Tuesday, 11 April 2017

Investment and trading performance - year three

It's now almost three and a half years since I got my last pay cheque and started on my new career as a speculator (also sometime writer, and itinerant consultant), and exactly three years since I started running my fully automated futures trading system, for which my accounting period is the UK tax year ending on 5th April. Which means it's the third in this trilogy of which the first two instalments were:


Sharp eyed readers will notice a subtle difference between this and the previous posts - as well as looking at my futures trading I'll also be considering the performance of my wider portfolios. One of the reasons for doing this is that (spoiler alert) my futures trading hasn't done that well this year - but since the point of a managed futures portfolio is to provide diversification that should be seen in the context of what the wider market has done. Another reason is that I'm currently finalising a new book on building investment portfolios; so I thought it would be useful for you to see how I practice what I preach.

As well as looking at performance I'll also analyse my risk, and explain how I'm going to rebalance the 'investment' parts of my portfolio (the 'trading' part is fully automated).

My investments

In simple terms this is what my portfolio looks like:

  • An interactive brokers account containing:
    • My futures trading positions
    • An equity futures hedge
    • A mixture of UK stocks and equity ETFs against which the hedge is constructed
    • Cash margin
  • Various other brokerage accounts containing:
    • UK stocks
    • ETFs

The reason for all the complexity in my IB account is that when I started trading I didn't have sufficient cash to fund my futures trading; I couldn't sell investments to realise cash as this would have resulted in a lumpy capital gains tax bill; hence I dropped a dollop of stocks and ETFs into the account which I could borrow against for margin and to meet any losses.  But I wanted the performance of my futures account to be as 'pure' as possible, so I decided to hedge out the other assets by shorting equity futures against them. 

Broadly speaking I prefer to group my investments into the following sub-portfolios before I analyse them:

  1. A fully automated futures trading system. This requires cash for margin, and has an absolute return or peer benchmark.
  2. An equity futures hedge, constructed to hedge out the non futures assets I hold in my trading account. This has an absolute return benchmark and is low risk.
  3. A diversified portfolio of ETFs across stocks and bonds (with a small allocation to other alternatives). This is gradually mechanically rebalanced on an annual basis. Given my current allocation an appropriate benchmark would be a classic 60:40 fund like this one.
  4. A portfolio of large and mid cap individual UK stocks; traded (very slowly) using mechanical rules around dividend yield (which you'll find in my new book). Benchmark FTSE 350.
I'm going to look at these in reverse order, so we have the wider investment landscape covered before we discuss my dire futures trading.

UK stocks

My portfolio of UK stocks is chosen to give me broad sector exposure, with a tilt towards higher dividend yielders. This is partly because dividend is a risk factor which should earn an additional risk premium if you don't mind wearing the risk, but also because dividend income is a significant contributor to meeting our household expenses.

In terms of numbers this is what the raw performance looks like:

Dividends earned: 6.8%
Mark to market: 17.9%

Total return: 24.7%

Versus a total return benchmark (the FTSE 350 of large and mid cap stocks) which earned 23.5% in the same period, that's respectable but by no means spectacular. However these numbers understate the true performance, because I took a large chunk of money out of this portfolio last year and (as part of my gradual readjustment of my investments to reduce my exposure to UK equities, which three years ago stood at 69% of all equities! 59% of my entire portfolio; far too high for a properly diversified portfolio). 

To deal with this we need to calculate the internal rate of return (IRR), for which I used the XIRR function in <insert name of favourite spreadsheet package here>.  

Portfolio IRR: 29.2%
FTSE 350 benchmark IRR: 22.7%

Better. Of the 17 stocks I owned at some point during the year, 9 were profitable and 8 were losers. The biggest winners were trucking company Stobart (simple total return, +99%), vampire blood sucking bank HSBC (69%), and manufacturer Vesuvius (24%). Most of the losers were small change losers that I only acquired in January when I did a periodic rebalance, one exception being Braemer shipping. 

Incidentally last year the portfolio returned around plus 8% versus a FTSE 350 loss of 7%. Unfortunately I don't keep records going back further than that.

