Model PortfolioOptimComparisons2Demo

PortfolioOptimComparisons2Demo — AlgoQuant usage tutorial

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These examples are tutorials that teach how to use AlgoQuant. Their numerical results are incidental and irrelevant to their teaching purpose. Use them to learn API calls, simulation setup, data flow and reporting. The technical examples use synthetic quick-mode data. Read a result here as an illustration of a library call, not as investment evidence.

Tutorials and quantitative model references · Pinned source · Javadoc

Related papers introduction

Harry Markowitz, Portfolio Selection (1952) explains diversification as a portfolio problem: an asset's risk cannot be judged independently of how its returns move with the other holdings. Expected portfolio return is a weighted mean; portfolio variance depends on the full covariance matrix.

The efficient set contains portfolios for which expected return cannot be improved without accepting more variance, or variance reduced without giving up expected return. An investor selects a tradeoff according to preferences and constraints. Holding many positively correlated assets need not provide much diversification.

The framework assumes the relevant return means and covariances are supplied. In practice, estimates can be unstable and constraints can materially change the answer. A solved optimization is therefore a set of weights under assumptions, not evidence of future outperformance. The original article was reviewed. Rolling calibration, rebalance schedules, costs and the dataset used here belong to the demo, not to the static 1952 formulation.

This comparison also includes Corvalán’s near-efficient diversification framework (2005) and Lai, Xing and Chen’s estimation-risk framework (2011). The first permits diversification within a tolerance of a risk–return target; the second accounts for uncertain estimated inputs through predictive/resampling methods. Equal-weight and simplified-input baselines help distinguish the effects of estimation, optimization and post-processing. A common historical interval does not make the algorithms’ objectives identical.

How this demo connects to the idea

Compares allocation methods on selected historical/local data. A common estimation window and asset ordering are required for a fair comparison. Several alternative dataset branches are embedded in main; results depend on the branch and its data coverage.

What this example teaches

Compares the different asset allocation algorithms. Prices are from historical data.

Using this example. Compares allocation algorithms on historical price data. Some branches reference local China datasets and an absolute Windows Compustat path; choose the intended branch and configure those inputs before running. Consistent asset ordering and common estimation periods are essential to the comparison.

Model and publication. Related theory and the scope of this example are distinguished below.

Implementation in this tutorial. Compares allocation methods on selected historical/local data. A common estimation window and asset ordering are required for a fair comparison. Several alternative dataset branches are embedded in main; results depend on the branch and its data coverage.

Verified execution record

Item	Value
Status	completed
Run	39122217560
UTC publication	2026-10-18 11:43 UTC
Source commit	f497645628296f441e1e254127a7547d15106bbc
Data mode	original main defaults
Exit code	0
Elapsed seconds	35.94
Time limit seconds	1800
Maximum Java heap	6g
AlgoQuant source commit	`aba178deb0e78dc72184546a1e0934c3abce74a1`
NM Dev source commit	`04c12d1640fb700f52a2f7dc5cadf560040490e6`
Combined runtime SHA-256	`c1199a1c204cc4ffdf937b756bceacaf30bb64f35a844770490fea268742379b`

The original main returned successfully without a detected calculation error. Read its assumptions before interpreting it.

Reproduce the calculation

Follow the repository setup for JDK 8, Maven credentials and an external NM license. From the repository root:

mvn -U -Dmaven.test.skip=true clean package
mvn exec:java -Dexec.mainClass=tech.nmfin.algoquant.demo.model.portfoliooptimization.PortfolioOptimComparisons2Demo

The automated run uses scripts/ModelDemoRunner.java to initialize the external license before the unchanged main, save JFreeChart windows as PNGs, and exit after main returns. It uses an isolated working directory with the repository datasets/configuration linked in. Running directly may leave desktop windows open.

