_Desir8

[dannykollexion]

Abiroid Pinbar Scanner Choose Pin bar checks: PinBar Body Options PinBar Nose and Tail Options Left Eye Options Engulfing Bar After Pin Bar Overbought/Oversold with CCI or Stochastic or RSI Distance of Pin bar body from nearest Quarter Point Option to use Majors, halfpoints, quarters Volatility Check

Abiroid Pinbar Scanner - Abiroid

[dannykollexion]

Hello, I'm going to start some experiment with function "Strategies merged to one (trading in parallel)" but I know that it is still an experimental

[dannykollexion]

Next Build

1] Stochastic Oscillator Envelopes Williams' Percent Range Average True Range Standard Deviation Awesome Oscillator ADX

2] Momentum Stochastic Oscillator

3] Price Action Cycle Strength SMA Strength RSI

*Price Action SnR Moving averages BB RSI Fibo

5] Stochastic ATR

6] Fractals Currency Valuation

*Currency Valuation MA RSI Fibo BB MACD RVI (+Stochastic)

8] Price Movement SnR Trend lines Chart Pattern

Price Movement ADX Ichi Parabolic SAR %R Williams OBV

Trend Lines Volume Moving Average Enverlopes ATR Relative Momentum Index Pivot

9] Accelerator Oscillator Accumulation/Distribution Bears power Bollinger Bands Commodity Channel Index Envelopes Ichimoku Kinko Hyo moving average Parabolic Stop And Reverse System Relative Strength Index ZigZag

[dannykollexion]

https://player.vimeo.com/video/332229372

[dannykollexion]

https://player.vimeo.com/video/332229011

[dannykollexion]

Lessons learned: 1. In algo-trading 1 year is not statistically significant 2. So after years of try and error, this is one of my best long term algo-trading results: as example see figure below, last 2 years of trading on my live account on TradeStation. Now you can see more or less what you can expect…and I am pretty sure there are many traders here with much better results! 3. For those who are saying that SQX doesn’t work: SQX works. Period. SQX strategies can make money. Period. Once you know what to do, it is not that hard to find a strategies that really make money. Period. 4. Finding long term strategies is pretty hard, but it is really possible to find them. Previously I could find only short term strategies, that stopped working after few months of trading. Now I see years of constant profitability. Once a year I run WFA to re-optimize systems. 5. Forget about forex, try something else like futures! 6. Find a good borker: avoid “cheap” MT4/MT5 brokers. 7. Stick to your own plan and try to do the opposite of what everyone is telling you Remember that only 2% of traders make money. 8. The one most important thing I can share with you is: !!! Before you will start developing and tweaking your workflows, first make sure you see a good correlation between your live trades and what you see when you backtest your strategy in SQX!!! This is the key to success, at least in my opinion, this single improvement allowed me to develop my workflows and in the end to find profitable strategies.

StrategyQuant trading results 2022

[dannykollexion]

[dannykollexion]

[dannykollexion]

There’s somethings that I keep no matter what I’m trying, like profit trailing, stop loss, etc..but generally, as few building blocks as possible, because I want it to develop on the idea I have, and explore that idea specifically, not just random stuff. I will sometimes mix it up, like try a trailing stop loss instead of trailing profit, but I always have some stops, either profit or loss. I don’t really use profit/risk ratios. ATR, I keep pretty loose, to not stop out on noise.

Your favourite building blocks - StrategyQuant Forum Topic

[dannykollexion]

Every year the market works in slightly different regime (also depending on what markets we are talking about). That’s why it is recommended to use as much data as possible for building and optimization. For me personally when you go down to M1, M3 it’s complete noise – very difficult to find something which would survive for a longer period especially while using the classic technical analysis approach (indicators, price action)

Building, Improvement and Optimization - StrategyQuant Forum Topic

[dannykollexion]

