Tag Archives: TA-Lib

Popular indicators from TA-Lib Python wrapper

Different analytical indicators

Popular indicators were introduced from 2 recent videos. These were from the TA-Lib package Python wrapper.  I further tested to see which indicators could be found useful. Although, I would give you a different answer from my recent analysis video where I demonstrated popular indicators Williams R% and Stochastic, you would think everything looks clean. This is just another way of saying they do not lag when they change direction at fast timeframes like Tick or 1 Minute. I really emphasized the importance of this in the videos.

Different results vs Dukascopy JForex

I went ahead to start analyzing the same indicator with exact timeframes using TA-Lib within Python. As compared from within Dukascopy JForex, It seems I got different results so I tested a complete pile of them. This included:

1. Stochastics was just to jumpy to work with any form of trend.

2. Beta was more consistent which did not move around as much.

3. Williams R was again to volatile (in short periods) moving between in upper and lower ranges

4. Linear Regression and Chaikin A/D Oscillator was the same effect as Williams R

The only ones that seem to work were the popular indicators which include:

1. Normalized ATR

2. SMA

3. Bollinger Bands

4. Rate of Change Percentage

As a result, I will stick these 4 above to find out the magical combination. There are others to pick from within TA-LIB but I find you want to keep the combination simple. This also is important to really understand how properly interpret the unpredictable indicators I list above.

Next steps and considerations

I need to show how to  properly implement these but it depends when there data stored eg. database vs flat file. It looks the simplest is to use CSV with multiple instrument access is less utilized on the computer hardware front. You can obviously understand hoq critical these decisions are for when using an interpreted scripting language like Python.

There will be lots more to report as I continue along. Do note I find working with Python is much more product than Java within Dukascopy Jforex API.

Package info https://github.com/mrjbq7/ta-lib

Williams % and Stochastics most reliable Matlab technical indicator

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Technical Analysis trading with TA-Lib with Python

How to use TA-Lib with Python for technical analysis trading

This video will highlight the need of using a hopeful reliable technical analysis indicator library. My video explains the history of how this library was built and used in other popular projects.

Correct technical analysis indicators 

I could go on and on about technical analysis but I do find it useful for timing your positions including entry and exit. In past videos on testing visually various technical indicators with JForex, you will clearly see why I use this process. For instance, I thought linear regression would be useful. By checking visually on charts, it clearly showed  clearly how this indicator was not right. It was too sensitive on potential market direction at low levels e.g. 1 minute timeframe.

Technical indicator lessons

Using the chosen indicators it clearly  showed how they are not as sensitive/noisy nor lagging. This was an important eureka moment.  It is unfortunate I spent too many weeks to figure this out. Logging your positions in full detail of the indicators results you want to use is very helpful.  This is a critical process you need to understand instead of guessing where your trading positions results will end up. Many retail traders will never to get to this point. As a result, it does help to have this point of view when testing your trading ideas.

Python faster to develop with 

Also, the difference between developing 100% in the JForex API is very time consuming. As you get more confident with Python. you will be able to bang out trading scripts much faster. You will n longer be bogged down by the limitation of a broker or their API. As hinted in my video, this is why I would prefer to have all the market and trading data in one central hub (eg. Redis or CSV).  Once again, i cover this in my video.

Here is one benefit of using Python for my own development!

I now have the ability to fully backtest with the backtrader Python package as opposed to what I did in the past.

Here are the links from the video

https://github.com/mrjbq7/ta-lib

https://mrjbq7.github.io/ta-lib/func_groups/momentum_indicators.html

Create powerful trading robots with JForex API

#1 goal in forex trading is not to lose money but profit is 2nd

 

 

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TA-LIB for C and C++ is best open source code library yet for technical analysis and any trading inidicator

TA-LIB for C and C++ is best open source code library yet for technical analysis and any trading inidicator

I am looking at this for the purpose of understanding simple strategies. The first I plan to implement is easily the simple moving average or other types. This library has many of other types you would never know about.

Here is the list of functions:

http://www.ta-lib.org/function.html

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To implement forex trading strategies in C++, you need TA-Lib for technical analysis library

To implement forex trading strategies in C++, you need TA-Lib for technical analysis library

Check out the functions available here:

http://ta-lib.org/function.html

It seems easy to implement but the latest forex strategies I listed uses mostly technical analysis not quant. Sorry about that one.

There appears to be a Matlab one as well:

http://sourceforge.net/projects/mlmechtrade/

 

NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!