# Tag Info

Accepted

• 12.2k

### Beginner FFT (Fourier) transforms on closing prices for Apple

The blue line that you have fit starts at 140 and also ends at 140 because when you fit a Fourier Series the signal is assumed to be periodic (repeated again and again) and continuous. 140 is a ...
• 11.4k
1 vote

### What is the common accepted/ best performed method to classify trends and mean-reversion for fixed peroid?

Up to interpretation, and specifics about this is generally not disclosed since it provides a real edge in trading. One common approach that use is Regime modelling using Hidden State Markov Models. ...
• 56
1 vote

### Python: detecting measured moves of candlestick data

I can only offer apriori solutions which are slightly overfit: to calculate the slope of N lookback periods and drop the ones that have a low and high std dev (how to determine low and high?) the ...
1 vote

### Python: detecting measured moves of candlestick data

You can use fractals to identify highs and lows. You can also measure movements as a percentage of the nearest extreme points. Here I showed how to find down fractals, and here I measured movements in ...
• 111
1 vote

### Identifying "logical" segments on trading charts

I don't know, because your chart shows no time stamps, but I'd hazard a guess that the first third is the "overnight" session after the New York close until the London open, the second third ...
• 2,159
1 vote

### Identifying "logical" segments on trading charts

You could look into the trend-scanning method which is described in a new book by Marcos Lopez de Prado, "Machine Learning for Asset Managers". Essentially you fit a linear regression to ...
• 155
1 vote

### Detect trend of an index

I think part of the problem may be a lack of a formal definition for what constitutes the trend. At least it lacks a definition of some kind of statistical property. (I was thinking autocorrelation ...
1 vote

### Determine trends of data (direction detection or turning point detection)

Your question is very general and I am sure it can be approached from different angles. Segmenting a time series as per the diferent components may help you to forecast each individua part also ...
• 436

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