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Monthly Archives: May 2015

Reverse tax lotteries — taxes where a basic parameter (the amount, the taxpayer) is chosen randomly — are an interesting concept which may have a wealth of applications. Maybe there’s a series coming here.

Today’s instalment is about using taxes as a regulatory device to control for financial concentration and increase risk awareness and management among market players.

Financial products are not aircrafts

One problem with the mainline approach to financial regulation is that it’s aimed at trying to find fragile features of the financial system, and then regulate around the fragility to make it impossible to happen. This is basically the aircraft industry’s approach to safety. This may not be such a good idea in finance because financial failure are as such not as catastrophic as a plane crash. Finance is about bookkeeping units of future resource allocation power, where failure causes more subtle problems — sometimes not even system-level negative — than a plane crash. Secondly in finance players are often trying to work around the safety procedures instead of consenting to the safety imperative as pilots and maintenance technicians generally do.

Regular failure

What best to teach people to cope with failure than having it happen frequently enough for it to become a manageable habit? Incandescent light bulbs fail frequently, so cars have two headlights, so they can keep operating at night should the predictable failure of one light bulb occur. The statistical chance of both lights failing is small enough, that one can take the small residual risk of having a complete failure between the failure of one lamp and its replacement.

In finance the solution to such issues is diversification. If one’s savings are split between 100 issuers, the failure of one of them is a non-event. Unfortunately, some classes of financial instruments, e.g. the quality end of fixed income, fail so rarely that people often forget they can fail, which in itself is a contributory factor to them failing en masse during systemic crisis.

Probabilistic bankruptcy

So, a way to remind people of that failure risk is to have forced bankruptcies: have the regulator pick some random issuers every so often, and simulate a bankruptcy, by taking all their assets and closing them down. Applied to equity for instance, this could be done by expropriating current shareholders of the randomly chosen company, and redistributing new shares via an IPO whose proceeds are tax revenue.

It’s a nice way to add some tax revenue as well, which could substitute some of the existing non-probabilistic taxation, of fund new public goods as desired. Alternatively this can be do in a tax neutral way, by redistributing the proceeds of the levy to the remaining players.

This tax could be applied to all asset classes, e.g. just pick 1% of all available financial products every year and fail them. For risky investments with an intrinsically high failure rate it will just be barely noticeable noise, and it spares the regulator the arduous and hazardous task of having to classify instruments.

In addition to reminding people of bankruptcy risk, by effectively introducing a floor to the level of total loss risk, it is a strong disincentive against having large single points of failure as nobody will want to put too much in any single basket.

Downsides

Some potential problems with the measure I can think of: this can’t be applied to brokerage-level institutions unless end consumers of financial service are required to diversify brokerages or bank accounts — although maybe that is desirable! Exempt brokerages¬† could help my making it easy to split savings or investement into diversified portfolios (e.g. replacing single-point of failure ETFs with auto-rebalanced direct holdings of the underlyings).

It does not remove the risk of systemic misinvestment into asset classes represented by many instruments, e.g. if wouldn’t prevent sector bubbles. Still the higher background level of failure may have a slight moderating effect on the psychology of exuberance.

As with any new tax, the argument would be made in any jurisdiction introducing it first that all the money would leave. I see no reason why it should be the case at a reasonable level, the tax load is not in essence that different from say stamp duty style taxes. Indeed in the UK it could replace stamp duty and be levied at the same rate of 0.5% (but here of instruments’ market cap rather than trading volumes).

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London holdings up to date

I’ve belatedly updated the Obliquity London portfolio page in the same style as the other (holdings, reweightings, disposals tables) with up to date data, which shows the full history of the portfiolio. Most of the slow movements have been reported in blog posts but the page wasn’t up to date pending an ever procrastinated automation. No automated process yet but this is backed by a little toolset I’ve been building in numeric Python (pandas) which should make future reporting easier.

IRR benchmark units reporting

The concept I’m playing with at the moment is using IRR (Internal Rate of Return) on cash flows expressed in benchmark units. That is for any given position I extract all the cash flows (trades, dividends and corporate actions), which I get from my broker in sterling, and then convert them in accumulating units of a benchmark ETF, as if it was a currency — remember that in essence any tradable paper is a currency. So each sterling flow is translated to an ETF units flow at the price (“exchange rate”) on the day of the cash flow. This shows the balance someone doing nominal accounting in benchmark units, or equivalently using the benchmark as their “cash” asset, would see.

This makes relative performance very clear: the sign of the nominal PNL (portfolio value change) tellls you if you have out- or underperformed the index. Basically if you had funded every buy by selling units of the benchmark, and bought them back on sales, it tells you if you’d have more or less units following trading than passively sitting on the benchmark units.

The use of the IRR also implies a normalisation of time effects, to capture that a N% change over 2 years is not the same as N% over 2 months, which is hard to see in classical nominal PnL reporting.

Stamps IRR charts

So here are a few of the result for the small cap London Stamps portfolio, valued as of 2015-05-08. This is early software so subject to errors and bugs, the numbers have merely passed a plausibility test.

The benchmark is iShares MSCI UK Small caps (CUKS) which is a good substitute economically (I’d happily buy it as a replacement allocation if I stopped playing stock picker in this segment) though a relatively poor short term benchmark technically. The reasons for that is that it uses a worldwide definition of small caps, which basically in the UK market captures the bottom of the FTSE250 — which are traditionally viewed as midcaps in the UK markets — and the top end of the local small caps section. So the average market capitalisation is significantly higher than my mostly AIM oddballs stock picks. A pure AIM index index wouldn’t be a good benchmark either as it would have a would bunch of junior resources stocks and overseas scams that I don’t touch, and I would never buy an AIM index as an economic substitute. The MSCI methodology is pretty good at excluding the darker corners of the market, so it is a valid benchmark in sector and industry terms.

Predictably the portfolio as a whole has underperformed by almost 10% since inception in money weighted terms. We’ll blame midcaps doing well while really small caps had a lacklustre year and say the jury is still out on my stamp collector skills or lack thereof.

Now, let’s do some digging down. Here is the IRR of each stock since inception, including closed positions, as a monthly return in benchmark units.

London Stamps IRR Ranks 2015-05-08

This is not very precise chart because the more recent positions produce outlier IRRs — the computation makes less sense in the very short terms. This excludes positions younger than 100 days (only AMD at the moment).

Other than that no surprises really, and apart from the GW Pharma pot bubble the next winners are tech companies that got taken over (indeed I held them for relatively short periods).

Now let’s watch our underperformance by plotting an histogram of these same returns (with AMD back in).

London Stamps IRR histogram 2015-05-08

So we’ve got the reasonable level of symmetry, as predicted by theory, the problem is only that zero is on the wrong side of the chart for the time being. It’ll shift if the performance reverses.

A thing to note in these charts is that the average monthly moves are not big, mostly within the -5/+5% range, which implies that with the typical spreads in small and micro-caps, long holding periods are essential. This is well known but nice to have another confirmation. Anyone flipping their portfolio every couple of months, in addition to having trouble to find alpha, would get trounced by transaction costs. It should also mean that long term returns should be better, so let’s do a little trend check by plotting our returns against holding period (remember this includes closed positions):

London Stamps IRR Age plot 2015-05-08

That one looks good. Patience pays so far.

That’s all for IRR analysis for today. Let’s finish with a little check we don’t have any undue overweight, with a simple visual check of portfolio weights for current holdings:

London Stamps weights 2015-05-08

So far so good.