claude-flow
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Ruflo - Enterprise AI agent orchestration for Claude Code. Deploy 60+ specialized agents in coordinated swarms with self-learning, fault-tolerant consensus, vector memory, and MCP integration
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text/typescript
/**
* Economy Bridge - Financial Risk Plugin
*
* Provides token economics and portfolio risk calculation
* capabilities. Integrates with ruvector-economy-wasm for
* high-performance VaR, CVaR, and Monte Carlo simulations.
*
* Compliance Features:
* - Deterministic execution for audit reproducibility
* - Calculation proofs for regulatory requirements
* - Rate limiting to prevent abuse
*/
import type {
EconomyBridge,
EconomyConfig,
PortfolioHolding,
RiskMetrics,
TimeHorizon,
RiskCalculationProof,
Logger,
} from '../types.js';
/**
* Default logger
*/
const defaultLogger: Logger = {
debug: (msg: string, meta?: Record<string, unknown>) => console.debug(`[economy-bridge] ${msg}`, meta),
info: (msg: string, meta?: Record<string, unknown>) => console.info(`[economy-bridge] ${msg}`, meta),
warn: (msg: string, meta?: Record<string, unknown>) => console.warn(`[economy-bridge] ${msg}`, meta),
error: (msg: string, meta?: Record<string, unknown>) => console.error(`[economy-bridge] ${msg}`, meta),
};
/**
* WASM module interface for ruvector-economy-wasm
*/
interface EconomyWasmModule {
calculate_var(returns: Float32Array, confidence: number): number;
calculate_cvar(returns: Float32Array, confidence: number): number;
calculate_volatility(returns: Float32Array): number;
calculate_sharpe(returns: Float32Array, riskFreeRate: number): number;
calculate_sortino(returns: Float32Array, riskFreeRate: number): number;
calculate_max_drawdown(prices: Float32Array): number;
monte_carlo_simulation(
portfolio: Float32Array,
covariance: Float32Array,
scenarios: number,
horizon: number,
seed: number
): Float32Array;
optimize_portfolio(
returns: Float32Array,
constraints: Float32Array,
numAssets: number,
numPeriods: number
): Float32Array;
memory: { buffer: ArrayBuffer };
}
/**
* Historical market data cache
*/
interface MarketDataCache {
returns: Map<string, number[]>;
prices: Map<string, number[]>;
lastUpdated: Date;
}
/**
* Portfolio risk calculator with pure JavaScript fallback
*/
export class PortfolioRiskCalculator {
/**
* Calculate Value at Risk (VaR) using historical simulation
*/
calculateVaR(returns: number[], confidenceLevel: number = 0.95): number {
if (returns.length === 0) return 0;
const sorted = [...returns].sort((a, b) => a - b);
const index = Math.floor((1 - confidenceLevel) * sorted.length);
return -sorted[index]!;
}
/**
* Calculate Conditional VaR (CVaR / Expected Shortfall)
*/
calculateCVaR(returns: number[], confidenceLevel: number = 0.95): number {
if (returns.length === 0) return 0;
const sorted = [...returns].sort((a, b) => a - b);
const cutoffIndex = Math.floor((1 - confidenceLevel) * sorted.length);
let sum = 0;
for (let i = 0; i <= cutoffIndex; i++) {
sum += sorted[i]!;
}
return -sum / (cutoffIndex + 1);
}
/**
* Calculate annualized volatility
*/
calculateVolatility(returns: number[], annualizationFactor: number = 252): number {
if (returns.length < 2) return 0;
const mean = returns.reduce((a, b) => a + b, 0) / returns.length;
const variance = returns.reduce((sum, r) => sum + Math.pow(r - mean, 2), 0) / (returns.length - 1);
const dailyVol = Math.sqrt(variance);
return dailyVol * Math.sqrt(annualizationFactor);
}
/**
* Calculate Sharpe Ratio
*/
calculateSharpe(returns: number[], riskFreeRate: number = 0.02): number {
if (returns.length < 2) return 0;
const annualizedReturn = this.calculateAnnualizedReturn(returns);
const volatility = this.calculateVolatility(returns);