Observed output

11:17:12.688 [main] INFO  t.n.a.m.p.s.OptimizationAlgorithmComparisonSimulation - Running algorithm 'equal' (window=P6M, rebalance=P6M)...
11:17:12.733 [main] INFO  tech.nmfin.algoquant.util.config.AQConfig - looking up configuration file: config.default.xml
11:17:12.734 [main] INFO  tech.nmfin.algoquant.util.config.AQConfig - looking up configuration file: config/config.default.xml
11:17:12.734 [main] INFO  tech.nmfin.algoquant.util.config.AQConfig - loading config file: file:/home/runner/work/algoquant/algoquant/target/model-results/PortfolioOptimComparisons2Demo/work/config/config.default.xml


11:17:13.004 [main] INFO  tech.nmfin.algoquant.util.config.AQConfig - current directory: /home/runner/work/algoquant/algoquant/target/model-results/PortfolioOptimComparisons2Demo/work
11:17:13.004 [main] INFO  tech.nmfin.algoquant.util.config.AQConfig - current config:
11:17:13.019 [main] INFO  tech.nmfin.algoquant.util.config.AQConfig - logback.configurationFile: /home/runner/work/algoquant/algoquant/config/model-demo-logback.xml
11:17:13.022 [main] INFO  tech.nmfin.algoquant.util.config.AQConfig - nm.license: /home/runner/work/algoquant/algoquant/license/nm.lic
11:17:13.023 [main] INFO  tech.nmfin.algoquant.util.config.AQConfig - DATA_FOLDER: ./test-data
11:17:13.023 [main] INFO  tech.nmfin.algoquant.util.config.AQConfig - DATA_GAINCAPITAL: ${DATA_FOLDER}/processed/gaincapital/extracted-from-raw-arrange-by-dates
11:17:13.024 [main] INFO  tech.nmfin.algoquant.util.config.AQConfig - DATA_BLOOMBERG: ${DATA_FOLDER}/processed/bloomberg
11:17:13.024 [main] INFO  tech.nmfin.algoquant.util.config.AQConfig - DATA_YAHOO: ${DATA_FOLDER}/yahoo
11:17:13.024 [main] INFO  tech.nmfin.algoquant.util.config.AQConfig - DATA_SGX: ${DATA_FOLDER}/raw/sgx
11:17:13.024 [main] INFO  tech.nmfin.algoquant.util.config.AQConfig - DATA_HOLIDAYS: ./log/holidays
11:17:13.025 [main] INFO  tech.nmfin.algoquant.util.config.AQConfig - DATA_COMPUSTAT_HK: ${DATA_FOLDER}/compustat/hk
11:17:13.025 [main] INFO  tech.nmfin.algoquant.util.config.AQConfig - PDF_OUTPUT_FOLDER: ./log/
11:17:13.025 [main] INFO  tech.nmfin.algoquant.util.config.AQConfig - PDF_PLOT_WIDTH: 800
11:17:13.026 [main] INFO  tech.nmfin.algoquant.util.config.AQConfig - PDF_PLOT_HEIGHT: 600
11:17:18.253 [main] INFO  t.n.a.d.h.yahoo.YahooEODCacheFactory - reading Yahoo! data for ^IRX from the Internet from 2016-06-29T00:00 to 2018-08-04T16:00
11:17:18.661 [main] INFO  t.n.a.d.h.yahoo.YahooEODCacheFactory - reading Yahoo! data for ^GSPC from the Internet from 2015-06-01T00:00 to 2019-01-15T16:00
11:17:19.096 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2016-07-29T00:00
11:17:19.100 [main] INFO  t.n.a.m.s.rebalance.RebalancePortfolioTechnical - dropped products with no data (13): [low_risk_1(CNY), low_risk_2(CNY), low_risk_3(CNY), low_risk_4(CNY), low_risk_5(CNY), risk_1(CNY), risk_2(CNY), risk_3(CNY), risk_4(CNY), risk_5(CNY), risk_6(CNY), risk_7(CNY), risk_8(CNY)]
11:17:19.101 [main] INFO  t.n.a.m.s.rebalance.RebalancePortfolioTechnical - Rebalance deferred: calibration data are not yet available at 2016-07-29T00:00
11:17:19.124 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2017-01-29T00:00
11:17:19.238 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2017-07-29T00:00
