Model MRModelFixedGridOnSGXDataDemo

MRModelFixedGridOnSGXDataDemo — quantitative model reference

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This quantitative model reference is provided for study, further research and application within the AlgoQuant framework. Read the research idea and implementation choices separately from the execution record.

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Strategy introduction

This example illustrates a mean-reversion or grid-style trading policy assembled in code. No single original publication has been established for the exact rule, so this page explains the strategy without inventing a paper citation.

The broad idea is to change inventory as price moves through configured levels, or as a spread deviates from a reference. Reversals can allow purchases and sales at different levels, while a persistent trend can accumulate exposure or losses. A rule that repeatedly realizes small gains can still carry substantial open-position risk.

The result depends on grid spacing, reference updates, position limits, data frequency, fills and costs. Mean reversion is an assumption to examine, not a property created by the grid itself. Read the implementation below for the exact configuration, and inspect both account value and outstanding inventory when interpreting a simulation.

How this demo connects to the idea

This fixed-grid adaptation supplies SGX futures tick caches instead of the FX caches used by MRModelFixedGridDemo; product conventions differ. These are library-specific spread/grid trading policies. A basket converts product prices into a spread; the configured mean-reversion model maps its level or deviation into a desired state, and MeanReversionStrategy translates that state into product orders. Grid distance, periodic/ranged update behavior and scale are distinct controls. The folder name does not mean that option implied volatility is being traded. Mean reversion is an assumption to check, not a property guaranteed by this policy.

What this example teaches

Using this example. Runs a fixed-grid mean-reversion basket using local SGX SiMSCI and NK tick caches. The two instruments and basket coefficient must be interpreted with their product and currency conventions; the result is not a normalized portfolio return.

Model and publication. No single original research publication is claimed for this library/example policy.

Implementation in this tutorial. This fixed-grid adaptation supplies SGX futures tick caches instead of the FX caches used by MRModelFixedGridDemo; product conventions differ. These are library-specific spread/grid trading policies. A basket converts product prices into a spread; the configured mean-reversion model maps its level or deviation into a desired state, and MeanReversionStrategy translates that state into product orders. Grid distance, periodic/ranged update behavior and scale are distinct controls. The folder name does not mean that option implied volatility is being traded. Mean reversion is an assumption to check, not a property guaranteed by this policy.

Verified execution record

Item	Value
Status	completed
Run	39114360151
UTC publication	2026-10-18 11:43 UTC
Source commit	355aa9242fc2a247b256aecc8406cbb409aa5ff3
Data mode	original main defaults
Exit code	0
Elapsed seconds	20.17
Time limit seconds	180
Maximum Java heap	1200m

The original main returned successfully. Read the output and model 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.volarb.MRModelFixedGridOnSGXDataDemo

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

09:13:31.218 [main] INFO  t.n.algoquant.util.config.AQConfig,194 - looking up configuration file: config.default.xml
09:13:31.222 [main] INFO  t.n.algoquant.util.config.AQConfig,194 - looking up configuration file: config/config.default.xml
09:13:31.222 [main] INFO  t.n.algoquant.util.config.AQConfig,209 - loading config file: file:/home/runner/work/algoquant-examples/algoquant-examples/target/model-results/MRModelFixedGridOnSGXDataDemo/work/config/config.default.xml


09:13:31.328 [main] INFO  t.n.algoquant.util.config.AQConfig,95 - current directory: /home/runner/work/algoquant-examples/algoquant-examples/target/model-results/MRModelFixedGridOnSGXDataDemo/work
09:13:31.328 [main] INFO  t.n.algoquant.util.config.AQConfig,169 - current config:
09:13:31.339 [main] INFO  t.n.algoquant.util.config.AQConfig,11 - nm.license: /home/runner/work/algoquant-examples/algoquant-examples/license/nm.lic
09:13:31.339 [main] INFO  t.n.algoquant.util.config.AQConfig,11 - DATA_FOLDER: ./test-data
09:13:31.339 [main] INFO  t.n.algoquant.util.config.AQConfig,11 - DATA_GAINCAPITAL: ${DATA_FOLDER}/processed/gaincapital/extracted-from-raw-arrange-by-dates
09:13:31.340 [main] INFO  t.n.algoquant.util.config.AQConfig,11 - DATA_BLOOMBERG: ${DATA_FOLDER}/processed/bloomberg
09:13:31.340 [main] INFO  t.n.algoquant.util.config.AQConfig,11 - DATA_YAHOO: ${DATA_FOLDER}/yahoo
09:13:31.340 [main] INFO  t.n.algoquant.util.config.AQConfig,11 - DATA_SGX: ${DATA_FOLDER}/raw/sgx
09:13:31.340 [main] INFO  t.n.algoquant.util.config.AQConfig,11 - DATA_HOLIDAYS: ./log/holidays
09:13:31.340 [main] INFO  t.n.algoquant.util.config.AQConfig,11 - DATA_COMPUSTAT_HK: ${DATA_FOLDER}/[database configuration redacted]/hk
09:13:31.341 [main] INFO  t.n.algoquant.util.config.AQConfig,11 - PDF_OUTPUT_FOLDER: ./log/
09:13:31.341 [main] INFO  t.n.algoquant.util.config.AQConfig,11 - PDF_PLOT_WIDTH: 800
09:13:31.341 [main] INFO  t.n.algoquant.util.config.AQConfig,11 - PDF_PLOT_HEIGHT: 600
09:13:50.590 [main] INFO  t.n.a.d.m.v.MRModelFixedGridOnSGXDataDemo,146 - report = Performance Report:
Product	Profit Loss	Information Ratio For Trades	Omega For Trades
NK	-9374.099999999977	-2.714561416802233	-1.0
SiMSCI	7.29652E7	6.425031460219233	Infinity
Total	7.29558259E7	0.9243955958299965	127.10519270537083

Charts from this run

Reported performance statistics

Products and aggregate shown exactly as reported; P/L is monetary, not percent. Currency conventions belong to the demo.

Derived from stdout.log using the precision available in that file. Download plotted data. Undefined or malformed cells are omitted, never replaced by zero.

Downloadable evidence

Download MRModelFixedGridOnSGXDataDemo.zip contains stdout, stderr, the execution record, checksums and any exported CSV/chart files.

Export	Bytes
files/charts/chart-01.png	74839
files/derived-charts/charts.json	521
files/derived-charts/derived-01.csv	379
files/derived-charts/derived-01.png	95368

Interpreting the result

Read the reported units: optimizer weights, model-fit coefficients, forecast correlations and simulated P/L are different outputs. Synthetic runs demonstrate the API rather than historical market returns. Inspect undefined values and open positions instead of replacing them with zero. Chart exports visualize exactly this run.

For model assumptions, original publications and adaptation limits, use the literature guide.