At the time of writing Astra Zeneca shares are up around 15% over a few days on the back of a forthcoming takeover offer. I own a chunk of these and my fingers have been twitching over the 'sell' button with the natural inclination being to take profits as any behavioural finance textbook will tell you.
Indeed I am not the only one http://www.telegraph.co.uk/finance/personalfinance/investing/shares/10794055/AstraZeneca-shares-are-up-14pc-in-a-week.-Should-I-sell.html.
The part of my brain running what Daniel Kahneman in http://en.wikipedia.org/wiki/Thinking,_Fast_and_Slow calls System one is in control. But the same fast instinctive behaviour that made sense when our ancestors were hunting woolly mammoths thousands of years ago isn't a lot of use in this situation. The other part of my brain, System two, knows that logically I should analyse some data and see whether it really does make sense to sell or to hang on. After all analysing data is pretty much what I do.
Enter the black box
I could really do with some kind of rule to tell me whether I should go ahead. That means I would be less likely to succumb to temptation. Three classic trading strategies that would apply in this situation are 'momentum', 'value' and 'merger arbitrage'. The first would say 'price has gone up, buy or hold a long position as it should go up more'. The second would tell me that the dividend yield on these shares has gone done to around the FTSE 100 average so I should probably sell. The latter would say 'Hold the shares until the merger is complete'. Incidentally two out of three these strategies would not sell; one reason they tend to make money in the long run is that they deliberately go against peoples natural (system one) inclinations to take profits early. The second tends to make money by being contrary as well; mainly on the downside people find it hard to buy things that have dropped a lot in price and so represent better value.
Imagine then I have a little black box sitting next to me calculating the correct decisions to make based on one or both of these trading models. Or perhaps more realistically in a separate window on my computer; next to my online brokerage account control panel. Which is resolutely saying as two out of three systems agree: do not sell these shares! But there is nothing stopping me from doing so. I can just move my mouse over to the window and click sell. The black box, assuming it has some kind of data feed to read my positions, will then change its recommendation to a slightly churlish buy Astra Zeneca – unlike me it won't have changed its mind and thinks we should be owning this still British pharma company until the bitter end.
If I then rang a friendly economist (they do exist) he or she would tell me what I need is a commitment mechanism. This is some way of preventing me from pulling the trigger and ignoring my black box. Similar in fact to when a gambling addict requests that he be barred from an online poker site. Yes the irony of the analogy isn't lost on me either. So perhaps I could set up my black box so it automatically submits the trades for me. Note that I no longer just have a systematic strategy for investing, but one which is fully automated. Just to be on the safe side I should also hide my brokerage account password deep within my computer so it takes me a few hours to dig it out.
Borrowing the Black Box
There is a much easier way of achieving this however, which would also free up some spare time to do more socially useful and fun activities. I just need to invest my money with a hedge fund which specialises in merger arbitrage and/or momentum trading. We can ignore for the moment the difficulties faced by small retail investors in trying to open accounts with hedge funds. Also this will not be cheap; I will have to pay at least 2% of my investment every year in fees and probably hand over a fifth of any profits.
But I can do even better by finding a systematic hedge fund, i.e. one which has its own black boxes. This should be cheaper; black boxes are less greedy than shouty blokes in red braces (human traders), even after you have paid some geeks to come up with the models and program them in. In practise it tends not to be cheaper with the resulting higher operating margin going to the funds owners or staff, but that is another story. It is also hard to find systematic merger arbitrage funds but fortunately equity valuation funds are two a penny, and systematic momentum funds are also quite common. Indeed I actually used to work for such a fund. By the way anything in this post isn't necessarily a reference to that particular fund or its employees. It could be about any large systematic hedge fund owned by a publicly traded UK listed company.
One man and his dog (and his computer)
There is a great cliché in the systematic investment industry, which I think was stolen from a famous quote about the space programme. The ideal systematic fund should consist of a computer, a human and a dog. The computer does the trading whilst the human feeds the dog. The dog's job is to bite the human if he goes near the computer. In practise you do need to have humans involved in the running of these things. What sort of things might they be doing?
- Process control. Its almost impossible to design a system which is completely automated. Much easier and safer to make something that requires an occasional knob to be twisted, or rather a particular script to be manually run.
- Data cleaning. Cruddy prices are more common than you think.
- Watch dogging. In case of bugs, incorrect inputs or data, something falling over …. you don't want the computer running amok and trying to trade the entire GDP of Korea in one bond trade. Famously a number of firms trading high frequency strategies have managed to lose their entire capital in a few seconds.
- Improving the strategy, i.e. research.
- Extending the strategy to a wider number of tradeable instruments.
- Reparameterisation; necessary if something changes. If you are running a slow trading strategy this shouldn't be happening very often. High frequency traders need to refit their models frequently. Arguably overlaps with research.
- Exogenous risk control. A good fund will have endogenous risk control, i.e. the risks the models know about are controlled within the models. If a model doesn't know about the risk then you need to exogenously do something about it.