This is what the UK equity portfolio currently looks like (cash weighting as proportion of this sub portfolio value):

STOB 22.41%
ICP 14.05%
VSVS 9.45%
BKG 9.02%
MARS 7.76%
HSBA 7.63%
LGEN 7.62%
KIE 7.53%
PFC 7.39%
RMG 7.14%

The portfolio isn't quite as textbook as I'd like - Stobart is an obvious overweight even though I sold some during the year, as is the financial sector generally (represented by both ICP and bank HSBA); some of these stocks are still held in taxable accounts on which I have to pay CGT which puts a brake on the rebalancing I can do.

Diversified ETF portfolio

This is a classic bond/equity strategic portfolio, although I do have some other asset classes in tiny amounts (it would be more, but bear in mind a quarter of my risk budget is already in one 'alternative' asset: managed futures). 

I don't target my asset allocation just on this portfolio, but instead on my investments holistically. More on that later.

The ETFs I hold give me exposure in equities and bonds across all the main regions (asia, europe, UK, US and emerging markets) with the exception of Asian bonds where I have no exposure. I also have a small amount in Gold, and commercial property.

Raw performance-
Dividends: 5.0%
Mark to market: 21.6%

Total return: 26.6%

That looks amazing against the benchmark (Vanguard 60:40), but once again this is misleading because as part of my rebalancing I was a net buyer of ETFs during the year. Using the more realistic IRR:

Portfolio IRR: 19.1%
60:40 Benchmark: 18.7%

Roughly in line with the benchmark. Last year the XIRR was 6.2%, and the benchmark earned 0.11%. Incidentally the benchmark and my own portfolio have done so strongly partly because of the depreciation of GBP against most other countries last year. US investors who make up most of the readership of this blog won't have seen such great returns; global equities were up about 14.6% and global bonds were flat, giving a return of around 9% on a 60:40 portfolio.

It might make more sense to consider the performance of my investment portfolio 'in toto' (UK shares plus ETF) since that is what I target my asset allocation against:

Whole investment portfolio IRR: 22.3%
60:40 Benchmark IRR: 17.7%

So far, so good. I won't show the individual ETFs I own, since it's the overall risk in my portfolio which is important - and that will come later.

Futures trading and equity hedge

That was the good news; now for the less good news. Here is the 'money shot'; a graph showing the total value of my trading account (which remember consists of my futures trading, some equities and ETFs which I've already accounted for above, and my futures hedge):

The first plot shows the performance since inception, and the second plot over the last 12 months. In fact I've made almost exactly nothing in the relevant period (the UK tax year 2016-17); in percentage terms just 0.3%.

However that net figure hides a lot of movement; here's the full breakdown:

Stocks & ETF
Mark to market: 22.6%
Dividends 4.9%
Commissions: -0.02% 

Subtotal: 27.6%

Mark to market: -13.2%
Commissions: -0.03%

Subtotal: -13.2%

Total for stocks and hedge: 14.4%

Gross profit: -14.3%
Commissions: -0.73% 
Slippage: -0.56% (Bid ask -0.97%, less execution algo profit 0.41%)
Data fees: -0.03%
FX adjustments: 1.74%
Interest: -0.15% 

Total for futures: -14.0%

Grand total: 0.3%

So broadly speaking I made a bunch of money on my stocks hedge which I promptly lost on my futures trading. Trading costs were an acceptable 1.3% versus a backtested 1.5%. As usual commissions were a little higher than expected (since I don't calculate them for rolls), bid-ask was exactly in line, and algo profit was a bonus since I don't include that in my backtest to be conservative.


These are all for my overall account (futures, stocks, and hedges):

Standard deviation of returns (based on weekly, annualised): 22.2% versus long term target 25%
Average drawdown: 9.6%
Max drawdown: -19.4%
Worst day: -5.7%
Best day: +4.8%
Win/Loss ratio: 1.66
% wins: 37%


I've said before it's difficult to benchmark this portfolio against a pure managed futures fund like AHL, my former employers, because (a) the volatility target I use is a little higher than typical and (b) the inclusion of my stocks plus hedging returns.

