private double GetMonteCarloProbHighTouchesM(double sigma, int numSteps, double m, int iterations)
        {
            var countAbove = 0;

            for (var i = 0; i < iterations; i++)
            {
                var hasAbove = false;

                var startPrice = 0.0;
                for (var j = 0; j < numSteps; j++)
                {
                    startPrice += Gaussian.BoxMuller(0, sigma);
                    if (startPrice >= m)
                    {
                        hasAbove = true;
                        break;
                    }
                }

                if (hasAbove)
                {
                    countAbove++;
                }
            }

            return((double)countAbove / iterations);
        }
示例#2
0
        private void GenerateLoop()
        {
            var genPass    = new Random();
            var quoteNames = new[] { "EURUSD", "GBPUSD", "USDJPY", "USDCHF" };
            var quoteMO    = new[] { 1.2858f, 1.4261f, 96.45f, 0.9875f };
            var quoteSig   = new[] { 0.0003f, 0.0004f, 0.03f, 0.0003f };

            while (!stopFlag)
            {
                var lstNames  = new List <string>();
                var lstQuotes = new List <QuoteData>();

                for (var i = 0; i < quoteNames.Length; i++)
                {
                    // случайно пропустить пару
                    if (genPass.Next(100) > 70)
                    {
                        continue;
                    }
                    // расчитать новое значение
                    quoteMO[i] = quoteMO[i] + quoteSig[i] * (float)Gaussian.BoxMuller(0, 0.00015f);
                    lstNames.Add(quoteNames[i]);
                    lstQuotes.Add(new QuoteData(quoteMO[i], quoteMO[i] + quoteSig[i], DateTime.Now));
                    if (onQuotesReceived != null)
                    {
                        onQuotesReceived(lstNames, lstQuotes);
                    }
                }

                Thread.Sleep(200);
            }
        }
示例#3
0
    //public override void Add(Plant p)
    //{
    //	p.Tilt = InitialTilt();
    //	p.currNormal = Quaternion.identity;
    //}

    protected Quaternion InitialTilt()
    {
        var gaussian = Gaussian.BoxMuller();
        var tilt     = Quaternion.FromToRotation(Vector3.up, Vector3.back)
                       * Quaternion.Euler(tiltPower * gaussian.x, Random.Range(0f, ROUND_IN_DEG), tiltPower * gaussian.y);

        return(tilt);
    }
示例#4
0
文件: MCMC.cs 项目: Hengle/Gist
        public Vector2 RandomStep()
        {
#if RANDOM_UNIFORM
            return(new Vector2(
                       sigma * dist.x * Random.Range(-1f, 1f),
                       sigma * dist.y * Random.Range(-1f, 1f)));
#else
            var g = Gaussian.BoxMuller();
            return(new Vector2(sigma * dist.x * g.x, sigma * dist.y * g.y));
#endif
        }
示例#5
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        public void TestDeltaGeneration()
        {
            var candles = new List <CandleData>();

            for (var i = 0; i < 10000; i++)
            {
                var delta = Gaussian.BoxMuller(0, 1);
                candles.Add(new CandleData(100, 100,
                                           99, 100 + (float)delta, new DateTime(), new DateTime()));
            }
            // небольшой процент больших смещений
            for (var i = 0; i < 10; i++)
            {
                var delta = 5 * (i % 2 == 0 ? 1 : -1);
                candles.Add(new CandleData(100, 100,
                                           99, 100 + 1f * (float)delta, new DateTime(), new DateTime()));
            }
            var listOc = candles.Select(c => (double)(c.close - c.open)).OrderBy(c => c).ToList();
            var model  = new PriceModel(listOc);

            const int checksCount = 5000;
            var       deltas      = new double[checksCount];

            for (var i = 0; i < checksCount; i++)
            {
                deltas[i] = model.GetRandomDelta();
            }

            var meanDelta = deltas.Average();
            var maxDelta  = deltas.Max(d => Math.Abs(d));
            var vl        = deltas.Sum(d => (d - meanDelta) * (d - meanDelta));

            vl = Math.Sqrt(vl / checksCount);

            Assert.Less(Math.Abs(meanDelta), 0.3, "Mean value should be around 0");
            Assert.Less(Math.Abs(vl - 1), 0.3, "AD should be around 1");
            Assert.Greater(maxDelta, 1, "max delta should be greater than 1");
        }
 public double CalculateDelta()
 {
     return(Gaussian.BoxMuller(0, volatility.Value));
 }