Cryptocurrencies are usually prone to higher volatility and a larger number of trades, compared to fiat-based assets. That’s why crypto-trading is significantly taxing on the system. Fortunately, there are several ways to optimize the performance of the Tiger.Trade platform even during the high load periods.
Method 1. Increase the price scale
This optimization method significantly reduces the amount of RAM consumed and has virtually no effect on the technical analysis functions. Additionally, a compressed DOM becomes much more convenient for trading when market volatility is high.
The price scale works as follows. For example, a BTCUSDT futures is open, and it has a price step of $0.01. If you set the price scale to 100, the price step for the BTCUSDT futures becomes $1. That is, the volumes at different price levels are combined into one level, and the volume of data is reduced by nearly 100 times.
To change the price scale in the DOM window or Charts window, click the Price scale icon on the tool panel, enter a new value and click Apply.
Method 2. Change data type from clusters to bars
With this optimization method, the complete data set is not loaded, as it is with clusters. Instead, only the OHLC bar, volume, and delta is loaded from the server.
This method has some downsides: it's not possible to view clusters, and some volume indicators (Volume Profiles and Dynamic Levels) and the Volume Profile graphical object also do not work.
To change the data type, open the timeframe selection window and change the data type to Bars.
Method 3. Reduce the amount of downloaded history
If you don’t need a chart with a deep history, you can set the maximum number of days that are shown for each timeframe.
To adjust these settings, open the timeframe selection window and click Edit. Next, for each preset timeframe, you can set the history depth in days separately for the Charts window and the DOM window. These settings are not automatically applied to all windows after editing. The timeframe must be selected again in each window.
