The returns on your portfolio depend on two things: the products you buy/sell and the price at which you buy/sell them. For example, if you buy a product at 0.1% less that the ask price and then turn around and sell it at 0.1% higher than the bid price, your returns increase by 0.2%.
Over the course of many days and various trades, compounding produces some serious returns. At qplum, we use execution algorithms in order to obtain the best prices at which to trade products in your portfolio.
Many of our execution algorithms have their origins in High-Frequency Trading. Download our report "High-Frequency Trading as a Service".
Execution Algorithms are strategies that decide the best way to place an order in the market. These strategies enable us to split orders into smaller sizes and provide control over the price at which they are placed.
For example, a simple strategy is to split the order into 4 smaller orders of equal size and place market orders in 15 minute intervals.
To get you the best possible price, we need to monitor the market closely at all times in order to detect small swings in prices. This is no small feat for a human.
When you factor in the emotional swings of manual monitoring, less-than-desired results occur.
They monitor the market around the clock and make emotion-free decisions to buy or sell, ensuring the best price for you.
An execution strategy could be as simple as placing a market order or as complex as crunching historical data, predicting the price movement, and then placing the order. Smart execution makes use of sophisticated algorithms. It involves analyzing historical data using Machine Learning methodologies and finding the best time and price for your order. Watch our webinar on how we apply HFT techniques to increase portfolio returns.
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