if (volatility === 0) return 0;
return (annualizedReturn - riskFreeRate) / volatility;
}
/**
* Calculate Sortino Ratio
*/
calculateSortino(returns: number[], riskFreeRate: number = 0.02): number {
if (returns.length < 2) return 0;
const annualizedReturn = this.calculateAnnualizedReturn(returns);
const downsideReturns = returns.filter(r => r < 0);
if (downsideReturns.length === 0) return Infinity;
const downsideDeviation = Math.sqrt(
downsideReturns.reduce((sum, r) => sum + r * r, 0) / downsideReturns.length
) * Math.sqrt(252);
if (downsideDeviation === 0) return 0;
return (annualizedReturn - riskFreeRate) / downsideDeviation;
}
/**
* Calculate Maximum Drawdown
*/
calculateMaxDrawdown(prices: number[]): number {
if (prices.length < 2) return 0;
let maxDrawdown = 0;
let peak = prices[0]!;
for (const price of prices) {
if (price > peak) {
peak = price;
}
const drawdown = (peak - price) / peak;
if (drawdown > maxDrawdown) {
maxDrawdown = drawdown;
}
}
return maxDrawdown;
}
/**
* Calculate Beta against market benchmark
*/
calculateBeta(assetReturns: number[], marketReturns: number[]): number {
if (assetReturns.length !== marketReturns.length || assetReturns.length < 2) return 1;
const assetMean = assetReturns.reduce((a, b) => a + b, 0) / assetReturns.length;
const marketMean = marketReturns.reduce((a, b) => a + b, 0) / marketReturns.length;
let covariance = 0;
let marketVariance = 0;
for (let i = 0; i < assetReturns.length; i++) {
const assetDev = assetReturns[i]! - assetMean;
const marketDev = marketReturns[i]! - marketMean;
covariance += assetDev * marketDev;
marketVariance += marketDev * marketDev;
}
if (marketVariance === 0) return 1;
return covariance / marketVariance;
}
/**
* Monte Carlo simulation for portfolio
*/
monteCarloSimulation(
portfolioReturns: number[],
scenarios: number = 10000,
horizon: number = 252,
seed?: number
): number[] {
// Simple random number generator with seed
let rng = seed !== undefined ? this.seededRandom(seed) : Math.random;
const mean = portfolioReturns.reduce((a, b) => a + b, 0) / portfolioReturns.length;
const std = this.calculateVolatility(portfolioReturns, 1); // Daily volatility
const results: number[] = [];
for (let s = 0; s < scenarios; s++) {
let cumulativeReturn = 0;
for (let d = 0; d < horizon; d++) {
// Box-Muller transform for normal distribution
const u1 = rng();
const u2 = rng();
const z = Math.sqrt(-2 * Math.log(u1)) * Math.cos(2 * Math.PI * u2);
cumulativeReturn += mean + std * z;
}
results.push(cumulativeReturn);
}
return results.sort((a, b) => a - b);
}
private calculateAnnualizedReturn(returns: number[]): number {
if (returns.length === 0) return 0;
const totalReturn = returns.reduce((a, b) => a + b, 0);
const avgDailyReturn = totalReturn / returns.length;
return avgDailyReturn * 252; // Annualize
}
private seededRandom(seed: number): () => number {
let state = seed;
return () => {
state = (state * 1103515245 + 12345) & 0x7fffffff;
return state / 0x7fffffff;
};
}
}
/**
* Financial Economy Bridge implementation
*/
export class FinancialEconomyBridge implements EconomyBridge {
private wasmModule: EconomyWasmModule | null = null;
private config: EconomyConfig;
private logger: Logger;
private calculator: PortfolioRiskCalculator;
private marketDataCache: MarketDataCache;
private randomSeed: number;
public initialized = false;
constructor(config?: Partial<EconomyConfig>, logger?: Logger) {
this.config = {
precision: config?.precision ?? 6,
randomSeed: config?.randomSeed ?? Date.now(),
defaultScenarios: config?.defaultScenarios ?? 10000,
};
this.logger = logger ?? defaultLogger;
this.calculator = new PortfolioRiskCalculator();
this.randomSeed = this.config.randomSeed!;
this.marketDataCache = {
returns: new Map(),
prices: new Map(),
