Leveraging your trades with Algologic.ai trading counts data
The majority of trading platforms online aggregated trading information from 1 minute up to 1 week. These aggregated data called candlesticks usually contains the open, close, high, low prices, and volume traded on that interval. All standards indicators (e.g. moving average, bollinger bands) are drawn on top of these 5 data points. Consequently, a large amount of trading strategies are built using these 5 data points as well. What if there was another trading data point out there?
In fact, such data exists: all trades are classified as ‘buys’, when ‘taker’ orders are executed against the ask part of an order book; or ‘sells’, when ‘taker’ orders are executed against the bid part of an order book. This result in 4 additional data points: buy/sell volume, and buy/sell trading counts, i.e. how many trades were executed in the aggregation interval. Although trading counts may not be relevant for candlestick charting, it is relevant for strategy designed based on machine learning. Studies performed by our quantitative analysts showed that trading volume and trading counts (buy/sell) correlates with extreme price moves and it has improved the predictability of Algologic.ai’s algorithms.
Here is were Algologic.ai candlestick data can make a different on your trades. We provide trading count as a data point in our datasets. Algologic.ai candlestick is an enriched candlestick dataset including more data points that you will find in standard datasets or APIs available online. Among open, close, high, low and volume, we provide buy and sell volume and also buy and sell trading counts and total trading counts.
We invite you try and see whether the trading count may provide you new insights on your analysis.
You can download our data at algologic.ai
