Many speculators will happily say that they would never enter into a trade if they didnt think they were right. As such they believe that there is very little chance of error. On the surface it seems a logical thing to say; if you thought you were wrong then you wouldn't take a position in the first place.
However this black and white attitude is at the heart of many peoples losses. As most experienced traders will admit, losses come thick and fast and the good trader is the one who makes a profit on balance.
Not taking losses is often put forward as a classic sign that an investor or speculator is doomed to fail and a stop loss is often proffered as the first line of defence in risk management. A stop loss is meant to ensure that a trader is profitable by ensuring losses do not run away with the traders capital.
However a lot of nonsense is talked about stop losses and in a vacuum a stop loss system is at best a neutral strategy but in practise, due to costs, a slightly negative one. Stop loses are not a method for just dropping your bucket into a lake of money, if they were it would all be siphoned away already.
Simply put, the efficient market hypotheses state that there is no free money to be made in the market and a robotic stop loss system cannot add to a traders returns unless he is already trading so badly he is doomed anyway. If you can apply a rule robotically then a robot can do it. However a robot will do it faster or cheaper than you and take all the advantage.
Schemes of stop losses that require running profits with tight stops for a contra move, call for the trader to know the underlying trend in order to make a profit from it. In the end, selling in an unthinking way is as costly as buying arbitrarily. To make entry and exit points work, they must be based on something more than caprice.
Pooh-poohing stop losses is of course an anathema in many circles but in the muddle of pseudo science, that constitutes a lot of trading advice, it is not surprising that much trader law is also half right and half wrong.
As we will see later, it is the size and breadth of a trade that represents the core of good risk management, rather than cutting losses or running profits.
Risk management is about the avoidance of Gamblers Ruin and the optimisation of returns.
All that follows is underpinned by the idea that markets, liquid ones in particular, are in the main highly random. Randomness is not a term many traders or investors like to hear. Randomness is equated with powerlessness. How can a trader predict the market when it is random? This is of course a very interesting point, especially when you begin to crunch stock price histories only to find the bell curve of distributions again and again.
Below is an example taken at random from my records of five years worth of Dow moves between the open and the previous nights close. This normal distribution is the footprint of the Random Walk.
However lets leave the random argument to one side because in the end we accept that there is an average return paid to participants by the market for the provision of liquidity. Put another way, you should make a profit in line with the risks you are taking, if you didnt you would put your money in the bank and sit on your hands. While dreams of getting rich quick might recede at this thought, this is a good place to start anyway.
Risk management is the key to reaping return whilst avoiding disaster.
Avoiding disaster sounds like a good idea. So many traders and investors simply do not avoid disaster. This is often because they either dont understand the risks or do not know how its ramifications affect them.
Before going any further I want to address the Martingale. This is a technique of increasing stake size as a run of losses extends. Classically the Martingale comes into play with gambling games like Blackjack or Roulette, where a stake is doubled after every sequential loss. When a win is made, the player gets back his losses and earns a One unit win; the stake size is then reset. In theory with infinite money you will always end up winning in the end.
The Martingale and its many permutations have been, are currently and will be very popular systems for trading. While the Martingale works on paper it fails in practise. The flaw in the model is that in the end you will run out of money before your luck turns. Bad luck simply happens with greater regularity than the capital required to fund the operation can provide. I have actually witnessed red come up 23 times in a row on a roulette table, which, if I had been running a Martingale would have cost me 40m to win back my 1. Even if I had 40m, the table limit would have defeated me.
Another classic example of the impact of money management or lack of it were the stock market day trading systems run by unlicensed trading establishments at the turn of the 20th century called bucket shops.
The rules for trading were simple. For example, buy a 100 share on margin for 2. This 2, the so-called bootstrap margin also acted as a stop loss. If the share went down 2, the position was closed and you lost your margin money. This 2 margin/stop loss also represents a 50 times leverage.
If the share went to 110 or higher, you would make 10 or more. This sounds like an easy game; a fixed downside with an infinite upside looks like an offer too good to refuse.
However, volatility and probability are not your friends in this set-up. Even if the odds of this trade are slightly in your favour, on a random basis a price will at some point go below 100 around nine times out of ten. So with a mere 2 margin, you can get stopped out very easily indeed. Looking at this another way, if a price has a normal daily range of four points even in a sideways trend, you are going to be closed out every time. It takes a very strong jump for a stock not to hit 98 at some point in the future of the proceedings. One touch however and you are out. This is a microcosm of Gamblers Ruin and it is essential to avoid it. This of course was why bucket shops got rich and speculators got poor. Volatility is why stop losses in themselves can be toxic and are in no way a simple panacea.
So if stop losses by themselves are not the answer, what is?
Firstly lets turn our thoughts to a random game so as to avoid the consequences of an identifiable trend. Imagine a roulette table with black and red. Lets further say the wheel has 35 reds on it and one black, yet the payout is still even money. On this table we could make lots of money very quickly indeed, yet we can still lose everything. Lets imagine we have 100 £1 chips. We sit down and think about beginning to play. If we play £1 at a time we will make £1, 35 times out of 36, which whilst pleasant is hardly optimal. This table after all would be a way to get very rich very quickly. We could place £2 down and we would clearly make twice as much per go. With this in mind we could place £4 or £10 down at each turn and increase our profit per turn. However, the higher your stake the higher the probability that a run of bad luck will take all your money.