Quite a few of these activities can at least be partially automated, with the exception of research (automated research is just reparameterisation). As with risk control you can view these as endogenising the activity inside the black box. I always try to move any exogenous ad-hoc activity inside the box; first by systematising it and then by automating it. For example suppose you got nervous about executing orders around important non farm payrolls. First you might just turn off your trading system when a big non farm number was coming (ad-hoc). Then you might create a procedure where you turned off your trading for every non farm number (systematised process). Finally you could create a data feed for non farm dates and have the system pull out just before each one (automated process).
However we are still left with the biggest potential source of exogenous risk control, or as I prefer to put it 'I know instinctively better than the trading model I have spent hundreds of man hours developing, because of X' (you can perhaps see where I am going with this). Often in my experience I have found myself or observed others labelling changes as 'research' that were clearly done for risk control reasons. For example 'Our research indicates that we should remove some asymmetrical long bias from our corporate bond bond, corporate bonds feel overvalued so this is clearly a good time to introduce it'. Notice that the researcher speaking here hasn't got a corporate bond valuation model so there is no way of backing up their feelings with data... its System One not System Two speaking here.
We also see the same sort of behavioural biases that the systematic trading model has been designed to avoid coming back in again. So again I have found myself saying 'We should reduce this models risk to take profits because it has been a good year' and mainly heard others saying 'This model hasn't made money for 3 months we should turn it off'. In case you didn't realise 3 months is an statistically pointless length of time to measure performance over for the kinds of models we are talking about.
Gut feeling and behavioural bias is human nature and there is not much we can do about it. Instead you need rigorous peer /management reviews of any proposed change or the critical self examination based on bitter experience if you are on your own. Another good trick is to make the process for making changes to the trading system so bureaucratic, difficult and torturous to do that nobody bothers. Inevitably though the risk manager will complain loudly if their gut calls, sorry rigorous analytical decisions, are too hard to implement.
Wanted: Risk Manager. Must be wantonly idle
Some more good advice is not to employ anyone with trading experience as a risk manager. Normally this is a good idea, since ex-traders know where the bodies are buried and are excellent supervisors of human traders. But with a systematic system they will just want to start making calls. A cardinal rule of running a systematic system is any risk management decision should reduce the size of a position but never change the sign. Ex-traders find it hard to follow that rule. They are also a bit prone to what Americans like to call Monday morning quarterbacking. Its very easy to see that a particular position shouldn't have been put on, or should have been reduced, if it loses money because something happens.
A better person to employ would be someone who is very smart but extraordinarily lazy, and who can only be bothered to do say one hours work a month. Since they still want to get paid they will make sure that they only take decisions but only when it really matters. You can simulate this by using a variation of Warren Buffets punched card idea. At the start of the year the risk manager gets a card. Every time they make a decision they punch a hole in it. When say 10 holes are in the card you take away their right to make any further decisions. The same rule could apply to any person who has the power to change a trading system parameter.
Two kinds of investors
Unfortunately it isn't just human nature or over enthusiastic risk managers that causes problems with system one thinking. In theory investors in the fund have deliberately handed over their money at least partly to ensure a commitment to the trading model. Certainly for larger institutions that could run their own money in this way this should be one reason, though most investors probably haven't consciously done this. But sure enough when there is poor performance for 3 months, many will put pressure on the manager to do something. Long lock ups, where you cannot redeem your investment for months or years, are unusual in this kind of hedge fund since the underlying assets are very liquid; indeed this is a selling point. However perhaps for systematic managers it makes sense to attract the right kind of investor by imposing a five year lockup on any money put in.
There is one more source of behaviourally inspired interference; the owners of the fund management business – shareholders and their representatives, the senior management of the business. Fund investors might be au fait with the nature of the business – research the model, implement it and then leave it alone unless its behaviour falls outside an expected envelope in a statistically significant way. But if senior managers are from a trading background they may also be prone to the behaviour of the risk managers mentioned above. Again you might be better off with very lazy senior management. If its any help I am available and perfectly happy to work a few hours a month for a CEO type salary.
Shareholders in public companies like predictable businesses with steady cash flows. They attach good price earnings ratios to such businesses. But this kind of business is effectively a non linear leveraged play on the success of the underlying trading strategy. This leads to very lumpy earnings, hard for public shareholders to stomach; they will tend to overvalue the firm when it is doing well and undervalue when vice versa occurs. Ideally then a hedge fund like this shouldn't be publicly owned, but like nearly all hedge funds owned by its employees. They know better than anyone what the business is like, and this is also great for lining up incentives.
But if it must be publicly owned then it is clear what the shareholders need to do. Yes: they need to buy a black box, entrust their hedge fund shares to it and hide their passwords...
To finish its probably worth noting that I only trade futures systematically; thus I really do have no formal trading model at all for Astra Zeneca. If anything my individual share portfolio is definitely value based, so I will probably sell having identified a company with a better dividend yield. When I get round to it that is.
Postscript: I sold my AZN shares on 8th May 2014 and traded them for the higher yielding GSK. Wish me luck!