Event-Driven Models are computational frameworks designed to react to specific, discrete occurrences or triggers rather than operating on a fixed, synchronous schedule. Their purpose is to enable highly responsive and efficient processing in systems where reactions to external stimuli are critical. This architecture is common in real-time systems.
Mechanism
These models function by continuously monitoring for predefined events, such as market data updates, order submissions, or system alerts. Upon detection of an event, a dedicated handler executes a specific set of actions or computations, typically in an asynchronous manner, potentially propagating further events as outcomes. This mechanism ensures prompt reactions to changes.
Methodology
The strategic approach prioritizes low-latency response and resource efficiency by processing only relevant data upon a trigger. This framework supports scalable and fault-tolerant architectures, enabling complex algorithmic trading strategies and real-time risk management. It allows systems to focus computational effort precisely when market changes occur, critical in volatile crypto environments.
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