git subrepo pull (merge) ore

subrepo:
  subdir:   "ore"
  merged:   "142a89c4f1"
upstream:
  origin:   "git@gitlab.acadiasoft.net:qs/ore.git"
  branch:   "master"
  commit:   "0b324ac7b4"
git-subrepo:
  version:  "0.4.6"
  origin:   "https://github.com/ingydotnet/git-subrepo"
  commit:   "110b9eb"

Author: jenkins

Docs/UserGuide/tradedata/fx_digitalbarrieroption.tex

@@ -67,9 +67,14 @@ \subsubsection{FX Digital Barrier Option}
 
 \end{itemize}
 
-\item BarrierData: This is a trade component sub-node outlined in section \ref{ss:barrier_data}.
+\item BarrierData: This is a trade component sub-node outlined in section \ref{ss:barrier_data}. 
+
+Note that the \emph{FxDigitalBarrierOption} is a single barrier instrument, and can have only one BarrierData node with one barrier level.
+
 Level specified in BarrierData should be quoted as the amount in DomesticCurrency per one unit of ForeignCurrency, with both currencies as defined in FxDigitalBarrierOptionData node.
 
+Type specified in BarrierData can be one of: \emph{UpAndIn, DownAndIn, UpAndOut, DownAndOut}
+
 \item StartDate[Optional]: The start date for checking if a barrier has been breached prior to today's date.  If omitted or left blank no check is made and it is assumed no barrier has been breached in the past. Has no impact if set to today's date or a date in the future. If`StartDate' is provided then the fixings for dates between this date and the asof date are checked to see if the option was triggered. If no fixing is available then we skip that date. This is to allow for backwards compatibility.
 
 Allowable values:  See \lstinline!Date! in Table \ref{tab:allow_stand_data}.

QuantExt/test/CMakeLists.txt

@@ -1,6 +1,7 @@
 # cpp files, this list is maintained manually
 
-set(QuantExt-Test_SRC analyticcashsettledeuropeanengine.cpp
+set(QuantExt-Test_SRC ad.cpp
+analyticcashsettledeuropeanengine.cpp
 analyticlgmswaptionengine.cpp
 basecorrelationcurve.cpp
 bfrrvolsurface.cpp

