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Why would Rich intentionally leave out important information and then give traders his own money for them to lose, not to mention losing his bet? There were no hidden secrets. The truth was that I actually used a much simpler trading method than most of the other Turtles employed. I traded using percent of my account allocated to the longer-term week breakout system.
This meant fewer trades and less monitoring of the markets. I certainly was not doing anything unusual or acting on information that had not been made public. Excuses, Excuses The idea that Rich had left out some key ideas was the easiest way for our paranoid Turtle to explain his inability to trade successfully during the program. This is a common problem in trading and in life. Many people blame their failure on others or on circumstances outside their control.
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They fail and then blame everyone but themselves. Trading is a good way to break that habit. In the end, it is only you and the markets. You cannot hide from the markets. If you trade poorly, over the long run you will lose money. Despite the obvious and unavoidable link between what you do and your trading results, some people still try to blame the markets. Although there is no question that there many traders endeavoring to take your money at any point in time, I have never seen any evidence of mass-scale collusion or fraud of the kind imagined by those who blame their failures on the market, their brokers, or other participants.
The bottom line is that you make the trades and you are responsible for the outcome. Blaming others for your mistakes is a sure way to lose. T rading is about buying at one price and then selling at a higher price later or selling short at a particular price and then buying to exit the short position at a later point. When they are determining when to enter a market, most beginners employ a strategy that is no better than throwing darts at the chart.
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Experienced traders would say that their strategy has no edge. The term edge is borrowed from gambling theory and refers to the statistical advantage held by the casino. It also refers to the advantage that can be gained by counting cards when one is playing blackjack. Without an edge in games of chance, you will lose money in the long run. This is true in trading as well. If you do not have an edge, the costs of trading will cause you to lose money. Commissions, slippage, computer costs, and exchange and pricing data fees add up very quickly.
An edge in trading is an exploitable statistical advantage based on market behavior that is likely to recur in the future. Simply put, to maximize your edge, entry strategies should be paired with exit strategies. Thus, trend-following entry strategies can be paired with many different types of trend-following exit strategies, countertrend entry strategies can be paired with many different countertrend exit strategies, swing trading entries can be paired with many different types of swing trading exit strategies, and so on.
Some concrete examples will help demonstrate this effect. The Edge Ratio E-Ratio When you are examining entry signals, you care about the price movement subsequent to the occurrence of the market actions that constitute the signal. One way to look at this movement is to break the price movement into two parts: the good part and the bad part. Good price movement is that which progresses in the direction of the trade.
Consider the case where a buy results in a price that initially moves in a direction that is bad for the trade, the price goes down; then it goes up and moves to a price higher than the entry price for the trade; after this move down, the price moves up for a while and then goes down again, as shown in Figure 5.
Traders refer to the maximum move in the bad direction as the maximum adverse excursion MAE and the maximum move in the good direction as the maximum favorable excursion MFE. You can use these to measure the edge of an entry signal directly. If the average MAE adverse movement was higher than the average MFE good movement , this would indicate that a negative edge existed. One would expect that a truly random entry would result in approximately the same good movement as bad movement. For example, take the case in which one bought if a coin landed heads up and sold if it landed tails up.
To turn this way of thinking about an edge of an entry into a concrete way of measuring the edge for entry signals, it is necessary to add a few more steps. First, you need a way to equate price movement across different markets. To normalize the MFE and MAE across markets so that you can compare the averages meaningfully, you can use the same mechanism the Turtles used to normalize the size of our trades across markets: equating them by using the average true range ATR.
To isolate the behavior of entries over various markets, it is useful to be able to compare the price behavior of an entry signal across different time frames. At Trading Blox, where I head Research and Development for a sophisticated system-testing environment, we have implemented an entry edge measure we call the E-ratio short for edge ratio. The E-ratio combines all of the pieces described above by using the following formula: 1.
Divide each of them by the ATR at entry to adjust for volatility and normalize across markets. Sum each of these values separately and divide by the total number of signals to get the average volatility-adjusted MFE and MAE. The E-ratio can be used to measure whether an entry has an edge. For example, you can use it to test whether a completely random entry has any edge.
The average of 30 individual tests showed an E5-ratio of 1. These numbers are very close to the 1. This is the case because the price is just as likely to go against a position as it is to go in a direction favorable to a position over any reasonable time period. You can also use the E-ratio to examine the major components of the Donchian Trend system.
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