Algorithmic Trading Strategies

Algorithmic trading is a trading methodology gaining popularity for its precision, consistency and reaction time. It uses formulas involving a series of parameters (such as time, price, volume) for making market transaction decisions. The rules built into the model attempt to determine the optimal time for an order to be placed that will cause the least amount of impact on a stock's price.

Algorithmic trading programs are essential to any equity execution strategy.
GlobalVest has partnered with 3rd party providers of suite of algorithmic trading strategies designed to offer clients an intelligent way to execute orders with specific benchmarks in mind, minimize market impact and improve performance, so traders can devote more valuable time to planning their next move.
The algorithmic strategies, combined with advanced order placement, work together to form a truly unique offering which seeks to enrich the performance of our customers' execution.

Each algorithm uses sophisticated anti-gaming logic to prevent abuse by other market participants (algorithm sniffers) and improve execution quality. Whichever option you choose, you will always remain in control -- stop or modify orders from your front-end, and easily access your orders from your DMA platform.

Partial List of Avilalble Trading Algorithms

Description: Executes desired quantity at a constant rate over a user-defined interval.
Trading Scenario: Spread it out over the day/number of hours.

Description: Creates a pre-trade schedule based on historical volume patterns and targets the volume weighted average price.
Trading Scenario: Match the volume-weighted average price over the day/number of hours.

Description: Tracks and reacts to real-time market volumes to target a user-defined participation rate.
Trading Scenario: Be X percent of the volume.

Description: Minimizes risk-adjusted trading costs relative to the arrival price by optimizing a trade-off between market impact and risk
Trading Scenario: Be as close to the entry price as possible.

Description: Builds on the ARRIVE trajectory by dynamically adjusting trading aggression as a function of real-time market conditions relative to a chosen benchmark price
Trading Scenario: Be as close to the entry price as possible. If the stock moves away, work lightly. If the stock comes in, be more aggressive.

Description: Minimizes risk-adjusted trading costs of the execution relative to the closing price by creating a back-weighted trajectory
Trading Scenario: Try to beat the closing price.

Description: Seeks liquidity in the marketplace, one price level at a time by intelligently routing orders to venues at the NBBO
Trading Scenario: Be aggressive to complete the order.

Description: Searches for non-displayed liquidity and dynamically recalibrates among venues based upon real-time fill rates
Trading Scenario: Use dark pools to complete the order.

Description: Hides the size of a parent order while maintaining a constant displayed order in the market
Trading Scenario: Keep an order in the market without showing your hand.

Description: Seeks liquidity in the marketplace by intelligently routing orders but limits the quantity of standing orders exposed to the market at any given time
Trading Scenario: I would inline but do not impact the quote.

Description: Floats on the passive side of the quote, functioning as a peg
Trading Scenario: Peg the passive side of the inside quote.

Description: 3rd party quantitative consulting team can work with our clients to create user-defined strategies that incorporate individual risk tolerance while reducing transaction costs.
Trading Scenario: User-defined


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