What exactly is a CTA?

When I use a word... it means just what I choose it to mean

CTA. An industry standard term, that seems straightforward to define: Commodity Trading Advisor. We can all name a bunch of CTAs - I used to work for one. There are indices for them, such as this one or this one (also this, and this, oh and this, plus this, and these guys have one, as do these guys, oh and dont' forget this one ... I probably missed some but I'm bored now).  But in practice, the term CTA is a somewhat ill defined term with multiple overlapping meanings. Let's dive in.

Advising and managed accounts

The most intriguing word in the term CTA is the final one: advisor. CTA's are not fund managers in the normal sense of the word. 

Fund managers normally do this: They take your cash and comingle it with others in a legal vehicle, selling you shares in the vehicle in exchange. Then they go out and buy assets with the cash. You don't legally own the assets - the fund does. There's normally a second legal vehicle which is responsible for actually managing the fund - the fund manager. You don't own shares in that. 

The CTA is a bit like the second legal vehicle in a standard fund structure - it advises but doesn't actually own the assets. But in a traditional CTA structure the assets are not comingled but kept seperate. So it works as follows: you open a managed account and put some cash into it. The CTA fund then makes decisions about what that account buys or sells. Importantly, you still own the assets in the account. If something happened to another customers assets, it wouldn't affect you.

Note that the advisory term is a bit misleading as it implies that you have full trading discretion on the account, and the CTA ocasionally rings you up and advises you about what you might think about trading. That may have been the case in the 1970s when CTAs started to become popular, but nowadays CTAs almost always trade customers accounts for them, often with automated execution algos that are a world away from requiring someone to pick up the phone. 

Choice of instrument

In theory any asset can be put inside a managed account, but they have normally been used to trade futures. The combination of a managed account and futures trading brings us to the term managed futures which is often used interchangeably with the designation CTA. Since CTA is a term of US legal art, this definition is safer and can be used across geographical regions.

An important implication of this is that you need a fair bit of money to have a managed account. To hold a properly diversified portfolio of futures with anything less than a few tens of millions, without running into discretisation issues is tricky, as I've discussed at length on this blog. There are also admin and operational fixed costs associated with having a number of managed accounts.

Over time many CTAs have gradually increased the minimum required to hold managed accounts, or have switched to using non managed account structures, which also allow them to trade assets that aren't futures. 

The asset class 

You might think that commodity trading advisors manage commodities: things like Wheat and Crude Oil. The easiest way to manage such things, especially in a managed account type setup, is through futures contracts.

However it's pretty rare for a CTA to only trade commodity futures. Nearly all of them also trade financial futures like the S&P 500 equity index or US 10 year bonds (there's perhaps an argument about whether metals like Gold are commodities or not).

Over time, CTAs have begun to trade non futures instruments. For example, it's hard to get adequate diversification in FX with just the available futures contracts. Adding FX forwards makes a lot of sense in this context, as they are very similar to futures although obviously OTC rather than exchange traded. This has implications for the legal structure of the CTA, since you can't easily put these in managed accounts.

The legal / regulatory definition

CTA is a US regulatory term. From the horses mouth:

Commodity Trading Advisor (CTA) Registration

A commodity trading advisor (CTA) is an individual or organization that, for compensation or profit, advises others, directly or indirectly, as to the value of or the advisability of trading futures contracts, options on futures, retail off-exchange forex contracts or swaps.

There's quite a bit to unpick there. The most obvious is this: the advisor is expected to advise, suggesting a managed account structure rather than a traditional structure. Secondly, and contrary to what has been stated before, you can be a CTA and manage non futures assets. This is somewhat alien to the concept of managed futures, but reflects the reality of the modern CTA industry. 

Trading style and speed

Until now I haven't discussed exactly how the CTA trades, only what it trades, and the legal structure set up to do that trading. In theory a CTA could be anything from a high frequency futures trader, up to a slow moving risk parity fund. They could be doing pure trend following, or some dangerous combination of carry, mean reversion, and a systematic short position in VIX.

Generally though when people refer to CTAs or managed futures they are mostly expecting such funds to trade medium to slow speed trend following. This is pure path dependence and tradition - there is nothing in the CFTC or NFA definition that says you have to trade like this. But because CTAs have been around for a while, and because trading costs where higher in the past, and because trends work well in futures particularly during the inflation ridden era when CTAs came to prominence, and because trends work better for holding periods between a few months and a year... for all of these reasons the CTA industry grew up as fairly slow trend followers.

(Remarkably this is true of both the US and European 'wings' of the CTA industry; even though the latter grew up fairly independently.)

There is a degree of self reinforcement here. CTAs have done very well in several market downturns, leading to the mythical status of 'crisis alpha'; something that is both uncorrelated and yet provides a positive return, plus nice skew properties. Some of that is just maths - a trend following strategy will have the payoff function of a long straddle and positive skew when judged at the right time horizon - and some of it may be myth, luck, or due to secular trends and correlations that may not hold in the future. But as a marketing story it's certainly become popular in certain circles, which means that many clients expect CTAs to have a certain trading style to fit within their particular style box.

However the fact that there are now seperate 'SG CTA', 'SG CTA Trend', and 'SG Short term' CTA indices suggests there is now more to the industry than slothful trend followers.

Note: The HFRI index family does not use the term CTA, but does have the following confusing set of indices:

• HFRI Macro: Systematic Diversified Index 
• HFRI Macro: Systematic Directional Index 
• HFRI Trend Following Directional Index 

Systematic or discretionary

The very first CTAs can really only have been discretionary; men (back then, always men!) in green eye shades in darkened rooms looking at point and figure charts. However the use of trend following naturally lends itself to a systematic process. Systematisation also allows maximal diversification across numerous futures instruments, something that will improve expected performance.

The term CTA has thus become synonymous with systematic trend following. 

Notice that systematic is not the same as automated. It's possible in theory to have a fully systematic process which is hand cranked, or done in spreadsheets or with a calculator. The original turtles operated in such a fashion. But the easy availability of computer power means that the generation of trades in the vast majority of CTAS is now done in an automated fashion.

The modern CTA

A modern CTA may well still have some legacy managed accounts, or accounts opened for particularly large clients who want that traditional structure, but they are more likely to have morphed into a more typical hedge fund setup.

Instead of opening a managed account clients will buy shares in various legal investment vehicles, and there is usually a good offering of alternative jurisdictions (both onshore and offshore), currencies and types of fund (eg UCITS). In many cases a single legal vehicle may have different share classes, offering different currencies or degrees of leverage. 

