name: ivx-economy-simulator description: >- Design, simulate, and monitor game economies for IntelliVerseX SDK games. Use when the user says "economy design", "currency flow", "balance economy", "inflation detection", "reward curves", "economy simulator", "Monte Carlo", "pricing optimization", "Gini coefficient", "economy health", "currency sinks", "currency sources", "exchange rates", "loot tables", or needs help with any virtual economy design or balancing. version: "1.0.0" author: "IntelliVerse-X team@intelli-verse-x.ai" allowed-tools:

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IntelliVerseX Economy Simulator

Overview

The Economy Simulator provides tools for designing, testing, and monitoring virtual game economies. It builds on top of the Hiro economy system to add currency flow modeling, Monte Carlo simulation, inflation detection, reward curve design, and real-time economy health monitoring.

Economy Design (offline)          Live Economy (runtime)
┌──────────────────────┐         ┌──────────────────────┐
│ Currency Flow Model  │         │ IVXEconomyMonitor    │
│ Reward Curve Design  │  ────►  │ Health Dashboard     │
│ Monte Carlo Sim      │  deploy │ Inflation Alerts     │
│ Pricing Optimizer    │         │ Player Wealth Dist.  │
└──────────────────────┘         └──────────────────────┘
         │                                │
         ▼                                ▼
  Hiro Economy Config              Satori Metrics
  (hiro_configs/economy)           (economy events)

1. Currency Flow Model

Defining Sources and Sinks

using IntelliVerseX.Economy;

var model = new IVXCurrencyFlowModel("coins");

model.AddSource(new CurrencySource
{
    Name = "level_reward",
    AveragePerDay = 500,
    Variance = 100,
    PlayerSegment = "all",
});

model.AddSource(new CurrencySource
{
    Name = "daily_login",
    AveragePerDay = 200,
    Variance = 0,
    PlayerSegment = "retained",
});

model.AddSource(new CurrencySource
{
    Name = "rewarded_ad",
    AveragePerDay = 300,
    Variance = 200,
    PlayerSegment = "ad_viewers",
});

model.AddSink(new CurrencySink
{
    Name = "store_purchase",
    AveragePerDay = 400,
    Variance = 150,
});

model.AddSink(new CurrencySink
{
    Name = "energy_refill",
    AveragePerDay = 150,
    Variance = 50,
});

model.AddSink(new CurrencySink
{
    Name = "gacha_pull",
    AveragePerDay = 200,
    Variance = 300,
});

Flow Analysis

var analysis = model.Analyze();

Debug.Log($"Daily net flow: {analysis.NetFlowPerDay:+#;-#;0}");
Debug.Log($"Source total: {analysis.TotalSourcesPerDay}/day");
Debug.Log($"Sink total: {analysis.TotalSinksPerDay}/day");
Debug.Log($"Balance ratio: {analysis.SinkToSourceRatio:F2}");
Debug.Log($"Inflation risk: {analysis.InflationRisk}");

Recommended sink-to-source ratio: 0.8–1.2 for a healthy economy. Below 0.8 indicates inflation risk.

2. Monte Carlo Simulation

Running Simulations

var sim = new IVXEconomySimulator();

sim.AddCurrency(model);
sim.SetPlayerCount(1000);
sim.SetDurationDays(90);
sim.SetIterations(100);

sim.SetPlayerBehavior(new PlayerBehaviorProfile
{
    DailySessionProbability = 0.6f,
    PurchaseProbability = 0.05f,
    AdViewProbability = 0.3f,
    ChurnCurve = ChurnCurve.Exponential(halfLifeDays: 14),
});

var results = await sim.RunAsync();

Debug.Log($"Day 30 median balance: {results.GetMedianBalance(30)}");
Debug.Log($"Day 30 P90 balance: {results.GetPercentileBalance(30, 90)}");
Debug.Log($"Day 60 Gini coefficient: {results.GetGiniCoefficient(60):F3}");
Debug.Log($"Day 90 inflation rate: {results.GetInflationRate(90):P1}");