GA’s in general are a way to quickly search large inputs spaces to give results that while are not optimal are usually very good, as opposed to a brute force approach that will take a long time to search the same input space and find the same results, however if you use brute force approach and have enough time you will find the BEST result as you do an exhaustive search so eventually you will find it ultimate result at the Global Maxima, Obviously Random approach is just that, it will randomly search the input space and hopefully come up with something worthwhile.   The theory behind GA is that inputs to a large search space are mapped/encoded to a genome (i.e. could be an array or string representing the inputs to be searched), in this case with SQ it is the functions are mapped to form a strategy, and the search space the market, a fitness function based on rules is applied to the genome to determine whats a good result and who gets to survive to the next population, in this case the fitness are the rules you apply, such as profit and draw down and is what determines what strategy gets selected as parents for the next generation.   An initial population is created using random generated genomes (or sometimes seeded with pre-populated genomes, i.e. you may have some non optimal solutions you want to further search) and much like the theory of evolution the genomes that are the fitness survive (result of applying the fitness function to each genome in the population ), so only the fitness survive and along with new randomly generated genomes generated to make up the population, crossover and mutation will occur, where with crossover simulates breeding and a pair of parent genomes will swap part of their genome to form the children that go to make up the new generation, each genome in the new population has a small random chance of mutation, this mutation helps the population to not get stuck in local maxima type situations, the fitness function get applied and it all begins again.   Over time the overall fitness value of the population usually increases to a point where it won’t increase much further, i.e. fitness stagnation.  When this occurs it’s usually the result of having found a local maxima in the search space and is usually a sign that it can’t evolve further. It is therefore best to start again with a new population to try and fine another local maxima.   So to answer your question, in SQ the results using GA VS Random, IMHO is that GA will find profitable strategies quicker that random, however the resulting population will all be similar and may not be any more optimal than random generated strategies so both will need some form of optimisation.   So really both are just a form of searching, just that Ga will find solutions quicker, but the solution found while being good may not be optimal, i.e as is not at global maxima.  What I do is start with random and my top ones there are used to seed GA   Many moons ago (back in the late 90’s) for my final undergraduate project I wrote a multitasking OS for embedded systems on the Motorola 68HC11 MPU that used GA as the task scheduler.   Stephen…

Question for Mark - Genetic Evolution details? - StrategyQuant Forum Topic

[dannykollexion]

Toolbox-Workflow Generator

Question: What is Toolbox? Answer: Toolbox is a collection of helpfull tools for strategy analysis Question: How much cost Toolbox? Answer: Nothing, this is freeware by Thomas Nickel Question: What ist Toolbox-Workflow Generator Answer: This is a complex tool to generate workflows for the StrategyQuantX

Toolbox contains a workflow generator for the StrategyquantX. A workflow generator have different usecases.

1) Check stability of strategy generation in different time periods. You can check if a workflow is stable in different timeperiods.

2)  Check if a Building Block setting is good or not.

3) You can optimize strategy generation with a workflow generator

[dannykollexion]

This workflow contains 11 Steps Clear databanks Build strategies Retest with unknown data Retest in other markets Montecarlo simulation and filtering of the best strategies Optimize strategies Endtest (check how good this found strategies are) Store the best strategies to harddisk folder Create portfolio Clean databanks Goto next workflow

Generating Strategies - monitortools Webseite!

[dannykollexion]

5 posts!

Cool

[dannykollexion]

Make automatic money

In this channel I will show how to make money with shares/fonds or currency market

Question:

Tell me some features of this software

Answer:

Installation of 1000 strategies automaticaly in a short time on demo and on realaccount on the metatrader4 plattform. Check the performance of this strategies in a short time. Activate the best stratgies on realaccount with "one click". Monitor all 1000 strategies with "one click". Deactivate or delete the bad strategies. Increase/decrease the risk of every strategy with "one click" (set lotsize). Install Strategies for StrategyQuantX or Expert Advisor Studio.

[dannykollexion]

Forex Monitortool

The Monitortool is a software to observe metatrader eas. The monitortool observe every ea and show the tradingresults in a clear form. You can compare trading results of the same ea on demo and life accounts.

Forex Monitortool 

The Monitortool is a software to observe metatrader eas. The monitortool observe every ea and show the tradingresults in a clear form. You can compare trading results of the same ea on demo and life accounts.

[dannykollexion]

1. Note down the optimization period and days in history. 2. Safe the original strategy 3. Load the original strategy using “Simple Optimization” and adjust the time period in the data tab under Settings (number of history days backwards). 4. Optimize and take the best result (save the mq4 file).

After Walk-Forward Matrix - StrategyQuant Forum Topic