(Another possibility is that the CTA uses a master-feeder structure. The client puts money into a feeder, which in turn is invested in various master funds. For example, a CTA might offer a variety of options that blend between a more traditional futures trend following fund, and an alternative that holds OTC assets.) 

These various funds will then have futures accounts opened them. Arguably these are also managed accounts, but the legal owner of the assets within them are funds not the final clients, so this is different from the traditional setup. 

However the investment funds can also go out shopping for assets that aren't futures. These can include other on exchange assets, like options on futures, or equities; or OTC assets like FX forwards, interest rate swaps or cash bonds.  This gives the clients access to a more diviersified set of instruments, something that would be extremely difficult in a traditional managed account structure. Consider for example the hassle of setting up 50 ISDA agreements for 50 $20 million managed accounts, rather than a single $1 billion fund.

It's likely that a modern CTA is fully systematic and automated up to the point of trade generation, although many funds will outsource the execution of their trades to in house human traders or external brokers. 

The variety of trading strategies is probably the area where the industry remains most heterogeneous. 

Many CTAs probably still have some medium speed trend following at their core, and may offer funds that are purer, but will have plenty of other signals such as carry and mean reversion. They may also offer funds that are very different but leverage off their experience, such as leveraged risk parity or equity market neutral. But this is a generalisation, and there are plenty of CTAs that have stuck more to their traditional knitting of medium speed trend following "plus nothing". We can even have a further debate about what does, or does not, constitute the correct use of the word trend following - but perhaps we should not do that today!

Conclusion

In summary, when you say CTA you may mean something quite different from what I mean. There is no such thing as a 'pure' or 'true' CTA. This is most true when it comes to defining the trading style. CTA is a poorly defined term, but it seems we are stuck with it (after all, 'managed futures' is not much better!).

Trading and investing performance - year five

Hard to believe, but it has been five and a half years since I had to go to an office to manage other peoples money, and exactly five years since I began systematically trading my own. Time then for another annual review. Perhaps it is confusing for overseas readers, but these reviews follow the UK tax year which runs from 6th April to 5th April, rather than any logical period like a calendar year (or even 1st to April to 31st March would make more sense, frankly).

Previous updates can be found here, here, here and here.

Overview of my world

My investments fall into the following categories:

• In my investment accounts:
• 1 UK stocks
• 2 Various ETFs, covering stocks, bonds, gold and property
• 3 Usually some uninvested cash
• In my trading account:
• 4 Various ETFs, covering stocks and bonds
• 5 A futures contract hedge against those long only ETFs in 2.1, so that the net Beta is around zero
• 6 Futures contracts traded by my fully automated trading system
• 7 Cash needed for futures margin, and to cover potential trading losses (there is also some cash in my investment accounts, but it's pretty much a rounding error)

Excluded from this analysis is:

• Net property equity in my PPR (primary private residence, i.e. the bricks and mortar I am currently writing this in)
• My 'cash float', roughly 6 months of household expenditure that is kept separately from my investment and trading accounts. This is used to smooth out lumpy income arriving from multiple sources and means I can sleep easily at night.

For the purposes of benchmarking it makes most sense to lump my investments in the following way:

• A: UK single stocks
• Benchmarked against ISF, a cheap FTSE 100 ETF (FTSE 350 is probably a better benchmark but these ETFs tend to be more expensive).
• B: Long only investments: All ETFs (in both investment and trading accounts) and UK stocks
• Benchmarked against a cheap 60:40 fund. This is the type of top down asset allocation portfolio I deal with in my second book.
• C: Equity neutral: The ETFs in my trading account, plus the equity hedge. 
• Benchmark is zero.

• D: Futures trading: Return from the futures contracts traded by my fully automated system. This is the type of portfolio I deal with in chapter 15 of my first book. The denominator of performance here is the notional capital at risk in my account (usually close to, but not exactly the same as the account value).
• Benchmarks are a similar fund run by my ex employers, or the SG CTA index, adjusted for volatility.
• E: Trading account value: This is essentially everything in my trading account, and consists of equity neutral + futures trading. 
• No relevant benchmark.
• F: Everything: Long only investments, plus futures hedge, plus futures trading. I include the value of any cash included in my trading or investment accounts, since if I wasn't trading I could invest this. 
• For the benchmark here again I use a cheap 60:40 fund.

If you prefer maths, then the relationship to the first set of categories is:

A = 1
B = 1 + 2 + 4
C = 4 + 5
D = 6 + 7
E = 4 + 5 + 6 + 7 = C + D
F = 1 + 2 + 3 + 4 + 5 + 6 + 7 = B + 3 + 5 + D

Performance contribution

The figures shown are the contribution of each category to my total investment performance (on an XIRR basis):

A, or 1) UK equities -0.45%
2) ETFs +4.35%
B) Long only investments +3.9%
C) Equity hedge -0.2%
D) Systematic futures trading +1.0%
E) Trading account: +0.8%
F) Total 4.4% (won't add up exactly because of XIRR effects)

UK Equities

This is effectively a 'trading' portfolio, using a mechanical system described here. Since I published that post I have added a new twist in that I enforce sector diversification.

Mostly it's held inside SIPP and ISAs, to avoid paying CGT. There are also a couple of legacy stocks with larger positions, which are held outside tax shelters. I have been gradually reducing their position tactically over time.

Start of the year:

ICP 18.8% (legacy)
STOB 17.1% (legacy)
BKG 10.4%
VSVS 9.5%
RMG 8.9%
LGEN 7.6%
GOG 7.5%
HSBA 7.4%
IBST 6.9%
BP 6.0%


I sold some STOB to crystallise a CGT loss, and all the other trades were mechanical:

Bought and sold Babcock, for a 26% loss.
Sold RMG for a 31% loss
Sold IBST for a 20% loss
Bought CEY
Bought PTEC

So now the portfolio looks like this:

ICP 20.98%
VSVS 10.79%
BKG 10.59%
CEY 8.91%
STOB 8.76%
GOOG 8.69%
PTEC 8.66%
LGEN 8.47%
HSBA 7.21%
BP 6.94%


Although the yield was 4.4% the total return was negative; an XIRR of -2.3% to be precise. This compares badly with the FTSE 100 tracker I use as my benchmark coming in at 7.6%. Looking back over the years since I started doing being this anal about my performance, this is the first year I've underperformed. Apart from the losers I sold Stobart also underperformed (though it's still up 100% from my original purchase price), and both CEY and PTEC have lost money since I bought them. On the upside BP and GOOG (which is Go-ahead, not Google in case you didn't know) both earned around 20% over the year.

