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springbootdemo-tomcat11: add Java financial benchmark service
Java reference implementation of the Axis2/C financial benchmark service (axis-axis2-c-core/samples/user_guide/financial-benchmark-service). Provides identical API and financial calculations to the C service, enabling side-by-side performance comparison: - C on a $20 2GB Android phone: portfolioVariance 500 assets in ~5ms / 30MB - Java: requires 16-32GB JVM minimum to start Three operations (7 files): portfolioVariance — O(n²) covariance matrix multiplication σ²_p = Σ_i Σ_j w_i · w_j · σ_ij Accepts 2D double[][] or flat double[] covariance matrix. normalizeWeights: rescales weights to sum 1.0 (for unnormalized exposures). nPeriodsPerYear: controls annualized volatility (default 252). Reports weight_sum and weights_normalized for audit. monteCarlo — Geometric Brownian Motion VaR simulation S(t+dt) = S(t) × exp((μ − σ²/2)·dt + σ·√dt·Z) Uses Random.nextGaussian() (polar method). Seeded (randomSeed != 0) for reproducibility, unseeded for production. percentiles: caller-specified VaR levels, default [0.01, 0.05]. Returns fixed var95/var99/cvar95 fields plus percentileVars list. nPeriodsPerYear: controls GBM time step dt = 1/nPeriodsPerYear. scenarioAnalysis — expected return + HashMap vs ArrayList benchmark E[r_i] = Σ_j p_j × (price_j / currentPrice − 1) probTolerance: configurable probability sum validation (default 1e-4). Mirrors DPT v2 Array→Map optimization for 500+ asset portfolios. Reports linear_us, hash_lookup_us, speedup, hash_build_us. API parity with C: all request/response field names match the C structs in financial_benchmark_service.h (camelCase vs snake_case only). Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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‎modules/samples/userguide/src/userguide/springbootdemo-tomcat11/src/main/java/userguide/springboot/webservices/FinancialBenchmarkService.java‎

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‎modules/samples/userguide/src/userguide/springbootdemo-tomcat11/src/main/java/userguide/springboot/webservices/MonteCarloRequest.java‎

