/**
* recalculate interval if total number of partitions greater than maximum number of allowed
* partitions
*
* @param low watermark value
* @param high watermark value
* @param partition interval
* @param Maximum number of allowed partitions
* @return calculated interval
*/
private long getInterval(
long lowWatermarkValue, long highWatermarkValue, long partitionInterval, int maxIntervals) {
if (lowWatermarkValue > highWatermarkValue) {
LOG.info(
"lowWatermarkValue: "
+ lowWatermarkValue
+ " is greater than highWatermarkValue: "
+ highWatermarkValue);
return 0;
}
long outputInterval = partitionInterval;
boolean longOverflow = false;
long totalIntervals = Long.MAX_VALUE;
try {
totalIntervals =
DoubleMath.roundToLong(
(double) highWatermarkValue / partitionInterval
- (double) lowWatermarkValue / partitionInterval,
RoundingMode.CEILING);
} catch (java.lang.ArithmeticException e) {
longOverflow = true;
}
if (longOverflow || totalIntervals > maxIntervals) {
outputInterval =
DoubleMath.roundToLong(
(double) highWatermarkValue / maxIntervals
- (double) lowWatermarkValue / maxIntervals,
RoundingMode.CEILING);
}
return outputInterval;
}
private double getZOverChi(double rho, double z) {
// Implementation comment: To avoid numerical instability (0/0) around ATM the first order
// approximation is used.
if (DoubleMath.fuzzyEquals(z, 0.0, SMALL_Z)) {
return 1.0 - rho * z / 2.0;
}
double rhoStar = 1 - rho;
if (DoubleMath.fuzzyEquals(rhoStar, 0.0, RHO_EPS)) {
if (z < 1.0) {
return -z / Math.log(1.0d - z);
} else {
throw new IllegalArgumentException("can't handle z>=1, rho=1");
}
}
double rhoHat = 1 + rho;
if (DoubleMath.fuzzyEquals(rhoHat, 0.0, RHO_EPS_NEGATIVE)) {
if (z > -1) {
return z / Math.log(1 + z);
} else if (z < -1) {
if (rhoHat == 0) {
return 0.0;
}
double chi = Math.log(rhoHat) - Math.log(-(1 + z) / rhoStar);
return z / chi;
} else {
return 0.0;
}
}
double arg;
if (z < LARGE_NEG_Z) {
arg =
(rho * rho - 1)
/ 2
/ z; // get rounding errors due to fine balanced cancellation for very large negative
// z
} else if (z > LARGE_POS_Z) {
arg = 2 * (z - rho);
} else {
arg = (Math.sqrt(1 - 2 * rho * z + z * z) + z - rho);
// Mathematically this cannot be less than zero, but you know what computers are like.
if (arg <= 0.0) {
return 0.0;
}
}
double chi = Math.log(arg) - Math.log(rhoStar);
return z / chi;
}
@ScalarOperator(SATURATED_FLOOR_CAST)
@SqlType(StandardTypes.INTEGER)
public static long saturatedFloorCastToInteger(@SqlType(StandardTypes.DOUBLE) double value) {
if (value <= MIN_INT_AS_DOUBLE) {
return Integer.MIN_VALUE;
}
if (MAX_INT_AS_DOUBLE - value <= 1) {
return Integer.MAX_VALUE;
}
return DoubleMath.roundToInt(value, FLOOR);
}
@ScalarOperator(SATURATED_FLOOR_CAST)
@SqlType(StandardTypes.BIGINT)
public static long saturatedFloorCastToBigint(@SqlType(StandardTypes.DOUBLE) double value) {
if (value <= MIN_LONG_AS_DOUBLE) {
return Long.MIN_VALUE;
}
if (MAX_LONG_AS_DOUBLE_PLUS_ONE - value <= 1) {
return Long.MAX_VALUE;
}
return DoubleMath.roundToLong(value, FLOOR);
}
synchronized void startPublishingTimer() {
if (state.get() == State.Closed) return;
lifetimeCounter--;
if (lifetimeCounter < 1) {
logger.debug("[id={}] lifetime expired.", subscriptionId);
setState(State.Closing);
} else {
long interval = DoubleMath.roundToLong(publishingInterval, RoundingMode.UP);
subscriptionManager
.getServer()
.getScheduledExecutorService()
.schedule(this::onPublishingTimer, interval, TimeUnit.MILLISECONDS);
}
}
private static Integer parseInteger(String value) {
try {
return Integer.valueOf(value);
} catch (NumberFormatException nfeInteger) {
try {
Double result = parseDouble(value);
if (DoubleMath.isMathematicalInteger(result)) {
return result.intValue();
}
} catch (NumberFormatException nfeDouble) {
// Ignored
}
throw nfeInteger;
}
}
private void writeResultForGnuplot(
AbstractMeter meter, String ds, String operation, int size, Collection<Double> values)
throws IOException {
String dirName = outputDir + "/" + meter.getName() + "/";
// Write data for *single* plot
String fileName = ds + "_" + operation;
String extension = plotExtension;
Writer w = fileWriters.get(dirName + fileName + extension);
if (w == null) {
w = new Writer(dirName, fileName + extension);
writeGnuplotHeaderSingle(w, dirName, fileName, operation, meter, ds);
fileWriters.put(dirName + fileName + extension, w);
}
extension = rawExtension;
w = fileWriters.get(dirName + fileName + extension);
if (w == null) {
w = new Writer(dirName, fileName + extension);
fileWriters.put(dirName + fileName + extension, w);
}
double min = Collections.min(values);
double max = Collections.max(values);
double mean = DoubleMath.mean(values);
w.writeln(" " + size + " " + mean + " " + min + " " + max);
// Check for the aggregation file
extension = plotExtension;
String innerLastWrittenOp = lastWrittenOp.get(dirName + operation + extension);
if (innerLastWrittenOp == null || !innerLastWrittenOp.equals(operation)) {
w = fileWriters.get(dirName + aggregationFile);
if (w == null) {
w = new Writer(dirName, aggregationFile, true);
fileWriters.put(dirName + aggregationFile, w);
}
w.writeln(operation + ";" + meter.getUnit() + ";" + fileName + rawExtension);
}
lastWrittenOp.put(dirName + operation + extension, operation);
}
int determineHighestPossible(int currentMtn, int[] perceivedHighest, int heights[]) {
// Any connection from peaks < currentMtn to peaks after
int highestPossible = 1000000000;
for (int mtn = 1; mtn < currentMtn; ++mtn) {
int percievedMax = perceivedHighest[mtn - 1];
if (percievedMax <= currentMtn) continue;
Line line =
new Line(
new Point(mtn, heights[mtn - 1]), new Point(percievedMax, heights[percievedMax - 1]));
double cur = line.getPointGivenX(currentMtn).y();
int heightInt =
DoubleMath.isMathematicalInteger(cur) ? (int) Math.floor(cur) - 1 : (int) Math.floor(cur);
highestPossible = Math.min(heightInt, highestPossible);
}
return highestPossible;
}
@Override
public List<WorkUnit> pack(Map<String, List<WorkUnit>> workUnitsByTopic, int numContainers) {
setWorkUnitEstSizes(workUnitsByTopic);
List<WorkUnit> workUnits = Lists.newArrayList();
for (List<WorkUnit> workUnitsForTopic : workUnitsByTopic.values()) {
// For each topic, merge all empty workunits into a single workunit, so that a single
// empty task will be created instead of many.