I have been a net seller of UK equities for many years now, but my allocation is now about right. I reinvested the dividends earned from all UK stocks back into the UK, but they are still a smaller proportion of my portfolio due to the relatively poor performance. I'll return to questions of portfolio allocation later.

ETFs and funds

All my non UK and non equity exposure is in ETFs, with a smattering of investment trusts. As usual trading was done for tax optimisation, to generate funds for SIPP and ISA Investment, and to get the right risk exposure (discussed later). I don't look at the performance of my ETF portfolio seperately, only in conjuction with UK shares.

Long only

Performance here was better, but still not fantastic. Dividends on the whole piece were identical to the UK share, with a yield on starting value of 4.4%. The aggregate XIRR was 4% exactly, hence a small capital loss was made. This under performed a benchmark Vanguard 60:40 fund, which came in at 7.2%.

Systematic futures trading and equity hedge

The systematic futures trading system I run is effectively what you can in find in "Systematic Trading", and code-wise is an older version of the implementation in pysystemtrade.

For my trading account as a whole the breakdown looks like this (all numbers are as a % of the notional maximum capital at risk, which happens to be a bit less than the trading account value):

Hedging futures: -1.1%
Hedged stocks, total return: +2.0%
Net equity neutral: +1.0%

Futures trading-
MTM: 5.7%
Interest: 0.08%
Fees: -0.04%
Commissions: -0.6%
FX gain/loss: +0.02%
Net futures trading: +5.2%

Grand total: +6.1%

Some more statistics (futures trades only):

Profit factor: 1.0
Win/loss ratio: 1.31
Profit factor: 1.0
Hit rate: 43.2%
Avg holding period, winners: 39 days
Avg holding period, losers: 29 days

So is this good or bad? Let's look at benchmarks.

 'Bench1' is this AHL fund, using monthly returns from April to March in each year, and a new benchmark 'Bench2' is the SG CTA index, with matching daily returns. Both have returns scaled up to match my volatility. Remember the benchmark should only be compared against futures trading, not the equity neutral component of the portfolio.

Year:    14/15   15/16   16/17   17/18  18/19

Total:   57.2%   39.6%    0.3%    0.4%   6.1%
Hedge:   -1.1%   16.3%   14.4%    4.1%   1.0%  
Futures: 58.2%   23.2%  -14.0%   -3.7%   5.2%

Bench1: 106.9%  -10.6%   -6.2%   16.4%  10.3%
Bench2:          -6.7%* -21.9%   -3.8%   0.7%

* From 13th April 2015

A very good performance from 'Bench1' here, but against the entire industry (bench2) my performance is more respectable.

You will be used to seeing pretty pictures and more detailed analysis here. Unfortunately I couldn't run my normal annual performance attribution in the increasingly creaky old legacy code that my system runs on (after all it's five years old now). I am gradually building up to replacing this with pysystemtrade, however this is a slow process (interrupted by the new book I am finishing off, plus various random side projects like writing this blog post).

Total investment return

My total return on all my investments, including cash held for futures margin, came in at an XIRR of 4.4%. Once again Vanguard 60:40 seems an appropriate benchmark (since if I wasn't trading futures I could throw all my cash into that fund), at 7.2%. All in all then a slightly disappointing year, although unlike the last two years my futures trading added to rather than detracted from my performance.

Risk

My investment portfolio asset allocation at the end of the year in cash terms stood at 22.7% in bonds, 65.1% in equities, 9.5% in cash and 2.7% in other (Gold and commercial property).

This is more cash than I normally have. About 2.6% (of the 9.5%) was transferred to ISAs and will be invested shortly. I am toying with the idea of starting another little portfolio which will invest in investment trusts using some simple filters around discount and yield. I also have a little more than usual in my current account, and in my trading account. In practical terms this just means I have more of a cushion against the rather lumpy arrival of income in the form of dividends and royalties.

My allocation in my preferred risk weighted terms looks like this:

|Asset    |Strategic|Start of year|Current|
-------------------------------------------
|Bonds    |   22%   |   13.1%     | 12.0% |
|Equity   |   50%   |   59.4%     | 60.7% |
|Futures  |   25%   |   24.5%     | 24.7% |
|Other    |    3%   |    2.9%     |  2.5% |


As usual the lower allocation to bonds reflects a mechanical trading rule that uses the last 12 months of relative risk adjusted performance; bonds are down around -0.5% and equities up 5.5%. See the relevant chapters of "Smart Portfolios" for more detail.

Regional exposures, should you care (each row adds up to 100%):

|      | Asia | EM   | Euro |  UK   |  US  |
------------------------------------------------
|Bonds | 0%   | 22%  | 19% |  18%  |  41% |
|Equity| 26%  | 27%  | 17% |  27%  |   3% |


The 0% weight in Asia reflects a lack of decent bond ETFs, whilst the 3% in US equities is because they are frightfully expensive (again there are mechanical rules lurking behind these numbers, this time based on relative valuation metrics: dividend yield and PE ratios).

Thoughts and plans

There are enough numbers in these posts that there will always be good news (relative futures trading, equity hedge) and bad news (everything else). Naturally none of it is statistically significant. So there are no conclusions to draw in the shape of "Oh my gawd, this is awful, I need to change everything right now".

But gradual improvement in a sensible way is fine. I haven't yet got round to implementing any serious changes to my futures trading (waiting for my code migration to finish first), but in the mean time I've started a very small portfolio which buys investment trusts trading at a large discount and with large yield, with some minimum liquidity requirements. So far this constitutes PGIT and VSL.

So you want to be a trader?

I often get asked, or see people asking, how they should become a trader or fund manager? The short answer is in this diagram:

Don't worry there is a bigger version of this later

.... but that probably won't make a lot of sense unless you read the rest of this post.

The four kinds of trader

 

When I speak of a "trader" I'm going to include both those who actually do the buying and selling, as well as those who make the decisions to buy and sell, since they won't always be the same person. So fund managers are 'traders' even if they have someone else to do the actual clicking of the button (or nowadays, an execution algorithim). I'm also including systematic traders who outsource both the decision making and execution to computers, but have to design and manage the system.

