Ptimizing Algorithmic Trading Strategies for Emerging Markets: Evidence From Esg-focused Stocks in Borsa Istanbul
Year: 2026
Type: article
Abstract: Today, algorithmic trading (AT) plays a crucial role in financial forecasting. This study explores AT strategies for an emerging market, Borsa İstanbul (BIST). Analyzing Environmental, Social, and Governance (ESG)-focused stocks from the BIST Sustainability Index, a robotic trading algorithm implemented in C# optimizes trading parameters for return. Key technical indicators; Relative Strength Index (RSI) and Simple Moving Average (SMA) evaluate trends and improve decisions. Results show longer timeframes achieve higher profitability, while shorter intervals face volatility. The study underlines the potential of tailored AT strategies in emerging markets, offering insights for small investors to manage risk and return. Findings emphasize the role of local market dynamics in building robust, algorithm-driven trading solutions.
Authors: Çağdaş GÜNDÜZ, Fatih AKKOYUN
Institutions: Pamukkale University, İzmir Demokrasi Üniversitesi
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W7204532092