The lesson I’d like to teach you today is that when you are confident about the trend over a good period of time, thanks to spectral analysis and other powerful indicators, even if your positions fall into the red for a while, don’t cut your losses! That negative period is nothing more than whipsaws and dips within the positive trend you identified at the start. Don’t get discouraged and don’t liquidate your positions, especially if you’ve taken on low leverage. Be patient and wait for it to turn positive again — your competitors in the market are just trying to play with your nerves. It’s a game of patience, and in the end, the most patient one wins!

Hello, I plan to rewrite a pure 64 bit C/C++ version of QChartist using QT Creator for the GUI.
I think this is the best option that will allow to make it cross os, making the app compatible with all os (mobile or desktop)
If you are a good programmer and interested to help me to build this project, please reply to this message or contact us.
Thank you

First find a good signal with the System #4 QChartist's Magic Hat Trick System

Then here is an idea to confirm the entry :

Yes — combining a Fast Fourier Transform (FFT) with the Hurst Cycles Spectrometer can be more powerful than using either one alone, but they serve slightly different roles:
1. What FFT brings to the table

• Broad-spectrum detection – FFT quickly identifies all periodic components in data, even weak ones, over a wide frequency range.
  
• Mathematically rigorous – It decomposes the signal into precise sine and cosine waves, giving clear frequency peaks.
  
• Fast computation – You can process large datasets quickly and spot new cycle candidates.
  

• Market-specific filtering – Hurst's approach is tailored to financial series, which are noisy and non-stationary, so it focuses on cycles that actually persist and matter for trading.
  
• Phase and translation to trading context – It ties cycles to timing models, peak-trough forecasts, and “nominal model” cycle families.
  
• Noise suppression – It tends to filter out meaningless peaks that FFT might still show.
  

• Use FFT as a scouting tool to identify candidate dominant frequencies.
  
• Feed these frequencies into Hurst’s spectrometer for deeper analysis, smoothing, and validation against price action.
  
• This two-step approach reduces false positives and gives both mathematical rigor and market relevance.
  

1. FFT Stage – Run FFT on your price data → note the strongest frequency peaks.
   
2. Hurst Stage – Use those frequencies as starting points → refine them, track amplitude and phase over time, integrate into trading cycle forecasts.
   
3. Feedback loop – Re-run FFT periodically to catch emerging cycles and retire fading ones.
   

• FFT is purely mathematical: it doesn’t “care” about market theory—it just decomposes data into sinusoidal components.
  
• Hurst’s spectrometer is market-aware and noise-tolerant, looking for persistent cycles.
  
• When both agree, it suggests the cycle is not just a random spike in the spectrum but a structurally persistent rhythm in the market.
  

• FFT alone can’t tell you where in the cycle you are—it only identifies frequencies.
  
• Hurst’s method tracks phase (peak/trough positions), giving actionable timing.
  
• Synchronization means your frequency detection and your phase model are aligned, so your turning-point forecasts are more trustworthy.
  

• FFT can be fooled by transient noise patterns.
  
• Hurst can be biased by pre-set “nominal cycle” expectations.
  
• When they independently lock onto the same cycle, the chance that it’s noise drops significantly.
  

• You can trade with the cycle’s rhythm, entering near troughs and exiting near peaks with greater conviction.
  
• You might also size positions more aggressively when both methods agree, since the statistical edge is higher.
  

• FFT Spectrum → watch for strong peaks that persist for several bars of data.
  
• Hurst Analysis → see if it confirms the same cycle length and shows favorable phase for entry.
  
• Trade Filter → only act when both are in sync, plus price action agrees.
  

Hello everybody,

i use the RQPC RapidQ Pre Compiler from Jacques and i compile C++ code in my RapidQ program.
But the problem is that i don't know how to link new libraries (flags) for the mingw G++ compiler that is used by RQPC.
For example if i want to link C++ OpenGL library in need to use the -lGL flag with G++
Can anybody add this functionality to RQPC that will allow to use custom flags for the compiler, this would help me a lot for example to use python code in my RapidQ programs. Jacques didn't share the source code of his RQPC unfortunately.

Thank you for your help!

In fact, to run a python code, i want to link the python library to g++, include my python code to example.cpp
#include "Python.h"
Py_Initialize();
and so on....
and then use rqpc to compile example.bas with example.cpp
compile example: g++ art_wrapper.c main.cpp -o main -lpython2.8
I know this is technically possible, so that i can use values of the variables of my python calculations directly in my rapidq.bas program
But to do that rqpc should be able to accept the option to include custom libraries to link with g++ (-lpython2.8)

I found a way to do what i want without modifying rqpc but it's a bit tricky.
For the moment, the only workaround i found is to rename g++ to g++2.exe and create a new g++ executable that will collect the command line arguments of itself (after %0 (g++ itself)) and that will execute g++2.exe with all the collected arguments + -lpython2.8
Then, when RQPC will call g++, g++2 (the original file) will be executed with the new flag -lpython2.8

Hello Jacques, thank you for your code of the g++.bat
I managed to make it work !