Broadly speaking there are four kinds of trader:

• Proprietary ("prop") trader (someone who trades the firms capital)
• Institutional, buy side, portfolio manager (trades other peoples money, makes the decisions or designs the system, may or not do the execution)*
• Institutional, sell side (eg investment bank options trader, uses bank capital but not primarily a risk taker)
• Self funded independent trader (someone who trades their own capital)

Note that the 2nd and 3rd categories are salaried traders; they get paid a salary which is normally pretty good, plus a bonus. Prop traders normally only get a percentage of profits, though there might also be low base pay in some of the better shops. Independent traders eat everything they kill; and also stump up for losses.

I feel qualified to write this as I've worked in 3 out of these 4 jobs (portfolio manager, sell side and independent), although I have never been a proprietary trader (I do know quite a few though, so I'm not writing in complete ignorance).

An important caveat: I'm mostly ignoring the distinction between discretionary and systematic trading** here, or between asset classes. However the educational background required to be a systematic fixed income options trader is clearly different from what a discretionary spot FX trader needs; so bear that in mind. 

* in the interests of clarity I'm excluding 'execution traders', who execute buy side trades but do not make decisions as to the size or sign of the total order. This is not done for any particular reason other than making the picture above close to readable, and it's a relatively niche job; I'm not suggesting execution traders aren't real traders or anything like that... some of my best friends are execution traders...

** Systematic high frequency traders normally trade prop capital; but their career path is more similar to a systematic buy side portfolio manager so this where I categorise them.

Why do you want to be a trader?

 

This is the first question to ask yourself. The answer to this will determine if trading is really for you, and also help you decide which of the four categories you should be aiming for. Typical answers include:

• Money (financial security)
• Prestige (impressing people of the appropriate gender and sexual orientation at cocktail parties)
• A deep interest in the financial markets
• A fast paced working enviroment
• Working with intelligent and interesting people
• An interest in an academic subject (eg maths, computing, economics, pyschology ...) and the chance to use this in real life.
• A high degree of autonomy 
• Being judged on results, not subjective BS
• Short working hours (at least compared to other finance jobs, and being say a doctor or something)

You should probably think hard about your answer. Don't say "yeah I want to work with intelligent people", if the real answer is money. This isn't a job interview. Be honest with yourself.

If you say "money", then why? Is it financial security you want, or do you want to be able to buy a flashy lifestyle and thus gain "prestige". Would you be happy as the "millionaire next door", financially secure but outwardly thrifty?

http://doesyourbaghaveholes.blogspot.co.uk/2009/07/what-cars-do-wealthy-drive.html

Or do you need to be the guy or gal turning up to a school reunion in a red Ferrari?

If you fall into the latter category I highly recommend reading Affluenza if you haven't already done so.

Which type of trading is best for me?

Now I'm going to discuss each type of trader in turn, to see how they match up to the different motivations above. Note that (a) this is all my subjective opinion and (b) things vary considerably within categories - what I'm showing is an average here. So for example whether your job is academically relevant depends more on your academic interest, and the type of trading you are doing, than on if you are on the buy side or sell side. Also working hours for salaried traders are more correlated with experience - juniors tend to do more - than with category.


First though a word about money.

Money

In general traders are paid like footballers. To be more exact there is a massively skewed or if you like pyramid distribution of income for both "professions" (although top traders earn much more than the best footballers; and the mean salaried trader probably earns more than the mean professional footballer). At the top end are the likes of Wayne Rooney* (perhaps £20 million including sponsorship deals), and the likes of George Soros, Ray Dalio and Steve Cohen (£1 billion plus). Then there are lower paid premiership players (£1 million upwards) comparable to mostly buy side and a smaller number of sell side high earners, with perhaps a handful of individual and proprietary traders (tens of millions). 

* apologies for the UK football centric figures here; feel free to transpose to your own preferred sport and country

Mr Rooney, no doubt wishing he was a hedge fund manager. http://www.theguardian.com/football/blog/2014/aug/13/wayne-rooney-manchester-united-captain-louis-van-gaal-robin-van-persie

Then we gradually descend through the lower ranks of professional footballers, at the bottom of which are bottom end league 2 players on about £30,000. Somewhere in the professional leagues are the equivalent of the average buyside and sellside traders; with average proprietary traders coming in closer to the bottom (in relative ranking, if not in actual equivalent pay).

We then have the part time and amateur footballers. Note that no footballer earns a negative number, although an amateur might end up spending a couple of thousand a year on membership, kit and travel costs. In contrast the majority, and perhaps up to 90%, of independent traders lose money. Some might be getting through five or six figures a year (though one hopes this is not for very long).

Averages are meaningless with such skewed groups. A better way of summarising is to look at ranges. First I've put a normal range which I'm reasonably confident covers about two thirds of people in each group. I've also put an extreme range, which I think 98% of people fall into (with some extremes at the upper and lower end). Apologies for putting these figures in GBP, but all the readers of this blog can probably do currency coversions in their head.

• Proprietary trader: Normal range: £20K to £100K. Extreme range: -£10K (cost of a training courses) to £2 million.
• Portfolio manager: Normal range: £100K to £500K. Extreme range: £50K to £10 million
• Sell side: Normal range: £75K to £300K. Extreme range: £50K to £2 million
• Independent trader: Normal range: £-5K to 0K. Extreme range: -£50K to £500K

Notice that some parts of the profession have a wider range than others; and that the salaried traders (sell side and portfolio manager) have higher minimums.

Proprietary trading

Success in prop trading is proportional to how many screens you have. Apparently.
Source http://cn-chillies.com/

Good for: fast paced,  judged on results

Okay for: money, prestige, interest in finance, autonomy, working hours
 
Bad for: co-workers, academic relevance

Being a prop trader means it's all about your p&l. Nothing else matters. You're only job is to trade the firms money. No staying late at the office to score political points. If you're an adrenalin junkie, there's no better enviroment. If you're not then working with hyper competitive people for several hours a day might be a little draining. Also forget about using your econometrics phd. It's just like playing a computer game.

I have never been a prop trader, and wouldn't ever want to be. But I do know some poor deranged souls who are.

Portfolio manager

John Paulson. Hugely successful hedge fund manager. So good, he can trade with his back to the desk.
www.businessinsider.com

Good for: money, prestige, interest in finance, co-workers, academic relevance, judged on results

Okay for:fast paced, autonomy, working hours

Bad for: I can't think of anything. Which is why this is the most sought after kind of trading job.


Oh yes, to be a fund manager, especially at a hedge fund collecting 2 and 20 rather than long only getting a mere 0.5 and 0. The best of these jobs are very pleasant indeed, and very, very, very, well paid. There is often the chance to spend lots of time thinking interesting thoughts, and little doing boring stuff. The only people you have to answer to (unless you've made enough money) are outside investors, and annoying risk managers.