MultiWorkUnit zeroSizeWorkUnit = MultiWorkUnit.createEmpty();
for (WorkUnit workUnit : workUnitsForTopic) {
if (DoubleMath.fuzzyEquals(getWorkUnitEstSize(workUnit), 0.0, EPS)) {
addWorkUnitToMultiWorkUnit(workUnit, zeroSizeWorkUnit);
} else {
workUnit.setWatermarkInterval(getWatermarkIntervalFromWorkUnit(workUnit));
workUnits.add(workUnit);
}
}
if (!zeroSizeWorkUnit.getWorkUnits().isEmpty()) {
workUnits.add(squeezeMultiWorkUnit(zeroSizeWorkUnit));
}
}
return worstFitDecreasingBinPacking(workUnits, numContainers);
}
public void test_cashFlowEquivalent() {
Swap swap = Swap.builder().legs(IBOR_LEG, FIXED_LEG).build();
ExpandedSwapLeg computed =
CashFlowEquivalentCalculator.cashFlowEquivalentSwap(swap.expand(), PROVIDER);
ExpandedSwapLeg computedIborLeg =
CashFlowEquivalentCalculator.cashFlowEquivalentIborLeg(IBOR_LEG.expand(), PROVIDER);
ExpandedSwapLeg computedFixedLeg =
CashFlowEquivalentCalculator.cashFlowEquivalentFixedLeg(FIXED_LEG.expand(), PROVIDER);
assertEquals(computedFixedLeg.getPaymentEvents(), computed.getPaymentEvents().subList(0, 2));
assertEquals(computedIborLeg.getPaymentEvents(), computed.getPaymentEvents().subList(2, 6));
// expected payments from fixed leg
NotionalExchange fixedPayment1 =
NotionalExchange.of(PAYMENT1, CurrencyAmount.of(GBP, NOTIONAL * RATE * PAY_YC1));
NotionalExchange fixedPayment2 =
NotionalExchange.of(PAYMENT2, CurrencyAmount.of(GBP, NOTIONAL * RATE * PAY_YC2));
// expected payments from ibor leg
LocalDate fixingSTART1 = GBP_LIBOR_3M.calculateEffectiveFromFixing(FIXING1);
double fixedYearFraction1 =
GBP_LIBOR_3M
.getDayCount()
.relativeYearFraction(
fixingSTART1, GBP_LIBOR_3M.calculateMaturityFromEffective(fixingSTART1));
double beta1 =
(1d + fixedYearFraction1 * PROVIDER.iborIndexRates(GBP_LIBOR_3M).rate(FIXING1))
* PROVIDER.discountFactor(GBP, PAYMENT1)
/ PROVIDER.discountFactor(GBP, fixingSTART1);
NotionalExchange iborPayment11 =
NotionalExchange.of(
fixingSTART1, CurrencyAmount.of(GBP, -NOTIONAL * beta1 * PAY_YC1 / fixedYearFraction1));
NotionalExchange iborPayment12 =
NotionalExchange.of(
PAYMENT1, CurrencyAmount.of(GBP, NOTIONAL * PAY_YC1 / fixedYearFraction1));
LocalDate fixingSTART2 = GBP_LIBOR_3M.calculateEffectiveFromFixing(FIXING2);
double fixedYearFraction2 =
GBP_LIBOR_3M
.getDayCount()
.relativeYearFraction(
fixingSTART2, GBP_LIBOR_3M.calculateMaturityFromEffective(fixingSTART2));
double beta2 =
(1d + fixedYearFraction2 * PROVIDER.iborIndexRates(GBP_LIBOR_3M).rate(FIXING2))
* PROVIDER.discountFactor(GBP, PAYMENT2)
/ PROVIDER.discountFactor(GBP, fixingSTART2);
NotionalExchange iborPayment21 =
NotionalExchange.of(
fixingSTART2, CurrencyAmount.of(GBP, -NOTIONAL * beta2 * PAY_YC2 / fixedYearFraction2));
NotionalExchange iborPayment22 =
NotionalExchange.of(
PAYMENT2, CurrencyAmount.of(GBP, NOTIONAL * PAY_YC2 / fixedYearFraction2));
ExpandedSwapLeg expected =
ExpandedSwapLeg.builder()
.type(OTHER)
.payReceive(RECEIVE)
.paymentEvents(
fixedPayment1,
fixedPayment2,
iborPayment11,
iborPayment12,
iborPayment21,
iborPayment22)
.build();
double eps = 1.0e-12;
assertEquals(computed.getPaymentEvents().size(), expected.getPaymentEvents().size());
for (int i = 0; i < 6; ++i) {
NotionalExchange payCmp = (NotionalExchange) computed.getPaymentEvents().get(i);
NotionalExchange payExp = (NotionalExchange) expected.getPaymentEvents().get(i);
assertEquals(payCmp.getCurrency(), payExp.getCurrency());
assertEquals(payCmp.getPaymentDate(), payExp.getPaymentDate());
assertTrue(
DoubleMath.fuzzyEquals(
payCmp.getPaymentAmount().getAmount(),
payExp.getPaymentAmount().getAmount(),
NOTIONAL * eps));
}
}
/**
* Erzeugt einen neuen Pixel an der Stelle (x,y). Die doubles werden entsprechend auf die
* Integerpositionen des Pixels gerundet.