Simulation Output

3. Reward Curve Designer

Defining Progression Rewards

var curve = new IVXRewardCurve("level_rewards");

curve.SetBaseReward(100);
curve.SetGrowthFunction(RewardGrowth.Logarithmic);
curve.SetGrowthRate(1.15f);
curve.SetMaxLevel(100);
curve.SetMilestones(new Dictionary<int, int>
{
    { 10, 500 },
    { 25, 2000 },
    { 50, 10000 },
    { 100, 50000 },
});

for (int level = 1; level <= 20; level++)
{
    int reward = curve.GetReward(level);
    Debug.Log($"Level {level}: {reward} coins");
}

Growth Functions

4. Store Pricing Optimization

A/B Testing Prices

using IntelliVerseX.Economy;

var optimizer = new IVXPricingOptimizer("gem_pack_small");

optimizer.SetBasePrice("coins", 500);
optimizer.SetVariants(new[]
{
    new PriceVariant { Name = "control", Price = 500 },
    new PriceVariant { Name = "discount", Price = 350 },
    new PriceVariant { Name = "premium", Price = 750 },
});

optimizer.LinkToExperiment("store_pricing_test");

This creates a Satori experiment that assigns players to price variants and tracks conversion and revenue per variant.

Elasticity Analysis

var elasticity = await optimizer.GetElasticityAsync();

Debug.Log($"Price elasticity: {elasticity.Coefficient:F2}");
Debug.Log($"Revenue-maximizing price: {elasticity.OptimalPrice}");
Debug.Log($"Expected conversion at optimal: {elasticity.OptimalConversion:P1}");

5. Economy Health Monitor

Real-Time Monitoring

var monitor = IVXEconomyMonitor.Instance;

monitor.StartMonitoring(new MonitorConfig
{
    Currencies = new[] { "coins", "gems" },
    SampleIntervalMinutes = 60,
    AlertOnInflation = true,
    InflationThresholdPercent = 10.0f,
    AlertOnDeflation = true,
    DeflationThresholdPercent = 5.0f,
});

monitor.OnAlert += (alert) =>
{
    Debug.LogWarning($"Economy alert: {alert.Currency} - {alert.Type}: {alert.Message}");
};

Health Dashboard Metrics

Querying Health

var health = await IVXEconomyMonitor.Instance.GetHealthAsync("coins");

Debug.Log($"Status: {health.Status}");
Debug.Log($"Avg balance: {health.AverageBalance}");
Debug.Log($"Gini: {health.GiniCoefficient:F3}");
Debug.Log($"Velocity: {health.Velocity:F2}/week");
Debug.Log($"Inflation rate: {health.InflationRate:P1}");

6. Server-Side Economy Config

The economy simulator reads and writes to the Hiro economy config:

hiro_configs/economy
├── currencies[]          — currency definitions
│   ├── id, name, max_count
│   └── initial_amount
├── exchange_rates[]      — currency conversion rates
├── store_items[]         — purchasable items
└── donation_config       — team/guild economy settings

Deploying Simulation Results

var deployConfig = model.ToHiroConfig();
await IVXHiroConfigManager.Instance.SetAsync("economy", deployConfig);

7. Cross-Platform API

The full Monte Carlo simulator is available in Unity Editor and Node.js for offline design. Runtime monitoring works on all platforms.

Platform-Specific Economy Design

VR Platforms

Console Platforms

WebGL / Browser

Checklist

• Currency flow model defined for each currency (sources + sinks)
• Sink-to-source ratio within 0.8–1.2 range
• Monte Carlo simulation run with 90-day projections
• Gini coefficient below 0.7 in simulations
• Inflation rate below 5%/month in simulations
• Reward curves defined for all progression systems
• Store pricing A/B test configured via Satori
• Economy health monitor active with alert thresholds
• Hiro economy config deployed from simulation results
• VR earn rates tuned for short session lengths (if targeting VR)
• Console economy reviewed for platform monetization norms (if targeting consoles)
• Browser session persistence tested (if targeting WebGL)