Algorithmic trading automates trading strategies, optimizing execution and minimizing costs in the crypto market.
Defining Algorithmic Trading
Algorithmic trading is a computerized trading approach where trades are executed based on predefined parameters instead of human intervention. These parameters dictate the conditions under which trades are initiated or closed, as well as the trade volume.
For example, a common rule might trigger a buy if an asset's price drops by 5% from the prior day's close, or a sell if it rises by 5%. The algorithm continuously scans market conditions and executes trades based on these rules.
Various strategies can be programmed into these systems. A frequent tactic involves acquiring a significant amount of an asset while aiming to maintain an average purchase price close to the current market price.
However, challenges can occur due to the market's order book structure, which displays all buy and sell orders at various price levels. A large buy order can quickly consume lower-priced offers, leading to a higher average purchase price than intended.
This activity is also noticeable to other market participants. Observing that cheaper offers are vanishing rapidly may prompt sellers to withdraw their lower-priced offers and submit them at higher prices.
To mitigate this risk, algorithms often break down large orders into smaller, manageable batches known as child orders, which are executed at different times. This strategy, termed algorithmic execution, prioritizes minimizing transaction costs and market impact over immediate profit.
Common methodologies in algorithmic trading include:
- VWAP (Volume Weighted Average Price)
- TWAP (Time Weighted Average Price)
- Iceberg orders
These strategies are predominantly employed by large institutions such as banks, hedge funds, and pension funds. Given their substantial trading volumes, even without segmenting orders, prices can escalate significantly before a trade is finalized, which may take several hours.
Another critical role of algorithms is to determine the timing and direction of trades. Instead of following a pre-defined order, the program assesses conditions to decide on market entry. The essential rules for such an automated trading system can be summarized in three points: when to initiate a trade, the investment amount, and when to exit a position.
The Ambiguity Surrounding Definitions
The distinction between the two primary functions—decision-making and execution—results in varied interpretations of algorithmic trading within the market.
Some definitions limit the term to the execution of large trades while treating trading robots with distinct strategies as a separate category. Conversely, others adopt a broader view, encompassing all forms of automated trading within the definition.