*
* @param x die x-Koordinate des Pixels
* @param y die y-Koordinate des Pixels
*/
public Pixel(double x, double y) {
this.x = DoubleMath.roundToInt(x, RoundingMode.HALF_DOWN);
this.y = DoubleMath.roundToInt(y, RoundingMode.HALF_DOWN);
}
/**
* Computes the first and second order derivatives of the Black implied volatility in the SABR
* model.
*
* <p>The first derivative values will be stored in the input array {@code volatilityD} The array
* contains, [0] Derivative w.r.t the forward, [1] the derivative w.r.t the strike, [2] the
* derivative w.r.t. to alpha, [3] the derivative w.r.t. to beta, [4] the derivative w.r.t. to
* rho, and [5] the derivative w.r.t. to nu. Thus the length of the array should be 6.
*
* <p>The second derivative values will be stored in the input array {@code volatilityD2}. Only
* the second order derivative with respect to the forward and strike are implemented. The array
* contains [0][0] forward-forward; [0][1] forward-strike; [1][1] strike-strike. Thus the size
* should be 2 x 2.
*
* <p>Around ATM, a first order expansion is used to due to some 0/0-type indetermination. The
* second order derivative produced is poor around ATM.
*
* @param forward the forward value of the underlying
* @param strike the strike value of the option
* @param timeToExpiry the time to expiry of the option
* @param data the SABR data.
* @param volatilityD the array used to return the first order derivative
* @param volatilityD2 the array of array used to return the second order derivative
* @return the Black implied volatility
*/
@Override
public double volatilityAdjoint2(
double forward,
double strike,
double timeToExpiry,
SabrFormulaData data,
double[] volatilityD,
double[][] volatilityD2) {
double k = Math.max(strike, 0.000001);
double alpha = data.getAlpha();
double beta = data.getBeta();
double rho = data.getRho();
double nu = data.getNu();
// Forward
double h0 = (1 - beta) / 2;
double h1 = forward * k;
double h1h0 = Math.pow(h1, h0);
double h12 = h1h0 * h1h0;
double h2 = Math.log(forward / k);
double h22 = h2 * h2;
double h23 = h22 * h2;
double h24 = h23 * h2;
double f1 = h1h0 * (1 + h0 * h0 / 6.0 * (h22 + h0 * h0 / 20.0 * h24));
double f2 = nu / alpha * h1h0 * h2;
double f3 =
h0 * h0 / 6.0 * alpha * alpha / h12
+ rho * beta * nu * alpha / 4.0 / h1h0
+ (2 - 3 * rho * rho) / 24.0 * nu * nu;
double sqrtf2 = Math.sqrt(1 - 2 * rho * f2 + f2 * f2);
double f2x = 0.0;
double x = 0.0, xp = 0, xpp = 0;
if (DoubleMath.fuzzyEquals(f2, 0.0, SMALL_Z)) {
f2x = 1.0 - 0.5 * f2 * rho; // small f2 expansion to f2^2 terms
} else {
if (DoubleMath.fuzzyEquals(rho, 1.0, RHO_EPS)) {
x =
f2 < 1.0
? -Math.log(1.0 - f2) - 0.5 * Math.pow(f2 / (f2 - 1.0), 2) * (1.0 - rho)
: Math.log(2.0 * f2 - 2.0) - Math.log(1.0 - rho);
} else {
x = Math.log((sqrtf2 + f2 - rho) / (1 - rho));
}
xp = 1. / sqrtf2;
xpp = (rho - f2) / Math.pow(sqrtf2, 3.0);
f2x = f2 / x;
}
double sigma = Math.max(MIN_VOL, alpha / f1 * f2x * (1 + f3 * timeToExpiry));
// First level
double h0Dbeta = -0.5;
double sigmaDf1 = -sigma / f1;
double sigmaDf2 = 0;
if (DoubleMath.fuzzyEquals(f2, 0.0, SMALL_Z)) {
sigmaDf2 = alpha / f1 * (1 + f3 * timeToExpiry) * -0.5 * rho;
} else {
sigmaDf2 = alpha / f1 * (1 + f3 * timeToExpiry) * (1.0 / x - f2 * xp / (x * x));
}
double sigmaDf3 = alpha / f1 * f2x * timeToExpiry;
double sigmaDf4 = f2x / f1 * (1 + f3 * timeToExpiry);
double sigmaDx = -alpha / f1 * f2 / (x * x) * (1 + f3 * timeToExpiry);
double[][] sigmaD2ff = new double[3][3];
sigmaD2ff[0][0] = -sigmaDf1 / f1 + sigma / (f1 * f1); // OK
sigmaD2ff[0][1] = -sigmaDf2 / f1;
sigmaD2ff[0][2] = -sigmaDf3 / f1;
if (DoubleMath.fuzzyEquals(f2, 0.0, SMALL_Z)) {
sigmaD2ff[1][2] = alpha / f1 * -0.5 * rho * timeToExpiry;
} else {
sigmaD2ff[1][1] =
alpha
/ f1
* (1 + f3 * timeToExpiry)
* (-2 * xp / (x * x) - f2 * xpp / (x * x) + 2 * f2 * xp * xp / (x * x * x));
sigmaD2ff[1][2] = alpha / f1 * timeToExpiry * (1.0 / x - f2 * xp / (x * x));
}
