I'm very happy that I succeeded in importing Tick Data from MetaTrader 5 Strategy Tester.

This opens the possibility of having real-time, real-ticks, and real-spread testing in our next strategy builder and generator.

I already have a prototype of the data import.

How it works in my tests:

1. Run a special Expert Advisor on any symbol, M1, and "Every tick based on real ticks". It took 10 seconds for 5 years of tick data.
2. A tick data file is exported. Drag and drop it onto the new Strategy Builder Professional - 2 seconds for the import.
3. The Tick data are available within the program. Higher time frames are composed from the tick data. The data is stored locally in the browser.

Tick Data Import - 1.8 million barts

Higher Time-frame data composed from Ticks

A future version of the backtester will be able to open positions within the bars without ambiguity

Trade safe!

I was curious whether swaps change frequently and whether I need to use "real swaps" in my newest and greatest backtester.

I made a simple script to collect swaps from MetaTrader 5 for each day. It stores the swaps in a local database for later use.

I checked it today and noticed the swaps had already changed twice over the last two weeks.

I'll try to find historical information for the swaps and will use it in my next program.

Trade Safe!

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1. Candlestick Patterns X(more than 100 known candlestick patterns) This is actual a slight modification of the CandleStick Patterns indicator.
2. Candlestick Patterns
3. Candle Color Pressure
4. Candle Wick Pressure
5. Session VWAP CCI Stepped
6. Advanced Entry Hour Stepped
7. PivotPointsXStepped
8. AdvancedExitTimeStepped
9. SessionVWAPStochasticStepped
10. SessionVWAPATRBandsStepped
11. Session VWAP MACD Stepped
12. Session VWAP Bollinger Bands Stepped
13. SessionVWAPRSIStepped
14. Advanced SessionVWAP Crossover Stepped
15. Advanced Day of Week Entry Time
16. RecentSwingHighLowXStepped
17. AVWAP Crossover
18. AVWAP (Anchored VWAP)
19. SessionVWAPCrossoverStepped
20. SessionVWAPStepped
21. RecentSwingHighLowX
22. AdvancedSessionVWAPStepped
23. Moving Average of ATR Indicator
24. AdvancedSessionVWAP
25. VWAP Crossover
26. VWAP
27.  AdvanceExitTime.

I'd need a clarification about the logic of "N Bars Exit".

I attach a demo strategy example with Bar Closing exit condition and 2 logical groups:

a) with N Bars Exit = 1
b) with N Bars Exit = 10 AND Donchian Channel

Do I understand it correctly if I say that a) OR b) must be satisfied at the end of every bar to close a position?

If so, I'd expect all the positions to be closed after 1 bar, being b) constrained by a minimum of 10 bars.
It doesn't seem to be the case in my attachment, i.e. the group b) is effectively playing a role in the exit strategy.

I'm rather confused and I'd appreciate a clarification on that.

Thanks.

I'd like to introduce the condition in subject, to be able to close a position if in loss after a certain amount of time.

Any suggestions on how to specify it in a logical group?

Thank you.

I spent a lot of time analysing the performance of EA Studio and Express Generator's indicators over the last two weeks.

I designed a simulation program to load a particular data file and calculate the Moving Average and RSI indicators.

I made it first in JavaScript using the code from Express Generator.

After testing, refactoring and optimisation, I made a similar program in C.

The C version was 2 times faster for calculating the Moving Average and 15% faster for RSI.

Then, I made it in Fortran. It took me a week to read several Fortran books and to "master" the language.
Expectedly, the Frotran version was about 30% faster than the C version.

I continued researching and learned that Fortran is faster than C, not because of the features it has but because of the features it does not have.

I almost accepted those results. However, I wondered "why" it happens and the particular reason.
Several days later, I learned a lot about modern 64-bit Assembly, disassembled the programs and studied the code.

I was very happy when I found the reason the Fortran code was faster. (It was rather geeky, but if you are interested, I may explain).

On that latter, I decided to use this knowledge to improve my current code.

The first result is compiling C to a similar assembly as Fortran. It practically made the program very similar.
Then, I did the same in JavaScript.

And ... surprise, surprise. All three programs, Fortran, C, and JavaScript, performed similarly.

Calculating 2000 indicators with periods from 1 to 200 on 200k bars.

