public void CanSample()
{
var n = new Laplace();
n.Sample();
}
public void CanSampleSequence()
{
var n = new Laplace();
var ied = n.Samples();
GC.KeepAlive(ied.Take(5).ToArray());
}
public void ValidateDensity(double location, double scale, double x)
{
var n = new Laplace(location, scale);
double expected = Math.Exp(-Math.Abs(x - location)/scale)/(2.0*scale);
Assert.AreEqual(expected, n.Density(x));
Assert.AreEqual(expected, Laplace.PDF(location, scale, x));
}
public void ValidateDensityLn(double location, double scale, double x)
{
var n = new Laplace(location, scale);
double expected = -Math.Log(2.0*scale) - (Math.Abs(x - location)/scale);
Assert.AreEqual(expected, n.DensityLn(x));
Assert.AreEqual(expected, Laplace.PDFLn(location, scale, x));
}
public void ValidateMean(double location, double scale)
{
var n = new Laplace(location, scale);
Assert.AreEqual(location, n.Mean);
}
public void SetScaleFailsWithNegativeScale(double scale)
{
var n = new Laplace();
Assert.Throws<ArgumentOutOfRangeException>(() => n.Scale = scale);
}
public void ValidateEntropy(double location, double scale)
{
var n = new Laplace(location, scale);
Assert.AreEqual(Math.Log(2.0 * Constants.E * scale), n.Entropy);
}
public void CanCreateLaplace(double location, double scale)
{
var n = new Laplace(location, scale);
Assert.AreEqual(location, n.Location);
Assert.AreEqual(scale, n.Scale);
}
public void ValidateVariance(double location, double scale)
{
var n = new Laplace(location, scale);
Assert.AreEqual(2.0 * scale * scale, n.Variance);
}
public void ValidateStdDev(double location, double scale)
{
var n = new Laplace(location, scale);
Assert.AreEqual(Constants.Sqrt2 * scale, n.StdDev);
}
public void SetScaleFailsWithNegativeScale(double scale)
{
var n = new Laplace();
Assert.That(() => n.Scale = scale, Throws.ArgumentException);
}
public void SetLocationFailsWithNegativeLocation()
{
var n = new Laplace();
Assert.That(() => n.Location = Double.NaN, Throws.ArgumentException);
}
static void Main(string[] args)
{
var randomGenerator = new Random();
var fundamentalValue = GenerateFunamentalValuePath(SimulationSteps, FundamentalValueInitial, FundamentalValueDrift, FundamentalValueVariance);
var fundamentalistScale = 10;
var chartistScale = 1.2;
var noiseScale = 1;
var fundamentalistDistribution = new Laplace(0, fundamentalistScale);
fundamentalistDistribution.RandomSource = randomGenerator;
var chartistDistribution = new Laplace(0, chartistScale);
chartistDistribution.RandomSource = randomGenerator;
var noiseDistribution = new Laplace(0, noiseScale);
noiseDistribution.RandomSource = randomGenerator;
var normal = new Normal(0, 5);
_agents = new HetroTradingRulesAgent[NumberOfAgents];
var solver = new Brent();
for (int i = 0; i < NumberOfAgents; i++)
{
_agents[i] = new HetroTradingRulesAgent(Math.Abs(fundamentalistDistribution.Sample()), Math.Abs(chartistDistribution.Sample()), Math.Abs(noiseDistribution.Sample()), ReferenceAgentTimeHorizon, ReferenceRiskAversionLevel, randomGenerator, solver);
_agents[i].StockHeld = (int)Math.Floor(MaxNumberOfStock * randomGenerator.NextDouble());
_agents[i].CashHeld = Math.Round(MaxNumberOfStock * FundamentalValueInitial * randomGenerator.NextDouble(), 2);
}
Thread.Sleep(1000);
var connection = new HubConnection(@"http://*****:*****@"c:\temp\hetroTradingRulesNoiseFundChart.csv";
File.WriteAllLines(outputFile, new string[] { string.Format("{0},{1},{2}", "TimeStep", "Price", "Fundamental") });
for (int i = stepsToFill; i < SimulationSteps - ReferenceAgentTimeHorizon; i++)
{
var agentIndex = (int)Math.Round((NumberOfAgents - 1) * randomGenerator.NextDouble());
Order order = null;
try
{
order = _agents[agentIndex].GetAction(i, spotPrice, fundamentalValue, noise, _currentLimitOrderBook != null ? _currentLimitOrderBook.BestBidPrice : null, _currentLimitOrderBook != null ? _currentLimitOrderBook.BestAskPrice : null);
}
catch (Exception e)
{
System.Console.WriteLine("ERROR: {0}", e.Message);
}
if (order != null)
{
order.UserID = agentIndex.ToString();
var r = hub.Invoke<bool>("ProcessOrderInstruction", order, agentIndex.ToString());
r.Wait();
Thread.Sleep(10);
if (order.Type == OrderType.MarketOrder)
{
spotPrice[i] = order.Price;
}
else
if (_currentLimitOrderBook != null && _currentLimitOrderBook.BestAskPrice.HasValue && _currentLimitOrderBook.BestBidPrice.HasValue)
{
spotPrice[i] = (_currentLimitOrderBook.BestBidPrice.Value + _currentLimitOrderBook.BestAskPrice.Value) / 2;
}
//else if (_currentLimitOrderBook != null && _currentLimitOrderBook.BestAskPrice.HasValue)
//{
// spotPrice[i] = _currentLimitOrderBook.BestAskPrice.Value;
//}
//else if (_currentLimitOrderBook != null && _currentLimitOrderBook.BestBidPrice.HasValue)
//{
// spotPrice[i] = _currentLimitOrderBook.BestBidPrice.Value;