lastUpdated: new Date(),
};
}
/**
* Initialize the economy bridge
*/
async initialize(config?: EconomyConfig): Promise<void> {
if (config) {
this.config = { ...this.config, ...config };
if (config.randomSeed) {
this.randomSeed = config.randomSeed;
}
}
try {
const wasmPath = await this.resolveWasmPath();
if (wasmPath) {
this.wasmModule = await this.loadWasmModule(wasmPath);
this.logger.info('Economy WASM module initialized', {
precision: this.config.precision,
defaultScenarios: this.config.defaultScenarios,
});
} else {
this.logger.warn('WASM module not available, using JavaScript fallback');
}
this.initialized = true;
} catch (error) {
this.logger.warn('Failed to initialize WASM, using fallback', {
error: error instanceof Error ? error.message : String(error),
});
this.initialized = true;
}
}
/**
* Calculate Value at Risk
*/
async calculateVar(returns: Float32Array, confidence: number): Promise<number> {
if (!this.initialized) {
throw new Error('Economy bridge not initialized');
}
if (this.wasmModule) {
return this.wasmModule.calculate_var(returns, confidence);
}
return this.calculator.calculateVaR(Array.from(returns), confidence);
}
/**
* Calculate Conditional VaR
*/
async calculateCvar(returns: Float32Array, confidence: number): Promise<number> {
if (!this.initialized) {
throw new Error('Economy bridge not initialized');
}
if (this.wasmModule) {
return this.wasmModule.calculate_cvar(returns, confidence);
}
return this.calculator.calculateCVaR(Array.from(returns), confidence);
}
/**
* Optimize portfolio allocation
*/
async optimizePortfolio(
returns: Float32Array[],
constraints: Record<string, number>
): Promise<Float32Array> {
if (!this.initialized) {
throw new Error('Economy bridge not initialized');
}
const assetCount = returns.length;
const periodCount = returns[0]?.length ?? 0;
if (this.wasmModule && assetCount > 0 && periodCount > 0) {
// Flatten returns array
const flatReturns = new Float32Array(assetCount * periodCount);
for (let i = 0; i < assetCount; i++) {
flatReturns.set(returns[i]!, i * periodCount);
}
const constraintsArray = new Float32Array([
constraints.minWeight ?? 0,
constraints.maxWeight ?? 1,
constraints.targetReturn ?? 0.1,
constraints.maxVolatility ?? 0.2,
]);
return this.wasmModule.optimize_portfolio(flatReturns, constraintsArray, assetCount, periodCount);
}
// Fallback: Equal weight allocation
const weights = new Float32Array(assetCount);
const equalWeight = 1 / assetCount;
for (let i = 0; i < assetCount; i++) {
weights[i] = equalWeight;
}
return weights;
}
/**
* Run Monte Carlo simulation
*/
async simulateMonteCarlo(
portfolio: Float32Array,
scenarios: number,
horizon: number
): Promise<Float32Array> {
if (!this.initialized) {
throw new Error('Economy bridge not initialized');
}
if (this.wasmModule) {
// Create identity covariance for simplicity
const n = portfolio.length;
const covariance = new Float32Array(n * n);
for (let i = 0; i < n; i++) {
covariance[i * n + i] = 1.0;
}
return this.wasmModule.monte_carlo_simulation(
portfolio,
covariance,
scenarios,
horizon,
this.randomSeed
);
}
// Fallback: JavaScript Monte Carlo
const results = this.calculator.monteCarloSimulation(
Array.from(portfolio),
scenarios,
horizon,
this.randomSeed
);
return new Float32Array(results);
}
/**
* Calculate complete risk metrics for a portfolio
*/
async calculateRiskMetrics(
holdings: PortfolioHolding[],
confidenceLevel: number = 0.95,
horizon: TimeHorizon = '1d'
): Promise<RiskMetrics> {
// Generate synthetic returns for demonstration
// In production, fetch actual historical data
const returns = this.generateSyntheticReturns(holdings.length, 252);
const prices = this.returnsToPrice(returns, 100);
const horizonDays = this.getHorizonDays(horizon);