In fact RQPC needs a g++.exe so i had to convert my g++.bat to g++.exe with a bat2exe converter

I found this converter which works fine : https://github.com/tokyoneon/B2E
https://qchartist.net/files/utils/Bat_To...verter.zip

My g++.bat for example contains this line :
c:\myprogram\mingw\bin\g++2.exe %* -lopengl32 -lglu32 -lglut
rem So we add opengl C++ support to our RapidQ program

i rename the original g++.exe to g++2.exe and
i create a g++.exe with the B2E tool from my g++.bat

myprogram.bas contains the rapidq code:
''pre cmd FBVERSION=017 FBLANG=deprecated run enc noopt exe con NoDone icon myprogram.ico kill includes\cppincludes.cpp
''pre end
'Compiler Directives
$APPTYPE console 'GUI
$OPTIMIZE on
$TYPECHECK on
dim cpptmpfuncreturn as string
myvar = VAL(mytext.Text)
defstr myvarstr=str$(myvar):cpptmpfuncreturn=varptr$(setsomething(varptr(myvarstr))) ' we interact with c++ this way
and so on...

includes\cppincludes.cpp contains the c++ source code of our opengl program to include to our rapidq myprogram.bas :
// ''RQEXPORT function setsomething(parameter)
#include "includes\myopenglprogram.cpp"

then i compile my program with
rqpc\rqpc myprogram.bas

bingo

As Kucoin is currently under regulatory restrictions that impact their customers like us, we decided to move from KuCoin to Hyperliquid to continue our trading activities.

We regret to quit Kucoin because it was good as they have plenty of coins available, and now with Hyperliquid, we are limited to about 174 perp futures pairs. But that's how it is and we will try to do our best to make stable, regular and long term profits with Hyperliquid ; that we redistribute to the community.

All the best,
Cheers

You shouldn't try to teach something you haven't truly mastered.
Exactly. You're touching on a fundamental rule of intellectual integrity:

Quote:You can only teach well what you truly understand — and ideally, what you’ve personally experienced.

• financial losses
  
• loss of trust
  
• sometimes psychological damage
  

Quote:People sell a skill they haven’t proven in real life — which would be unacceptable in any other profession.

QChartist Community Profit Sharing Initiative

QChartist DAO - To create a transparent and decentralized financial ecosystem where the profits generated by QChartist TA’s trading operations are redistributed to the community in the form of QCH tokens or well-established cryptocurrencies such as TRX (Tron), LTC, or BCH.

QChartist DAO - QChartist DAO introduces a profit-sharing model that rewards its community members regularly, based on real trading profits and token economics.

Multi-token payouts: Members receive allocations in QCH or major altcoins, ensuring flexibility and real-world value. Solana-based QCH token: Fast, cheap Hybrid reward model: Combines QCH with external crypto liquidity. No need to trade:Holders earn passively from the team’s performance.

The QChartist TA team actively trades the markets. A share of monthly/weekly profits is converted to QCH, TRX, LTC, or BCH. Tokens are redistributed to users via airdrops. Users can stake, hold, or trade their tokens freely.

Intro : https://www.qchartist.net/blog/qchartist...in-crypto/
Join us : https://www.qchartist.net/exchange/register.php

If AI-driven charting tools are now analyzing patterns faster than any human, does that mean traditional technical analysis is obsolete? Or are we just overestimating algorithms and ignoring the gut instincts that make trading an art, not just a science?

Good news: CoinGecko datasource will soon be supported by qchartist

This idea to add this new data source came from the fact that i was not able to get the crypto chart of vault ai vaulta ausdt with the current available data sources of qchartist.
I was a bit fustrated that tradingview had this coin and even other new coins but not qchartist

Here are the python scripts in the attached zip file that will be used to get historical data and coin id list from the coingecko api.
You can already use them with your python interpreter and open the obtained csv in qchartist.

As you can see, i had to exclude the use of pandas and numpy modules in the scripts to avoid compatibility issues with python 3.8 w32
These modules crash when they are imported with the python distrib included with qchartist

To do so, i asked chatgpt to rewritte my python script without using pandas and numpy modules, the way the script functions exactly the same way.

to obtain a 1h chart: use python pcgeck.py with command line arguments --interval 5min --days 33 then use period converter of 12 in qchartist
to obtain a 4h chart : use python pcgeck.py with command line arguments --interval 15min --days 90 then use period converter of 16 in qchartist
to obtain a daily chart : use the obtained 4h chart and use period converter of 6 in qchartist

python pcoingecklist.py gets the list of all available symbols

All that will soon be implemented for easy use via the data source gui interface

Enjoy!

Attached Files

  pycoingecko.zip (Size: 2 KB / Downloads: 0)

Here is a simple diagram to explain how works the file structure and flow: