打开 MQL5 个人资料My academic background combines undergraduate study in applied mathematics and computer science with training in statistics and finance. That combination shaped how I approach markets—with historical basis, structured reasoning, and a willingness to abandon an idea when the evidence doesn’t support it.
The coding languages I have most of my experience in are Python, C++, and MQL5, particularly the challenge of translating research into reliable automated trading logic. I’m drawn to understandable systems: explicit entry conditions, disciplined position sizing, consistent exits, and safeguards for unexpected market conditions.
My research philosophy is straightforward: All factors contribute to a profitable trading strategy. Transaction costs, out-of-sample testing, parameter sensitivity, and live execution deserve as much attention as the original trading idea.
Build with logic. Test with skepticism. Refine with evidence.
Trust comes with communication and accountability
