Learn Computer and Data Science using Algorithmic Trading

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Documentation for package ‘lazytrade’ version 0.5.4

• DESCRIPTION file.
• Package NEWS.

Help Pages

aml_collect_data	Function to read, transform, aggregate and save data for further retraining of regression model for a single asset
aml_consolidate_results	Function to consolidate model test results
aml_make_model	Function to train Deep Learning regression model for a single asset
aml_score_data	Function to score new data and predict change for each single currency pair
aml_simulation	Function to simulate multiple input structures
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 predicted price change
dlog	Create log difference distribution
encrypt_api_key	Encrypt api keys
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
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.
indicator_dataset	Table with indicator dataset
macd_100	Table with indicator only used to train model, 128 col 1646 rows
macd_df	Table with one column indicator dataset
macd_ML60M	Table with indicator and market type category used to train model
mt_evaluate	Function to score data and predict current market type using pre-trained classification model
mt_import_data	Import Market Type related Data to R from the Sandbox
mt_make_model	Function to train Deep Learning Classification model for Market Type recognition
mt_stat_evaluate	Function to prepare and score data, finally predict current market type using pre-trained classification model
mt_stat_transf	Perform Statistical transformation and clustering of Market Types on the price data
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
price_dataset_big	Table with price dataset, 30000 rows
profit_factorDF	Table with Trade results samples
profit_factor_data	Table with Trade results samples
result_prev	Table with one column as result from the model prediction
result_R	Table with predicted price change
result_R1	Table with aggregated trade results
rl_generate_policy	Function performs Reinforcement Learning using the past data to generate model policy
rl_generate_policy_mt	Function performs RL and generates model policy for each Market Type
rl_log_progress	Function to retrieve and help to log Q values during RL progress.
rl_log_progress_mt	Function to retrieve and help to log Q values during RL progress. This function is dedicated to the situations when Market Types are used as a 'states' for the Environment.
rl_record_policy	Record Reinforcement Learning Policy.
rl_record_policy_mt	Record Reinforcement Learning Policy for Market Types
rl_write_control_parameters	Function to find and write the best control parameters.
rl_write_control_parameters_mt	Function to find and write the best control parameters.
test_data_pattern	Table with several columns containing indicator values and Label values
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_find_file_with_code	R function to find file with specific code within it's content
util_find_pid	R function to find PID of active applications
util_generate_password	R function to generate random passwords for MT4 platform or other needs
util_profit_factor	Calculate Profit Factor
write_command_via_csv	Write csv files with indicated commands to the external system
write_ini_file	Create initialization files to launch MT4 platform with specific configuration
x_test_model	Table with a dataset to test the Model
y	Table with indicators and price change which is used to train model