innovative new ways to bring childcare to single mothers who want to work, and much more.

What did a rich man ever do for you?

In the midst of this debate, it’s refreshing to watch a video like the following (via Objective Wealth) that reminds me of the ultra-Libertarian other side.

It’s not often you hear Bill Gates chastised for giving billions to charity:

The guy is clearly extreme in his views (I’m sure his moguls are comforted by their billions when society overlooks their achievements) but maybe you have to be to get a view like this across. I’ve just embedded the video, haven’t I?

So what do you think? Is it time to bring back Greed is Good?

It’s hard to stomach the thought, given what those who never surrendered money as the ultimate scorecard – the bankers – did under that flag in the last decade.

[continue reading…]

It’s easy for passive investors to get wound up by the arrival of cheaper funds. We’re all about cost management, but should we leap like a lizard every time a new fund turns up with a slimmer Ongoing Charge Figure (OCF)?

We’ve previously looked at how to calculate whether the cost savings are worth the hassle of switching funds. But an even bigger consideration is the chances of wild and dangerous Mr Market moving against us.

If you trade from one index fund to another then you’re likely to spend a significant amount of time out of the market due to the way the system works.

If you swap between two index funds that track the same index, this delay means:

• You will lose if the market – and so your new fund – rises in value between trades. The money you raised from selling your old fund will buy fewer units in the new fund.

• You will gain if the market – and so your old fund’s price – drops after you sell. Now the money you cashed out of your old fund buys more of the new fund’s cheaper units.

How long will you be out the market?

This depends on your chosen platform. Here’s TD Direct’s turnaround schedule:

• Submit your sell order in time to meet the fund’s valuation point that day. That’s anytime from 9.30am – 12pm, depending on your fund provider. Your old fund is flogged and you will receive cash in line with that day’s valuation.

• Orders that come in too late will be executed the following day.

• Now we’re in business, no? No. It takes up to four days for the fund to settle. In other words, it’ll be four days before the money goes all the way down the chain from the buyer to you. If you sold on Monday, it’s now Friday.

• Submit your buy order. If you missed the Friday morning deadline then your trade won’t go through until Monday. You’re out of the market for a week. Empires have fallen in less time.

Happily the dance doesn’t have to take that long. If you ring up TD Direct on the second day after the sale, it can tell you how much you raked in and will buy the next fund. Move quickly and you could get your buy order off that day. Your time out the market is reduced to two days.

Check with your broker for its own timetable.

Worst case scenario

Popping champagne corks at City trading desks are a fearful sign for us when we’re switching funds. A good day for the markets is a bad day for us if we’re not in the game.

The FTSE 100’s best day ever was a 9.84% rise on 24 November 2008. The second best day saw an 8.84% boost. I’ll use these movements to model our worst case two-day scenario: where the first rise was followed by the second. In reality that didn’t happen and no fund-hopping passive investor will have had a comeuppance quite this bad. Yet.

You can simulate these movements well enough by using Candid Money’s investment charges impact calculator to work out the effect of asymmetrical costs on each fund.

We’ll take a look at the impact of such an adverse market movement using the Salami Slicer example from our previous fund switching post. In this instance, our new fund is only a sliver cheaper than the old – it’s OCF is 0.2% versus 0.3%.

In this example, we have £1o,000 after we cashed out of the first fund. While we’re waiting for our money to go into the new fund, the market rises by that nightmare 9.84% on day one, followed by a “Why me!?” 8.84% on day two.

Our old fund would have been worth £11,954.991 if we’d just left well alone. Instead, we have a paltry £10,000 to put into the new fund, which has experienced the same accursed good fortune over the two days.

Still, we’ve got 20 years of cheaper OCFs to look forward to in the new fund. Let’s see what the trade-off has brought us:

Old fund OCF 0.3%
Fund worth £11,954.99

New fund OCF 0.2%
Fund worth £10,000

Future contributions £100 a month
Investment horizon 20 years
Annual return 6%

Fund value after 20 years of cost savings:

Old fund = £80,281
New fund = £75,432

You lose £4,849 or -6.04%.

The market swing against us – in just those two days – is something we never recovered from in this Doomsday scenario. That’s despite 20 years laughing it up with a slightly cheaper fund.

