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;
}
}
}