Nevertheless, here are the results of my portfolio for the last 3 years:

Hedge:   -1.1%, 16.3%,  14.4%
Futures: 58.2%, 23.2%, -14.0%
Net:     57.2%, 39.6%,   0.3%

And for comparision AHL diversity GBP class with returns multiplied by 2.8 (reflecting my 25% risk target versus the 9% of this AHL fund), of course this is a pure managed futures portfolio:

Futures: 106.9%, -10.6%, -6.2%

[All these figures are based on notional capital; they would be around 4 times higher if calculated as a percentage of margin. AHL figures have fees deducted; my futures figure ignores any cash I'd get on excess margin]

Over the entire 3 years using constant capital (so I can just add up annual returns) the returns of my pure futures portfolio are around 67% versus 77% for AHL; equating to a Sharpe Ratio of just under one for me; exactly in line with my backtest expectations (to which I'd add a large pinch of salt). Not bad for a one man and his laptop operation. Casting a slightly wider net, the SG CTA index that fundseeder use to benchmark my performance had returns of 30%, -3.6% and -7.5% over the relevant three years. 

Overall I think it's fair to say I've probably underperformed the overall CTA world this year based on my pure futures performance, though over two and three years I'm fairly happy with how things have gone.

Performance by instrument

The biggest winners over the year were: VIX +6.4% (contribution), AEX +4.7%, V2X +4.3%, JPY +2.3% and NASDAQ +1.2%

The losers were GAS_US -5%, Corn -2.7%, Eurodollar -2.6%, GBP -2.2%, BTP -2.0%

Only an idiot couldn't have made money out of being short volatility this year; firstly the level slightly fell (from around spot 14.1 to 12.9 over the year) but more importantly there was the usual strong roll return (effectively earning the volatility premium):

AEX is a more interesting picture:

Here the system gradually bled a little money whilst keeping positions small. Then once an uptrend was confirmed in mid december it went strongly long and has benefitted from the continuing rise since then.

JPY (the JPYUSD IMM currency future) shows a classic trend following picture:

There is only one decent trend in the whole year, and the system captures it in classic fashion, giving up a little on the entry and the exit, and bleeding slightly the rest of the time.

What about the losses? Heres GAS:

This is an evil whipsawing with predictable results. Eurodollar is normally a star of trend following portfolios but not this year:

The problem here is that the strong carry in Eurodollar keeps us long even as the trend moves against us after Trump is elected. Another topical market was GBPUSD:

You can probably spot June 23rd! There isn't much one can do about this kind of event, except diversifying; because I have over 40 futures markets the damage done by this multiple sigma event was limited to just 1% of portfolio value, and I actually ended up as a net beneficary of Brexit this year (see here).

Overall performance

Summarising my overall investment portfolio, the numbers look something like this (as a percentage of my total investment assets, including cash held for margin):

Sub-portfolio  / contribution

UK Shares  +8.0%
ETFs +15.8%
Hedge -2.7%

Net investments 21.1%

Futures trading -2.9%

Grand total +18.2%

I think a reasonable benchmark here again is a fully invested 60:40 portfolio I'd hold if I didn't do any trading; and I've narrowly underperformed that (simple return 19.3%). But to reiterate, adding a diversifying asset like managed futures in your portfolio reduces your risk and improves your sharpe ratio; it may also improve your overall return (and this has certainly what has happened in backtesting and also over the last 3 years) but it won't do so every single year. For example, here are the figures for last year (2015-16):

Shares & ETFs  +6.1%
Hedge          +3.8%

Net investments 9.9%

Futures trading +5.4%

Grand total +14.4%

The benchmark here (60:40 again) barely moved with a total return of 0.1%. Clearly the previous year 2014-15 (for which I don't have precise figures) would have been even better since managed futures had a fantastic year.

It's worth considering what might happen in another 2008 event; with equities down 40% and assuming bonds don't bail you out this time round you're looking at a net loss of around 36% in a 60:40 portfolio. If managed futures do as well as they did in 2008 (around 2 times annual vol target, or 50%) then  hypothetically that would give me the following set of returns:

Shares & ETFs  -36%
Hedge          +4%

Net investments -32%

Futures trading +10%

Grand total -22% (versus benchmark 60:40 -36%)

That 10% reduction in losses is the insurance policy that managed futures would hopefully provide in a total market meltdown, and it's worth occasionally underperforming the 60/40 benchmark to get it.

