//Project Showcase
Project Showcase 2016-10-31T13:57:56+00:00

Project Showcase

Within our project showcase we display three projects with varying degree of complexity. Together with our download section this should give you an idea about our ability realize your projects.


Book Ratio

Book Ratio The Depth of Market (DOM) displays the volume offered at bid and ask. By summing the levels for all volume at the ask and bid, you can calculate a book ratio. The order book will never be exactly balanced. One side can show a lot more volume than the other from time to time. This can be used in trying to gather the direction of the market movement. Of course this is not as simple as it sounds. The order book will be influenced by participants offering and cancelling orders in huge numbers. This will also influence the book ratio directly. Over the years we have created several studies for Ninjatrader and Multicharts, accessing the order book levels and calculating a book ratio based on certain scenarios. You can specify how many levels to sum or weight differently. For every price tick the order book will change a lot more. Therefore it makes sense to update the study independent from price ticks. This however can result in high CPU loads, especially if you update it with every book change. So it can make sense to limit the updating to one second or slightly less. In Ninjatrader you could access the order book values directly from the code before Multicharts had this ability. Since Multicharts 8 it’s possible to access the broker data feeds directly from the chart, too. Now we are able to work with the order book directly from within studies. Before that it was a bit more complex. We used Microsoft Excel to obtain the broker data, manipulate it and feed it into Multicharts via Universal DDE. While the current implementation is much more convenient, you can see that there [...]


Sentiment Index

Custom Sentiment Index Often times a project requires a study to be able to access data or values from other charts or sources like text files for examples. At the same time it’s crucial to accomplish this in a user friendly and easily customizable way. While it is possible to have several data sources within one chart, it can become hard to handle quickly. More data streams diminish the visibility of each individual data stream. Referencing each data stream in the code can make your code less flexible. The goal for this project was to build a custom sentiment index. It was constructed out of several individual streams of data. None on the data streams was coming from traditional indicators. This means indicators, which display information by a derivation of price data. The sentiment index had to be constructed from several market internals, order book information and proprietary implied volatility calculations. A moving average for example would be derived from price directly. It only gives you a delayed image of the situation you can see within the price data directly. The average will be smoother than the raw price data, but introduces a certain amount of lag. When building an index each index component usually has a different price value. Therefore it is crucial to normalize the inputs. It is also possible to weight each component differently. After the normalization you can calculate a meaningful sentiment index. The final custom sentiment index was displayed with an indicator, so it could be used for manual trading. This indicator can automatically track the extremes and draw trendlines based on user conditions. Once set up, the indicator was able to perform the tasks the trader had to [...]


Volume Profile

Volume Profile Studies Today Multicharts has the build in ability to display Volume Profiles or Volume Delta charts. Before that we created several studies incorporating these features for customers. A more complex project was creating an external database to store the volume information at each price. This was done to be able to accurately build a volume profile on every chart of choice. A shortcoming in EasyLanguage or Powerlanguage is that you can’t access the volume that was traded at a certain price on a chart. Therefore a typical approach is to divide the total volume for a bar and equally distribute it for every price within the bar. As this doesn’t offer an accurate result and becomes even more inaccurate if you move to higher timeframes, a workaround was desperately needed. The framework was optimized for accuracy, speed and reliability. The volume data can be backadjusted before being plotted on a chart. This can be used to adjust for rollovers between several futures contracts. Another feature is long term profiles with the ability to display Naked POC (Virgin POC) prices. The study can create custom profiles by grouping bars or sessions by simply clicking on the area you want to combine. As calculation speed was critical special attention was placed on this during the development. As a result a long term profile using several years of accurate volume information for example is calculated in less than a second on medium computers. The speed could be reached although the study was using the previously stored volume information and adjusting the data to account for the contract rollovers. This project is another display of our ability to create complex projects for our clients. We like [...]