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L'essor de STARTRADER

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Le courtage à la croissance la plus rapide au monde

L'essor de STARTRADER

L'un des
Le courtage à la croissance la plus rapide au monde

Glossaire du trading

Le commerce par glossaire fait référence à un type de stratégie commerciale dans laquelle les traders utilisent un ensemble prédéfini de termes, de définitions ou de concepts pour prendre des décisions éclairées. Cela implique souvent un jargon spécifique au secteur, des mesures financières et des outils analytiques pour naviguer efficacement sur les marchés.

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Electronic Brokering Services (EBS)

A major FX ECN, founded in 1990 by a consortium of large banks fed up with paying voice brokers. Now owned by CME Group following the 2018 NEX acquisition. EBS dominates spot trading in the major pairs anchored by the euro, yen, and Swiss franc. Refinitiv Matching (the old Reuters Matching) historically held the edge in commonwealth pairs, GBP, AUD, CAD. The two platforms split the interbank pie roughly along those lines, though the boundaries have softened over the years. EBS prices are foundational. They feed into countless other platforms, either directly or through reference. When you see a EUR/USD quote anywhere in the world, there’s a high chance the underlying price formation happened on EBS. Example: A bank trading EUR/JPY on EBS sees a centralised order book showing bids and offers from dozens of counterparties globally. Real-time updates. Anonymous matching engine. Standard FX settlement on the back end. The whole stack works because everyone trusts the same platform.

Electronic Direct Trading:

A model where a client gets quotes directly from one bank and executes against that bank’s price. Single-counterparty execution. The bank is the liquidity provider, taking the other side onto its own book. Citi’s Velocity, JPMorgan’s Athena, Deutsche Bank’s Autobahn, these are direct-trading platforms. Fast execution, integrated post-trade services, deep credit lines, single relationship. The trade-off is obvious: you only see one bank’s price. Aggregation platforms would show you ten. So why do clients use direct platforms? Because for relationship-driven flows or specific products where the bank has unique expertise, direct trading wins on dimensions other than headline price. Example: A corporate treasurer hedging $50 million of euro receivables uses their primary FX bank’s direct-trading platform. The spread is slightly wider than they’d get on an ECN. In exchange, the hedge integrates cleanly with the company’s existing credit facility, settles through familiar plumbing, and gets reported on familiar formats. The treasurer optimises for total workflow cost, not bid-ask alone.

Electronic Indirect Trading

The opposite model. A client accesses aggregated liquidity from multiple banks and non-bank market makers through a single platform, with quotes competing in real time. FXall, FXSpotStream, Currenex, 360T, these are aggregators. The platform itself doesn’t take principal risk. It just routes orders to whoever offers the best price at the moment of execution. Asset managers love this model. Hedge funds love this model. Sophisticated corporates with serious execution teams love this model. The competitive pressure from aggregation has been one of the main forces compressing FX spreads over twenty years. Example: A large asset manager executing $200 million of GBP/USD through 360T might see streaming quotes from 15 different liquidity providers. The platform routes to whoever shows the tightest price at that millisecond. Execution-quality reports track performance against arrival price and benchmarks. The asset manager’s traders never see most of the providers’ names, they see a single composite book.

Electronic Market Maker

A firm that provides continuous two-sided quotes on electronic venues, profiting from the spread. The modern ones aren’t banks. They’re specialised non-bank firms, Citadel Securities, Virtu, Jump Trading, Jane Street, XTX, DRW, that have taken massive share from traditional bank market makers. Faster systems, better tech, no legacy compliance overhead, narrow focus. The economics depend on managing inventory risk while flipping positions in milliseconds. There’s no directional view. The edge comes from technology, market microstructure expertise, and risk management. The position is held just long enough to lay off against another order. Example: Citadel Securities executes a meaningful fraction of all US retail equity orders through wholesale market-making. When you place a market order through Robinhood or E*TRADE, there’s a high chance Citadel takes the other side, gives you a small price improvement over the public quote, and turns over inventory faster than you can refresh the page. The retail customer wins on price. Citadel wins on volume.

Elliott Wave Theory

Elliott Wave Theory suggests that financial markets follow a 5-3 wave pattern: five waves in the trend’s direction and three waves in the opposite direction.

Elliott Wave Theory (EWT)

Ralph Nelson Elliott’s 1930s framework, claiming markets move in repeating wave patterns driven by mass psychology. The basic structure: a five-wave impulsive move in the trend’s direction, followed by a three-wave correction against it. Each wave contains smaller waves of the same shape, fractal nesting all the way down. Practitioners label the waves obsessively (1-2-3-4-5 for impulses, a-b-c for corrections) with strict rules about which wave can be longest, how deep retracements can run, and how patterns nest. Critics call it unfalsifiable. The labels can always be revised after the fact, which means the theory “works” because it’s flexible enough to accommodate any outcome. Defenders say it provides structure for thinking about exhaustion and reversal. The truth probably depends on the practitioner. Example: Robert Prechter, the most famous modern Elliott practitioner, called both the 1987 crash and the 2000 dot-com top using wave analysis. Impressive. He also called for major bear markets through most of the post-2009 bull run that didn’t materialise on his timeline. The framework has predictive ambition. It’s also early when it’s not just wrong.

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