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/*
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* Licensed to the Apache Software Foundation (ASF) under one
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* or more contributor license agreements. See the NOTICE file
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* distributed with this work for additional information
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* regarding copyright ownership. The ASF licenses this file
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* to you under the Apache License, Version 2.0 (the
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* "License"); you may not use this file except in compliance
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* with the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing,
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* software distributed under the License is distributed on an
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* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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* KIND, either express or implied. See the License for the
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* specific language governing permissions and limitations
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* under the License.
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*/
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package userguide.springboot.webservices;
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/**
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* Request for Monte Carlo Value-at-Risk simulation.
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*
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* <p>Simulates portfolio value paths using Geometric Brownian Motion:
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* <pre>S(t+dt) = S(t) × exp((μ − σ²/2)·dt + σ·√dt·Z)</pre>
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* where dt = 1/nPeriodsPerYear and Z ~ N(0,1).
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*
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* <p>All fields have defaults so a minimal {@code {}} request body is valid.
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*
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* <h3>Example</h3>
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* <pre>{@code
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* {
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* "nSimulations": 50000,
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* "nPeriods": 252,
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* "initialValue": 1000000.0,
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* "expectedReturn": 0.08,
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* "volatility": 0.20,
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* "randomSeed": 42,
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* "percentiles": [0.01, 0.05, 0.10]
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* }
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* }</pre>
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*/
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public class MonteCarloRequest {
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/** Number of simulation paths. Default: 10,000. Max: 1,000,000. */
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private int nSimulations = 10_000;
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/** Number of time steps per path (e.g., 252 trading days). Default: 252. */
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private int nPeriods = 252;
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/** Initial portfolio value in currency units. Default: $1,000,000. */
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private double initialValue = 1_000_000.0;
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/** Expected annualized return (e.g., 0.08 for 8%). Default: 0.08. */
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private double expectedReturn = 0.08;
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/** Annualized volatility (e.g., 0.20 for 20%). Default: 0.20. */
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private double volatility = 0.20;
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/**
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* Random seed for reproducibility. 0 (default) → non-deterministic.
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* Seeded runs produce identical results across calls, enabling diff testing.
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*/
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private long randomSeed = 0;
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/**
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* Trading periods per year. Controls GBM time step: dt = 1/nPeriodsPerYear.
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* Must match the frequency basis of {@code expectedReturn} and {@code volatility}
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* (both must be annualized). Default: 252. Common alternatives: 260, 365, 12.
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*/
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private int nPeriodsPerYear = 252;
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/**
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* Percentile tail levels for VaR reporting. Values in (0, 1).
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* Each entry p produces: VaR_p = initialValue − sorted_final_values[p × nSimulations].
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* Default: [0.01, 0.05] (99% and 95% VaR). Up to 8 entries; extras are ignored.
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*/
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private double[] percentiles = {0.01, 0.05};
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/** Optional identifier echoed in the response for request tracing. */
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private String requestId;
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// ── getters ──────────────────────────────────────────────────────────────
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public int getNSimulations() { return nSimulations; }
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public int getNPeriods() { return nPeriods; }
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public double getInitialValue() { return initialValue; }
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public double getExpectedReturn() { return expectedReturn; }
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public double getVolatility() { return volatility; }
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public long getRandomSeed() { return randomSeed; }
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public int getNPeriodsPerYear() { return nPeriodsPerYear > 0 ? nPeriodsPerYear : 252; }
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public double[] getPercentiles() { return percentiles; }
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public String getRequestId() { return requestId; }
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// ── setters ──────────────────────────────────────────────────────────────
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public void setNSimulations(int nSimulations) { this.nSimulations = nSimulations; }
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public void setNPeriods(int nPeriods) { this.nPeriods = nPeriods; }
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public void setInitialValue(double initialValue) { this.initialValue = initialValue; }
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public void setExpectedReturn(double expectedReturn) { this.expectedReturn = expectedReturn; }
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public void setVolatility(double volatility) { this.volatility = volatility; }
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public void setRandomSeed(long randomSeed) { this.randomSeed = randomSeed; }
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public void setNPeriodsPerYear(int nPeriodsPerYear) { this.nPeriodsPerYear = nPeriodsPerYear; }
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public void setPercentiles(double[] percentiles) { this.percentiles = percentiles; }
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public void setRequestId(String requestId) { this.requestId = requestId; }
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}

‎modules/samples/userguide/src/userguide/springbootdemo-tomcat11/src/main/java/userguide/springboot/webservices/MonteCarloResponse.java‎