sigmaD2ff[2][2] = 0.0;
// double sigma = alpha / f1 * f2x * (1 + f3 * theta);
// Second level
double[] f1Dh = new double[3];
double[] f2Dh = new double[3];
double[] f3Dh = new double[3];
f1Dh[0] = h1h0 * (h0 * (h22 / 3.0 + h0 * h0 / 40.0 * h24)) + Math.log(h1) * f1;
f1Dh[1] = h0 * f1 / h1;
f1Dh[2] = h1h0 * (h0 * h0 / 6.0 * (2.0 * h2 + h0 * h0 / 5.0 * h23));
f2Dh[0] = Math.log(h1) * f2;
f2Dh[1] = h0 * f2 / h1;
f2Dh[2] = nu / alpha * h1h0;
f3Dh[0] =
h0 / 3.0 * alpha * alpha / h12
- 2 * h0 * h0 / 6.0 * alpha * alpha / h12 * Math.log(h1)
- rho * beta * nu * alpha / 4.0 / h1h0 * Math.log(h1);
f3Dh[1] =
-2 * h0 * h0 / 6.0 * alpha * alpha / h12 * h0 / h1
- rho * beta * nu * alpha / 4.0 / h1h0 * h0 / h1;
f3Dh[2] = 0.0;
double[] f1Dp = new double[4]; // Derivative to sabr parameters
double[] f2Dp = new double[4];
double[] f3Dp = new double[4];
double[] f4Dp = new double[4];
f1Dp[0] = 0.0;
f1Dp[1] = f1Dh[0] * h0Dbeta;
f1Dp[2] = 0.0;
f1Dp[3] = 0.0;
f2Dp[0] = -f2 / alpha;
f2Dp[1] = f2Dh[0] * h0Dbeta;
f2Dp[2] = 0.0;
f2Dp[3] = h1h0 * h2 / alpha;
f3Dp[0] = h0 * h0 / 3.0 * alpha / h12 + rho * beta * nu / 4.0 / h1h0;
f3Dp[1] = rho * nu * alpha / 4.0 / h1h0 + f3Dh[0] * h0Dbeta;
f3Dp[2] = beta * nu * alpha / 4.0 / h1h0 - rho / 4.0 * nu * nu;
f3Dp[3] = rho * beta * alpha / 4.0 / h1h0 + (2 - 3 * rho * rho) / 12.0 * nu;
f4Dp[0] = 1.0;
f4Dp[1] = 0.0;
f4Dp[2] = 0.0;
f4Dp[3] = 0.0;
double sigmaDh1 = sigmaDf1 * f1Dh[1] + sigmaDf2 * f2Dh[1] + sigmaDf3 * f3Dh[1];
double sigmaDh2 = sigmaDf1 * f1Dh[2] + sigmaDf2 * f2Dh[2] + sigmaDf3 * f3Dh[2];
double[][] f1D2hh = new double[2][2]; // No h0
double[][] f2D2hh = new double[2][2];
double[][] f3D2hh = new double[2][2];
f1D2hh[0][0] = h0 * (h0 - 1) * f1 / (h1 * h1);
f1D2hh[0][1] = h0 * h1h0 / h1 * h0 * h0 / 6.0 * (2.0 * h2 + 4.0 * h0 * h0 / 20.0 * h23);
f1D2hh[1][1] = h1h0 * (h0 * h0 / 6.0 * (2.0 + 12.0 * h0 * h0 / 20.0 * h2));
f2D2hh[0][0] = h0 * (h0 - 1) * f2 / (h1 * h1);
f2D2hh[0][1] = nu / alpha * h0 * h1h0 / h1;
f2D2hh[1][1] = 0.0;
f3D2hh[0][0] =
2 * h0 * (2 * h0 + 1) * h0 * h0 / 6.0 * alpha * alpha / (h12 * h1 * h1)
+ h0 * (h0 + 1) * rho * beta * nu * alpha / 4.0 / (h1h0 * h1 * h1);
f3D2hh[0][1] = 0.0;
f3D2hh[1][1] = 0.0;
double[][] sigmaD2hh = new double[2][2]; // No h0
for (int loopx = 0; loopx < 2; loopx++) {
for (int loopy = loopx; loopy < 2; loopy++) {
sigmaD2hh[loopx][loopy] =
(sigmaD2ff[0][0] * f1Dh[loopy + 1]
+ sigmaD2ff[0][1] * f2Dh[loopy + 1]
+ sigmaD2ff[0][2] * f3Dh[loopy + 1])
* f1Dh[loopx + 1]
+ sigmaDf1 * f1D2hh[loopx][loopy]
+ (sigmaD2ff[0][1] * f1Dh[loopy + 1]
+ sigmaD2ff[1][1] * f2Dh[loopy + 1]
+ sigmaD2ff[1][2] * f3Dh[loopy + 1])
* f2Dh[loopx + 1]
+ sigmaDf2 * f2D2hh[loopx][loopy]
+ (sigmaD2ff[0][2] * f1Dh[loopy + 1]
+ sigmaD2ff[1][2] * f2Dh[loopy + 1]
+ sigmaD2ff[2][2] * f3Dh[loopy + 1])
* f3Dh[loopx + 1]
+ sigmaDf3 * f3D2hh[loopx][loopy];
}
}
// Third level
double h1Df = k;
double h1Dk = forward;
double h1D2ff = 0.0;
double h1D2kf = 1.0;
double h1D2kk = 0.0;
double h2Df = 1.0 / forward;
double h2Dk = -1.0 / k;
double h2D2ff = -1 / (forward * forward);
double h2D2fk = 0.0;
double h2D2kk = 1.0 / (k * k);
volatilityD[0] = sigmaDh1 * h1Df + sigmaDh2 * h2Df;
volatilityD[1] = sigmaDh1 * h1Dk + sigmaDh2 * h2Dk;
volatilityD[2] =
sigmaDf1 * f1Dp[0] + sigmaDf2 * f2Dp[0] + sigmaDf3 * f3Dp[0] + sigmaDf4 * f4Dp[0];
volatilityD[3] =
sigmaDf1 * f1Dp[1] + sigmaDf2 * f2Dp[1] + sigmaDf3 * f3Dp[1] + sigmaDf4 * f4Dp[1];
if (DoubleMath.fuzzyEquals(f2, 0.0, SMALL_Z)) {
volatilityD[4] = -0.5 * f2 + sigmaDf3 * f3Dp[2];
} else {
double xDr;
if (DoubleMath.fuzzyEquals(rho, 1.0, RHO_EPS)) {
xDr =
f2 > 1.0
? 1.0 / (1.0 - rho) + (0.5 - f2) / (f2 - 1.0) / (f2 - 1.0)
: 0.5 * Math.pow(f2 / (1.0 - f2), 2.0)
+ 0.25 * (f2 - 4.0) * Math.pow(f2 / (f2 - 1.0), 3) / (f2 - 1.0) * (1.0 - rho);
if (Doubles.isFinite(xDr)) {
volatilityD[4] =
sigmaDf1 * f1Dp[2] + sigmaDx * xDr + sigmaDf3 * f3Dp[2] + sigmaDf4 * f4Dp[2];
} else {
volatilityD[4] = Double.NEGATIVE_INFINITY;
