Files
Quantitative-Trading-Platform/static/js/mock-data.js
JamesTang f30bcdc680 feat: Integrated Dashboard v2.0 with LLM-driven Mock Backend
- Promoted prototype dashboard to main app
- Added /api/market-data endpoint
- Implemented market_simulator.py for realistic OHLCV generation
- Updated MoomooClient to serve simulated scenarios
- Wired frontend to backend API
2026-02-07 06:34:19 +08:00

414 lines
12 KiB
JavaScript

/*
* Quantitative Trading Platform - Interactive Mockup
* Mock data generation for charts and displays
*/
// Chart initialization
function initCharts() {
// Initialize Portfolio Chart
initPortfolioChart();
// Initialize Data Quality Chart
initDataQualityChart();
// Initialize Backtest Chart
initBacktestChart();
// Initialize Risk Chart
initRiskChart();
}
// Portfolio Performance Chart
function initPortfolioChart() {
const ctx = document.getElementById('portfolioChart');
if (!ctx) return;
const data = generatePortfolioData();
AppState.charts.portfolioChart = new Chart(ctx, {
type: 'line',
data: {
labels: data.map(d => d.date),
datasets: [{
label: 'Portfolio Value',
data: data.map(d => d.value),
borderColor: '#4caf50',
backgroundColor: 'rgba(76, 175, 80, 0.1)',
fill: true,
tension: 0.4,
pointRadius: 2,
pointHoverRadius: 5
}]
},
options: {
responsive: true,
maintainAspectRatio: false,
plugins: {
legend: {
display: false
},
tooltip: {
mode: 'index',
intersect: false,
callbacks: {
label: function(context) {
return `$${context.parsed.y.toLocaleString()}`;
}
}
}
},
scales: {
x: {
grid: {
color: 'rgba(255, 255, 255, 0.05)'
},
ticks: {
color: '#b0bec5'
}
},
y: {
grid: {
color: 'rgba(255, 255, 255, 0.05)'
},
ticks: {
color: '#b0bec5',
callback: function(value) {
return '$' + (value / 1000).toFixed(0) + 'k';
}
}
}
}
}
});
}
// Data Quality Chart
function initDataQualityChart() {
const ctx = document.getElementById('dataQualityChart');
if (!ctx) return;
const data = generateDataQualityData();
AppState.charts.dataQualityChart = new Chart(ctx, {
type: 'line',
data: {
labels: data.map(d => d.date),
datasets: [
{
label: 'Completeness (%)',
data: data.map(d => d.completeness),
borderColor: '#4caf50',
backgroundColor: 'rgba(76, 175, 80, 0.1)',
fill: true,
tension: 0.4,
yAxisID: 'y'
},
{
label: 'Latency (ms)',
data: data.map(d => d.latency),
borderColor: '#2196f3',
backgroundColor: 'rgba(33, 150, 243, 0.1)',
fill: true,
tension: 0.4,
yAxisID: 'y1'
}
]
},
options: {
responsive: true,
maintainAspectRatio: false,
plugins: {
legend: {
position: 'top',
labels: {
color: '#b0bec5'
}
}
},
scales: {
x: {
grid: {
color: 'rgba(255, 255, 255, 0.05)'
},
ticks: {
color: '#b0bec5'
}
},
y: {
type: 'linear',
display: true,
position: 'left',
min: 80,
max: 100,
grid: {
color: 'rgba(255, 255, 255, 0.05)'
},
ticks: {
color: '#b0bec5',
callback: function(value) {
return value + '%';
}
}
},
y1: {
type: 'linear',
display: true,
position: 'right',
min: 0,
max: 30,
grid: {
drawOnChartArea: false
},
ticks: {
color: '#b0bec5',
callback: function(value) {
return value + 'ms';
}
}
}
}
}
});
}
// Backtest Results Chart
function initBacktestChart() {
const ctx = document.getElementById('backtestChart');
if (!ctx) return;
const data = generateBacktestData();
AppState.charts.backtestChart = new Chart(ctx, {
type: 'line',
data: {
labels: ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec'],
datasets: data.map((strategy, index) => {
const colors = ['#4caf50', '#2196f3', '#9c27b0'];
return {
label: strategy.strategy,
data: strategy.returns,
borderColor: colors[index],
backgroundColor: colors[index] + '20',
fill: false,
tension: 0.4
};
})
},
options: {
responsive: true,
maintainAspectRatio: false,
plugins: {
legend: {
position: 'top',
labels: {
color: '#b0bec5'
}
}
},
scales: {
x: {
grid: {
color: 'rgba(255, 255, 255, 0.05)'
},
ticks: {
color: '#b0bec5'
}
},
y: {
grid: {
color: 'rgba(255, 255, 255, 0.05)'
},
ticks: {
color: '#b0bec5',
callback: function(value) {
return '$' + value.toLocaleString();
}
}
}
}
}
});
}
// Risk Management Chart
