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Liquidity Aggregator
A system that merges quotes from various liquidity providers and market makers to find the tightest spread. Quotes aren’t firm, and you send a volume request to trade at the best price.
Execution styles
Sweep and full amount strategies.
Full amount execution
Placing an entire order with one liquidity provider, minimizing market impact but involving greater risk for that provider. Provider less likely to charge aggressive spread as they control trade. Builds client relationship. Capacity limitations.
Sweep execution
A strategy that splits a large trade into smaller parts executed across multiple liquidity providers. All trades occur nearly simultaneously, creating greater market impact and losses for the liquidity provider. Providers must hedge as quickly as possible.
Visible spread
The observable difference between the bid and ask price that indicates the initial cost of a transaction. Narrower = more competitive.
Rejection profile
A record of the frequency and reasons for trade rejections by the liquidity provider.
Market impact
The extent to which a liquidity provider affects the overall market price with its trades.
Correlation in liquidity
The similarity of quotes between liquidity providers and the aggregator, influencing diversification of liquidity. High correlation adds redundant liquidity.
Dark Pool
A private financial forum for trading securities that allows participants to make trades without revealing their identity.
Bid and offers mechanics in Dark Pools
Orders are placed by quantity without a price, filling at the current mid-price when opposing interests match. They often impose a minimum fill quantity or a minimum time before cancellation.
Adverse selection in Dark Pools
The risk of trading at a disadvantage due to asymmetric information, often mitigated through setting limit prices.
HFT arbitrageur strategy
A trading strategy where a high-frequency trader buys deep into the primary limit order book and sells at a high mid-price in a dark pool.
Toxicity metric
A measure of the likelihood that a trader is toxic, with values closer to zero indicating a more toxic trader. |r-r*| where r is the probability a toxic trader submits a trade and r* is nash equilibrium.
How to win in a dark pool
By having access to large datasets (e.g. large brokers). Then you are capable of making informed trading decisions and winning over less-informed participants.