Anyone with any sense would prefer this to any other kind of trading job, which is why they are insanely hard to get.

The author's last real job was working as a hedge fund portfolio manager, specifically at a systematic CTA.

Sell side

Tom Hayes, LIBOR fixer extraordinare. Currently the most famous sell side trader in the world. But perhaps not the best role model.
www.telegraph.co.uk

Good for: money, prestige, interest in finance, fast paced

Okay for: academic relevance, co-workers, judged on results

Bad for: autonomy, working hours


This is what most people think of when they think about traders: some guy in a bank barking 'buy! sell!' down a phone whilst snorting a line of coke as an exotic go go dancer shines his shoes with their naked derriere.

Now for reality.  Nobody has used an actual phone on a trading floor since 2006; it's all done electronically or on Bloomberg IM unless you are doing some insider trading or LIBOR rigging. Also coke and go go dancers may have been de riguer on the trading floors of the 1980's but no longer.

Also being a bank trader is nowhere near as interesting as it was pre 2008. Regulation and compliance mean that proprietary risk taking (rather than just hedging customer flow) is almost absent from banks. As a result although base salaries have risen top bank traders are now very much the poorer cousins of their buy side colleagues (though minimum pay is higher, and there is less variability). Plus the hours in banks were always longer than the buy side; that at least hasn't changed.

The author spent a year and a half working as an investment bank trader, and hated every minute.

Independent

Navinder Sarao. Alleged to have caused the flash crash (complete nonsense IMHO - Free #NavSarao). Currently the most famous  independent trader in the world.
cnbc.com

Good for: autonomy, working hours, judged on results,

Okay for: interest in finance, academic relevance, fast paced (but varies)

Bad for: co-workers, prestige

Terrible for: money

The main downside of trading independently is it's the only job in this post where you can get paid a negative amount; and indeed most people who try it manage to do that. And you don't get to work with interesting and intelligent co-workers, just some bozo who sits at home all day, probably just wearing his* boxer shorts (that's you)**. And it isn't that prestigous; since anyone in the know will realise (a) you probably don't make any money and (b) you're just some bozo who sits at home all day in his boxer shorts.

* if you don't wear boxer shorts, put the name of your favorite trading clothing here
** you could of course join a trading arcade; but that just means you'll be hanging around with other bozo's, though hopefully wearing slightly more.

The upside is you can, depending on your trading style, spend very little time on actually trading and lots about thinking interesting thoughts about the financial markets (though you're going to be a little out of the loop compared to those working in the febrile atmosphere of a real trading floor). You can use your obscure phd in neural networks to predict prices if that is your wont (though be warned, it probably won't work). And you never have to take any s*** from anybody. Except your wife, asking why you don't have a proper job anymore, and if you're home all the time anyway; perhaps you could do some chores?

In the interests of full disclosure the author of this post is currently an independent trader.

The map

We're now in a position to return to the map.

The various 'trader' boxes should now make sense. Within the buyside and sellside I've included additional boxes for the front and back office. I've also broken out 'unprofitable' prop and independent traders; these are a stop on the journey rather than the final destination.

The lines on the map show possible routes between boxes. Very thick lines are routes that are straightforward and heavily travelled; thinner lines less so (though this is all relative). So for example it's very easy to become an unprofitable independent trader; but very hard to go from independent trader to fund manager.

If a line isn't there it means I think it highly improbable that those trajectories will happen, though of course they are not impossible.

The lines are also coloured. Each colour represents a different route through the trading "profession", which I'll discuss next.

This is clearly a simplification; and I'll talk through some of the missing nuances below.

The main routes

Lone ranger (red)

It's very easy to become an independent trader. You just need some money and a brokerage account. A few clicks later and hey presto! You're a trader.

It's much, much harder for someone who is self taught, with no relevant experience and probably low starting capital, to become a profitable independent trader; one whom can give up all other work and live comfortably on the net profits from their business; with enough capital in reserve to smooth over the inevitable bad months and years that even brilliant traders will have.

A successful independent trader might want to become  a prop trader, and leverage their skills off a larger capital base. However the business model of most prop shops assumes that you trade pretty frequently to provide flow to brokers for hich the shop receives a kickback. It's very hard to be profitable if you trade a lot independently; surviving independents are most likely to be too slow to interest prop shops.

Even harder is for an independent to launch their own hedge fund. Despite this I often see people saying "I have traded for 6 months and made money, how do I start my own hedge fund". There are some new iniatives that might make this easier. But be warned this route is the one with the lowest chance of success.

Prop bandit (yellow)

It's just as easy to become a prop trader. All you need is some money, which you usually have to hand over to the prop shop for 'training'. There are some more reputable shops which don't require this up front payment, but obviously they are more selective with who they pick.

Not everyone who gets in to the training course will subsequently be chosen to trade the firms capital; and only a proportion of those will last for long enough to make a reasonable steady income.

A good prop trader can probably go independent quite easily; although if they are intraday traders they may need to stay within the fold of a prop shop to keep access to the low commission rates needed to succeed in this arena.

It's slightly easier for a good prop trader to become a fund manager than it is for an independent trader; larger amounts of capital and more trading equate to a verifiable track record. Nevertheless again this is a route which has a low probability of success.

Backroom boy (blue and green)

With many apologies to female wannabe traders, but the alliteration here is too good to miss. In the olden days it was relatively common for people to begin in the mail room (this guy didn't even start there, the mail room was a promotion for him) and work their way up to CEO. Exchange floor traders would frequently start as clerks and runners.

Sidney Weinberg, telling everyone for the like the millionth time that he started as a janitors assistant, and how young people today don't even know they are born.... https://en.wikipedia.org/wiki/Sidney_Weinberg

A modern day version of this parable is to begin in a back office role (or middle office), work hard, impress the right people and hoist yourself up to a front office role. This is do-able, but not easy. You're also going to be a few years behind the cohort who start out in the front office.

You'll also need the right qualifications; if you don't start without them you'll need to go back to school to get them. The reason this strategy makes sense is that it's easier to get a back office role than to go straight into the front office. It is however still a gamble and not a path that many people travel. If you can get straight into the front office (next route I discuss) you clearly should.

There isn't much difference between the buy and sell side; except in general it's harder to get into the buy side from scratch. You can also make a parallel move from sell side to buy side; with the reverse move being slightly easier.

