#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ XTZH AI 定价引擎 v2.0 ======================= NAC 宪法合规定价模型 核心公式: P_XTZH (USD) = (w_fx × V_fx + w_au × V_au + w_com × V_com) / 10000 三层价值(均以 USD 计,通过 SDR 换算): V_fx = 1 SDR 的 USD 等价值(货币篮子加权) V_au = 黄金 SDR 等价价值 × XTZH 黄金份额 V_com = 大宗商品 SDR 等价价值加权均值 × XTZH 商品份额 动态权重(VIX/DXY 作为调节杠杆,不参与价格计算): 基准:w_fx=4000, w_au=1000, w_com=5000(基点,总和=10000) VIX 高 → w_au ↑,w_com ↓(避险模式) DXY 高 → w_fx 微调 约束:w_au ∈ [500, 2000],w_fx ∈ [2000, 6000] 作者:NAC 系统 版本:2.0.0 """ import json import logging import time import urllib.request from datetime import datetime, timezone from http.server import BaseHTTPRequestHandler, HTTPServer # ============================================================================ # 日志配置 # ============================================================================ logging.basicConfig( level=logging.INFO, format='%(asctime)s [XTZH-PRICING-v2] %(levelname)s %(message)s', handlers=[ logging.StreamHandler(), logging.FileHandler('/opt/nac/xtzh-pricing/xtzh_pricing.log', encoding='utf-8') ] ) logger = logging.getLogger('xtzh-pricing') # ============================================================================ # NAC 宪法常量(来自 constants.rs) # ============================================================================ # 基准权重(基点,总和 = 10000) W_FX_BASE = 4000 # 货币层基准权重 40% W_AU_BASE = 1000 # 黄金层基准权重 10% W_COM_BASE = 5000 # 商品层基准权重 50% WEIGHT_SUM = 10000 # 权重总和约束 # 黄金层权重动态范围 W_AU_MIN = 500 # 最低 5% W_AU_MAX = 2000 # 最高 20% # 黄金信任锚覆盖率 125% GOLD_TRUST_ANCHOR_COVERAGE = 1.25 # SDR 货币篮子权重(IMF 2022-2026) SDR_BASKET = { 'USD': 0.4332, # 43.32% 'EUR': 0.2923, # 29.23% 'CNY': 0.1059, # 10.59% 'JPY': 0.0784, # 7.84% 'GBP': 0.0802, # 8.02% } # XTZH 黄金份额:每 1 XTZH 对应的黄金盎司数 # 基于 NAC 宪法:黄金储备覆盖率 125%,黄金层权重 10% # 设定:1 XTZH 对应 0.0005 盎司黄金(历史 SDR 黄金等价) XTZH_GOLD_SHARE_OZ = 0.0005 # 盎司/XTZH # 大宗商品篮子权重(商品层内部权重,总和 = 1.0) COMMODITY_BASKET = { 'wti_oil': 0.30, # WTI 原油 30% 'copper': 0.20, # 铜 20% 'wheat': 0.12, # 小麦 12% 'corn': 0.10, # 玉米 10% 'soybean': 0.10, # 大豆 10% 'natural_gas':0.10, # 天然气 10% 'silver': 0.08, # 白银 8% } # 商品基准价格(USD,用于计算 SDR 等价份额) # 每单位商品对应的 SDR 等价基准 COMMODITY_BASE_PRICES = { 'wti_oil': 75.0, # USD/桶 'copper': 4.2, # USD/磅 'wheat': 550.0, # USD/蒲式耳(美分/蒲式耳 ÷ 100 × 5000) 'corn': 450.0, # USD/蒲式耳 'soybean': 1200.0, # USD/蒲式耳 'natural_gas': 3.0, # USD/百万英热 'silver': 25.0, # USD/盎司 } # ============================================================================ # 数据缓存 # ============================================================================ _cache = { 'data': None, 'timestamp': 0, 'ttl': 300 # 5 分钟缓存 } # ============================================================================ # 数据获取函数 # ============================================================================ def fetch_url(url, timeout=10): """获取 URL 内容,返回解析后的 JSON""" try: req = urllib.request.Request(url, headers={ 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36', 'Accept': 'application/json' }) with urllib.request.urlopen(req, timeout=timeout) as resp: return json.loads(resp.read().decode('utf-8')) except Exception as e: logger.warning("获取 " + url + " 失败: " + str(e)) return None def fetch_yahoo_price(symbol): """从 Yahoo Finance 获取期货/指数价格""" url = "https://query1.finance.yahoo.com/v8/finance/chart/" + symbol + "?interval=1d&range=1d" data = fetch_url(url) if data: try: return float(data['chart']['result'][0]['meta']['regularMarketPrice']) except Exception: pass return None def fetch_sdr_rates(): """ 获取 SDR 汇率(1 XDR = ? 