=======================================
Indicator  Language       Time      
---------------------------------------
MA         Fortran        1.70 sec 
MA         C              1.72 sec 
MA         JavaScript     1.72 sec 
---------------------------------------
RSI        Fortran        6.81 sec 
RSI        C              6.80 sec 
RSI        JavaScript     6.84 sec 
=======================================

The tests are made under Linux with the latest GFortran, GCC, and NodeJS.
The optimisation level for Fortran and C was "O2".

I also made a test with the optimisation level "-Ofast." Both C and Fortran showed double improvement in performance.
"Ofast" option is not suitable for code distribution.

I'm going to use this knowledge in the PineGen generator.

I'm sharing the concept of the new PineGen application.

It will be a straightforward Strategy Builder and Generator for TradingView's Pine Script and others.

I'm designing PineGen's user experience and workflow.

Here is concept-001

Trade Safe!

I'm starting to work on a new trading-related application. I'll share more specific details later.

I'm working on a new backend framework for the new app. I aim to make it more secure, end users friendly, and easier for me to develop, debug, and maintain.

My first step is to develop new helper modules. I'll make all non-critical code open-source and publicly available.

Base64 encoding and decoding module for NodeJS

This module converts an arbitrary text to a combination of hexadecimal digits and letters suitable for online communication.

Example:
The text "Hello, World!" becomes: "SGVsbG8sIFdvcmxkIQ"
Later, the base64 text can be decoded to the original message.

This is very handy for the user's names and emails.

Link: https://github.com/PopovMP/base64

SHA-256 encoding module

This module encodes a piece of text with a private key. It encodes secure tokens to validate users.

For example, logging in to the software encodes your password in the browser. The password and your email go to the server, which checks if it corresponds to a currently active user. If so, the server will issue a secure token for the user.

The encoding works in one direction only. The encoded text cannot be recovered.

Link: https://github.com/PopovMP/sha256

JWT module

JWT stands for Jason Web Token. This is the secure token the server issues for a successfully logged-in user.
This module uses the above Base64 and SHA-256 modules.
The JWT token also contains information for the account type: free, trial, or premium...
It has an expiration time, which makes it handy for features such as "Remember me".

Link: https://github.com/PopovMP/jwt

File-writer

I'm especially happy with this piece of code. It reliably saves files to the disk, even if there are many overlapping save requests with different contents.

I will use this module in the Logger and the DataBase I'm developing.

For example, we can send 1000 append file requests, and the file-writer will ensure the correct file content with only two save operations.

for (let i = 1; i <= 1000; i++) {
    appendAndForget("mambo.txt", "Mambo number: " + i);
}

Link: https://github.com/PopovMP/file-writer

Logger

This module helps the server save log messages to a file or show them on the terminal. It prints the messages in different colours depending on their kind.

Link: https://github.com/PopovMP/file-writer

Happy holidays!

This limitation , if arbitrary programmed, forces us to switch to a higher time frame to get within range but we lose precision of smaller bars data.
There are some indicators that smooth the stepping effects using "artificial' averaging methods or just linearly connects the different points from close to close for example.
I would prefer a more refined way, using the actual bars data from the smaller time frames as basis to calculate the Moving averages of higher time frames.
For example: Assuming an instrument trades 24h,  a 200 MA on Daily time frame would correspond to 4800SMA on H1, or 19200 MA on M15, all the way to 288000 MA on M1 time frames...that's very large, yes, but let's say I want to use a close of the 5 min bar across from 200 Daily MA line? I may be a far distance or far time before Daily bar closes to get the cross number...that's just not taking advantage of intraday information available, or whatever other purpose one may have.

I searched around but couldn't find anything that's already available. Maybe someone can help get a breakthrough with this issue? Mr Footon?  Is this even feasible or what would be the MAX period number a coder could extend their MA design to ? Please?

.mq5/4 , .cs

Just starting out with FSB Pro and very excited about the possibilities!

I have been trying to convert an indicator called Ultimate RSI , from .MQ4 to C# by using ChatGPT.
I have no background in coding so my question here is, if anybody can help me to check the results that i got from ChatGPT. I started with the Youtube videos about custom indicators but can not find there what i am looking for.

Also i want to make an adjustment that already works the same in the standard "moving average crossover"  indicator that excists in FSB.

I added the indicators in Pinescript, .MQ4 and my first draft of the ChatGPT outcome in C#.

Would really aprecciate the help here!

Kind regards,

Clint

Would be possible to request a indicator that Exit at certain hours or minutes after the trade are made?

Thank!