Lets imagine that this wheel is a mistake and that it will only be open for this single night and that £100 is all we have to play. We can be assured that if we do find a wrinkle in the market it will not last forever, so extracting value will also be against the clock. The question for us is how to make as much as possible in that evening.
The answer is not to put down the whole of your money on the red each time as although the chance of black coming up is low, it will come up. If it did we would lose all our money and would experience Gamblers Ruin.
You simply cannot play at the table if you have no money, no matter how lucrative the game. Yet somewhere between £1 a go and £100 on each turn, there is an optimal stake threshold, which maximises your return, yet avoids Gamblers Ruin.
The optimal stake pops up in different guises. In equities the stake limit is often said to be between 2.5% to 5% of your investment capital. In options trading, a rule of thumb says a trader needs capital of three times his maximum losing streak. The losing streak divided by the money lost would therefore dictate the position size.
Mathematically the rule is a lot more exact, it is expressed by the equation of Kelly's Optimisation Model. This model is often used in wagering but is just as applicable to investment. It assumes that the size of a positive outcome is the same as negative outcome in terms of quantity and as such is a useful outlet for stop loses.
P is the percentage probability of the outcome, so that if the probability of the trade being good is 52.5% (that is 5.25 times out of 10) then the Kelly model says you should put:
(20.525) - 1 of your capital on the trade. That is 1.05 - 1 or .05 of your capital or 5%
If your chances were 90% then you would stake: (0.92)-1, which is 1.8-1 or .8 or 80% of your capital.
While it is interesting to know exactly where results are optimal it is more important to realise that if you stake more than the sum given by this equation you are guaranteed to suffer Gamblers Ruin, or put another way, you are certain to go bust. It might take time but thats a probabilistic certainty.
If you were to use Kelly's Optimisation, the size of your positions would be right on this hair-raising make or break line. This is a pretty torrid place, so much so that many gamblers simply back 50% of this amount on the basis that they will still make plenty of money yet live a much more comfortable existence. In the case of our funny roulette wheel it only takes an hour or so to own the casino whether you back a half or a whole of the amount.
The kind of ruin we have avoided here is the disaster of compound events. We are in effect avoiding a run of bad luck on a single tack from emptying our pockets in a series unlucky turns. In this model our money is chipped away at while the majority of it lays dormant.
The sister technique to this is portfolio management, where the resources are spread in such a way that they are engaged in risk yet protected from what is known as unsystemic risk.
This unsystemic risk is for example that our wonky roulette table might attract the management of the Casino's attention and we might end up, up to our ears in a car park. To avoid a single disastrous event we must diversify our risks. Suffering Gamblers Ruin from a single disaster is what a portfolio approach avoids.
The subtle difference is that while Kellys optimisation applies to the allocation of resources for a single position, portfolio management describes the kind of simultaneous positions to carry. With diversification more money can be safely deployed and hence a better return made.
Portfolio theory once again does not require trending markets and merely considers that a market has a systemic rate of return. This rate is on average proportional to the risk involved with the instrument invested in. So for example the return on government bonds will be small as the risk is low but the returns will be higher for corporate bonds as they are riskier.
As risk levels grow for any one instrument, so does the chance of a big loss - but these instruments will be priced to take this into account and so will on average pay out more. The market pays us like we pay car insurance for our teenagers. As more teenagers will crash the premiums are higher.
The trouble is picking the risky stock that wont crash.
Rather than hire a financial genius to work out the best instrument, portfolio theory works on the basis of buying a bundle. This simply captures the average result. Advocates of the Random Walk state that this is the best you can do in any event as markets are just like teenagers in cars; impossible to predict. This technique will however capture the average return, as winners will counterbalance losers, as you will, like the car insurer enjoy safety in numbers.
Of course not holding all your eggs in one basket is hardly the latest of maxims, but depending on the volatility and hence risk of an asset the more of them that are held, the more certain your money is of growing at the systemic return. In equities this is considered to be upwards of 30 stocks in a portfolio.
You could use it to pick a portfolio of tech stocks in such a way, as you would receive the returns of the tech sector. This might be a nasty negative return, but at least it would reflect this market as a whole rather than risk a total wipe out on a single stock. It could also be used to capture returns on a whole market or perhaps the returns of a collection of markets or even a broad spread of different asset types. Portfolio theory enables you to slice and dice the risk return potentials of all kinds of markets, be they technical or otherwise. It is not simply of use to those wanting to safely wrap up their capital against catastrophe.
While it might seem that creating a portfolio is simply a way of destroying both the upside and downside of investing, it can be used to increase returns by giving a structure of holding extremely risky investments. To capture these returns the portfolio must be wider, so the most speculative investments would as a group perform extremely well so long as there were very many more of them. A few huge winners would outweigh the large proportion of losses and all in all returns should be a few percent higher than investing in blue chips. This is not free money, you are being rewarded for taking risk and providing liquidity, a portfolio is simply a method of smoothing out the volatility of that reward.
This of course is just like a full Kelly optimisation, one for the fearless, but then so is trading.
Clem Chambers is CEO of ADVFN,
Email: clemcham@advfn.com