11:17:19.277 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2018-01-29T00:00
11:17:19.320 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2018-07-29T00:00
11:17:19.773 [main] INFO  t.n.a.m.p.s.OptimizationAlgorithmComparisonSimulation - Finished algorithm 'equal' (window=P6M, rebalance=P6M)
... excerpt shortened; complete stdout is in the release archive ...
11:17:21.230 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2016-07-29T00:00
11:17:21.230 [main] INFO  t.n.a.m.s.rebalance.RebalancePortfolioTechnical - dropped products with no data (13): [low_risk_1(CNY), low_risk_2(CNY), low_risk_3(CNY), low_risk_4(CNY), low_risk_5(CNY), risk_1(CNY), risk_2(CNY), risk_3(CNY), risk_4(CNY), risk_5(CNY), risk_6(CNY), risk_7(CNY), risk_8(CNY)]
11:17:21.230 [main] INFO  t.n.a.m.s.rebalance.RebalancePortfolioTechnical - Rebalance deferred: calibration data are not yet available at 2016-07-29T00:00
11:17:21.232 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2017-01-29T00:00
11:17:21.263 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2017-07-29T00:00
11:17:21.287 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2018-01-29T00:00
11:17:21.309 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2018-07-29T00:00
11:17:21.395 [main] INFO  t.n.a.m.p.s.OptimizationAlgorithmComparisonSimulation - Finished algorithm 'sample-mean-shrank-cov/markowitz' (window=P6M, rebalance=P6M)
11:17:21.395 [main] INFO  t.n.a.m.p.s.OptimizationAlgorithmComparisonSimulation - Running algorithm 'markowitz-corvalan' (window=P6M, rebalance=P6M)...
11:17:21.396 [main] INFO  t.n.a.d.h.yahoo.YahooEODCacheFactory - reading Yahoo! data for ^GSPC from the Internet from 2015-06-01T00:00 to 2019-01-15T16:00
11:17:21.568 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2016-07-29T00:00
11:17:21.568 [main] INFO  t.n.a.m.s.rebalance.RebalancePortfolioTechnical - dropped products with no data (13): [low_risk_1(CNY), low_risk_2(CNY), low_risk_3(CNY), low_risk_4(CNY), low_risk_5(CNY), risk_1(CNY), risk_2(CNY), risk_3(CNY), risk_4(CNY), risk_5(CNY), risk_6(CNY), risk_7(CNY), risk_8(CNY)]
11:17:21.568 [main] INFO  t.n.a.m.s.rebalance.RebalancePortfolioTechnical - Rebalance deferred: calibration data are not yet available at 2016-07-29T00:00
11:17:21.570 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2017-01-29T00:00
11:17:21.658 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2017-07-29T00:00
11:17:21.684 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2018-01-29T00:00
11:17:21.705 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2018-07-29T00:00
11:17:21.801 [main] INFO  t.n.a.m.p.s.OptimizationAlgorithmComparisonSimulation - Finished algorithm 'markowitz-corvalan' (window=P6M, rebalance=P6M)
11:17:21.801 [main] INFO  t.n.a.m.p.s.OptimizationAlgorithmComparisonSimulation - Running algorithm 'lai2010' (window=P6M, rebalance=P6M)...
11:17:21.801 [main] INFO  t.n.a.d.h.yahoo.YahooEODCacheFactory - reading Yahoo! data for ^GSPC from the Internet from 2015-06-01T00:00 to 2019-01-15T16:00
11:17:21.974 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2016-07-29T00:00
11:17:21.974 [main] INFO  t.n.a.m.s.rebalance.RebalancePortfolioTechnical - dropped products with no data (13): [low_risk_1(CNY), low_risk_2(CNY), low_risk_3(CNY), low_risk_4(CNY), low_risk_5(CNY), risk_1(CNY), risk_2(CNY), risk_3(CNY), risk_4(CNY), risk_5(CNY), risk_6(CNY), risk_7(CNY), risk_8(CNY)]