Risk analysis and rebalancing

As part of this annual evaluation I like to look at my risk and evaluate where some rebalancing might be prudent. 

Here are the raw figures. The equity allocation includes the effect of my hedge.

Asia EM Euro UK US Global Total
Bonds 5.06% 3.97% 3.93% 7.17% 1.15% 21%
Equity 6.85% 7.62% 11.32% 21.55% 0.41% 0.07% 48%
Futures 27.55% 28%
Commodities 0.13% 0%
Property 3.22% 3%

As an aside 'property' does not include the value of the house where I live, which is excluded from these calculations. Commodities is a small investment in a gold ETF.

Another way of looking at this is to work out the geographical allocations within bonds and equities, as a proportion of the asset class:

Asia EM Euro UK US Global
Bonds 0.0% 23.8% 18.6% 18.5% 33.7% 5.4%
Equity 14.3% 15.9% 23.7% 45.1% 0.9% 0.2%

My long term strategic risk allocation is: bonds 20%, equities 50%, futures trading 25%, others 5%. I use simple trend following rules (another plug for the new book if you want detail) to vary these weights, which right now are suggesting an overweight to equities with a little less in bonds. After some judicious rebalancing, being careful not to incur a tax liability and minimising transaction costs, my new allocation is: bonds 17%, equities 54%, futures trading 26%, others 3%.

The regional allocation in each asset class is now:

Asia EM Euro UK US Global
Bonds 0.0% 27.3% 21.0% 19.2% 27.0% 5.5%
Equity 14.8% 20.6% 19.9% 37.8% 6.7% 0.1%

Remember the lack of Asian bond exposure is because of a lack of suitable ETFs, not because I hate them.


Overall I'm perfectly happy with my overall investment strategy. One year isn't long enough to give you statistically significant evidence, and indeed neither is three years, but .

Doing this kind of analysis is quite time consuming, even when you are a spreadsheet ninja, and filling in tax returns also becomes quite onerous. Nevertheless so far at least following an active investment and trading strategy has been a good use of the few days a year I spend on this activity.


  1. Dear Rob,

    thank you for providing so much insight in the structure and performance of your total portfolio.
    I have a question about the JPY chart and your comments about it. You show the clear trend, starting in Nov. 2016 and ending in Jan. 2017, and the response of your trading system. You notice the lagging system response at the begin and end. Would the system perform better if less weight would be placed on trading rules using longer lookback periods and more weight on trading rules with shorter lookback periods? This would (I guess) lead to more frequent trading and trading costs, but would capture the trend better.
    In your book you give (more or less) equal weights to faster/slower EWMAC trading rules, other than taking care of correlations, but I wonder whether that gives optimum results?

    1. The correct weights depend on (a) costs (b) correlations and (c) pre-cost returns. A proper optimisation would produce weights that factor these in, but also account for the uncertainty in estimating them: costs [almost none], correlations [some], pre-cost returns [loads and loads].

      The costs of JPY are fairly average; about 0.16% in SR units a year compared to about 0.04% for the cheapest markets.

      For correlations we'd want to avoid the middle variations since more 'spaced out' speeds would be better diversified.

      Although looking at a single example it might seem that the pre-cost returns would be higher for faster trading rules, this isn't generally true; it's almost impossible to distinguish between them statistically and inside a broad range of speeds the returns are very similar (although very fast, and very slow, don't do that well).

      Generally glancing at one year of performance and drawing these kinds of conclusions is a rocky road at the end of which is someone overfitting their system...

    2. I agree about the risk of overfitting. But at the same time wonder what trading rules should be taken into account and what not. For a trend following rule (e.g. EWMAC) should a slow lookback period of 1 year be used? 5 years be used? Or only 6 months be used? To the purist even this could be considered overfitting?
      I am including EWMAC(256,64) in my system as slowest but wonder whether it is dampening/suppressing the response to faster moves. My system is running less than one year, so it is indeed too short to be conclusive.

