Trading Example Part 4. Filter on calculated values

Intrinsic to collection change notifications, items can be notified by add, update and remove events. If ordering is supported a collection will support a move notification. Of course Dynamic Data supports these. Yet something which is often overlooked is data or functions of data are sometimes by necessity mutable. How can a collection which notifies respond to mutable changes?

To deal with this scenario, dynamic data introduces the concept of an Evaluate notification. This notification forms part of a change set and tells a consumer an item needs to be re-assessed or re-evaluated. This may effect things like filtering or sorting of an item. I feel a concrete example best illustrates this concept. Suppose we have the following function:

Func<Trade,bool> isNearToMarketPrice = trade => return Math.Abs(trade.PercentFromMarket) <= 1 %

Where PercentFromMarket is a calculation which is recalculated with each and every market data tick. Using standard linq a list of near to market trades can be retrieved as follows.

var nearToMaketTrades = myListOfTrades.Where(isNearToMarketPrice);

The manifest problem with this query is it pull based only and has no means of observing when the market price has been recalculated, or alternatively how can re-evaluation be forced. Based on practical experience of dealing with this kind problem I introduced multiple means of injecting the evaluate command into a dynamic data stream. Here I will use a filter controller illustrated in a previous blog and we will apply it to the trade service here.

In summary any of the controllers in dynamic data are used to inject commands and meta data into a stream. For this example we need a dynamic filter which is applied to a stream of trades.

//create a filter controller and set it's filter
var filter = new FilterController<Trade>();
filter.Change(trade => Math.Abs(trade.PercentFromMarket) <= percentFromMarket());

//create a stream of live trades where the trade matches the above filter
var filteredByPercent  = myTradeService.Trades
                         .Connect(trade=>trade.Status==TradeStatus.Live)
                         .Synchronize(locker)
                         .Filter(filter)

The filter controller has an overload to force re-evaluation.

filter.Revalue() // to reevaluate all
// or
filter.Reevaluate(Func<T,bool> itemSelector) //to re-evaluate selected items

The only missing element is when do we invoke re-evalulation. We have 2 choices. Either the service which calculates market prices provides a notification of trades which have been re-calculated or we poll on a period. Option 1 would be suitable for algo trading where everything must happen preferably with zero latency but for simplicity in the example we will poll as follows.

//re-evaluate filter periodically
var reevaluator = Observable.Interval(TimeSpan.FromMilliseconds(250))
                         .Subscribe(_ => filter.Reevaluate());

And that is that. We have a live stream of trades, where closed trades are automatically filtered out from the source and the filter controller constantly re-applies to ensure only trades near to the market are included in the result.   And as ever what is beginning to become my catch phrase – that is easy!

After wrapping the function into a cold observable, here’s the final code.

public IObservable<IChangeSet<Trade, long>> Query(Func<uint> percentFromMarket)
{
    if (percentFromMarket == null) throw new ArgumentNullException("percentFromMarket");
    return Observable.Create<IChangeSet<Trade, long>>
	(observer =>
	 {
	     var locker = new object();
	     Func<Trade,bool> nearToMaketTrades = trade => Math.Abs(trade.PercentFromMarket) <= percentFromMarket();
	     var filter = new FilterController<Trade>(nearToMaketTrades);

	     //re-evaluate filter periodically
	     var reevaluator = Observable.Interval(TimeSpan.FromMilliseconds(250))
		 .Synchronize(locker)
		 .Subscribe(_ => filter.Reevaluate());

	     //filter on live trades matching % specified
	     var subscriber = _tradeService.Trades
		 .Connect(trade=>trade.Status==TradeStatus.Live)
		 .Synchronize(locker)
		 .Filter(filter)
		 .SubscribeSafe(observer);

	     return new CompositeDisposable(subscriber, filter, reevaluator);
	 });
}

This observable will form part of a future post where I want to build the foundation of an auto trading system.

But for now, in a few lines of code (see NearToMarketViewer.cs) we can put the data onto the screen.

Near to market

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Demo app

I have been busy creating example code of how to use dynamic dynamic data yet this blog has fallen well behind the code. The demo now has 5 simple yet powerful examples with a 6th in mind. The problem is I love being creative with code too much to be spending my time writing about it. With new years on the way perhaps a resolution is required.

Although I am no designer I like systems to look good. After all during the development cycle F5 can be pressed tens of thousands of times so I have taken the trouble to apply some styles.

A big thanks to MahApps for their awesome wpf library and to Dragablz for creating Chrome style draggable tabs.

Trading Demo Menu

As you can see from the image, the menu page has hyperlinks to the code behind and to this blog. Hopefully this will give a coherent means of seeing how the data on the screen matches up with the code.

Almost forgot, but the demo is on GitHub at https://github.com/RolandPheasant/TradingDemo