各货币) 返回:{'USD': 1.3745, 'EUR': 1.1663, 'CNY': 9.4448, 'GBP': 1.0171, 'JPY': 215.27} """ data = fetch_url("https://open.er-api.com/v6/latest/XDR") if data and data.get('rates'): r = data['rates'] result = { 'USD': r.get('USD', 1.3745), 'EUR': r.get('EUR', 1.1663), 'GBP': r.get('GBP', 1.0171), 'JPY': r.get('JPY', 215.27), 'CNY': r.get('CNY', 9.4448), 'updated': data.get('time_last_update_utc', '') } logger.info("SDR汇率: 1 SDR = USD:" + str(round(result['USD'],4)) + " EUR:" + str(round(result['EUR'],4)) + " CNY:" + str(round(result['CNY'],4))) return result # 备用值(2026-02-26 实测) logger.warning("SDR汇率获取失败,使用备用数据") return {'USD': 1.3745, 'EUR': 1.1663, 'GBP': 1.0171, 'JPY': 215.27, 'CNY': 9.4448, 'updated': 'fallback'} def fetch_gold_price(): """ 获取黄金价格(USD/盎司) 主源:Yahoo Finance GC=F 备源:Binance PAXG """ # 主源 price = fetch_yahoo_price("GC=F") if price and price > 0: logger.info("黄金价格 (Yahoo GC=F): $" + str(price) + "/oz") return price, "Yahoo Finance GC=F" # 备源:Binance PAXG data = fetch_url("https://api.binance.com/api/v3/ticker/price?symbol=PAXGUSDT") if data and data.get('price'): price = float(data['price']) logger.info("黄金价格 (Binance PAXG): $" + str(price) + "/oz") return price, "Binance PAXG" logger.warning("黄金价格获取失败,使用备用值 $2650") return 2650.0, "fallback" def fetch_commodity_prices(): """ 获取大宗商品价格(USD) 返回:{'wti_oil': 65.53, 'copper': 6.023, 'wheat': 569.0, ...} """ symbols = { 'wti_oil': 'CL=F', 'copper': 'HG=F', 'wheat': 'ZW=F', 'corn': 'ZC=F', 'soybean': 'ZS=F', 'natural_gas': 'NG=F', 'silver': 'SI=F', } prices = {} for name, sym in symbols.items(): price = fetch_yahoo_price(sym) if price and price > 0: prices[name] = price logger.info("商品价格 " + name + " (" + sym + "): " + str(price)) else: prices[name] = COMMODITY_BASE_PRICES[name] logger.warning("商品价格 " + name + " 获取失败,使用基准值 " + str(COMMODITY_BASE_PRICES[name])) return prices def fetch_risk_indicators(): """ 获取风险调节指标(仅用于动态权重调节,不参与价格计算) VIX:恐慌指数 DXY:美元指数 """ vix = fetch_yahoo_price("^VIX") dxy = fetch_yahoo_price("DX-Y.NYB") if not dxy: dxy = fetch_yahoo_price("DX=F") result = { 'vix': vix if vix else 20.0, 'dxy': dxy if dxy else 104.0, } logger.info("风险指标 (权重杠杆): VIX=" + str(result['vix']) + " DXY=" + str(result['dxy'])) return result # ============================================================================ # 三层价值计算 # ============================================================================ def calc_fx_layer(sdr_rates): """ 货币层价值 V_fx(USD) V_fx = 1 SDR 的 USD 等价值 即:以 IMF SDR 货币篮子权重,加权计算 1 SDR 对应的 USD 价值 由于 SDR/USD 汇率已经是货币篮子的综合结果, 直接取 1 SDR = sdr_rates['USD'] USD """ v_fx = sdr_rates['USD'] # 1 SDR 的 USD 等价值 logger.info("货币层 V_fx = $" + str(round(v_fx, 6)) + " USD (1 SDR)") return v_fx def calc_gold_layer(gold_price_usd, sdr_rates): """ 黄金层价值 V_au(USD) V_au = 黄金 SDR 等价价值 × XTZH 黄金份额 × 黄金信任锚覆盖率 计算步骤: 1. 黄金 SDR 等价价值(USD/oz)= gold_price_usd(直接以 USD 计) 2. 每 1 XTZH 对应 XTZH_GOLD_SHARE_OZ 盎司黄金 3. 