function initRiskChart() {
const ctx = document.getElementById('riskChart');
if (!ctx) return;
const data = generateRiskData();
AppState.charts.riskChart = new Chart(ctx, {
type: 'radar',
data: {
labels: data.map(d => d.metric),
datasets: [{
label: 'Risk Metrics',
data: data.map(d => d.values[0]),
backgroundColor: 'rgba(255, 152, 0, 0.2)',
borderColor: 'rgba(255, 152, 0, 1)',
pointBackgroundColor: 'rgba(255, 152, 0, 1)',
pointBorderColor: '#fff',
pointHoverBackgroundColor: '#fff',
pointHoverBorderColor: 'rgba(255, 152, 0, 1)'
}]
},
options: {
responsive: true,
maintainAspectRatio: false,
plugins: {
legend: {
display: false
}
},
scales: {
r: {
angleLines: {
color: 'rgba(255, 255, 255, 0.1)'
},
grid: {
color: 'rgba(255, 255, 255, 0.1)'
},
pointLabels: {
color: '#b0bec5'
},
ticks: {
color: '#b0bec5',
backdropColor: 'transparent'
},
min: 0,
max: 10
}
}
}
});
}
// Update functions for live data
function updatePortfolioChart() {
if (!AppState.charts.portfolioChart) return;
const newData = generatePortfolioData();
AppState.charts.portfolioChart.data.labels = newData.map(d => d.date);
AppState.charts.portfolioChart.data.datasets[0].data = newData.map(d => d.value);
AppState.charts.portfolioChart.update('none');
}
function updateDataQualityChart() {
if (!AppState.charts.dataQualityChart) return;
const newData = generateDataQualityData();
AppState.charts.dataQualityChart.data.labels = newData.map(d => d.date);
AppState.charts.dataQualityChart.data.datasets[0].data = newData.map(d => d.completeness);
AppState.charts.dataQualityChart.data.datasets[1].data = newData.map(d => d.latency);
AppState.charts.dataQualityChart.update('none');
}
function updateBacktestChart() {
if (!AppState.charts.backtestChart) return;
const newData = generateBacktestData();
newData.forEach((strategy, index) => {
AppState.charts.backtestChart.data.datasets[index].data = strategy.returns;
});
AppState.charts.backtestChart.update('none');
}
function updateRiskChart() {
if (!AppState.charts.riskChart) return;
const newData = generateRiskData();
AppState.charts.riskChart.data.datasets[0].data = newData.map(d => d.values[0]);
AppState.charts.riskChart.update('none');
}
// Data generation functions (same as in app.js but exported for use)
function generatePortfolioData() {
const data = [];
let value = 100000;
for (let i = 0; i < 30; i++) {
const date = new Date();
date.setDate(date.getDate() - (30 - i));
const change = (Math.random() - 0.4) * 0.02 * value;
value += change;
data.push({
date: date.toLocaleDateString('en-US', { month: 'short', day: 'numeric' }),
value: Math.max(90000, value)
});
}
return data;
}
function generateDataQualityData() {
const data = [];
for (let i = 0; i < 7; i++) {
const date = new Date();
date.setDate(date.getDate() - (7 - i));
data.push({
date: date.toLocaleDateString('en-US', { weekday: 'short' }),
completeness: 90 + Math.random() * 8,
latency: 5 + Math.random() * 15,
errors: Math.floor(Math.random() * 5)
});
}
return data;
}
function generateBacktestData() {
const strategies = ['Dual Momentum', 'Mean Reversion', 'Pairs Trading'];
const data = [];
strategies.forEach(strategy => {
let returns = 100;
const returnsData = [];
for (let i = 0; i < 12; i++) {
const monthlyReturn = (Math.random() - 0.2) * 0.1;
returns *= (1 + monthlyReturn);
returnsData.push(returns);
}
data.push({
strategy,
returns: returnsData,
sharpe: 0.8 + Math.random() * 1.5,
winRate: 50 + Math.random() * 30
});
});
return data;
}
function generateRiskData() {
const metrics = ['VaR', 'CVaR', 'Max Drawdown', 'Volatility'];
const data = [];
metrics.forEach(metric => {
const values = [];
for (let i = 0; i < 10; i++) {
values.push(Math.random() * 10);
}
data.push({ metric, values });
});
return data;
}
// Export for use in other scripts
window.MockData = {
initCharts,
updatePortfolioChart,
updateDataQualityChart,
updateBacktestChart,
updateRiskChart,
generatePortfolioData,
generateDataQualityData,
generateBacktestData,
generateRiskData
};