QuantExt/test/ad.cpp

@@ -0,0 +1,195 @@
+/*
+ Copyright (C) 2019 Quaternion Risk Management Ltd
+ All rights reserved.
+
+ This file is part of ORE, a free-software/open-source library
+ for transparent pricing and risk analysis - http://opensourcerisk.org
+
+ ORE is free software: you can redistribute it and/or modify it
+ under the terms of the Modified BSD License.  You should have received a
+ copy of the license along with this program.
+ The license is also available online at <http://opensourcerisk.org>
+
+ This program is distributed on the basis that it will form a useful
+ contribution to risk analytics and model standardisation, but WITHOUT
+ ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
+ FITNESS FOR A PARTICULAR PURPOSE. See the license for more details.
+*/
+
+#include "toplevelfixture.hpp"
+
+#include <qle/ad/backwardderivatives.hpp>
+#include <qle/ad/forwardderivatives.hpp>
+#include <qle/ad/forwardevaluation.hpp>
+#include <qle/ad/ssaform.hpp>
+#include <qle/math/randomvariable_ops.hpp>
+
+#include <ql/math/distributions/normaldistribution.hpp>
+#include <ql/math/randomnumbers/inversecumulativerng.hpp>
+#include <ql/math/randomnumbers/mt19937uniformrng.hpp>
+
+#include <boost/test/unit_test.hpp>
+
+using namespace QuantExt;
+
+BOOST_FIXTURE_TEST_SUITE(QuantExtTestSuite, qle::test::TopLevelFixture)
+
+BOOST_AUTO_TEST_SUITE(AdTest)
+
+BOOST_AUTO_TEST_CASE(testForwardEvaluation) {
+
+    constexpr Real tol = 1E-14;
+
+    // z = x+y, z = ux = (x+y)x = x^2+yx
+    ComputationGraph g;
+    auto x = cg_var(g, "x", ComputationGraph::VarDoesntExist::Create);
+    auto y = cg_var(g, "y", ComputationGraph::VarDoesntExist::Create);
+    auto u = cg_add(g, x, y, "u");
+    auto z = cg_mult(g, u, x, "z");
+
+    BOOST_TEST_MESSAGE("SSA Form:\n" + ssaForm(g, getRandomVariableOpLabels()));
+
+    std::vector<RandomVariable> values(g.size(), RandomVariable(1, 0.0));
+    values[x] = RandomVariable(1, 2.0);
+    values[y] = RandomVariable(1, 3.0);
+
+    forwardEvaluation(g, values, getRandomVariableOps(1), RandomVariable::deleter, false);
+
+    // BOOST_CHECK_CLOSE(values[x][0], 2.0, tol); // deleted
+    // BOOST_CHECK_CLOSE(values[y][0], 3.0, tol);
+    // BOOST_CHECK_CLOSE(values[u][0], 5.0, tol);
+    BOOST_CHECK_CLOSE(values[z][0], 10.0, tol);
+}
+
+BOOST_AUTO_TEST_CASE(testBackwardDerivatives) {
+
+    constexpr Real tol = 1E-14;
+
+    // z = x+y, z = ux = (x+y)x = x^2+yx
+    ComputationGraph g;
+    auto x = cg_var(g, "x", ComputationGraph::VarDoesntExist::Create);
+    auto y = cg_var(g, "y", ComputationGraph::VarDoesntExist::Create);
+    auto u = cg_add(g, x, y, "u");
+    auto z = cg_mult(g, u, x, "z");
+
+    BOOST_TEST_MESSAGE("SSA Form:\n" + ssaForm(g, getRandomVariableOpLabels()));
+
+    // forward evaluation
+
+    std::vector<RandomVariable> values(g.size(), RandomVariable(1, 0.0));
+    values[x] = RandomVariable(1, 2.0);
+    values[y] = RandomVariable(1, 3.0);
+
+    forwardEvaluation(g, values, getRandomVariableOps(1), RandomVariable::deleter, true,
+                      getRandomVariableOpNodeRequirements());
+
+    // BOOST_CHECK_CLOSE(values[x][0], 2.0, tol); // deleted
+    // BOOST_CHECK_CLOSE(values[y][0], 3.0, tol);
+    // BOOST_CHECK_CLOSE(values[u][0], 5.0, tol);
+    BOOST_CHECK_CLOSE(values[z][0], 10.0, tol);
+
+    // backward derivatives
+
+    std::vector<RandomVariable> derivativesBwd(g.size(), RandomVariable(1, 0.0));
+    derivativesBwd[z] = RandomVariable(1, 1.0);
+
+    std::vector<bool> keep(g.size(), false);
+    keep[x] = true;
+    keep[y] = true;
+    keep[z] = true;
+    keep[u] = true;
+
+    backwardDerivatives(g, values, derivativesBwd, getRandomVariableGradients(1), RandomVariable::deleter, keep);
+
+    // dz/dx = 2x+y
+    BOOST_CHECK_CLOSE(derivativesBwd[x][0], 7.0, tol);
+    // dz/dy = x
+    BOOST_CHECK_CLOSE(derivativesBwd[y][0], 2.0, tol);
+    // dz/du = x
+    BOOST_CHECK_CLOSE(derivativesBwd[u][0], 2.0, tol);
+    // dz/dz = 1
+    BOOST_CHECK_CLOSE(derivativesBwd[z][0], 1.0, tol);
+}
+
+BOOST_AUTO_TEST_CASE(testForwardDerivatives) {
+
+    constexpr Real tol = 1E-14;
+
+    // z = x+y, z = ux = (x+y)x = x^2+yx
+    ComputationGraph g;
+    auto x = cg_var(g, "x", ComputationGraph::VarDoesntExist::Create);
+    auto y = cg_var(g, "y", ComputationGraph::VarDoesntExist::Create);
+    auto u = cg_add(g, x, y, "u");
+    auto z = cg_mult(g, u, x, "z");
+
+    BOOST_TEST_MESSAGE("SSA Form:\n" + ssaForm(g, getRandomVariableOpLabels()));
+
+    // forward evaluation
+
+    std::vector<RandomVariable> values(g.size(), RandomVariable(1, 0.0));
+    values[x] = RandomVariable(1, 2.0);
+    values[y] = RandomVariable(1, 3.0);
+
+    forwardEvaluation(g, values, getRandomVariableOps(1), RandomVariable::deleter, true,
+                      getRandomVariableOpNodeRequirements());
+
+    // forward derivatives
+
+    std::vector<RandomVariable> derivativesFwdX(g.size(), RandomVariable(1, 0.0));
+    std::vector<RandomVariable> derivativesFwdY(g.size(), RandomVariable(1, 0.0));
+    derivativesFwdX[x] = RandomVariable(1, 1.0);
+    derivativesFwdY[y] = RandomVariable(1, 1.0);
+
+    forwardDerivatives(g, values, derivativesFwdX, getRandomVariableGradients(1), RandomVariable::deleter);
+    forwardDerivatives(g, values, derivativesFwdY, getRandomVariableGradients(1), RandomVariable::deleter);
+
+    // dz/dx = 2x+y
+    BOOST_CHECK_CLOSE(derivativesFwdX[z][0], 7.0, tol);
+    // dz/dy = x
+    BOOST_CHECK_CLOSE(derivativesFwdY[z][0], 2.0, tol);
+}
+
+BOOST_AUTO_TEST_CASE(testIndicatorDerivative) {
+    BOOST_TEST_MESSAGE("Testing indicator derivative...");
+
+    Size n = 5000000;    // number of samples
+    Real epsilon = 0.05; // indcator derivative bandwidth
+
+    ComputationGraph g;
+    auto z = cg_var(g, "z", ComputationGraph::VarDoesntExist::Create); // z ~ N(z0,1)
+    auto y = cg_indicatorGt(g, z, cg_const(g, 0.0));                   // ind = 1_{z>0}
+
+    InverseCumulativeRng<MersenneTwisterUniformRng, InverseCumulativeNormal> normal(MersenneTwisterUniformRng(42));
+
+    Real tol = 30.0E-4;
+
+    Real z0 = -3.0;
+    while (z0 < 3.01) {
+        std::vector<RandomVariable> values(g.size(), RandomVariable(n)), derivatives(g.size(), RandomVariable(n));
+        BOOST_TEST_MESSAGE("z0=" << z0 << ":");
+        for (Size i = 0; i < n; ++i) {
+            values[z].set(i, z0 + normal.next().value);
+        }
+        forwardEvaluation(g, values, getRandomVariableOps(n));
+        Real av = expectation(values[y])[0];
+        Real refAv = 1.0 - CumulativeNormalDistribution()(-z0);
+        BOOST_TEST_MESSAGE("E( 1_{z>0} ) = " << av << ", reference " << refAv << ", diff " << refAv - av);
+        BOOST_CHECK_SMALL(av - refAv, tol);
+
+        derivatives[y] = RandomVariable(n, 1.0);
+        backwardDerivatives(g, values, derivatives,
+                            getRandomVariableGradients(1, 2, QuantLib::LsmBasisSystem::Monomial, epsilon));
+        Real dav = expectation(derivatives[z])[0];
+        Real refDav = NormalDistribution()(-z0);
+        // it is dz / dz0 = 1, so we are really computing  d/dz0 E(1_{z>0})
+        // and we have E(1_{z>0}) = 1 - \Phi(-z0), so d/dz0 E(1_{z>0}) = phi(-z0)
+        BOOST_TEST_MESSAGE("E( d/dz 1_{z>0} ) = " << dav << ", reference " << refDav << ", diff " << refDav - dav);
+        BOOST_CHECK_SMALL(dav - refDav, tol);
+
+        z0 += 0.5;
+    }
+}
+
+BOOST_AUTO_TEST_SUITE_END()
+
+BOOST_AUTO_TEST_SUITE_END()