黄金层价值 = gold_price_usd × XTZH_GOLD_SHARE_OZ × 1.25(覆盖率) 注意:黄金层权重 10% 已在最终加权公式中体现, 这里计算的是"如果 100% 都是黄金层,每 1 XTZH 值多少 USD" """ # 黄金 SDR 等价(USD/oz) gold_sdr_value = gold_price_usd / sdr_rates['USD'] # 黄金价格的 SDR 等价 # 每 1 XTZH 对应的黄金 SDR 价值(USD) v_au = gold_price_usd * XTZH_GOLD_SHARE_OZ * GOLD_TRUST_ANCHOR_COVERAGE logger.info("黄金层 V_au: 金价=$" + str(round(gold_price_usd,2)) + "/oz × " + str(XTZH_GOLD_SHARE_OZ) + "oz × " + str(GOLD_TRUST_ANCHOR_COVERAGE) + " = $" + str(round(v_au,6)) + " USD") return v_au def calc_commodity_layer(commodity_prices, sdr_rates): """ 商品层价值 V_com(USD) V_com = Σ (商品权重 × 商品价格 SDR 等价 / 基准价格 SDR 等价) × 1 SDR USD 等价 计算步骤: 1. 每种商品的当前价格与基准价格的比值(价格偏离因子) 2. 以商品篮子权重加权求和,得到综合商品价格指数 3. 乘以 1 SDR 的 USD 等价值,得到商品层价值 逻辑:商品层代表"以大宗商品衡量的 1 SDR 购买力" 当商品价格整体上涨时,XTZH 的商品层价值随之上升 """ sdr_in_usd = sdr_rates['USD'] # 计算各商品价格偏离因子(当前价格 / 基准价格) commodity_index = 0.0 detail = {} for name, weight in COMMODITY_BASKET.items(): current_price = commodity_prices.get(name, COMMODITY_BASE_PRICES[name]) base_price = COMMODITY_BASE_PRICES[name] price_ratio = current_price / base_price # 价格偏离因子 contribution = weight * price_ratio commodity_index += contribution detail[name] = { 'current': round(current_price, 4), 'base': base_price, 'ratio': round(price_ratio, 4), 'weight': weight, 'contribution': round(contribution, 6) } logger.info(" 商品 " + name + ": $" + str(round(current_price,4)) + " / 基准$" + str(base_price) + " = " + str(round(price_ratio,4)) + " × " + str(weight) + " = " + str(round(contribution,6))) # 商品层价值 = 1 SDR USD 等价 × 综合商品价格指数 v_com = sdr_in_usd * commodity_index logger.info("商品层 V_com: 综合指数=" + str(round(commodity_index,6)) + " × 1SDR=$" + str(round(sdr_in_usd,4)) + " = $" + str(round(v_com,6)) + " USD") return v_com, commodity_index, detail # ============================================================================ # 动态权重计算(VIX/DXY 作为调节杠杆) # ============================================================================ def calc_dynamic_weights(risk_indicators): """ 动态权重计算 VIX 和 DXY 作为权重调节杠杆,不参与价格计算 规则: - VIX > 30:高风险,黄金权重上调(避险需求增加) - VIX < 15:低风险,黄金权重下调 - DXY > 110:美元强势,货币层权重微减(美元强则其他货币弱) - DXY < 95:美元弱势,货币层权重微增 约束: - w_au ∈ [500, 2000](5% ~ 20%) - w_fx ∈ [2000, 6000](20% ~ 60%) - w_fx + w_au + w_com = 10000 """ vix = risk_indicators.get('vix', 20.0) dxy = risk_indicators.get('dxy', 104.0) # 1. 黄金权重调节(VIX 杠杆) if vix > 30: # 高风险:每超过 30 增加 30bp,最高 2000bp w_au = min(W_AU_MAX, W_AU_BASE + int((vix - 30) * 30)) elif vix < 15: # 低风险:每低于 15 减少 25bp,最低 500bp w_au = max(W_AU_MIN, W_AU_BASE - int((15 - vix) * 25)) else: w_au = W_AU_BASE # 2. 货币层权重调节(DXY 杠杆) if dxy > 110: fx_adj = -200 # 美元强势,货币层权重减 200bp elif dxy < 95: fx_adj = +200 # 美元弱势,货币层权重增 200bp else: # 线性插值:DXY 在 95-110 之间线性调整 fx_adj = int((104.0 - dxy) * 15) w_fx = W_FX_BASE + fx_adj w_fx = max(2000, min(6000, w_fx)) # 3. 商品层补足剩余权重 w_com = WEIGHT_SUM - w_fx - w_au w_com = max(2000, min(7000, w_com)) # 4. 