Fronting up (cyan and yellow)

This is probably the most common route into trading; and hence probably the most straightforward.

If you have the right qualifications, land a few good internships, and impress at an interview; then you can go straight into the front office. From here the trading desk is much, much closer. Of course there are fine variations within the front office; some front office jobs are more relevant than others, and the journey to the trading desk will be easier depending on your starting point and the kind of trading you wish to do.

Economists and strategists will fit neatly into global macro type roles, equity (bond) analysts will obviously find it easy to move to equity (bond) trading, whereas quant analysts are a more natural fit for options trading and systematic trading. Good technologists with the right experience can also move into systematic portfolio management roles. Moving from risk management into trading is harder, but I know of people that have moved between those two roles comfortably*.

* If I ruled the world all traders would have to work as junior risk analysts for 2 years before buying a single thing. And all senior risk managers would have to have at least 5 years trading experience.

If you're in an M&A or sales role then it's harder to see how a move into trading would make sense, but then these are worlds I know almost nothing about so I can't really comment.

Again it's harder to get into the buy side, and you can move from sell to buy side; with the reverse move being slightly easier.

Overachiever (dark blue and purple)

A very small number of people will go straight on to jobs on a sell side trading desk (although initially it's likely to be very junior, with relatively small budgets). An even smaller number of people do the same on the buy side.

Clearly this is the dream ticket, but you shouldn't pin your hopes on it. It really is very difficult. You should have a plan B in case this doesn't work out, like another front office job.

You can move from sell to buy side; with the reverse move being slightly easier, yeah yeah you know this by now...

There are some lines that might seem odd on the graph; from sell side trader and portfolio manager back up to independent trader. Well it's pretty simple; these are very well paid jobs. Which means trading independently is possible; and you're probably going to have the skills to do it pretty well (although the move is slightly harder for sell side traders who may find their trading strategies don't work so well when not embedded within the customer flow of a banks market making).

Final advice

If you really want to be a trader the easiest route is as follows:

• Go to a really good university and get good qualifications
• Get a sell side front office role that will put you near the relevant trading desk
• Move to the relevant sell side trading desk.
• If desired a move over to buy side portfolio management can follow
• At this point if you're any good and you don't blow your bank account on frivolous pursuits you'll end up with enough money to trade independently, or spend the rest of your life at the beach if that is your thing.

Finally, if you're curious, and in the interests of full disclosure, below is the route I took:*

* I had a 2.5 year break from finance when moving from the sell side, to buy side fund manager...

Make of that, what you will.

Best of luck to you all in whatever career you decide to pursue.

"Systematic Trading" - the book - now available to pre-order

Isn't it pretty?

The website, and pre-order page, for my magnum opus are now ready:

www.systematictrading.org

http://www.harriman-house.com/book/view/4598/trading/robert-carver/systematic-trading/

Like it says on the back

"This is not just another book with yet another trading system. This is a complete guide to developing your own systems to help you make and execute trading and investing decisions. It is intended for everyone who wishes to systematise their financial decision making, either completely or to some degree."

I couldn't have put it better myself.

Remember this blog is free. It has no ads. I don't sell trading courses, newsletters, or do coaching. So if you appreciate it, please buy the book (which will have the added advantage of hopefully significantly improving your trading or investing).

Now if you'll excuse me I just have to finish the tedious task of proof-reading 325 plus pages, so you can actually get your hands on it in the near future...

Should billionaires and bricklayers have the same investments?

I permanently cut my the risk of my trend following futures trading system last week and invested my profits into bonds, because I was feeling richer. Let me explain. why...

The basics

There are many ways to measure risk. My favourite is the expected daily standard deviation of your portfolio returns, and I usually look at the annualised version of this - multiply by 16. Until recently I was targeting 50% a year (or about 4% a day). I hasten to add that I only have a fraction of my net worth in my futures trading system - this would be an inappropriately high level if it was my entire asset base. I've now cut it to 25% a year, which is closer to the 10 - 20% that most systematic trend following firms target.

It's a well known result that to be consistent with the continuous Kelly criterion you should target the same standard deviation as you expect your Sharpe Ratio (SR) to be. I'll talk about what the right Sharpe Ratio might be in a moment.

So if you expect a SR of 0.5, you should run at 50% annualised risk. However that is a little bit rich for me, and for any sensible person. Consider the following graph:

Recovering the Kelly criterion from simulated data. Source: Author's research.

Focusing on the blue line for the moment (apologies to the colour blind, it's the middle one once we get to the right) you can see it peaks at around 0.50, or 50%, which is Kelly optimal for a portfolio (trading system, or long only portfolio with one or more assets in it) with a true Sharpe Ratio of 0.5 as we have here. However suppose you don't know what your true Sharpe is, which is the normal state of affairs.

Suppose you think that your SR is 1.0, in which case you would be betting at a risk target of 100% annualised risk. As the picture shows if the true SR is really 0.5 you would on average lose money in the long run, and in many cases you'd lose a lot. A far safer bet is to run at 'Half-Kelly'. Expecting a SR of 1.0 you'd run at 50% risk. If you thought you'd get a SR of 0.50 as in the graph then 25% annualised risk is fine. This isn't optimal, your average annual return will be about a third less than 'Full Kelly', but it's better than risking too much and ending up on the right hand side of the peak.

That is the result for a normal asset with symmetric returns. The other two lines show you the results of different kinds of assets. The green line (bottom line on the right) is for a negative skew asset - like a trading system that sells volatility either directly or through running relative value type trades. The red line (top line on the right) is for a positive skew asset like trend following. As you can see the negative skew asset becomes toxic much quicker than the other two.

Overestimating the Sharpe ratio of a negative skew asset and Kelly betting accordingly is a one way ticket to bankruptcy. This is made worse by the fact that these strategies normally have quite low natural volatility, so to get up to the likes of 50 or 100% annualised risk they will need enormous leverage.

In contrast the positive skew asset is relatively benign at larger risk percentages. It's still better to run at the optimal Kelly, and safer to run at half Kelly, but running too much risk isn't quite as damaging.

What is a reasonable Sharpe Ratio to expect?

All this is well and good but what sort of Sharpe should we expect? Most people would at this point just get some estimates of past returns and volatility, or if you run a trading system you fire up some back test software. Two reasons why you should take what comes of this with a pinch of salt.

Firstly asset returns in the future are unlikely to be as high as they were in the past. Take stocks. Even with the financial crisis over the last 40 years they have done pretty well. A good chunk of that comes from effects that won't be repeated (falling inflation) or could well reverse (rising proportion of GDP as corporate profits, rerating of earnings:price ratios). This also affects trading systems, since if assets have generally been going up then trend following for example will work better.

