@Test
public void testMixed() {
final DoubleMatrix2D jacobian = MIXED.evaluate(XNM);
assertEquals(N + M, jacobian.getNumberOfRows());
assertEquals(N + M, jacobian.getNumberOfColumns());
for (int i = 0; i < N; i++) {
for (int j = 0; j < N + M; j++) {
if (i == j) {
assertTrue(jacobian.getEntry(i, j) > 0.0);
} else if (i == (j + 1)) {
assertTrue(jacobian.getEntry(i, j) < 0.0);
} else {
assertEquals(0.0, jacobian.getEntry(i, j), 0.0);
}
}
}
for (int i = N; i < N + M; i++) {
for (int j = 0; j < N + M; j++) {
if (i == j) {
assertEquals(Math.exp(XNM.getEntry(i) * (i - N)), jacobian.getEntry(i, i), 1e-8);
} else {
assertEquals(0.0, jacobian.getEntry(i, j), 0.0);
}
}
}
}
@Test
public void testFirstOrderOnly() {
final ParametricVaRDataBundle result = CALC.evaluate(DATA_FIRST_ORDER).get(1);
final List<String> names = result.getNames();
assertEquals(
names,
Arrays.asList(
"A_IMPLIED_VOLATILITY",
"A_SPOT_PRICE",
"A_INTEREST_RATE",
"B_INTEREST_RATE",
"B_SPOT_PRICE",
"B_IMPLIED_VOLATILITY",
"C_SPOT_PRICE",
"C_IMPLIED_VOLATILITY",
"C_IMPLIED_VARIANCE"));
final Matrix<?> sensitivities = result.getSensitivities();
assertEquals(sensitivities.getClass(), DoubleMatrix1D.class);
final DoubleMatrix1D v = (DoubleMatrix1D) sensitivities;
assertEquals(v.getNumberOfElements(), 9);
assertArrayEquals(
v.getData(),
new double[] {
VEGA_A_1,
DELTA_A_1 + DELTA_A_2,
RHO_A_1 + RHO_A_2,
RHO_B,
DELTA_B,
VEGA_B,
DELTA_C,
VEGA_C,
VARIANCE_VEGA_C
},
EPS);
final Matrix<?> covariance = result.getCovarianceMatrix();
assertEquals(covariance.getClass(), DoubleMatrix2D.class);
final DoubleMatrix2D m = (DoubleMatrix2D) covariance;
assertEquals(m.getNumberOfRows(), 9);
assertEquals(m.getNumberOfColumns(), 9);
for (int i = 0; i < 9; i++) {
assertArrayEquals(m.getData()[i], C2[i], EPS);
}
}
@Test
public void testFirstOrderOnlyNoDuplicateGreeks() {
final ParametricVaRDataBundle result = CALC.evaluate(A_DATA_FIRST_ORDER_1).get(1);
final List<String> names = result.getNames();
assertEquals(names, Arrays.asList("A_IMPLIED_VOLATILITY", "A_SPOT_PRICE", "A_INTEREST_RATE"));
final Matrix<?> sensitivities = result.getSensitivities();
assertEquals(sensitivities.getClass(), DoubleMatrix1D.class);
final DoubleMatrix1D v = (DoubleMatrix1D) sensitivities;
assertEquals(v.getNumberOfElements(), 3);
assertArrayEquals(v.getData(), new double[] {VEGA_A_1, DELTA_A_1, RHO_A_1}, EPS);
final Matrix<?> covariance = result.getCovarianceMatrix();
assertEquals(covariance.getClass(), DoubleMatrix2D.class);
final DoubleMatrix2D m = (DoubleMatrix2D) covariance;
assertEquals(m.getNumberOfRows(), 3);
assertEquals(m.getNumberOfColumns(), 3);
assertArrayEquals(m.getData()[0], C1[0], EPS);
assertArrayEquals(m.getData()[1], C1[1], EPS);
assertArrayEquals(m.getData()[2], C1[2], EPS);
}
@Override
public DoubleMatrix2D getInitializedMatrix(
final Function1D<DoubleMatrix1D, DoubleMatrix2D> jacobianFunction, final DoubleMatrix1D x) {
Validate.notNull(jacobianFunction);
Validate.notNull(x);
final DoubleMatrix2D estimate = jacobianFunction.evaluate(x);
final DecompositionResult decompositionResult = _decomposition.evaluate(estimate);
return decompositionResult.solve(
