Learn Computer and Data Science using Algorithmic Trading

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Documentation for package ‘lazytrade’ version 0.3.9

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aml_collect_data Function to read new data, transform data, save data for further retraining of regression model for a single currency pair
aml_make_model Function to train Deep Learning regression model for a single currency pair
aml_score_data Function to score new data and predict change for each single currency pair
aml_test_model Function to test the model and conditionally decide to update existing model for a single currency pair
check_if_optimize Function check_if_optimize.
create_labelled_data Create labelled data
create_transposed_data Create Transposed Data
data_trades Table with Trade results samples
decrypt_mykeys Function that decrypt encrypted content
DFR Table with aggregated trade results
EURUSDM15X75 Table with indicator and price change dataset
evaluate_macroeconomic_event Function used to evaluate market type situation by reading the file with Macroeconomic Events and writing a trigger to the trading robot
evaluate_market_type Function to score data and predict current market type using pre-trained classification model
generate_RL_policy Function performs RL and generates model policy
generate_RL_policy_mt Function performs RL and generates model policy for each Market Type
get_profit_factorDF Function that returns the profit factors of the systems in a form of a DataFrame
import_data Import Data file with Trade Logs to R.
import_data_mt Import Market Type related Data to R from the Sandbox
indicator_dataset Table with indicator dataset
load_asset_data Load and Prepare Asset Data
log_RL_progress Function to log RL progress.
log_RL_progress_mt Function to log RL progress, dedicated to Market Types
macd_df Table with one column indicator dataset
opt_aggregate_results Function to aggregate trading results from multiple folders and files
opt_create_graphs Function to create summary graphs of the trading results
policy_tr_systDF Table with Market Types and sample of actual policy for those states
price_dataset Table with price dataset
profit_factor Calculate Profit Factor
profit_factorDF Table with Trade results samples
profit_factor_data Table with Trade results samples
record_policy Record Reinforcement Learning Policy.
record_policy_mt Record Reinforcement Learning Policy for Market Types
result_prev Table with one column as result from the model prediction
result_R Table with predicte price change
self_learn_ai_R Function to train Deep Learning regression model
test_data_pattern Table with several columns containing indicator values and Label values
test_model Test model using independent price data.
to_m Convert time series data to matrix with defined number of columns
TradeStatePolicy Table with Trade States and sample of actual policy for those states
trading_systemDF Table with trade data and joined market type info
util_generate_password R function to generate random passwords for MT4 platform or other needs
writeCommandViaCSV Write csv files with indicated commands to the external system
write_command_via_csv Write csv files with indicated commands to the external system
write_control_parameters Function to find and write the best control parameters.
write_control_parameters_mt Function to find and write the best control parameters.
write_ini_file Create initialization files to launch MT4 platform with specific configuration
x_test_model Table with a dataset to test the Model