A ten-part video series and a growing library of long-form essays — execution, liquidity, market structure and the realities of running algorithmic strategies, explained by the people who built the brokerage around them.
~75% of stock-market volume is now machine-driven, yet most retail brokers were built for a world that no longer exists. Episode 1 lays out what the shift to algorithmic execution actually means for the people placing the trades — and the specific things to look for if you run systematic or automated strategies.
Every broker uses the phrase. Most can't define it. A precise breakdown of latency, fill quality, liquidity depth, routing logic and API throughput — and why the gap between the marketing claim and the operational reality matters to anyone running an algorithmic strategy.
Read article →A technical look at where copy-trade systems break in production — what fidelity drift actually is, where it comes from, and the architectural choices that prevent it from compounding into real P&L damage.
Read article →A practical framework for assessing whether a brokerage is genuinely built for automated and algorithmic strategies — covering execution quality, API design, copy-trade fidelity, and the structural signals that separate marketing from reality.
Read article →What it actually means when a broker quotes "tier-1 multi-venue liquidity" — where the liquidity comes from, how it's aggregated, and why depth matters more than headline spreads in volatile market conditions.
Read article →Fund safety isn't a regulator stamp — it's a banking arrangement. A clear look at what fund segregation actually involves, how to read the operational signals that matter, and why some structures hold up better than others.
Read article →Risk-disclosure documents are often skipped or skimmed. They contain more useful information about how a broker actually operates than any marketing page — here's how to read one critically and what to look for.
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