11:17:21.974 [main] INFO  t.n.a.m.s.rebalance.RebalancePortfolioTechnical - Rebalance deferred: calibration data are not yet available at 2016-07-29T00:00
11:17:21.976 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2017-01-29T00:00
optimal eta = 40.000000
11:17:26.485 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2017-07-29T00:00
optimal eta = 6.000000
11:17:27.602 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2018-01-29T00:00
optimal eta = 5.000000
11:17:28.463 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2018-07-29T00:00
optimal eta = 40.000000
11:17:31.242 [main] INFO  t.n.a.m.p.s.OptimizationAlgorithmComparisonSimulation - Finished algorithm 'lai2010' (window=P6M, rebalance=P6M)
11:17:31.242 [main] INFO  t.n.a.m.p.s.OptimizationAlgorithmComparisonSimulation - Running algorithm 'NMSAAM' (window=P6M, rebalance=P6M)...
11:17:31.242 [main] INFO  t.n.a.d.h.yahoo.YahooEODCacheFactory - reading Yahoo! data for ^GSPC from the Internet from 2015-06-01T00:00 to 2019-01-15T16:00
11:17:32.302 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2016-07-29T00:00
11:17:32.303 [main] INFO  t.n.a.m.s.rebalance.RebalancePortfolioTechnical - dropped products with no data (13): [low_risk_1(CNY), low_risk_2(CNY), low_risk_3(CNY), low_risk_4(CNY), low_risk_5(CNY), risk_1(CNY), risk_2(CNY), risk_3(CNY), risk_4(CNY), risk_5(CNY), risk_6(CNY), risk_7(CNY), risk_8(CNY)]
11:17:32.303 [main] INFO  t.n.a.m.s.rebalance.RebalancePortfolioTechnical - Rebalance deferred: calibration data are not yet available at 2016-07-29T00:00
11:17:32.304 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2017-01-29T00:00
optimal eta = 3.500000
11:17:32.895 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2017-07-29T00:00
optimal eta = 14.000000
11:17:33.307 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2018-01-29T00:00
optimal eta = 11.000000
11:17:33.737 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2018-07-29T00:00
optimal eta = 2.500000
11:17:34.117 [main] INFO  t.n.a.m.p.s.OptimizationAlgorithmComparisonSimulation - Finished algorithm 'NMSAAM' (window=P6M, rebalance=P6M)
11:17:34.117 [main] INFO  t.n.a.m.p.s.OptimizationAlgorithmComparisonSimulation - Running algorithm 'partial-NMSAAM' (window=P6M, rebalance=P6M)...
11:17:34.118 [main] INFO  t.n.a.d.h.yahoo.YahooEODCacheFactory - reading Yahoo! data for ^GSPC from the Internet from 2015-06-01T00:00 to 2019-01-15T16:00
11:17:34.776 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2016-07-29T00:00
11:17:34.776 [main] INFO  t.n.a.m.s.rebalance.RebalancePortfolioTechnical - dropped products with no data (13): [low_risk_1(CNY), low_risk_2(CNY), low_risk_3(CNY), low_risk_4(CNY), low_risk_5(CNY), risk_1(CNY), risk_2(CNY), risk_3(CNY), risk_4(CNY), risk_5(CNY), risk_6(CNY), risk_7(CNY), risk_8(CNY)]
11:17:34.776 [main] INFO  t.n.a.m.s.rebalance.RebalancePortfolioTechnical - Rebalance deferred: calibration data are not yet available at 2016-07-29T00:00
11:17:34.777 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2017-01-29T00:00
optimal eta = 3.500000
11:17:35.081 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2017-07-29T00:00
optimal eta = 14.000000
11:17:35.381 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2018-01-29T00:00