Tools/PythonTools/compare_files.py

@@ -397,6 +397,17 @@ def compare_files_df(name, file_1, file_2, config):
         if 'optional_cols' in config:
             optional_cols = copy.deepcopy(config['optional_cols'])
             logger.debug('Optional columns found: %s', str (optional_cols))
+
+            # Check that each optional col either exists in both DataFrames, or is missing in both. Otherwise, we fail the test.
+            missing_ocols = []
+            for col in optional_cols:
+                if (col in df_1.columns and col not in df_2.columns) or (col not in df_1.columns and col in df_2.columns):
+                    missing_ocols.append(col)
+            if missing_ocols:
+                logger.warning('The columns, %s, are in one Dataframe but not the other.', str(missing_ocols))
+                return False
+
+            # For each optional col, check whether it is found in each DataFrame. If so, add it.
             for col in optional_cols:
                 if col in df_1.columns and col in df_2.columns :
                     logger.debug('Adding optional column %s to list of columns for comparison', col)

Tools/PythonTools/comparison_config.json

@@ -227,7 +227,24 @@
           "TradeType"
         ],
         "optional_cols": [
-          "BaseCurrency"
+          "BaseCurrency",
+          "end_date",
+          "trade_date",
+          "notional",
+          "trade_currency",
+          "notional2",
+          "trade_currency2",
+          "underlying",
+          "mtm_curr",
+          "mtm_value",
+          "settlement_type",
+          "strike",
+          "call_put",
+          "long_short",
+          "asset_class",
+          "base_product",
+          "sub_product",
+          "xccy_resettable"
         ],
         "optional_keys": [
           "collect_regulations",
@@ -763,6 +780,7 @@
           "ProductClass",
           "RiskClass",
           "MarginType",
+          "Bucket",
           "SimmSide"
         ],
         "rename_cols": {