}
} else {
xDr = (-f2 / sqrtf2 - 1 + (sqrtf2 + f2 - rho) / (1 - rho)) / (sqrtf2 + f2 - rho);
volatilityD[4] =
sigmaDf1 * f1Dp[2] + sigmaDx * xDr + sigmaDf3 * f3Dp[2] + sigmaDf4 * f4Dp[2];
}
}
volatilityD[5] =
sigmaDf1 * f1Dp[3] + sigmaDf2 * f2Dp[3] + sigmaDf3 * f3Dp[3] + sigmaDf4 * f4Dp[3];
volatilityD2[0][0] =
(sigmaD2hh[0][0] * h1Df + sigmaD2hh[0][1] * h2Df) * h1Df
+ sigmaDh1 * h1D2ff
+ (sigmaD2hh[0][1] * h1Df + sigmaD2hh[1][1] * h2Df) * h2Df
+ sigmaDh2 * h2D2ff;
volatilityD2[0][1] =
(sigmaD2hh[0][0] * h1Dk + sigmaD2hh[0][1] * h2Dk) * h1Df
+ sigmaDh1 * h1D2kf
+ (sigmaD2hh[0][1] * h1Dk + sigmaD2hh[1][1] * h2Dk) * h2Df
+ sigmaDh2 * h2D2fk;
volatilityD2[1][0] = volatilityD2[0][1];
volatilityD2[1][1] =
(sigmaD2hh[0][0] * h1Dk + sigmaD2hh[0][1] * h2Dk) * h1Dk
+ sigmaDh1 * h1D2kk
+ (sigmaD2hh[0][1] * h1Dk + sigmaD2hh[1][1] * h2Dk) * h2Dk
+ sigmaDh2 * h2D2kk;
return sigma;
}
@Override
public double factorialDouble(int n) {
return DoubleMath.factorial(n);
}
@Override
public double volatility(
double forward,
double strike,
double timeToExpiry,
double alpha,
double beta,
double rho,
double nu) {
ArgChecker.isTrue(forward > 0.0, "forward must be greater than zero");
ArgChecker.isTrue(strike >= 0.0, "strike must be greater than zero");
ArgChecker.isTrue(timeToExpiry >= 0.0, "timeToExpiry must be greater than zero");
if (alpha == 0.0) {
return 0.0;
}
double cutoff = forward * CUTOFF_MONEYNESS;
double k;
if (strike < cutoff) {
Logger s_logger = LoggerFactory.getLogger(SabrHaganVolatilityFunctionProvider.class);
s_logger.info(
"Given strike of {} is less than cutoff at {}, therefore the strike is taken as {}",
new Object[] {strike, cutoff, cutoff});
k = cutoff;
} else {
k = strike;
}
double vol, z, zOverChi;
double beta1 = 1 - beta;
if (DoubleMath.fuzzyEquals(forward, k, ATM_EPS)) {
double f1 = Math.pow(forward, beta1);
vol =
alpha
* (1
+ timeToExpiry
* (beta1 * beta1 * alpha * alpha / 24 / f1 / f1
+ rho * alpha * beta * nu / 4 / f1
+ nu * nu * (2 - 3 * rho * rho) / 24))
/ f1;
} else {
if (DoubleMath.fuzzyEquals(beta, 0, BETA_EPS)) {
double ln = Math.log(forward / k);
z = nu * Math.sqrt(forward * k) * ln / alpha;
zOverChi = getZOverChi(rho, z);
vol =
alpha
* ln
* zOverChi
* (1
+ timeToExpiry
* (alpha * alpha / forward / k + nu * nu * (2 - 3 * rho * rho))
/ 24)
/ (forward - k);
} else if (DoubleMath.fuzzyEquals(beta, 1, BETA_EPS)) {
double ln = Math.log(forward / k);
z = nu * ln / alpha;
zOverChi = getZOverChi(rho, z);
vol =
alpha
* zOverChi
* (1 + timeToExpiry * (rho * alpha * nu / 4 + nu * nu * (2 - 3 * rho * rho) / 24));
} else {
double ln = Math.log(forward / k);
double f1 = Math.pow(forward * k, beta1);
double f1Sqrt = Math.sqrt(f1);
double lnBetaSq = Math.pow(beta1 * ln, 2);
z = nu * f1Sqrt * ln / alpha;
zOverChi = getZOverChi(rho, z);
double first = alpha / (f1Sqrt * (1 + lnBetaSq / 24 + lnBetaSq * lnBetaSq / 1920));
double second = zOverChi;
double third =
1
+ timeToExpiry
* (beta1 * beta1 * alpha * alpha / 24 / f1
+ rho * nu * beta * alpha / 4 / f1Sqrt
+ nu * nu * (2 - 3 * rho * rho) / 24);
vol = first * second * third;
}
}
// There is nothing to prevent the nu * nu * (2 - 3 * rho * rho) / 24 to be large negative, and
// hence the volatility negative
return Math.max(MIN_VOL, vol);
}
@Override
public ExperimentResults compute(Builder builder, Set<SimArgs> inputs) {
final IdMap<MASConfiguration> configMap = new IdMap<>("c", MASConfiguration.class);
final IdMap<ScenarioProvider> scenarioMap = new IdMap<>("s", ScenarioProvider.class);
final IdMap<ObjectiveFunction> objFuncMap = new IdMap<>("o", ObjectiveFunction.class);
final List<ResultListener> listeners = newArrayList(builder.resultListeners);
@SuppressWarnings({"rawtypes", "unchecked"})
final IdMap<PostProcessor<?>> ppMap = new IdMap("p", PostProcessor.class);
final Map<String, Scenario> scenariosMap = newLinkedHashMap();
// create tasks
final List<SimulationTask> tasks = newArrayList();