//}
else
{
spotPrice[i] = spotPrice[i - 1];
}
}
else
{
spotPrice[i] = spotPrice[i - 1];
}
File.AppendAllLines(outputFile, new string[] { string.Format("{0},{1},{2}", i, spotPrice[i], fundamentalValue[i]) });
System.Console.WriteLine(string.Format("{0}\t\t{1}",i,spotPrice[i]));
}
}
public void ValidateCumulativeDistribution(double location, double scale, double x)
{
var n = new Laplace(location, scale);
double expected = 0.5*(1.0 + (Math.Sign(x - location)*(1.0 - Math.Exp(-Math.Abs(x - location)/scale))));
Assert.AreEqual(expected, n.CumulativeDistribution(x));
Assert.AreEqual(expected, Laplace.CDF(location, scale, x));
}
public void ValidateSkewness(double location, double scale)
{
var n = new Laplace(location, scale);
Assert.AreEqual(0.0, n.Skewness);
}
public void CanCreateLaplace()
{
var n = new Laplace();
Assert.AreEqual(0.0, n.Location);
Assert.AreEqual(1.0, n.Scale);
}
public void ValidateMinimum()
{
var n = new Laplace();
Assert.AreEqual(Double.NegativeInfinity, n.Minimum);
}
public void ValidateToString()
{
var n = new Laplace(-1d, 2d);
Assert.AreEqual("Laplace(μ = -1, b = 2)", n.ToString());
}
public void ValidateMaximum()
{
var n = new Laplace();
Assert.AreEqual(Double.PositiveInfinity, n.Maximum);
}
/// <summary>
/// Run example
/// </summary>
/// <a href="http://en.wikipedia.org/wiki/Laplace_distribution">Laplace distribution</a>
public void Run()
{
// 1. Initialize the new instance of the Laplace distribution class with parameters Location = {0}, Scale = {1}
var laplace = new Laplace(0, 1);
Console.WriteLine(@"1. Initialize the new instance of the Laplace distribution class with parameters Location = {0}, Scale = {1}", laplace.Location, laplace.Scale);
Console.WriteLine();
// 2. Distributuion properties:
Console.WriteLine(@"2. {0} distributuion properties:", laplace);
// Cumulative distribution function
Console.WriteLine(@"{0} - Сumulative distribution at location '0.3'", laplace.CumulativeDistribution(0.3).ToString(" #0.00000;-#0.00000"));
// Probability density
Console.WriteLine(@"{0} - Probability density at location '0.3'", laplace.Density(0.3).ToString(" #0.00000;-#0.00000"));
// Log probability density
Console.WriteLine(@"{0} - Log probability density at location '0.3'", laplace.DensityLn(0.3).ToString(" #0.00000;-#0.00000"));
// Entropy
Console.WriteLine(@"{0} - Entropy", laplace.Entropy.ToString(" #0.00000;-#0.00000"));
// Largest element in the domain
Console.WriteLine(@"{0} - Largest element in the domain", laplace.Maximum.ToString(" #0.00000;-#0.00000"));
// Smallest element in the domain
Console.WriteLine(@"{0} - Smallest element in the domain", laplace.Minimum.ToString(" #0.00000;-#0.00000"));
// Mean
Console.WriteLine(@"{0} - Mean", laplace.Mean.ToString(" #0.00000;-#0.00000"));
// Median
Console.WriteLine(@"{0} - Median", laplace.Median.ToString(" #0.00000;-#0.00000"));
// Mode
Console.WriteLine(@"{0} - Mode", laplace.Mode.ToString(" #0.00000;-#0.00000"));
// Variance
Console.WriteLine(@"{0} - Variance", laplace.Variance.ToString(" #0.00000;-#0.00000"));
// Standard deviation
Console.WriteLine(@"{0} - Standard deviation", laplace.StdDev.ToString(" #0.00000;-#0.00000"));
// Skewness
Console.WriteLine(@"{0} - Skewness", laplace.Skewness.ToString(" #0.00000;-#0.00000"));
Console.WriteLine();
// 3. Generate 10 samples of the Laplace distribution
Console.WriteLine(@"3. Generate 10 samples of the Laplace distribution");
for (var i = 0; i < 10; i++)
{
Console.Write(laplace.Sample().ToString("N05") + @" ");
}
Console.WriteLine();
Console.WriteLine();
// 4. Generate 100000 samples of the Laplace(0, 1) distribution and display histogram
Console.WriteLine(@"4. Generate 100000 samples of the Laplace(0, 1) distribution and display histogram");
var data = new double[100000];
for (var i = 0; i < data.Length; i++)
{
data[i] = laplace.Sample();
}
ConsoleHelper.DisplayHistogram(data);
Console.WriteLine();
// 5. Generate 100000 samples of the Laplace(0, 4) distribution and display histogram
Console.WriteLine(@"5. Generate 100000 samples of the Laplace(0, 4) distribution and display histogram");
data = new double[100000];
laplace.Scale = 4;
for (var i = 0; i < data.Length; i++)
{
data[i] = laplace.Sample();
}
ConsoleHelper.DisplayHistogram(data);
Console.WriteLine();
// 6. Generate 100000 samples of the Laplace(-10, 4) distribution and display histogram
Console.WriteLine(@"6. Generate 100000 samples of the Laplace(-10 4) distribution and display histogram");
laplace.Location = -10;
for (var i = 0; i < data.Length; i++)
{
data[i] = laplace.Sample();
}
ConsoleHelper.DisplayHistogram(data);
}
public void SetLocationFailsWithNegativeLocation()
{
var n = new Laplace();
Assert.Throws<ArgumentOutOfRangeException>(() => n.Location = Double.NaN);
}