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he following recipes feature the detoxification superfoods discussed in this book. Where required for cooking, recipes include only healthy sources of fat, including flax, olive, canola, and sesame oils. Frying or charcoal broiling methods are discouraged and therefore do not appear in these recipes. In addition, these recipes help you avoid the dangers of overheating food while cooking, particularly meat, which as you now know can be the source of strong carcinogens. The Detox Revolution suggests saut ing at gentle temperatures. In some recipes you will learn the trick of adding a little water in the pan first, before oil is added, to effectively reduce the cooking temperature. This prevents the oil from becoming heat damaged. Some unusual foods are also featured in the recipes foods that may not be familiar to you. I hope you will enjoy the wonderfully protective foods and new cooking techniques. Remember to select organic ingredients and low-sodium products whenever possible, wash all fruits and vegetables, and keep portions small. Enjoy!

experiments; corrected for multiple tests (100 generations), the probability is less than 13% that the observed profitability was due to chance On the in-sample data, 1,244 trades were taken, the average trade lasted 7 days, yielded $3,6 16, and was a winner 45% of the time Both long and short trades were profitable Given the statistics, there was a fair probability that the model would continue to be profitable out-of-sample; however, this was not the case The model lost heavily in the out-of-sample period Equity rose rather steadily from the beginning of the sample until August 1990, drifted slowly lower until May 1992, rose at a good pace until June 1995, then declined These results primarily reflect the decreasing ability of simple breakout models to capture profits from the markets.

25 34

All currencies had positive in-sample returns and all, except the British Pound and Canadian Dollar, were profitable out-of-sample-confirmation that breakout systems perform best on these markets, perhaps because of their trendiness Curiously, the currency markets with the greatest returns in-sample are not necessarily those with the largest returns out-of-sample This implies that it is desirable to trade a complete basket of currencies, without selection based on historical performance, when using a breakout system Although this model performed poorly on oils, it produced stunning returns on Coffee (both samples yielded greater than 65% annually) and Lumber (greater than 29%) Tesf 9: Volatility Breakout with Entry on Stop This model enters immediately at the point of breakout, on a stop which forms part of the entry model.

These numbers were derived from appended data that re ect the age of the head of the household. The company also asked its customers what their actual age was. The results were quite different, as shown in Figure 14-2. Here the company s customers actually were quite young between 13 and 24. While Figure 14-1 gave the age of the head of the household, most of the company s customers were children in the

The advantage is that entry takes place without delay: the disadvantage is that it may occur at a less favorable price than might have been possible later, on a limit, after the clusters of stops that are often found around popular breakout thresholds have been taken out To avoid multiple intmbar orders, only the stop for the band nearest the most recent closing price is posted; this rule was used in Test 6 The volatility breakout model buys on a stop when prices move above the upper volatility band, and sells short when they move below the lower volatility band The optimum values for the three model parameters were found with the aid of the genetic optimizer built into the C-Trader toolkit from Scientific Consultant Services, Inc The smallest risk-to-reward ratio occurred with a bandwidth of X.

Figure 14-3

3, a moving average length of 11, and an average true range of 21 bars Despite optimization, this solution returned only 116% annually There were 1,465 trades taken; 40% were winners The average trade lasted 6 days and took $931 out of the market Only long positions were profitable across parameter combinations Both long and short trades lost heavily in the verification sample There were 610 trades, of which only 29% were winners The equity curve and other simulation data suggested that deterioration in the out-of-sample period was much greater for the volatility breakout model with a stop entry than with entry on a limit, or even at the open using a market order..

30% percent of total 25% 20% 15% 10% 5% 0%