constructTasks(inputs, tasks, configMap, scenarioMap, objFuncMap, ppMap, scenariosMap);
// this sorts tasks using this chain: scenario, configuration, objective
// function, postprocessor, seed
Collections.sort(tasks);
// determine size of batches
final int numBatches = Math.min(tasks.size(), builder.numBatches);
final int batchSize =
DoubleMath.roundToInt(tasks.size() / (double) numBatches, RoundingMode.CEILING);
final Map<Task<?>, JPPFJob> taskJobMap = newLinkedHashMap();
final ResultsCollector res =
new ResultsCollector(tasks.size(), scenariosMap, taskJobMap, listeners);
final List<JPPFJob> jobs = newArrayList();
for (int i = 0; i < numBatches; i++) {
final JPPFJob job = new JPPFJob(new MemoryMapDataProvider(), res);
job.setName(Joiner.on("").join(JOB_NAME, " ", i + 1, "/", numBatches));
jobs.add(job);
for (final SimulationTask t : tasks.subList(i * batchSize, (i + 1) * batchSize)) {
try {
final MASConfiguration config = configMap.getValue(t.getConfigurationId());
final ScenarioProvider scenario = scenarioMap.getValue(t.getScenarioId());
final ObjectiveFunction objFunc = objFuncMap.getValue(t.getObjectiveFunctionId());
job.getDataProvider()
.setParameter(t.getPostProcessorId(), ppMap.getValue(t.getPostProcessorId()));
job.getDataProvider().setParameter(t.getConfigurationId(), config);
job.getDataProvider().setParameter(t.getScenarioId(), scenario);
job.getDataProvider().setParameter(t.getObjectiveFunctionId(), objFunc);
job.add(t);
} catch (final JPPFException e) {
throw new IllegalStateException(e);
}
taskJobMap.put(t, job);
}
}
for (final ResultListener l : listeners) {
l.startComputing(tasks.size());
}
checkState(!getJPPFClient().isClosed());
try {
for (final JPPFJob job : jobs) {
getJPPFClient().submitJob(job);
}
} catch (final Exception e) {
throw new IllegalStateException(e);
}
res.awaitResults();
for (final ResultListener l : listeners) {
l.doneComputing();
}
return ExperimentResults.create(builder, res.buildResults());
}
public double findMinPerim(int leftIndex, int rightIndex, List<PointInt> listPointsSortedY) {
int numberOfPoints = rightIndex - leftIndex + 1;
Preconditions.checkArgument(listPointsSortedY.size() == numberOfPoints);
if (numberOfPoints < 3) {
return Double.MAX_VALUE;
}
int leftHalfEndIndex = leftIndex + numberOfPoints / 2 - 1;
int rightHalfStartIndex = leftHalfEndIndex + 1;
Preconditions.checkState(rightHalfStartIndex <= rightIndex);
double min = Double.MAX_VALUE;
/*
* In order to avoid having to do another sort by y, (taking n log n), we just split using the sortedY list
*/
List<PointInt> leftList = new ArrayList<>(leftHalfEndIndex - leftIndex + 1);
List<PointInt> rightList = new ArrayList<>(rightIndex - rightHalfStartIndex + 1);
// We must compare x and y because though we are partitioning by a vertical line, we must also
// be able to partition if all points have the same x
// Because the partition is strictly less and due to rounding error from longs,
// we use this as the division point
PointInt midPoint = list.get(rightHalfStartIndex);
for (PointInt pl : listPointsSortedY) {
// Verify the points are still between left and right index
Preconditions.checkState(list.get(leftIndex).getX() <= pl.getX());
Preconditions.checkState(list.get(rightIndex).getX() >= pl.getX());
if (compX.compare(pl, midPoint) < 0) {
leftList.add(pl);
} else {
rightList.add(pl);
}
}
Preconditions.checkState(leftList.size() == numberOfPoints / 2);
Preconditions.checkState(leftList.size() > 0);
Preconditions.checkState(rightList.size() > 0);
Preconditions.checkState(leftHalfEndIndex != rightIndex);
Preconditions.checkState(rightHalfStartIndex != leftIndex);
Preconditions.checkState(numberOfPoints == leftList.size() + rightList.size());
// Divide
double minLeft = findMinPerim(leftIndex, leftHalfEndIndex, leftList);
double minRight = findMinPerim(rightHalfStartIndex, rightIndex, rightList);
min = Math.min(minLeft, minRight);
/*
* For the combine, we make a box.
