Algorithmic Trading Life Cycle of Algo Components Algorithms are used extensively in various stages of the trading cycle. we can classify them into pre-trade analytics, execution stage, and post-trade analytics. The Pre-trade analytics involve thorough analysis of historical data and current price and volume data to help clients determine where to send orders and when; whether to use algorithms or trade an order manually we can call this as back testing the algorithm etc.,. The pre-trade analysis is designed to help buy-side traders understand and minimize market impact by choosing the level of aggressiveness and a time horizon for trading various stocks. Traders can select varying levels of aggressiveness and visualize them against the time horizon for completing the trade. Most compare the spread between bid and ask prices, reference that against the volatility of a given stock, and attempt to create a range of potential outcomes. A lot of the broker-sponsored algorithmic tradi
Trading Algorithms: Areas of Concern Lack of Visibility We know what a specific algorithm is supposed to do, measure its pre-trade analytics and see how the post-trade results match up to that expectation. But if the trader didn’t select the most optimal algorithm for that trade little can be done. This problem is caused by a lack of visibility and transparency into the algorithm while it is executing orders. Algorithms Acting on Other Algorithms If fund managers trading pattern is spotted and regular; tracked with the use of algorithms, then these algorithms are liable to be ‘reverse engineered’. This implies that their buy and sell orders are pre-empted and used to the maximum effect by their competitors. Here, algorithms are acting on other algorithms. Which Algorithm to Use for Trading? With brokers offering many algorithmic strategies , one concern is that buy-side institutions lack the tools to understand which algorithm to use for a particular stock. The lack of a
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