DFR                     Table with predicted price change
EURUSDM15X75            Table with indicator and price change dataset
TradeStatePolicy        Table with Trade States and sample of actual
                        policy for those states
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
dlog                    Create log difference distribution
encrypt_api_key         Encrypt api keys
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_ML60M              Table with indicator and market type category
                        used to train model
macd_df                 Table with one column indicator dataset
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_R                Table with predicted price change
result_R1               Table with aggregated trade results
result_prev             Table with one column as result from the model
                        prediction
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
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