optimal eta = 12.000000
11:17:35.675 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2018-07-29T00:00
optimal eta = 2.000000
11:17:36.011 [main] INFO  t.n.a.m.p.s.OptimizationAlgorithmComparisonSimulation - Finished algorithm 'partial-NMSAAM' (window=P6M, rebalance=P6M)
11:17:36.011 [main] INFO  t.n.a.m.p.s.OptimizationAlgorithmComparisonSimulation - Running algorithm 'lai2010-corvalan' (window=P6M, rebalance=P6M)...
11:17:36.012 [main] INFO  t.n.a.d.h.yahoo.YahooEODCacheFactory - reading Yahoo! data for ^GSPC from the Internet from 2015-06-01T00:00 to 2019-01-15T16:00
11:17:36.668 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2016-07-29T00:00
11:17:36.668 [main] INFO  t.n.a.m.s.rebalance.RebalancePortfolioTechnical - dropped products with no data (13): [low_risk_1(CNY), low_risk_2(CNY), low_risk_3(CNY), low_risk_4(CNY), low_risk_5(CNY), risk_1(CNY), risk_2(CNY), risk_3(CNY), risk_4(CNY), risk_5(CNY), risk_6(CNY), risk_7(CNY), risk_8(CNY)]
11:17:36.668 [main] INFO  t.n.a.m.s.rebalance.RebalancePortfolioTechnical - Rebalance deferred: calibration data are not yet available at 2016-07-29T00:00
11:17:36.669 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2017-01-29T00:00
optimal eta = 40.000000
11:17:39.087 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2017-07-29T00:00
optimal eta = 6.000000
11:17:39.559 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2018-01-29T00:00
optimal eta = 5.000000
11:17:40.059 [main] INFO  t.n.a.m.strategy.rebalance.RebalancePortfolio - Calculating weights for rebalancing point at 2018-07-29T00:00
optimal eta = 40.000000
11:17:42.259 [main] INFO  t.n.a.m.p.s.OptimizationAlgorithmComparisonSimulation - Finished algorithm 'lai2010-corvalan' (window=P6M, rebalance=P6M)
11:17:44.804 [main] INFO  t.n.a.execution.report.SimulationResultsExporter - Saving to /home/runner/work/algoquant/algoquant/target/model-results/PortfolioOptimComparisons2Demo/work/log/PortfolioOptimComparisons2Demo.2026.10.18,11.17.44.measures.csv...
11:17:44.823 [main] INFO  t.n.a.execution.report.SimulationResultsExporter - Saving to /home/runner/work/algoquant/algoquant/target/model-results/PortfolioOptimComparisons2Demo/work/log/PortfolioOptimComparisons2Demo.2026.10.18,11.17.44.executions.csv...
11:17:44.830 [main] INFO  t.n.a.execution.report.SimulationResultsExporter - Saving to /home/runner/work/algoquant/algoquant/target/model-results/PortfolioOptimComparisons2Demo/work/log/PortfolioOptimComparisons2Demo.2026.10.18,11.17.44.trades.csv...
11:17:44.838 [main] INFO  t.n.a.execution.report.ValueHistoriesExporter - Saving to /home/runner/work/algoquant/algoquant/target/model-results/PortfolioOptimComparisons2Demo/work/log/PortfolioOptimComparisons2Demo.2026.10.18,11.17.44.computed.weights.csv...
11:17:44.845 [main] INFO  t.n.a.execution.report.ValueHistoriesExporter - Saving to /home/runner/work/algoquant/algoquant/target/model-results/PortfolioOptimComparisons2Demo/work/log/PortfolioOptimComparisons2Demo.2026.10.18,11.17.44.actual.weights.csv...
11:17:44.847 [main] INFO  t.n.a.execution.report.ValueHistoriesExporter - Saving to /home/runner/work/algoquant/algoquant/target/model-results/PortfolioOptimComparisons2Demo/work/log/PortfolioOptimComparisons2Demo.2026.10.18,11.17.44.profit.csv...

Charts from this run

Chart 1

Chart 2

Chart 3