DoubleMatrixUtils.getIdentityMatrix2D(x.getNumberOfElements()));
}
@Test
public void testCashOnly() {
final DoubleMatrix2D jacobian = CASH_ONLY.evaluate(XM);
assertEquals(M, jacobian.getNumberOfRows());
assertEquals(M, jacobian.getNumberOfColumns());
for (int i = 0; i < M; i++) {
for (int j = 0; j < M; j++) {
if (i == j) {
assertEquals(Math.exp(XM.getEntry(i) * i), jacobian.getEntry(i, i), 1e-8);
} else {
assertEquals(0.0, jacobian.getEntry(i, j), 0);
}
}
}
}
@Test
public void test() {
ParametricVaRDataBundle result = CALC.evaluate(DATA).get(1);
List<String> names = result.getNames();
assertEquals(
names,
Arrays.asList(
"A_IMPLIED_VOLATILITY",
"A_SPOT_PRICE",
"A_INTEREST_RATE",
"B_INTEREST_RATE",
"B_SPOT_PRICE",
"B_IMPLIED_VOLATILITY",
"C_SPOT_PRICE",
"C_IMPLIED_VOLATILITY",
"C_IMPLIED_VARIANCE"));
Matrix<?> sensitivities = result.getSensitivities();
assertEquals(sensitivities.getClass(), DoubleMatrix1D.class);
final DoubleMatrix1D v = (DoubleMatrix1D) sensitivities;
assertEquals(v.getNumberOfElements(), 9);
assertArrayEquals(
v.getData(),
new double[] {
VEGA_A_1,
DELTA_A_1 + DELTA_A_2,
RHO_A_1 + RHO_A_2,
RHO_B,
DELTA_B,
VEGA_B,
DELTA_C,
VEGA_C,
VARIANCE_VEGA_C
},
EPS);
Matrix<?> covariance = result.getCovarianceMatrix();
assertEquals(covariance.getClass(), DoubleMatrix2D.class);
final DoubleMatrix2D m = (DoubleMatrix2D) covariance;
assertEquals(m.getNumberOfRows(), 9);
assertEquals(m.getNumberOfColumns(), 9);
for (int i = 0; i < 9; i++) {
assertArrayEquals(m.getData()[i], C2[i], EPS);
}
result = CALC.evaluate(DATA).get(2);
names = result.getNames();
assertEquals(
names,
Arrays.asList(
"A_SPOT_PRICE",
"A_IMPLIED_VOLATILITY",
"A_STRIKE",
"A_TIME",
"B_SPOT_PRICE",
"B_IMPLIED_VOLATILITY",
"C_SPOT_PRICE",
"C_IMPLIED_VOLATILITY",
"A_YIELD"));
sensitivities = result.getSensitivities();
assertEquals(sensitivities.getClass(), DoubleMatrix2D.class);
final DoubleMatrix2D m1 = (DoubleMatrix2D) sensitivities;
assertEquals(m1.getNumberOfRows(), 9);
assertEquals(m1.getNumberOfColumns(), 9);
final double[][] s =
new double[][] {
new double[] {GAMMA_A_1 + GAMMA_A_2, VANNA_A, 0, DELTA_BLEED_A, 0, 0, 0, 0, DUMMY_A},
new double[] {VANNA_A, VOMMA_A_1 + VOMMA_A_2, 0, 0, 0, 0, 0, 0, 0},
new double[] {0, 0, STRIKE_GAMMA_A_1, 0, 0, 0, 0, 0, 0},
new double[] {DELTA_BLEED_A, 0, 0, 0, 0, 0, 0, 0, 0},
new double[] {0, 0, 0, 0, GAMMA_B, 0, 0, 0, 0},
new double[] {0, 0, 0, 0, 0, VOMMA_B, 0, 0, 0},
new double[] {0, 0, 0, 0, 0, 0, GAMMA_C, VANNA_C, 0},
new double[] {0, 0, 0, 0, 0, 0, VANNA_C, 0, 0},
new double[] {DUMMY_A, 0, 0, 0, 0, 0, 0, 0, 0}
};
for (int i = 0; i < 9; i++) {
assertArrayEquals(m1.getData()[i], s[i], EPS);
}
covariance = result.getCovarianceMatrix();
assertEquals(covariance.getClass(), DoubleMatrix2D.class);
final DoubleMatrix2D m2 = (DoubleMatrix2D) covariance;
assertEquals(m2.getNumberOfRows(), 9);
assertEquals(m2.getNumberOfColumns(), 9);
for (int i = 0; i < 9; i++) {
assertArrayEquals(m2.getData()[i], C5[i], EPS);
}
}
@Override
public DoubleMatrix2D evaluate(DoubleMatrix1D v) {
double[] x = v.getData();
return new DoubleMatrix2D(
new double[][] {{x[0] * x[0], x[0] * x[1]}, {x[0] - x[1], x[1] * x[1]}});
}
