A cyclical historyWe have all heard that the economy works in cycles, and so does the market. But what does this truly mean? Has anyone actually been able to show you where you can see these cycles occur? Well, here is a great graph that will show you how. By looking at the 6-month time frame, the percentages of stocks above the 20 daily MA, you are achieving 2 things.
Seeing price action at the timeframe used to declare technical recessions
Seeing the percentage of stocks in a short term uptrend or downtrend as the complement is also true
Here it's quite easy to see how an important world event unfolded with a clear, repeatable pattern. When the percentage oscillates heavily, it allows for many technical resets, causing a healthy uptrend when the percentage returns to above 50% by the end of the semester. Another patter is that after a period of over-performance, a period of under-performance is followed and vice versa.
When looking at world events, just remember at the end of the day we are all a number in a larger scheme. And the laws of statistics will end up controlling our outcomes, as there must be balance in all binomial systems. Even when biases can be present in distributions, the more we generalize and zoom out, the more we can see the statistical convergences in human behavior. At the end of the day, our lives are influenced by fractals, some of which we are not even aware exist.
Statisticalprobability
How to read mean returns (Expand the indicator)Mean returns is a trend detection and overextension indicator. It oscillates around the value of 0. The mean return line in reality is the orange one as well as the blue one. The difference is in the number of data points into the past that they consider. Since the value of those lines is the expected value of the returns in period t, then if it's over 0 the expectation is that returns will be positive, as previously the price has been trending higher. The opposite being true as well.
Meanwhile, the red and green line represent the expected upwards and expected downwards returns. That means you only take the expected value for the days in which the return was positive or negative accordingly. Therefore, if the mean returns are over the expected upwards returns the price is likely to be overextended, and vice versa.
Other adjustments were made to consider the current candle. This code will remain private, as it took a lot of effort to invent. I hope you are able to understand the math. If you can't, I hope this at least allowed you to read the meaning of the indicator through this.
The most common malpractice in all of Trading: Back-testingGiven ANY in- or out-of-sample time series, including purely random, synthetic data, anyone can generate (inflate) ANY Sharpe Ratio by repeatedly applying different trading or investment strategies to the same time series sample!
By definition, purely random data has no discernible structure. Consequently, no method can exist to predict such a sequence - I.e., Sharpe Ratio = 0 must hold in all instances.
Yet, ... See main graph!
In the past It has been shown just how easy it is to generate Sharpe Ratios of 4, 5 or even >6, on any data, including on purely random, synthetic time series data when in fact, the only possible value in those instances should be S.R. = 0.
As a matter of fact, this misleading (self-defeatists?) practice is so common and wide spread in finance and trading that the American Statistical Association considers it "unethical" (American Statistical Association ). (More importantly, it is a remarkably expensive way to fool oneself.)
The above stems from applying the same rejection threshold for the null hypothesis under multiple testing will grossly underestimate the probability of obtaining a false positive.
Unlike in the "other sciences", there is no "replication crisis" in finance or trading, simply because such checks don't even exist there - since those would be impossible to carry out. (Is that why the only two kinds of academic papers which never get revised or retracted are written in the fields of Finance and Theology?)
The bottom line;
In the common case of testing a trading or investment system, given a set of out-of-sample time series, one MUST increase the rejection threshold for the null hypothesis in proportion to the number of times ("peeks") such tests are carried out! (Good luck fooling yourself that way!)
Anything less is just simple curve-fitting!
For more in-depth explorations:
Marcos López de Prado, Michael J. Lewis
codemacher.com
Statistical Probability of A Price GuessA price guess has 33% to be correct because the price has only three directions. The price of a security may trade higher, may trade in a narrow range, or trade lower.
Thank you for reading!
Greenfield
Disclosure: I am not a financial advisor. This is not a recommendation, not a representation, and not a solicitation. You should do your research and come to your own decision. Investment involves significant risks. You need to understand that you may lose your money. Past performance is not an indication of future performance. Chart reading is subjective information.
