Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Journal of Computers and Digital Business
Nurnadiah Zamri
Unknown Affiliation
Computer Science & IT Decision Sciences, Operations Research & Management

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Design Algorithmic Trading Strategies with Expert Advisor Using Linear Weighted Moving Average (LWMA) and Stochastic Oscillator Technical Indicators Zulkifli, Zarith Sofia; Nurnadiah Zamri; Hairuddin Mohammad; Rashidi Arash Abdul Rashid Al-Saadi
Journal of Computers and Digital Business Vol. 3 No. 2 (2024)
Publisher : PT. Delitekno Media Madiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56427/jcbd.v3i2.404

Abstract

Earlier this decade, the financial sector saw a paradigm change, with automated trading (AT) systems gaining popularity as essential tools for traders and investors. This research explores deeply the design and implementation of Expert Advisors (EAs) for automated financial built using a combination of the Linear Weighted Moving Average (LWMA) and Stochastic oscillator technical indicators. The EAs are built using the programming language MetaQuotes Language 4 (MLQ4) at Metatrader 4 (MT4) platform, enabling automated trade execution. It implements a machine learning genetic algorithm, trained on historical data to optimize the parameters of the LWMA and Stochastic trading rules. The core strategy relies on the LWMA to identify the overall market trend direction while the Stochastic oscillator provides additional signals for timing entry and exit points based on momentum. The EAs were coded to generate automated buy and sell signals for algorithmic trading (AT) based on a set of defined rules using thresholds for each indicators. Extensive historical backtesting using Gold (XAU/USD) currency pair across multiple timeframes from 5-minute (M5) up to 4-hour (H4) charts was conducted using 5 years of price data from 2019 to 2023 for evaluation. The goal of this study is to assess if the EAs could potentially produce consistent profits over time while minimizing drawdowns in different market conditions. The results demonstrate that the system was able to generate annual returns ranging from 3.04% up to 232.19% depending on the aggression of the timeframe settings. Meanwhile, maximum drawdowns were controlled to reasonable levels between 0.5% to 8.27% which is below 10% of potential loss throughout the backtests. An hourly timeframe configuration provided a balanced blend between strong profitability and drawdown control based on the backtest analysis. All the timeframes used for the test show positive results and the M5 timeframe is the best chosen timeframe to trade using this EAs implementation.
Conceptual Framework for Designing an Expert Advisor System Based on Technical Indicators: Evidence from Malaysian Forex Traders Zarith Sofia Zulkifli; Nurnadiah Zamri
Journal of Computers and Digital Business Vol. 5 No. 1 (2026)
Publisher : PT. Delitekno Media Madiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56427/jcbd.v5i1.793

Abstract

The evolution of algorithmic trading (AT) has dramatically transformed the Foreign Exchange (Forex) market by integrating computational intelligence into trading and decision-making processes. Despite these advancements, Malaysian traders remain challenged in adopting such systems, particularly due to limited technical expertise, inadequate adaptation to local trading practices, and a lack of customized automated tools. This concept paper proposes a framework for designing Expert Advisors (EAs) that incorporate technical indicators (TIs) aligned with Malaysian traders' preferences and prevailing market conditions. The framework integrates three core components: trader competency assessment, indicator-based strategy development, and EA system architecture design, aimed at improving trade accuracy, profitability, and risk management. A qualitative approach grounded in literature synthesis and contextual analysis is employed to construct the proposed framework. The resulting model offers a structured and context-sensitive approach that combines trader preferences, technological innovation, and ethical considerations, with practical implications for system developers, educators, and regulators. The originality of this study lies in its localization of EA design to Malaysian traders' needs, bridging the gap between advanced algorithmic tools and local market readiness, while providing a replicable model for other emerging markets adopting AT solutions.
Co-Authors Hairuddin Mohammad Rashidi Arash Abdul Rashid Al-Saadi Zarith Sofia Zulkifli Zulkifli, Zarith Sofia