In contrast, an investor with all the dynamism of a cabbage ended up nearly £5,000 better off than us, because they did nothing. Our move proved to be the financial equivalent of blasting our own feet off.

So much for knowing all about the funky new funds.

Average case scenario

Okay, so far so ill-advised, but that was an extreme case. What might the markets do to us on a more average day?

To give us a rough idea2, I’ve had a grapple with daily pricing data for the FTSE All-Share index. Thanks Yahoo Finance!

Daily prices are available from 4 January 2000 to 11 January 2013, which is long enough for our purposes.

The average daily rise in the market was 0.658% during this period. The average daily fall was -0.603% and if you average out the gains and losses then the market moves a pitiful 0.004% per day.

Back to our example. We sold our fund for £1o,000, but this time the market carried on rising without us at 0.658% per day for two days before we were able to buy back in.

So our old fund was worth £10,1323 by the time we bought £10,000 worth of the new fund.

Old fund OCF 0.3%
Fund worth £10,132 (after two days average gain)

New fund OCF 0.2%
Fund worth £10,000 (no gain while in cash)

Future contributions £100 a month
Investment horizon 20 years
Annual return 6%

Fund worth after 20 years cost savings:

Old fund = £74,757
New fund = £75,432

You gain £675 or 0.9%

Well, at least we’re up. After 20 years baking our investment pie with a lower OCF, we cash out slightly ahead.

In fact, after merely 10 years we’re up £19. Sound the vuvuzelas.

Whether such a (potential) gain is worth the risk and effort depends on how devil-may-care you are, how long you invest for, the actual difference in fund costs, how much you invest, and the return you get.

It’s pretty obvious though that there’s no need to sweat small stuff like this. Especially as keeping things simple is the essence of passive investing.

Hey, wouldn’t we profit more if the market fell?

Okay, calm down Gordon Gecko. To round out the picture, you’d indeed be £1,500 up if the market took an average dive (-0.603%) on both days.

Oh, and you’d be a smidge over £1,000 up if you averaged out the daily gains and losses to creep ahead 0.004% each day.

Intriguingly there was a 51.7% chance of a rise on any given day and a 47.8% chance of a fall. The market stayed flat 0.5% of the time.

Exchange Traded Fund (ETF) scenario

The ability to trade ETFs all day long makes them less risky than index funds when it comes to a quick switcheroo. You’ll lose a bit on the bid-offer spread, you’ll pay a dealing fee to buy and sell, but you need only be out of the market for a few minutes thanks to real-time online trading.

In the example below, I assume a bid-offer spread of 0.1% between my two funds. This is the cost of having to sell shares for slightly less than they’re worth and buy for slightly more than they’re worth so that the men in the middle can make a living. Think buying and selling foreign currency when you go abroad.

Our £10,000 holding is whittled down to £9,990.02 after deducting the cost of this 0.1% spread. That becomes £9,980.02 after subtracting £2o of dealing fees (one sell and one buy order).

I’m not going to worry about any change in price between the two trades. It would amount to pennies either way in a reasonably liquid ETF, assuming we’re not in the middle of a flash crash.

Well worth making the change, even considering the trading costs. (We’d only be a bit further ahead at £1,075 after 20 years if ETF trading costs were zero).

I’d definitely be more sanguine about switching liquid ETFs with tight-bid offer spreads, assuming I didn’t mind the bother and that I was trading at least £2,000 a pop. Remember ETF dealing fees can take big bites out of small trades.

Keep It Simple, Stupid

My two posts on this subject have definitely failed the KISS test.

The first post demonstrated that it’s definitely worth the trouble to switch from high-fee active funds to reasonably priced index trackers, but we knew that anyway.

The benefits of switching out of a tracker with a sub 0.5% OCF are far more debatable and taper away the less money you have, as well as exposing you to the risk of the market moving against you.

There quickly comes a point where jumping ship isn’t worth worrying about.

That said, even if two trackers seem similar in cost, it’s always worth comparing their tracking error. That’s the true measure of an index tracker’s cost and can betray some hidden truths that don’t show up in the OCF.

Take it steady,

The Accumulator

1. 10,000 x 1.0984 x 1.0884. [↩]
2. You could decide to look at median average moves instead or to work with standard deviations or similar. If you do then please share your findings in the comments! I think keeping it simple works well enough here. [↩]
3. 10,000 x 1.00658 x 1.00658 [↩]