The second problem is most back tests are overfitted. Unless you've genuinely put in the first set of trading rules you thought of, not looked at the performance, not thrown anything away; and done a pure backward looking optimisation. Even if you do all of these things chances are you're still using trading rules that somebody else has come up, using past data or experience.

You can either apply a very sophisticated method, adjusting past asset class performance to take out secular effects and using statistical techniques to estimate the effect of overfitting, or just use a reasonable rule of thumb which is to cut the expected back test performance in half.

In long only world for a single average stock a SR of 0.2 is likely. For a diversified portfolio of equities you could get up to 0.3. Diversifying across asset classes might get you up to a SR of 0.5. Adding a trading system on top of these numbers could half again; with a mixture of styles you could probably double this.

For a very well diversified system like mine (45 futures markets over all major asset classes, 8 types of signal over three different styles) then backtested SR of 2.0 translate to an expectation of 1.0.

Unless you're in high frequency world, and benefiting from low latency technology or have market maker advantages, then I don't believe a SR above this is realistic.

So far I haven't justified why I cut my annual risk percentage by half, since if I was expecting a Sharpe of 1.0 then my 50% target was probably okay. So now we need to think about how wealth influences risk taking.

Should wealth determine the amount of risk you take, and the kinds of investments you have?

Economic theory generally assumes constant relative risk aversion. This would imply that wealth doesn't affect your desire for risk. A bricklayer who somehow managed to come a billionaire would maintain the same level of risk as a percentage of their portfolio. Financial theory also assumes that everyone should have the same portfolio of investments, with the highest possible Sharpe Ratio, and then leverage as required to get the risk they want.

I am not picking on bricklayers for any reason, except for the alliterative opportunities they offer here.

In practise this doesn't seem to happen. For example under prospect theory the bricklayer would probably become more risk averse as they get richer, for fear of losing their new found gains. Secondly most people also aren't comfortable using leverage, except when buying residential property.

Imagine you're a 64 year old bricklayer, who will be retiring next week. You only have a state pension and no other investments, except £10,000 in cash. Economically you own an annuity (the pension) worth perhaps £180,000 plus the cash which is 5.3% of your net worth.

Is the best use of £10,000 to invest it in a Sharpe ratio 1.0 opportunity which will return 10%, or to buy lottery tickets? The latter is more likely and also makes more sense. £1,000 isn't going to make any difference at all (adding 0.53% to wealth, and if invested risk free about the same to income). But in the 2 million to one or so chance of a lottery jackpot and winning £10 million the bricklayer could be much better off.

Point one: people who don't / can't use leverage and need / want high returns will pay for risky investments - lottery tickets, growth story stocks, 100-1 horses - even if they have a negative expectation.

If the bricklayer could infinitely leverage up his £10,000 the lottery ticket would make no sense as it would be dominated by a leveraged form of the SR 1.0 investment. This could net him £10 million (a leverage factor so large I can't be bothered to work it out) with a positive expectation. But that would be well beyond half or even full Kelly. Betting at half Kelly - five times leverage - would still only expect to earn £5,000 again - not enough to make a huge difference (2.5% of wealth). It's more likely the builder will bet beyond half or even full Kelly, even if they don't go all the way to lottery like levels.

Point two: people who have a low level of financial wealth, which is dominated by other income, will often use too much leverage or go for riskier investments.

Now suppose you are a billionaire, with a billion quid, and 5.3% or £53 million spare. You could certainly afford to throw it away on lottery tickets, or buy a football team, both of which have negative expectation. However it's much more likely that you will put it into the SR 1.0 investment - that after all is how you became rich, not by making stupid financial decisions but by making good ones.

Or maybe you inherited the money, in which case good decision to be born to the right parents. Go you!

I also think it's much more likely that you will be very cautious, investing at most half-Kelly, and probably not even leveraging at all. You don't need the extra income, so preserving your wealth is more important than taking additional risk to get it. This is why rich people like investments with consistent returns. Prospect theory tells us that fear of losing new found wealth makes people more risk averse than if they are trying to recover gains.

This also opens things up for the billionaires. They can invest in high SR, but low return, investments that other people would spurn.

This effect applies to all levels of wealth. Now hopefully you understand why after a good run on the futures markets I wanted to lower the risk of my portfolio, by scaling back on my leveraged derivative exposure and putting the money into relatively low risk bonds.

Point three: As people get more wealth they become risk averse, able to invest in low risk but high SR investments, and they use less leverage.

Let's get a bit more sophisticated...

Apart from risk preferences can we say anything else about preferences for different wealth levels. I was inspired to write this post by the following which also generated some discussion with my ex colleague Matt. The paper argues that wealthier investors are more likely to be 'value' investors, whereas others are 'momentum' investors.

By cutting my exposure to momentum (which I did before reading about the Lettau et al paper) I have definitely followed this track, at least to a degree.

The authors postulate that investors with different wealth levels are hedging different risk exposures that they already have.

"Thus shareholders in the bottom 90% of the wealth distribution may seek to hedge risks associated with an increase in the capital share by chasing returns and sticking to stocks whose prices have appreciated most recently. On the other hand, those in the top 10%, such as corporate executives whose fortunes are highly correlated with recent stock market gains, may have compensation structures that are already momentum-like. These shareholders may seek to hedge their compensation structures by undertaking contrarian investment strategies that go long in stocks whose prices are low or recently depreciated."

There may be other reasons. It's possible we can wrap this up with what we already know from above. Pure value strategies are relative value, exactly the kind of high SR, naturally low risk strategy that rich people like. Momentum strategies tend to be have higher natural risk, due to low futures margin and the positive skew that means you can safely run higher risk targets.

Another explanation relates to liquidity. Billionaires are more likely to be owners of 'patient capital', money that can be tied up for years or decades in family trusts. Value strategies - buying stuff that's cheap - particularly illiquid stuff like private equity or land - do better if they don't have to suddenly liquidate after losses due to redemption's by impatient investors. Again momentum strategies tend to be in more liquid futures which for the common or garden retired investor who relies on regular returns for income is a good thing.

Concluding thought

Although the story in the paper is an interesting one, and might have some truth to it, ultimately having a good mix of investment styles is undoubtedly better than favouring one or another, and will give you a higher Sharpe Ratio overall. So although getting a little bit richer might be a good excuse for reducing your risk appetite and leverage, it doesn't justify trusting all your money to one investing style.