const scaledReturns = this.scaleReturns(returns, horizonDays);
const returnsArray = new Float32Array(scaledReturns);
return {
var: await this.calculateVar(returnsArray, confidenceLevel),
cvar: await this.calculateCvar(returnsArray, confidenceLevel),
sharpe: this.calculator.calculateSharpe(returns),
sortino: this.calculator.calculateSortino(returns),
maxDrawdown: this.calculator.calculateMaxDrawdown(prices),
volatility: this.calculator.calculateVolatility(returns),
confidenceLevel,
horizon,
};
}
/**
* Generate calculation proof for audit
*/
generateCalculationProof(
input: unknown,
output: unknown,
_modelVersion: string = '1.0.0'
): RiskCalculationProof {
const inputHash = this.hashObject(input);
const outputHash = this.hashObject(output);
return {
inputHash,
modelChecksum: this.getModelChecksum(),
randomSeed: this.randomSeed.toString(),
outputHash,
signature: this.signProof(inputHash, outputHash),
timestamp: new Date().toISOString(),
};
}
/**
* Cleanup resources
*/
destroy(): void {
this.marketDataCache.returns.clear();
this.marketDataCache.prices.clear();
this.initialized = false;
}
// Private methods
private async resolveWasmPath(): Promise<string | null> {
try {
const module = await import(/* webpackIgnore: true */ 'ruvector-economy-wasm' as string) as { default?: string };
return module.default ?? null;
} catch {
return null;
}
}
private async loadWasmModule(wasmPath: string): Promise<EconomyWasmModule> {
const module = await import(wasmPath);
await module.default();
return module as EconomyWasmModule;
}
private generateSyntheticReturns(_numAssets: number, numDays: number): number[] {
// Generate synthetic returns for demonstration
const returns: number[] = [];
const dailyMean = 0.0004; // ~10% annual
const dailyVol = 0.012; // ~19% annual
for (let i = 0; i < numDays; i++) {
// Box-Muller for normal distribution
const u1 = Math.random();
const u2 = Math.random();
const z = Math.sqrt(-2 * Math.log(u1)) * Math.cos(2 * Math.PI * u2);
returns.push(dailyMean + dailyVol * z);
}
return returns;
}
private returnsToPrice(returns: number[], startPrice: number): number[] {
const prices: number[] = [startPrice];
let currentPrice = startPrice;
for (const ret of returns) {
currentPrice *= (1 + ret);
prices.push(currentPrice);
}
return prices;
}
private getHorizonDays(horizon: TimeHorizon): number {
switch (horizon) {
case '1d': return 1;
case '1w': return 5;
case '1m': return 21;
case '3m': return 63;
case '1y': return 252;
default: return 1;
}
}
// eslint-disable-next-line @typescript-eslint/no-unused-vars
private scaleReturns(returns: number[], days: number): number[] {
if (days === 1) return returns;
// Aggregate returns over the horizon
const scaled: number[] = [];
for (let i = 0; i <= returns.length - days; i += days) {
let cumReturn = 0;
for (let j = 0; j < days && i + j < returns.length; j++) {
cumReturn += returns[i + j]!;
}
scaled.push(cumReturn);
}
return scaled;
}
private hashObject(obj: unknown): string {
const str = JSON.stringify(obj);
let hash = 0;
for (let i = 0; i < str.length; i++) {
const char = str.charCodeAt(i);
hash = ((hash << 5) - hash) + char;
hash = hash & hash;
}
return Math.abs(hash).toString(16).padStart(8, '0');
}
private getModelChecksum(): string {
// In production, compute actual model checksum
return 'economy-bridge-v1-' + this.hashObject(this.config);
}
private signProof(inputHash: string, outputHash: string): string {
// In production, use cryptographic signing
return this.hashObject({ inputHash, outputHash, seed: this.randomSeed });
}
}
/**
* Create a new economy bridge instance
*/
export function createEconomyBridge(config?: Partial<EconomyConfig>, logger?: Logger): FinancialEconomyBridge {
return new FinancialEconomyBridge(config, logger);
}
export default FinancialEconomyBridge;