private static decimal GetScaleFactor(FactorFile factorFile, DataNormalizationMode mode, DateTime date)
{
switch (mode)
{
case DataNormalizationMode.Raw:
return(1);
case DataNormalizationMode.TotalReturn:
case DataNormalizationMode.SplitAdjusted:
return(factorFile.GetSplitFactor(date));
case DataNormalizationMode.Adjusted:
return(factorFile.GetPriceScaleFactor(date));
default:
throw new ArgumentOutOfRangeException();
}
}
/// <summary>
/// For backwards adjusted data the price is adjusted by a scale factor which is a combination of splits and dividends.
/// This backwards adjusted price is used by default and fed as the current price.
/// </summary>
/// <param name="date">Current date of the backtest.</param>
private void UpdateScaleFactors(DateTime date)
{
switch (_config.DataNormalizationMode)
{
case DataNormalizationMode.Raw:
return;
case DataNormalizationMode.TotalReturn:
case DataNormalizationMode.SplitAdjusted:
_config.PriceScaleFactor = _factorFile.GetSplitFactor(date);
break;
case DataNormalizationMode.Adjusted:
_config.PriceScaleFactor = _factorFile.GetPriceScaleFactor(date);
break;
default:
throw new ArgumentOutOfRangeException();
}
}
/// <summary>
/// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
/// </summary>
/// <param name="data">Slice object keyed by symbol containing the stock data</param>
public override void OnData(Slice data)
{
if (!Portfolio.Invested)
{
SetHoldings(_aapl, 1);
}
if (data.Splits.ContainsKey(_aapl))
{
Log(data.Splits[_aapl].ToString());
}
if (data.Bars.ContainsKey(_aapl))
{
var aaplData = data.Bars[_aapl];
// Assert our volume matches what we expect
if (_expectedAdjustedVolume.MoveNext() && _expectedAdjustedVolume.Current != aaplData.Volume)
{
// Our values don't match lets try and give a reason why
var dayFactor = _factorFile.GetSplitFactor(aaplData.Time);
var probableAdjustedVolume = aaplData.Volume / dayFactor;
if (_expectedAdjustedVolume.Current == probableAdjustedVolume)
{
throw new ArgumentException($"Volume was incorrect; but manually adjusted value is correct." +
$" Adjustment by multiplying volume by {1 / dayFactor} is not occurring.");
}
else
{
throw new ArgumentException($"Volume was incorrect; even when adjusted manually by" +
$" multiplying volume by {1 / dayFactor}. Data may have changed.");
}
}
}
if (data.QuoteBars.ContainsKey(_aapl))
{
var aaplQuoteData = data.QuoteBars[_aapl];
// Assert our askSize matches what we expect
if (_expectedAdjustedAskSize.MoveNext() && _expectedAdjustedAskSize.Current != aaplQuoteData.LastAskSize)
{
// Our values don't match lets try and give a reason why
var dayFactor = _factorFile.GetSplitFactor(aaplQuoteData.Time);
var probableAdjustedAskSize = aaplQuoteData.LastAskSize / dayFactor;
if (_expectedAdjustedAskSize.Current == probableAdjustedAskSize)
{
throw new ArgumentException($"Ask size was incorrect; but manually adjusted value is correct." +
$" Adjustment by multiplying size by {1 / dayFactor} is not occurring.");
}
else
{
throw new ArgumentException($"Ask size was incorrect; even when adjusted manually by" +
$" multiplying size by {1 / dayFactor}. Data may have changed.");
}
}
// Assert our bidSize matches what we expect
if (_expectedAdjustedBidSize.MoveNext() && _expectedAdjustedBidSize.Current != aaplQuoteData.LastBidSize)
{
// Our values don't match lets try and give a reason why
var dayFactor = _factorFile.GetSplitFactor(aaplQuoteData.Time);
var probableAdjustedBidSize = aaplQuoteData.LastBidSize / dayFactor;
if (_expectedAdjustedBidSize.Current == probableAdjustedBidSize)
{
throw new ArgumentException($"Bid size was incorrect; but manually adjusted value is correct." +
$" Adjustment by multiplying size by {1 / dayFactor} is not occurring.");
}
else
{
throw new ArgumentException($"Bid size was incorrect; even when adjusted manually by" +
$" multiplying size by {1 / dayFactor}. Data may have changed.");
}
}
}
}