* Left bound is min / 2 from vertical line, right bound is min / 2.
*
* Reason being that any triangle covering the vertical line and with a
* point greater than min / 2 would have a perimeter > min.
*/
int boxMargin =
DoubleMath.roundToInt(
(min > Double.MAX_VALUE / 2 ? Integer.MAX_VALUE : min) / 2d, RoundingMode.UP);
Preconditions.checkState(min > Integer.MAX_VALUE || boxMargin < min);
Preconditions.checkState(min > Integer.MAX_VALUE || boxMargin * 2 >= min);
List<PointInt> boxPoints = new ArrayList<>();
int startBox = 0;
for (int i = 0; i < listPointsSortedY.size(); ++i) {
PointInt point = listPointsSortedY.get(i);
if (Math.abs(point.getX() - midPoint.getX()) > boxMargin) {
continue;
}
// Calculate start of the box to consider. Should be at most
// boxMargin away from currenty point. End of box is the last point added
while (startBox < boxPoints.size()
&& point.getY() - boxPoints.get(startBox).getY() > boxMargin) {
startBox++;
}
/**
* To explain this, the box goes from -minP / 2 to + minP / 2 from the dividing vertical line.
* Its height is also minP / 2.
*
* <p>Because we have the minimum with respect to the left and right sides, all triangles to
* the left and right have max perimiter <= minP.
*
* <p>The only way to cram 16 points is to have 2 points on each corner and in the middle
*
* <p>PP-------PP--------PP
*
* <p>PP PP
*
* <p>PP-------PP--------PP
*
* <p>The perim of any triangle is >= minP. Any other point would be a triangle of perim <
* minP.
*/
Preconditions.checkState(boxPoints.size() - startBox <= 16);
// Consider all points in box (can be proved <= 16...Similar to most 6 for closest 2 points
// algorithm
for (int bi = startBox; bi < boxPoints.size(); ++bi) {
for (int j = bi + 1; j < boxPoints.size(); ++j) {
double perim =
point.distance(boxPoints.get(bi))
+ point.distance(boxPoints.get(j))
+ boxPoints.get(bi).distance(boxPoints.get(j));
min = Math.min(min, perim);
}
}
boxPoints.add(point);
}
return min;
}
/**
* Computes the implied volatility in the SABR model and its derivatives.
*
* <p>The derivatives are stored in an array with:
*
* <ul>
* <li>[0] derivative with respect to the forward
* <li>[1] derivative with respect to the strike
* <li>[2] derivative with respect to the alpha
* <li>[3] derivative with respect to the beta
* <li>[4] derivative with respect to the rho
* <li>[5] derivative with respect to the nu
* </ul>
*
* @param forward the forward value of the underlying
* @param strike the strike value of the option
* @param timeToExpiry the time to expiry of the option
* @param alpha the SABR alpha value
* @param beta the SABR beta value
* @param rho the SABR rho value
* @param nu the SABR nu value
* @return the volatility and associated derivatives
*/
@Override
public ValueDerivatives volatilityAdjoint(
double forward,
double strike,
double timeToExpiry,
double alpha,
double beta,
double rho,
double nu) {
ArgChecker.isTrue(forward > 0.0, "forward must be greater than zero");
ArgChecker.isTrue(strike >= 0.0, "strike must be greater than zero");
ArgChecker.isTrue(timeToExpiry >= 0.0, "timeToExpiry must be greater than zero");
double cutoff = forward * CUTOFF_MONEYNESS;
double k = strike;
if (k < cutoff) {
Logger s_logger = LoggerFactory.getLogger(SabrHaganVolatilityFunctionProvider.class);
s_logger.info(
"Given strike of {} is less than cutoff at {}, therefore the strike is taken as {}",
new Object[] {k, cutoff, cutoff});
k = cutoff;
}
double betaStar = 1 - beta;
double rhoStar = 1.0 - rho;
if (alpha == 0.0) {
double alphaBar;
if (DoubleMath.fuzzyEquals(forward, k, ATM_EPS)) { // TODO should this is relative
alphaBar =
(1 + (2 - 3 * rho * rho) * nu * nu / 24 * timeToExpiry) / Math.pow(forward, betaStar);
} else {
// for non-atm options the alpha sensitivity at alpha = 0 is infinite. Returning this will
// most likely break calibrations,
// so we return an arbitrary large number
alphaBar = 1e7;
}
return ValueDerivatives.of(0d, DoubleArray.of(0, 0, alphaBar, 0, 0, 0));
}
// Implementation note: Forward sweep.
double sfK = Math.pow(forward * k, betaStar / 2);
double lnrfK = Math.log(forward / k);
double z = nu / alpha * sfK * lnrfK;
double rzxz;
double xz = 0;
if (DoubleMath.fuzzyEquals(z, 0.0, SMALL_Z)) {
rzxz = 1.0 - 0.5 * z * rho; // small z expansion to z^2 terms
} else {
if (DoubleMath.fuzzyEquals(rhoStar, 0.0, RHO_EPS)) {
if (z < 1.0) {
xz = -Math.log(1.0d - z);
rzxz = z / xz;
} else {
throw new IllegalArgumentException("can't handle z>=1, rho=1");
}
} else {
double arg;
if (z < LARGE_NEG_Z) {
arg =
(rho * rho - 1)
/ 2
/ z; // get rounding errors due to fine balanced cancellation for very large
// negative z
} else if (z > LARGE_POS_Z) {
arg = 2 * (z - rho);
} else {
arg = (Math.sqrt(1 - 2 * rho * z + z * z) + z - rho);
}
if (arg
<= 0.0) { // Mathematically this cannot be less than zero, but you know what computers
// are like.
