Model MRModelRanged1Demo

MRModelRanged1Demo — quantitative model reference

Wiki home · Quantitative model references · Execution records

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.

Tutorials and quantitative model references · Pinned source · Javadoc

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

The ranged variant is demonstrated on the configured basket in main; read the basket coefficient and model range together to interpret spread units. 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 ranged mean-reversion model on local GainCapital FX prices. A range parameter is expressed in spread/price units; the basket coefficients and lot scale control the traded quantities.

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

Implementation in this tutorial. The ranged variant is demonstrated on the configured basket in main; read the basket coefficient and model range together to interpret spread units. 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	6.21
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.MRModelRanged1Demo

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

09:14:33.813 [main] INFO  t.n.a.d.m.volarb.MRModelRanged1Demo,133 - Performance Report:
Product	Execution Count	Profit Loss	Information Ratio For Trades	Omega For Trades
NZD/CHF	10.0	-0.014190000016242266	-0.39867318222868187	-0.7518373726228952
Total	10.0	-0.014190000016242266	-0.39867318222868187	-0.7518373726228952

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 MRModelRanged1Demo.zip contains stdout, stderr, the execution record, checksums and any exported CSV/chart files.

Export	Bytes
files/charts/chart-01.png	100937
files/derived-charts/charts.json	521
files/derived-charts/derived-01.csv	374
files/derived-charts/derived-01.png	92205

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.