Why you shouldn't employ too many geniuses

"First class people hire first class people; second class people hire third class people" A famous quote, source unknown. Since presumably you are a first class person (otherwise you couldn't understand this blog) you must want to hire the smartest people you can? Right?

Wrong. I think there may be serious issues in hiring too many really smart people. This is especially the case if by 'smart' you mean 'academically gifted'.

Although these observations are based on working in the quantitative finance industry, to be precise a systematic hedge fund, they probably hold up elsewhere. This is especially true in similar industries where intellectual prowess is perceived to be particularly important.

First personal disclosure. I am pretty clever (137 Stanford-Binet if you care), but have had the experience of working with much cleverer people. Probably I would be lucky to be in the 25th percentile by IQ of the research and technology group where I was working (versus around 1st percentile in the general population). So I know exactly what I am talking about. Genius friends of mine reading this article will hopefully not be offended (and at least pleased I consider them to be geniuses). Of course since this article is full of gross generalizations it doesn't actually apply to you.

Now let's see why having too many super bright people is a problem.

Genius overconfidence

I am very interested in the cognitive biases that underpin the various facets of behavioral finance - the field which explains why people do not conform to rational economic behavior when trading and investing. The most potent behavioral bias in our brains is overconfidence. It leads to poor decision making, most markedly in decisions about money.

Now who is more likely to be overconfident, an average person or a genius? Ignoring delusions of grandeur  its probably going to be the genius. I have yet to meet a super bright person who is not aware of their high IQ, although many of them play it down in public so that some of their friends will continue to invite them to parties. Very clever people often have collections of academic qualifications and prizes that reinforce their self awareness of brilliance.

Most ironically are people who are extremely clever and also have advanced training in statistics or econometrics. This should lead to a deep suspicion of all statistically driven research as being potentially over fitted. Even when it does this suspicion rarely extends to their own research. Unfortunately most very able econometricians only gain in their ability to over fit in more complicated ways.

One way to combat genius overconfidence is to employ a range of abilities. Then at least the more stupid people (like myself) will have a stronger sense of their own deficiencies.

Genius group-think

When people go out and hire very clever people they tend to be fishing from a very small pool of graduates from elite universities. Elite universities at least in the social sciences have a habit of churning out people who all think in exactly the same way. Thus LTCM hired both Myron Scholes and Robert Merton - both geniuses. But that is like hiring the same person and paying them twice; when they might have been better off getting in some people with more heterodox views on financial economics.

Geniuses like other people also generally prefer to hire people with similar outlooks and prejudices.

The sense of collective brilliance can reinforce overconfidence when geniuses agree with each other; thus "We are all so clever that we must be right" (Thus the danger if you have all the smartest guys in the room in one room).

If you have some average people in the firm with your geniuses then you do have the problem that the mere mortals can be dazzled by the brainpower of the elite, leading them to agree with the most ridiculous notions just because someone very clever thought of them.

Geniuses are hard to manage

They refuse to do 'menial work'

Or in the words of Marvin, the paranoid android:
"Here I am, brain the size of a planet, and they ask me to take you to the bridge. Call that job satisfaction, 'cause I don't."

This is most usually a problem with very junior geniuses who think that their raw brain power should immediately put them in the job description of 'pure thinker'. They fail to realise they have to learn about the business and real life in general before their massive collection of neurons is likely to come up with any thoughts that are actually relevant or practical.

They go off on tangents

"Yes I know the client's project is late but I had some interesting ideas about solving the Riemann hypothesis using non Euclidean geometry and a Rubik's cube"

This is a difficult one because the only reason to employ geniuses (apart from gaining an edge in inter office quizzes) is often that they represent 'Out of the money options' - every now and then they will come up with some completely blinding off the wall idea that nobody else could think of. This one idea could easily pay the genius' salary for 1000 years. However you have to be able to spot it, and fend off the resentment from everyone else who is picking up the slack until it arrives.

They can't easily communicate with 'dumb' people

Geniuses find it difficult to articulate their ideas because it means slowing their brains down and trying to get the idea out before another one arrives. Its terribly boring trying to get some thicko to appreciate something that should be pretty obvious to any half intelligent person.

Note: This also makes it hard to distinguish geniuses from people who are just bluffing.

Genius support staff

All of the above means for every genius you need to hire three 'normals' - one relatively stupid person to do the menial work, one clever person to do the work the genius was supposed to do, and one person just below genius level to act as an interpreter.

Genius academic / theoretical bias

Geniuses tend to be attracted to paradigms that require high intelligence to understand. So highly complex models, academically 'sound', very theoretical ideas and anything with loads of unnecessary maths are all favored above more simplistic tools. Even if they are either pointless or downright dangerous.

Rewards to genius less than expected

In my previous career I was forced to repeatedly watch whilst sales people bragged about how many Phd's we employed (lots). This was a bit weird as I myself lack the crucial doctorate. But also as alluded to above I do not think that there is a direct correlation between having highly intelligent people and making profits.

Here is a quote from my current favorite book Daniel Kahneman's Thinking Fast and Slow:

'The most potent psychological cause of the illusion is certainly that people who pick stocks are exercising high level skills.... All this is serious work that requires extensive training... Unfortunately, skill in evaluating the business prospects of a firm is not sufficient for successful stock trading, where the key question is whether the information about the firm is already incorporated in the price of its stock. Traders apparently lack the skill to answer this crucial question, but they appear to be ignorant of their ignorance.'

Or to put it another way just because you are highly trained / clever does not mean you will be a great stockpicker, or indeed create fantastic models to pick stocks.

As far as I can tell success in research often comes down to a combination of luck and effort, once you have researchers with a baseline level of intelligence, skills and knowledge (which admittedly could be quite a high baseline). In quantitative finance its probably even worse; putting more effort into research often just results in more finely over fitted models.

In my field of interest employing a bunch of moderately clever people is necessary to create a half decent basic trading model. But the marginal gains of then adding a series of very clever people is probably small and even negative. The business success of that model will depend on having less academically gifted people with a variety of skills. Sadly these kinds of people are often neglected in the hunt for academic rock stars that it is assumed bring success.

To conclude

Of course none of this means the optimal business strategy is to hire a bunch of stupid people who will obey and bow to your superior intellect. But a nice blend of street smart, and practical pragmatists (with perhaps just the one Nobel prize winner) is probably much better than a room full of Phd's.

Why black box hedge funds should have lazy risk managers

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!