Review, testing of the finished project + configuration of GA optimized trading system
Budget: $30 – $250 USD
This job is only for a person who masters high education mathematics and has experience with Genetic Algorithm and can apply both in Python libraries. The invited freelancers are preferred.
Before starting each milestone, can you tell me an estimation of price -(from-to)?
Job has the following parts ( milestones):
1.) a) Review paper + Github code (applicability). Is missing some part of the code on Github for AUD -USD described in the article?
Are the text and software ready to use the way it is?
It is not necessary to understand all the specific rules, indicators of the Technical Analysis and mathematical formulas for GA optimization of the highest return and the lowest risk.
b) Is there a possibility of testing 2020 directly without further intervention using hyperparameters from 2018? (I will provide the data.)
If so, then
2.) "1st milestone."
2020 backtest (2021?) For AUD -USD with the following evaluation:
ROI - Return of Investment,
SR - Sharpe Ratio (Money management),
MD - Maximum Drawdown and
AP - Average Position (amount of invested capital),
for B&H, S&H (Buy or Sell and Hold), GA-MR (Maximum Return) and GA-MSSR.
+ c) would it be possible to see a letter with the dates and times of the beginnings of individual trades? Especially for GA-MR and Ga -MSSR (using - https://pypi.org/project/Backtesting/ ).
Before starting each milestone, can you tell me an estimation of price -(from-to)?
3.) Is it possible to re-train the new weights for each of the 16 rules on data from 2019 and 2020?
If yes, then -
"2nd milestone" Training and subsequent testing in 2021.
4.) Is it possible to a) complete - program new rules for entering trades? She's not ready yet.
b) optimize and test either Buy or Sell trades (1 and -1) separately as two independent trading strategies?
c) Searching for hyperparameters + optimization for 3 different parts of the day - according to Volatility? (Statistics determines it)
If so, it will be 3rd milestone.
5.) There is an opportunity to teach me how to use it all in the future. I've never done anything in Python.
P. S. : I will send the paper after short communication.
Before starting each milestone, can you tell me an estimation of price -(from-to)?
Job has the following parts ( milestones):
1.) a) Review paper + Github code (applicability). Is missing some part of the code on Github for AUD -USD described in the article?
Are the text and software ready to use the way it is?
It is not necessary to understand all the specific rules, indicators of the Technical Analysis and mathematical formulas for GA optimization of the highest return and the lowest risk.
b) Is there a possibility of testing 2020 directly without further intervention using hyperparameters from 2018? (I will provide the data.)
If so, then
2.) "1st milestone."
2020 backtest (2021?) For AUD -USD with the following evaluation:
ROI - Return of Investment,
SR - Sharpe Ratio (Money management),
MD - Maximum Drawdown and
AP - Average Position (amount of invested capital),
for B&H, S&H (Buy or Sell and Hold), GA-MR (Maximum Return) and GA-MSSR.
+ c) would it be possible to see a letter with the dates and times of the beginnings of individual trades? Especially for GA-MR and Ga -MSSR (using - https://pypi.org/project/Backtesting/ ).
Before starting each milestone, can you tell me an estimation of price -(from-to)?
3.) Is it possible to re-train the new weights for each of the 16 rules on data from 2019 and 2020?
If yes, then -
"2nd milestone" Training and subsequent testing in 2021.
4.) Is it possible to a) complete - program new rules for entering trades? She's not ready yet.
b) optimize and test either Buy or Sell trades (1 and -1) separately as two independent trading strategies?
c) Searching for hyperparameters + optimization for 3 different parts of the day - according to Volatility? (Statistics determines it)
If so, it will be 3rd milestone.
5.) There is an opportunity to teach me how to use it all in the future. I've never done anything in Python.
P. S. : I will send the paper after short communication.