    3. Very slow rules tend to perform badly and are statistically indistinguishable from noise (and in the case of markets with secular up trends, from long only). How slow you should stop at is partly a matter of choice / judgement (not overfitting if you do it without looking at real data). Bear in mind that very expensive instruments can only trade 16,64; 32,128; 64, 256 - I would be wary of dropping the slowest of these and leaving you with only two speed variations.

  2. Thank you. I agree that having only two speed variations is also not a desirable situation.
    I notice that it is difficult to suppress the urge to tweak a running system. Part of the learning curve, I guess.

  3. Hi Rob,

    Wonderful talk at Quantcon and excellent book!

    I had two questions I hope you don't mind sharing your thoughts on.

    One is somewhat in regards to the above comment. Let's say you have a variable x to predict y. Would too long of a signal be the 5-year change in x to predict y? for example if x is an economic variable.

    For strategies with a one month holding period, what do you think of the idea of "tranching" for lack of a better term. What I mean is, to take an extreme case, if you rebalanced 1/21 of the portfolio each day based on the new signal. Or essentially, on day 1 you calculate the signal and rebalance 1/21 of the portfolio, then on day 2 you calculate the new signal and rebalance 1/21..etc.

    What are your thoughts on this? or the potential cost implications of doing so?

    Thank you very much for your insights.

  4. Also assuming there is an appropriate buffer in place.

    1. Swell81:
      1) You could use such a signal but it would very difficult to work out if the alpha was statistically significant, unless you're using a lot of data eg cross sectional equity data (think back to DeBondt and Thaler showing that 3-5 year returns predict mean reversion).

      2) This is a reasonable thing to do, a technique I've used myself, and will in fact reduce your costs. It's going to be virtually identical to applying a moving average to the underlying signal.

      However there is no free lunch. Like using a buffer, or a smooth, or any way of slowing down your system you will lose pre cost return from having the 'wrong' signal. In this case your signal will be delayed by an average of two weeks.

      So I'd avoid using this method AND a buffer; and depending on the character of your signal the best cost reduction strategies are:

      a) buffering
      b) exponential smooth of signal
      c) moving average or 'tranching'

    2. Thank you for the response!

      One last question if you don't mind. In general, would you recommend the 21 day moving average('tranching') approach vs just rebalancing once a month and holding for a month?

    3. No, it would be better to rebalance monthly using a buffer.

    4. Thank you. My initial thought was that it would be better to do the 21 day moving average because a.) it would eliminate path dependency based on what day you decide to rebalance(for example, doing cross sectional carry for equities using raw carry(not averaged over a year) has a decent amount of path dependency because it appears to capture the dividend run up effect so rebalancing at month end is "optimal" and a decent amount of variation by changing what day of the month to rebalance) and b.) for less liquid markets it seems to be more effective moving 1/21 of the portfolio each day vs potentially trying to move the whole position in one day.

      Any thoughts on this??

    5. Yes path dependence is a pain, but the fact remains that buffering is theoretically the most efficient thing to to do.

    6. Great. So I suppose to the CS carry equity strategy above it would be best just to rebalance when "optimal" and using the buffering method?

    7. Thank you. I apologize I promise this will be my last question!

      For the buffering you use 10%, how did you derive this? You said it is theoretically the most efficient way to do it so I assume there is a way to derive this number?

    8. Yes, but it's quite an involved calculation with a lot of different inputs. 10% is a conservative value that will be fine in most cases.

  5. What is 'buffering' and what is the 10% in this context?

    1. It's a way to avoid trading too much. In my book I call it position inertia. You don't trade unless the theoretical position is more than 10% away from what you currently have.

  6. Hi Rob,
    would you consider holding these 2 ETNs (or similar things) in your long-term portfolio in small quantities: MORL and BDCL?

    Both ETNs appear to be highly-speculative but with very attractive yields (>10%) and seem to provide some narrow exposure to specific(risky?) market-segments, they're also 2x leveraged and cray a UBS counter party risk, as I understand. Expense-ratio is also of course higher than simple passive tracking ETFs..

    1. I hate leveraged ETFs. I hate ETNs. I hate expensive ETFs. So I wouldn't touch them.