Good evening all,

I am very new to QC and to coding and strive to figure things out on my own before seeking help.  So, now I seek help.  I have cloned the below algorithm below and made a few modifications.  The question I have today and as you can see below: I am trying to apply a 5 period SMA using the Close and a 5 period SMA using the open.  Yes, both are 5 periods but I am trying to use it as an indicator for when the open crosses below the close.  I've modeled this perfectly in R with some additional variables and conditions for profit/loss and risk management.

I don't think I am using the  Field Selectors appropriately or at least I don't think the functionality aligns with what I am aiming for.  Any help would be appreciated.  Thanks.

Very respectfully,

Geno

 

using System; using System.Linq; using QuantConnect.Indicators; using QuantConnect.Models; using QuantConnect.Algorithm; using QuantConnect.Data.Market; using QuantConnect.Data; namespace QuantConnect.Algorithm.Examples { /// <summary> /// /// QuantConnect University: EMA + SMA Cross /// /// In this example we look at the canonical 15/30 day moving average cross. This algorithm /// will go long when the 15 crosses above the 30 and will liquidate when the 15 crosses /// back below the 30. /// </summary> public class MySma : QCAlgorithm, IAlgorithm { private SimpleMovingAverage fast; private SimpleMovingAverage slow; private SimpleMovingAverage[] ribbon; private string symbol = "EURUSD"; public override void Initialize() { // set up our analysis span SetStartDate(2015, 01, 01); SetEndDate(2015, 06, 01); // request SPY data with minute resolution AddSecurity(SecurityType.Forex, symbol, Resolution.Minute); Securities[symbol].FeeModel = new ConstantFeeModel(0.0m); // create a 15 day exponential moving average fast = SMA(symbol, 5, Resolution.Minute, Field.Open); // create a 30 day exponential moving average slow = SMA(symbol, 5, Resolution.Minute, Field.Close); // the following lines produce a simple moving average ribbon, this isn't // actually used in the algorithm's logic, but shows how easy it is to make // indicators and plot them! // note how we can easily define these indicators to receive hourly data int ribbonCount = 7; int ribbonInterval = 15*8; ribbon = new SimpleMovingAverage[ribbonCount]; for(int i = 0; i < ribbonCount; i++) { ribbon[i] = SMA(symbol, (i + 1)*ribbonInterval, Resolution.Hour); } } private DateTime previous; public override void OnData(Slice data) { // a couple things to notice in this method: // 1. We never need to 'update' our indicators with the data, the engine takes care of this for us // 2. We can use indicators directly in math expressions // 3. We can easily plot many indicators at the same time // wait for our slow ema to fully initialize if (!slow.IsReady) return; // only once per day ////if (previous.Date == Time.Date) return; // define a small tolerance on our checks to avoid bouncing const decimal tolerance = 0.0m; var holdings = Portfolio[symbol].Quantity; // we only want to go long if we're currently short or flat if (holdings <= 0) { // if the fast is greater than the slow, we'll go long if (fast > slow)// * (1 + tolerance)) { Log("BUY >> " + Securities[symbol].Price); SetHoldings(symbol, 1.0); } } // we only want to liquidate if we're currently long // if the fast is less than the slow we'll liquidate our long if (holdings > 0 && fast < slow) { Log("SELL >> " + Securities[symbol].Price); Liquidate(symbol); } //Plot(symbol, "Price", data[symbol].Price); //Plot("Ribbon", "Price", data[symbol].Price); // easily plot indicators, the series name will be the name of the indicator Plot(symbol, fast, slow); Plot("Ribbon", ribbon); previous = Time; } } }

 

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