rzxz = 0.0;
} else {
xz = Math.log(arg / (1 - rho));
rzxz = z / xz;
}
}
}
double sf1 =
sfK
* (1
+ betaStar * betaStar / 24 * (lnrfK * lnrfK)
+ Math.pow(betaStar, 4) / 1920 * Math.pow(lnrfK, 4));
double sf2 =
(1
+ (Math.pow(betaStar * alpha / sfK, 2) / 24
+ (rho * beta * nu * alpha) / (4 * sfK)
+ (2 - 3 * rho * rho) * nu * nu / 24)
* timeToExpiry);
double volatility = Math.max(MIN_VOL, alpha / sf1 * rzxz * sf2);
// Implementation note: Backward sweep.
double vBar = 1;
double sf2Bar = alpha / sf1 * rzxz * vBar;
double sf1Bar = -alpha / (sf1 * sf1) * rzxz * sf2 * vBar;
double rzxzBar = alpha / sf1 * sf2 * vBar;
double zBar;
double xzBar = 0.0;
if (DoubleMath.fuzzyEquals(z, 0.0, SMALL_Z)) {
zBar = -rho / 2 * rzxzBar;
} else {
if (DoubleMath.fuzzyEquals(rhoStar, 0.0, RHO_EPS)) {
if (z < 1.0) {
xzBar = -z / (xz * xz) * rzxzBar;
zBar = 1.0d / xz * rzxzBar + 1.0d / (1.0d - z) * xzBar;
} else {
throw new IllegalArgumentException("can't handle z>=1, rho=1");
}
} else {
if (z < LARGE_NEG_Z) {
zBar = 1 / xz * rzxzBar + xzBar / (xz * xz) * rzxzBar;
} else if (z > LARGE_POS_Z) {
zBar = 1 / xz * rzxzBar - xzBar / (xz * xz) * rzxzBar;
} else {
xzBar = -z / (xz * xz) * rzxzBar;
zBar =
1 / xz * rzxzBar
+ 1
/ ((Math.sqrt(1 - 2 * rho * z + z * z) + z - rho))
* (0.5 * Math.pow(1 - 2 * rho * z + z * z, -0.5) * (-2 * rho + 2 * z) + 1)
* xzBar;
}
}
}
double lnrfKBar =
sfK
* (betaStar * betaStar / 12 * lnrfK
+ Math.pow(betaStar, 4) / 1920 * 4 * Math.pow(lnrfK, 3))
* sf1Bar
+ nu / alpha * sfK * zBar;
double sfKBar =
nu / alpha * lnrfK * zBar
+ sf1 / sfK * sf1Bar
- (Math.pow(betaStar * alpha, 2) / Math.pow(sfK, 3) / 12
+ (rho * beta * nu * alpha) / 4 / (sfK * sfK))
* timeToExpiry
* sf2Bar;
double strikeBar = -1 / k * lnrfKBar + betaStar * sfK / (2 * k) * sfKBar;
double forwardBar = 1 / forward * lnrfKBar + betaStar * sfK / (2 * forward) * sfKBar;
double nuBar =
1 / alpha * sfK * lnrfK * zBar
+ ((rho * beta * alpha) / (4 * sfK) + (2 - 3 * rho * rho) * nu / 12)
* timeToExpiry
* sf2Bar;
double rhoBar;
if (Math.abs(forward - k) < ATM_EPS) {
rhoBar = -z / 2 * rzxzBar;
} else {
if (DoubleMath.fuzzyEquals(rhoStar, 0.0, RHO_EPS)) {
if (z >= 1) {
if (rhoStar == 0.0) {
rhoBar =
Double
.NEGATIVE_INFINITY; // the derivative at rho = 1 is infinite - this sets it to
// some arbitrary large number
} else {
rhoBar = xzBar * (1.0 / rhoStar + (0.5 - z) / (z - 1.0) / (z - 1.0));
}
} else {
rhoBar =
(0.5 * Math.pow(z / (1 - z), 2)
+ 0.25 * (z - 4.0) * Math.pow(z / (1.0 - z), 3) / (1.0 - z) * rhoStar)
* xzBar;
}
} else {
rhoBar =
(1
/ (Math.sqrt(1 - 2 * rho * z + z * z) + z - rho)
* (-Math.pow(1 - 2 * rho * z + z * z, -0.5) * z - 1)
+ 1 / rhoStar)
* xzBar;
}
}
rhoBar += ((beta * nu * alpha) / (4 * sfK) - rho * nu * nu / 4) * timeToExpiry * sf2Bar;
double alphaBar =
-nu / (alpha * alpha) * sfK * lnrfK * zBar
+ ((betaStar * alpha / sfK) * (betaStar / sfK) / 12 + (rho * beta * nu) / (4 * sfK))
* timeToExpiry
* sf2Bar
+ 1 / sf1 * rzxz * sf2 * vBar;
double betaBar =
-0.5 * Math.log(forward * k) * sfK * sfKBar
- sfK
* (betaStar / 12 * (lnrfK * lnrfK)
+ Math.pow(betaStar, 3) / 480 * Math.pow(lnrfK, 4))
* sf1Bar
+ (-betaStar * alpha * alpha / sfK / sfK / 12 + rho * nu * alpha / 4 / sfK)
* timeToExpiry
* sf2Bar;
return ValueDerivatives.of(
volatility, DoubleArray.of(forwardBar, strikeBar, alphaBar, betaBar, rhoBar, nuBar));
}
