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PEF Portfolio Efficiency Front

45 USD

Published: 28 August 2025

Current version: 1.0

PEF Portfolio Efficiency Front

Utilities
Better Trader Every Day
Version: 1.0
Activations: 5

Methodology

PEF implements a portfolio optimization technique using the Pareto algorithm combined with bootstrap simulations. The goal is to compute the efficient frontier of a portfolio consisting of various financial instruments, allowing users to assess the trade-off between risk and return. The methodology involves generating random weight sets for the portfolio, calculating returns and risk metrics (CVaR), and identifying the optimal portfolios that lie on the Pareto front. The user will then select the portfolio weights from the front that satisfy his/her balance of risk aversion and return greed.

Theory

The efficient frontier is a key concept in modern portfolio theory, representing the set of optimal portfolios that offer the highest expected return for a given level of risk. PEF utilizes the following theoretical components:

Risk: Measured using Conditional Value at Risk (CVaR), which quantifies the expected loss in the worst-case scenarios beyond a specified confidence level.
Return: The expected return of the portfolio, calculated based on the weighted returns of the individual assets.
Pareto Optimization: A method to identify portfolios that cannot be improved in one objective (return) without worsening another (risk).
Bootstrap Simulations: A resampling technique used to estimate the distribution of returns, allowing for more robust risk assessments.

Input Variables

PEF requires the following input variables, which can be configured by the user:

Variable	Type	Description
InstrumentsList	String	List of financial instruments in the portfolio (comma-separated).
historyBars	Integer	Number of historical bars to collect data.
DataTimeFrame	ENUM_TIMEFRAMES	Time frame for each bar (e.g., daily, weekly).
SimuDays	Double	Number of simulation days (e.g., 21.6 for one month).
NumbRandWeightSets	Integer	Number of random weight sets to build the Pareto front.
useBootstrap	Boolean	Use bootstrap method (true) or Monte Carlo with fixed data returns (false).
NumberBootstrapTrials	Integer	Number of bootstrap trials to perform.
InpBeta	Double	Confidence level for CVaR calculation (e.g., 0.95).
addEqualWeightSet	Boolean	Include equal weight set result in output.
printSepCovCorr	Boolean	Print covariance and correlation matrices separately.
printCovCorr	Boolean	Print combined covariance and correlation matrices.
saveCSVfile	Boolean	Save Pareto front results to a CSV file.
AddCloud2CSVfile	Boolean	Include results for non-Pareto weight sets in the CSV file.
ParetoCSVfilename	String	Name of the output CSV file for Pareto front results.

Output Results

PEF generates the following output results (every thing is printed in the Expert tab of your MT5 terminal):

Pareto Front: A table displaying the portfolios on the efficient frontier, including:
- CVaR: Conditional Value at Risk percentage.
- Mean Return: Average return percentage.
- Weights: The allocation of each instrument in the portfolio.
Equal Weight Set: If enabled, PEF will also display the results for an equal weight portfolio, which is not necessarily on the Pareto front.
Covariance and Correlation Matrices: If enabled, PEF will print the covariance and correlation matrices, providing insights into the relationships between the assets in the portfolio.
CSV File: If enabled, the results will be saved to a CSV file, which includes the Pareto front data and optionally the non-Pareto weight sets.

Example Output Format

Portfolio Efficient Front - (Return vs Risk) Pareto for 21.6 trading days:

# CVaR_% Mean_Return_% XAUUSD USDJPY EURUSD

0 1.50 5.00 0.40 0.30 0.30

1 1.20 4.80 0.50 0.25 0.25

1.15 4.00 0.33 0.33 0.33 Equal Weight Case (not on Pareto front)

Notes

Ensure that the input variables are set according to your portfolio and analysis requirements.
PEF will print logs during execution, indicating the progress and any issues encountered.
The output CSV file will be saved typically in the MQL5/Files folder.

A more detailed explanation of PEF input/output is found in this blog page.

*** The Pareto front image below was created inside the CSV file output by PEF using standard spreadsheet manual command, not automatically created by PEF.
All other output can be seen in the Expert tab of the MetaTrader5 terminal.

more...

Screenshot #1 PEF Portfolio Efficiency Front

Screenshot #2 PEF Portfolio Efficiency Front

Screenshot #3 PEF Portfolio Efficiency Front

Screenshot #4 PEF Portfolio Efficiency Front

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USER MANUAL, GUIDE and SET FILE LINK Before running this EA, ma ke sure that your account size matches the initial deposit input parameter (RM0) in the set file you are running. ZING FEATURES - ZING is an expert advisor that uses four stochastic indicators and two time frames to predict the price trend and trigger a trade. - It trades ANY Forex symbol, ANY metal symbol. We recommend major ones: combinations of USD, GBP, JPY, EUR, AUD, CAD, XAU. - User may run any number of symbols in parallel

99 USD

Before running this EA, make sure that your account size matches the initial deposit input parameter (RM0) in the set file you are running. USER MANUALS, AND SET FILE LINK LYNX FEATURES - LYNX i s an expert advisor that combines Stochastic, MACD and RSI indicators to signal the entry of a trade. It trades ANY Forex symbol, ANY metal symbol. Use major ones: combinations of USD, GBP, JPY, EUR, AUD, CAD, XAU. User may run any number of symbols in parallel by running an instance of this robot on ea

99 USD

The RPP script computes the optimum weights of a portfolio of symbols (stocks, forex pairs, indices, etc.) using the Risk Parity Algorithm. You can read the theory of the Risk Parity algorithm in this Wikipedia page . Inputs : 1) Symbols in the portfolio. 2) Time frame you are interested in. 3) Number of past bars to compute the correlations. 4) Print the covariance matrix (true/false) 5) Print the correlation matrix (true/false) Output : Optimum weights for each symbol in the portfolio. These

30 USD

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