There are some ideas out there that the market is like a collection of quantum events and that it could all be broken down into sine waves. I created this script to put that to the test.
The idea is simple, I tested 3 different factors that could be put into sine wave form.
1.) Bar Change 2.) Volume Average Change 3.) Coin Flip
For the bar change, I simply allow the sine wave to move upwards or downwards if the bars have changed color in their sequence. For example, if there were 3 red bars and 1 green bar, it would not move the sine wave up or down until the green bar appeared.
For the average volume change, it was the same idea, except that the sine wave could only move up or down if the volume had moved up or below the average value of the length given for calculating the average volume.
Finally, the coin flip simply simulates flipping a coin, and allows the sine wave to move one direction or the other once it has a side that is different from the previous chosen side. For example, heads, heads, heads, tails (once it flipped to tails, this would allow it to move a direction).
The sine wave trading theory that I watched claimed that if you know the correct sine wave # (which is how large the peak is, and/or the sine wave count which is how many peaks and valleys occur) that you can successfully predict future trades. Their claims that the reason it does not look like a perfect sine wave for these events is because there is different amounts of trading going on, thus the timing will be slightly off.
I am posting this to disagree with their ideas. For example, if you select to turn on trading for coin flip and turn off bar change, you will see the coin flip did better on the default settings!
It just so happens that any setting will eventually be good, making all the sine wave variations just completely random if you win or not.
I posted this to demonstrate how silly trading sine waves is. The real trick is using cosine and tangent waves... lol j/k
I hope this helps someone avoid this scam concept.
@chasinalts, In mathematics and statistics, a stationary process (or a strict/strictly stationary process or strong/strongly stationary process) is a stochastic process whose unconditional joint probability distribution does not change when shifted in time.[1] Consequently, parameters such as mean and variance also do not change over time.
Since stationarity is an assumption underlying many statistical procedures used in time series analysis, non-stationary data are often transformed to become stationary. The most common cause of violation of stationarity is a trend in the mean, which can be due either to the presence of a unit root or of a deterministic trend. In the former case of a unit root, stochastic shocks have permanent effects, and the process is not mean-reverting. In the latter case of a deterministic trend, the process is called a trend-stationary process, and stochastic shocks have only transitory effects after which the variable tends toward a deterministically evolving (non-constant) mean.
A_Traders_Edge
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@xmd1979, You just broke my brain my friend. So you're saying that you are able to predict where things will go with decent accuracy?