I think you're avoiding the mathematics like the plague. Survival and hedges are structured strategies. Strategies have shape, form and consist of numbers. Repeatable numbers are what constitutes prediction. If you have the shape, form and numbers that are repeatable, you have prediction. Therefore, the data you just analyzed is not random. If it was random, your outcome would be random. And it's not.
I already answered your apple chart question. Globex was buying every dip and the institutions were liquidating stock (aggressively). They were selling into the bid all day. The news hit at the perfect time. There were 3 waves of buying on globex and the news hit right at the point of exhaustion of the third wave. I'm not using TA, I'm using quant modeling techniques. Not random to me but I dont buy price action blindly.
Thanks Real money, I bet you can give me a fable for Apples daily charts starting with January 2nd, 2019 to last Friday. Make a newsletter and tell me the story every day of Apples daily charts til year end. you’ll get buyers. Humans love stories.
Amahrix, Your post is very stupid and makes ZERO sense. You should be ashamed of yourself for posting such nonsense.
Nice edit? Here is the answer to your backtesting question that you deleted, imbecile. Problems with backtesting Excerpt from Fooled by Randomness. The hidden role of chance in life and in the markets.' by Nassim Nicholas Taleb. Page 134-136 A backtester is a software program connected to a database of historical prices, which allows me to check the hypothetical past performance of any trading rule of average complexity. I can just apply a mechanical trading rule, like buy NASDAQ stocks if they close more than 1.83% above their average of the previous week, and immediately get an idea of its past performance. The screen will flash my hypothetical track record associated with the trading rule. If I do not like the results, I can change the percentage to, say 1.2%. I can also make the rule more complex, I will keep trying until I find something that works well. What am I doing? The exact same task of looking for the survivor within the set of rules that can possibly work. I am fitting the rule on the data. This activity is called data snooping. The more I try, the more I am likely, by mere luck, to find a rule that worked on the past data. A random series will always present some detectable pattern. I am convinced that there exist a tradable security in the Western world that would be 100% correlated with the changes in the temperature in Ulan Bator, Mongolia. An outstanding paper by Sullivan, Timmerman and white goes further and considers that the rules that may be in use successfully today may be the result of survivorship bias. Suppose that over time, investors have experimented with technical trading rules drawn from a very wide universe in principle thousands of parameters of variety of types of rules. As time progresses, the rules that happen to perform well historically received more attention and are considered serious contenders by the investment community, while unsuccessful trading rules are more likely to be forgotten. If enough trading rules are considered over time, some rules are bound by pure luck, even in a very large sample, to produce superior performance even if they do not genuinely possess predictive power over asset returns. I have to decry some excess in backtesting that I have closely witnessed in my private career. There is an excellent product designed just for that, called Omega TradeStation, that is currently on the market, in use by tens of thousands of traders. It even offers its own computer language. Beset with insomnia, the computerized day traders become night testers plowing the data for some of its properties. By dint of adjusting the rules the trader will hit upon hypothetical gold somewhere. Many of them will blindly believe in it.