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Simple management of money wins over time

The difference between a good trader and a losing trader does much less than you might think about the successful trader being able to pick winners. All traders will experience losers and many. It’s a simple management of money wins over time.

A winner, however, understands that an important element of any trade is randomness – indeed, on a certain level, any trade is a gamble. Losing trade is inevitable and the winner takes account of this inevitability. Many successful managers have achieved it with a winning percentage just above 50 percent and even the best traders are only about 60 percent correct.

However, it is not necessary to achieve this success rate in the long term. It doesn’t even have to be 50% correct (see “Win some, lose some,” below). The scenario shown assumes a 40 percent win rate – in other words, eight out of 20 winning trades. The key to a 40 per cent winning rate is to structure your trade to make your winners at least twice as profitable as your losers are – and to keep your initial stake from unavoidable losses.

Many ill-informed analysts have said that Jon Corzine, a former MF Global Head, could finally be right in his foreign bond positions. No, no, no, no, no. You don’t just speculate in the direction of the market when you are taking a leveraged position, you make a market timing decision and position on volatility too. You limit how far the market can go before you have to bail out.

Take the assumptions in our table into account. Our hypothetical winning trades generate a profit of 2 000 $, which is half the losing trades. Of particular significance is that while 60 percent of trades are losers, the total balance is $4,000 after 20 trades. At one point, however, the total balance was $4,000.


In fact, the order of winners and losers has a significant impact on the way your account grows. In “Splitting our losses” (below), we show the same winning rate of 40%, but the sequence varies with a string of six winners that separates two large blocks of losers. The final profit is the same. In this case, however, we only received a drawdown of $3,000.

Why losers are losing

The problem here should be clear. You cannot predict the order of businesses and have to be prepared for the worst. Say you start with $8,000, and you need at least $2,000 to do every trade (the initial margin requirement). You are broken if you have eight losers in a row. In fact, you are shut down six losers in a row, taking account of the fees. You can’t last the entire 20 businesses. Instead of making $4,000, massive losses will stop you when your account falls below $2,000.

The worst scenario is that 12 straight trades may be lost and 8 straight winners will be hit. In other words, you would need more than $14,000 (losses plus initial margin) in order to even start trading to make the $4,000. The probability of such a loss string is remote, but it can happen.

This is why most traders end up losing. They don’t allow a large string of losing trades to happen. The truth is that while the worst case scenario is unlikely, something is relatively likely to occur. Over time, it is a virtual certainty that all traders will suffer a long series of trade losses somewhere.


Classes to win

It is not that difficult to develop a trading strategy with a 40 percent win rate, however. Trades producing a two-to-one profit/loss ratio are not as difficult to structure. Since the only factors which prevent a trader from succeeding in the long term do not begin with a sufficiently large account size and succeed in the temptation to over-trade.

In the first example, the trader required $4,000 more to make the business than the margin requirement. In the second example, an additional $3,000 was needed. With 12 direct losers and then eight straight winners, in the worst-case scenario, the trader would need $12,000 more than the initial margin.

To show this, consider a way to achieve the desired minimum performance metrics: 40% wins and a two-to-one winning ratio. Our tests cover the future of the dollar index from January 19 to June 3, 2011. The rules are straightforward. We bought or sold the closure on the basis of a coin flip on January 19. Heads we buy, and tails we sell; coin toss was heads in our test, and so we buy.

Regarding the profit/loss ratio, if two standard deviations in price move in our direction, we take profit and start an opposite trade. If the market is moving against us with a standard deviation, we lose and start trading in the other direction. Our strategy is designed to achieve our goals by managing our profits and losses. The first coin flip just gets us into the market objectively.

The objective of this strategy is to make two standard deviations if we win. If we lose, one standard deviation will be lost. (A standard deviation is a statistical pricing or volatility measure and is available in virtually all charting programmes.)

Understand that this approach can only be demonstrated. The purchase and sale take place in this way to reach a two-to-one profit/loss ratio. There is no reason to assume that the businesses are going to work because the only logic is a volatility measure to set profit and loss points at the desired level.


Results of the test

The results of this one demonstration confirm that the most important thing about a strategy is to size the account so that a number of losers can be allowed—that is, adequate financing. It is far more important than selecting winners (see “Random results,” below).

The margin for the dollar index is about 2.000 dollars, and the first trade was a loss of 840 dollars. In fact, we would start with an even bigger security account and use our base number for $3,500.

Five were winners and eight were losers of the trades that were made. This is a win rate of about 38 percent. The overall profit was $920, or on average $204 a month. The average loss was $572 and the average winner $1100, so we reached the target of a two-to-one profit-per-loss ratio. Projecting the same results over a period of 12 months would generate $2,448 in profit, or an annualised return of about 70 per cent on the initial account size.

We have also tested the results of this approach, based on the initial coin toss with a tail. In other words, the first business was a sale, the second trade was a buy, etc. These results are also displayed in “random results.”

The strategy works much better from selling rather than buying. The income was $5,200 instead of $920. There were a total of 17 trades and 9 winners — slightly better than 50%. The winner averaged $1,032, and the loser average was $5,11. The annualised return of $3,500 as an initial balance is 396 percent (and unlikely!).

Interestingly, “Random results” show that the last three businesses were the same in the examples. Our strategies converged, in other words. This is because interim volatility levels that trigger a loser’s opposite trade may not trigger a winner. In the first hypothetical scenario it would allow the winner to ride, while the other scenario would have changed direction. If the next move is sufficient to hit the trigger for each one, each strategy stops and moves in tandem. (It’d be interesting, in other markets and timeframes, to test this approach to see how long the scenarios would take to converge under other circumstances.)

What is important

For all traders, the trading structure and money management are crucial. Future markets are moving with a steady flow of opportunity, but the techniques used to capture this movement are secondary to a proper trading structure and beginning with sufficient funds to deal with drawdowns.

The entry and exit of a trade is not a system that makes you money in the long term if you do not follow the rules of the trading structure and management of money. The system will eventually disintegrate and you will suffer a string of losses. Accept this and plan for it, and you are going to enter winning traders’ ranks. Ignore these facts and the majority of traders who lose will remain.

Our objective is not to replace a signal generation programme with a random model, but to emphasise that correct risk management and size-fitness is as important as signal generation.

The discussion was about a broad framework for market success, but remain in a proper debate to formulate a workable strategy. In particular, they include how to determine the worst scenario of how sufficient capital can be allocated. In a future article, we will examine this.

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