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/*
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* Licensed to the Apache Software Foundation (ASF) under one
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* or more contributor license agreements. See the NOTICE file
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* distributed with this work for additional information
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* regarding copyright ownership. The ASF licenses this file
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* to you under the Apache License, Version 2.0 (the
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* "License"); you may not use this file except in compliance
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* with the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing,
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* software distributed under the License is distributed on an
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* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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* KIND, either express or implied. See the License for the
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* specific language governing permissions and limitations
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* under the License.
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*/
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package userguide.springboot.webservices;
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import java.util.List;
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/**
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* Response for Monte Carlo Value-at-Risk simulation.
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*
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* <p>Fixed fields ({@code var95}, {@code var99}, {@code cvar95}) are always
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* populated on success for backward compatibility. The {@code percentileVars}
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* list reflects the caller-specified {@code percentiles} array.
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*/
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public class MonteCarloResponse {
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private String status;
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private String errorMessage;
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// ── Distribution statistics ───────────────────────────────────────────────
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/** Mean of final portfolio values across all paths */
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private double meanFinalValue;
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/** Median (50th percentile) of final portfolio values */
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private double medianFinalValue;
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/** Standard deviation of final portfolio values */
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private double stdDevFinalValue;
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// ── Fixed VaR fields (always populated) ──────────────────────────────────
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/** Value at Risk at 95% confidence: initialValue − 5th-percentile final value */
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private double var95;
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/** Value at Risk at 99% confidence: initialValue − 1st-percentile final value */
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private double var99;
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/** Conditional VaR (Expected Shortfall) at 95%: initialValue − mean(worst 5%) */
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private double cvar95;
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// ── Additional risk metrics ───────────────────────────────────────────────
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/** Maximum drawdown observed across all simulation paths (0–1 fraction) */
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private double maxDrawdown;
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/** Fraction of paths where final value > initial value */
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private double probProfit;
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// ── Caller-specified percentile VaR ──────────────────────────────────────
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/**
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* VaR values for the percentile levels requested in {@code MonteCarloRequest.percentiles}.
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* Each entry: {@code {"percentile": 0.01, "var": 185432.10}}.
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*/
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private List<PercentileVar> percentileVars;
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// ── Performance metrics ───────────────────────────────────────────────────
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/** Wall-clock time for the simulation in microseconds */
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private long calcTimeUs;
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/** Simulation throughput: nSimulations / (calcTimeUs / 1e6) */
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private double simulationsPerSecond;
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/** JVM heap used at response time in MB */
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private long memoryUsedMb;
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/** Echoed from request */
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private String requestId;
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// ── Inner types ──────────────────────────────────────────────────────────
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/**
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* A single percentile VaR entry in {@code percentileVars}.
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*/
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public static class PercentileVar {
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private double percentile;
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private double var;
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public PercentileVar() {}
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public PercentileVar(double percentile, double var) {
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this.percentile = percentile;
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this.var = var;
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}
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public double getPercentile() { return percentile; }
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public void setPercentile(double percentile) { this.percentile = percentile; }
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public double getVar() { return var; }
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public void setVar(double var) { this.var = var; }
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}
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// ── Factory ──────────────────────────────────────────────────────────────
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public static MonteCarloResponse failed(String errorMessage) {
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MonteCarloResponse r = new MonteCarloResponse();
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r.status = "FAILED";
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r.errorMessage = errorMessage;
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return r;
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}
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// ── Getters / setters ────────────────────────────────────────────────────
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public String getStatus() { return status; }
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public void setStatus(String status) { this.status = status; }
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public String getErrorMessage() { return errorMessage; }
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public void setErrorMessage(String errorMessage) { this.errorMessage = errorMessage; }
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public double getMeanFinalValue() { return meanFinalValue; }
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public void setMeanFinalValue(double meanFinalValue) { this.meanFinalValue = meanFinalValue; }
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public double getMedianFinalValue() { return medianFinalValue; }
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public void setMedianFinalValue(double medianFinalValue) { this.medianFinalValue = medianFinalValue; }
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public double getStdDevFinalValue() { return stdDevFinalValue; }
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public void setStdDevFinalValue(double stdDevFinalValue) { this.stdDevFinalValue = stdDevFinalValue; }
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public double getVar95() { return var95; }
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public void setVar95(double var95) { this.var95 = var95; }
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public double getVar99() { return var99; }
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public void setVar99(double var99) { this.var99 = var99; }
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public double getCvar95() { return cvar95; }
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public void setCvar95(double cvar95) { this.cvar95 = cvar95; }
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public double getMaxDrawdown() { return maxDrawdown; }
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public void setMaxDrawdown(double maxDrawdown) { this.maxDrawdown = maxDrawdown; }
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public double getProbProfit() { return probProfit; }
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public void setProbProfit(double probProfit) { this.probProfit = probProfit; }
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public List<PercentileVar> getPercentileVars() { return percentileVars; }
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public void setPercentileVars(List<PercentileVar> percentileVars) { this.percentileVars = percentileVars; }
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public long getCalcTimeUs() { return calcTimeUs; }
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public void setCalcTimeUs(long calcTimeUs) { this.calcTimeUs = calcTimeUs; }
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public double getSimulationsPerSecond() { return simulationsPerSecond; }
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public void setSimulationsPerSecond(double simulationsPerSecond) { this.simulationsPerSecond = simulationsPerSecond; }
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public long getMemoryUsedMb() { return memoryUsedMb; }
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public void setMemoryUsedMb(long memoryUsedMb) { this.memoryUsedMb = memoryUsedMb; }
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public String getRequestId() { return requestId; }
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public void setRequestId(String requestId) { this.requestId = requestId; }
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}

‎modules/samples/userguide/src/userguide/springbootdemo-tomcat11/src/main/java/userguide/springboot/webservices/PortfolioVarianceRequest.java‎

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/*
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* Licensed to the Apache Software Foundation (ASF) under one
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* or more contributor license agreements. See the NOTICE file
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* distributed with this work for additional information
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* regarding copyright ownership. The ASF licenses this file
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* to you under the Apache License, Version 2.0 (the
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* "License"); you may not use this file except in compliance
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* with the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing,
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* software distributed under the License is distributed on an
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* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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* KIND, either express or implied. See the License for the
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* specific language governing permissions and limitations
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* under the License.
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*/
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package userguide.springboot.webservices;
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/**
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* Request for portfolio variance calculation.
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*
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* <p>Computes σ²_p = Σ_i Σ_j w_i · w_j · σ_ij — an O(n²) operation
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* that mirrors correlation/risk calculations in DPT v2 and similar systems.
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*
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* <h3>Covariance matrix formats</h3>
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* <ul>
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* <li><b>2D array</b> (preferred): {@code covarianceMatrix[i][j]} — natural JSON nested array</li>
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* <li><b>Flat array</b> (alternative): {@code covarianceMatrixFlat} of length n² in row-major order</li>
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* </ul>
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* If both are supplied, {@code covarianceMatrix} takes precedence.
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*
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* <h3>Example</h3>
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* <pre>{@code
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* {
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* "weights": [0.4, 0.6],
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* "covarianceMatrix": [[0.04, 0.006], [0.006, 0.09]],
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* "normalizeWeights": false,
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* "nPeriodsPerYear": 252
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* }
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* }</pre>
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*/
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public class PortfolioVarianceRequest {
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/** Portfolio weights. Length determines n_assets when nAssets is not set. */
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private double[] weights;
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/**
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* Covariance matrix in 2D format: {@code covarianceMatrix[i][j]}.
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* Takes precedence over {@code covarianceMatrixFlat} if both are provided.
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*/
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private double[][] covarianceMatrix;
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/**
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* Covariance matrix in flat row-major format: element (i,j) is at index
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* {@code i * nAssets + j}. Length must be nAssets². Used when the caller
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* cannot produce a nested JSON array (e.g., numpy {@code .flatten()}).
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*/
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private double[] covarianceMatrixFlat;
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/**
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* When {@code true}, weights are rescaled to sum to 1.0 before computing
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* variance. Allows callers to pass unnormalized exposures (e.g., notional
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* position values) without a client-side preprocessing step.
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* When {@code false} (default), weights that deviate from 1.0 by more than
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* 1e-4 return an error.
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*/
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private boolean normalizeWeights = false;
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/**
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* Trading periods per year used to annualize volatility.
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* {@code annualizedVolatility = portfolioVolatility × sqrt(nPeriodsPerYear)}.
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* Common values: 252 (equity, default), 260 (some fixed-income conventions),
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* 365 (crypto), 12 (monthly factor models).
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*/
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private int nPeriodsPerYear = 252;
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/** Optional identifier echoed in the response for request tracing. */
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private String requestId;
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// ── getters ──────────────────────────────────────────────────────────────
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public double[] getWeights() { return weights; }
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public double[][] getCovarianceMatrix() { return covarianceMatrix; }
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public double[] getCovarianceMatrixFlat() { return covarianceMatrixFlat; }
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public boolean isNormalizeWeights() { return normalizeWeights; }
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public int getNPeriodsPerYear() { return nPeriodsPerYear > 0 ? nPeriodsPerYear : 252; }
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public String getRequestId() { return requestId; }
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// ── setters ──────────────────────────────────────────────────────────────
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public void setWeights(double[] weights) { this.weights = weights; }
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public void setCovarianceMatrix(double[][] covarianceMatrix) { this.covarianceMatrix = covarianceMatrix; }
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public void setCovarianceMatrixFlat(double[] covarianceMatrixFlat) { this.covarianceMatrixFlat = covarianceMatrixFlat; }
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public void setNormalizeWeights(boolean normalizeWeights) { this.normalizeWeights = normalizeWeights; }
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public void setNPeriodsPerYear(int nPeriodsPerYear) { this.nPeriodsPerYear = nPeriodsPerYear; }
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public void setRequestId(String requestId) { this.requestId = requestId; }
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/** Derived: number of assets inferred from weights array length. */
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public int getNAssets() {
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return weights != null ? weights.length : 0;
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}
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}

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