归一化(确保总和精确等于 10000) total = w_fx + w_au + w_com if total != WEIGHT_SUM: w_com += (WEIGHT_SUM - total) logger.info("动态权重 (VIX=" + str(round(vix,1)) + " DXY=" + str(round(dxy,1)) + "): FX=" + str(w_fx/100) + "% AU=" + str(w_au/100) + "% COM=" + str(w_com/100) + "%") return w_fx, w_au, w_com # ============================================================================ # XTZH AI 定价引擎(核心函数) # ============================================================================ def calculate_xtzh_mint_price(): """ 计算 XTZH 当日铸造价格(统一价格) 公式: P_XTZH (USD) = (w_fx × V_fx + w_au × V_au + w_com × V_com) / 10000 其中: V_fx = 货币层价值(1 SDR 的 USD 等价值) V_au = 黄金层价值(黄金 SDR 等价 × XTZH 黄金份额 × 覆盖率) V_com = 商品层价值(大宗商品 SDR 等价加权均值) w_fx, w_au, w_com = 动态权重(VIX/DXY 调节,总和 10000bp) 返回:统一铸造价格(USD/XTZH)及详细计算过程 """ logger.info("=" * 60) logger.info("开始计算 XTZH 当日铸造价格 v2.0") logger.info("=" * 60) # ── 步骤 1:获取实时数据 ────────────────────────────────── sdr_rates = fetch_sdr_rates() gold_price_usd, gold_source = fetch_gold_price() commodity_prices = fetch_commodity_prices() risk_indicators = fetch_risk_indicators() # ── 步骤 2:计算三层价值 ────────────────────────────────── logger.info("--- 计算三层价值 ---") v_fx = calc_fx_layer(sdr_rates) v_au = calc_gold_layer(gold_price_usd, sdr_rates) v_com, commodity_index, commodity_detail = calc_commodity_layer(commodity_prices, sdr_rates) # ── 步骤 3:计算动态权重 ────────────────────────────────── logger.info("--- 计算动态权重 (VIX/DXY 杠杆) ---") w_fx, w_au, w_com = calc_dynamic_weights(risk_indicators) # ── 步骤 4:加权计算最终统一铸造价格 ───────────────────── price_usd = (w_fx * v_fx + w_au * v_au + w_com * v_com) / WEIGHT_SUM # ── 步骤 5:换算各货币价格 ──────────────────────────────── sdr_in_usd = sdr_rates['USD'] price_sdr = price_usd / sdr_in_usd # XTZH/SDR price_cny = price_usd * sdr_rates['CNY'] / sdr_in_usd price_eur = price_usd * sdr_rates['EUR'] / sdr_in_usd price_gbp = price_usd * sdr_rates['GBP'] / sdr_in_usd price_jpy = price_usd * sdr_rates['JPY'] / sdr_in_usd # ── 步骤 6:铸造比例 ────────────────────────────────────── mint_ratio_usd = 1.0 / price_usd # 1 USD 可铸造多少 XTZH # ── 步骤 7:黄金储备支撑值 ─────────────────────────────── gold_backing_per_xtzh = gold_price_usd * XTZH_GOLD_SHARE_OZ * GOLD_TRUST_ANCHOR_COVERAGE logger.info("=" * 60) logger.info("XTZH 铸造价格计算完成") logger.info(" 统一价格: $" + str(round(price_usd,6)) + " USD = " + str(round(price_sdr,6)) + " SDR") logger.info(" 权重: FX=" + str(w_fx/100) + "% AU=" + str(w_au/100) + "% COM=" + str(w_com/100) + "%") logger.info(" 三层价值: V_fx=$" + str(round(v_fx,4)) + " V_au=$" + str(round(v_au,4)) + " V_com=$" + str(round(v_com,4))) logger.info("=" * 60) return { # ── 核心输出:统一铸造价格 ── "price_usd": round(price_usd, 6), # 统一铸造价格(USD) "price_sdr": round(price_sdr, 6), # SDR 等价 "price_cny": round(price_cny, 6), # 人民币等价 "price_eur": round(price_eur, 6), # 欧元等价 "price_gbp": round(price_gbp, 6), # 英镑等价 "price_jpy": round(price_jpy, 4), # 日元等价 # ── 铸造比例 ── "mint_ratio_usd": round(mint_ratio_usd, 6), # 1 USD 可铸造 XTZH 数量 # ── 黄金储备支撑 ── "gold_backing_usd": round(gold_backing_per_xtzh, 6), # 每 1 XTZH 的黄金支撑值(USD) # ── 三层价值(透明计算过程) ── "layers": { "fx_layer": { "value_usd": round(v_fx, 6), "weight_bp": w_fx, "weight_pct": round(w_fx / 100, 2), "description": "货币层:1 SDR 的 USD 等价值", "sdr_usd_rate": round(sdr_in_usd, 6) }, "gold_layer": { "value_usd": round(v_au, 6), "weight_bp": w_au, "weight_pct": round(w_au / 100, 2), "description": "黄金层:黄金 SDR 等价 × XTZH 黄金份额 × 125% 覆盖率", "gold_price_usd": round(gold_price_usd, 2), "gold_source": gold_source, "xtzh_gold_share_oz": XTZH_GOLD_SHARE_OZ, "coverage_ratio": GOLD_TRUST_ANCHOR_COVERAGE }, "commodity_layer": { "value_usd": round(v_com, 6), "weight_bp": w_com, "weight_pct": round(w_com / 100, 2), "description": "商品层:大宗商品 SDR 等价加权均值", "commodity_index": round(commodity_index, 6), "commodities": commodity_detail } }, # ── 权重调节杠杆(风险指标) ── "weight_levers": { "vix": round(risk_indicators.get('vix', 20.0), 2), "dxy": round(risk_indicators.get('dxy', 104.0), 3), "description": "VIX/DXY 仅作为动态权重调节杠杆,不参与价格计算" }, # ── SDR 汇率 ── "sdr_rates": { "usd": round(sdr_rates['USD'], 6), "eur": round(sdr_rates['EUR'], 6), "cny": round(sdr_rates['CNY'], 6), "gbp": round(sdr_rates['GBP'], 6), "jpy": round(sdr_rates['JPY'], 4), "updated": sdr_rates.get('updated', '') }, # ── 模型信息 ── "model_info": { "version": "2.0.0", "algorithm": "NAC Constitutional Weighted Pricing v2", "formula": "P_XTZH = (w_fx×V_fx + w_au×V_au + w_com×V_com) / 10000", "gold_trust_anchor_coverage": "125%", "weight_constraint": "w_fx + w_au + w_com = 10000bp", "gold_weight_range": "5.00% - 20.00%", "commodity_basket": "WTI(30%) + Cu(20%) + Wheat(12%) + Corn(10%) + Soy(10%) + NG(10%) + Ag(8%)" }, "timestamp": datetime.now(timezone.utc).isoformat(), "next_update": "每5分钟更新一次" } # ============================================================================ # 缓存管理 # ============================================================================ def get_cached_price(): """获取缓存的价格数据(5分钟 TTL)""" now = time.time() if _cache['data'] is None or (now - _cache['timestamp']) > _cache['ttl']: logger.info("缓存过期,重新计算 XTZH 价格...") try: _cache['data'] = calculate_xtzh_mint_price() _cache['timestamp'] = now except Exception as e: logger.error("价格计算失败: " + str(e)) if _cache['data'] is None: # 返回基础备用值 _cache['data'] = { "price_usd": 1.3745, "price_sdr": 1.0, "price_cny": 9.4448, "price_eur": 1.1663, "error": str(e), "timestamp": datetime.now(timezone.utc).isoformat() } return _cache['data'] # ============================================================================ # HTTP 服务器 # ============================================================================ class XTZHPricingHandler(BaseHTTPRequestHandler): def log_message(self, format, *args): logger.info("HTTP " + str(args[0]) + " " + str(args[1]) + " " + str(args[2])) def send_cors_headers(self): self.send_header('Access-Control-Allow-Origin', '*') self.send_header('Access-Control-Allow-Methods', 'GET, OPTIONS') self.send_header('Access-Control-Allow-Headers', 'Content-Type, Authorization') self.send_header('Content-Type', 'application/json; charset=utf-8') def do_OPTIONS(self): self.send_response(200) self.send_cors_headers() self.end_headers() def do_GET(self): path = self.path.split('?')[0] if path == '/health': self.send_response(200) self.send_cors_headers() self.end_headers() resp = json.dumps({ "status": "ok", "service": "xtzh-pricing", "version": "2.0.0", "algorithm": "NAC Constitutional Weighted Pricing v2" }) self.wfile.write(resp.encode()) elif path in ['/price', '/api/xtzh/price', '/api/v1/xtzh/price']: data = get_cached_price() self.send_response(200) self.send_cors_headers() self.end_headers() resp = json.dumps({"success": True, "data": data}, ensure_ascii=False) self.wfile.write(resp.encode('utf-8')) elif path in ['/price/simple', '/api/xtzh/price/simple']: # 简化版:只返回统一铸造价格和各货币等价 data = get_cached_price() simple = { "price_usd": data.get("price_usd"), "price_sdr": data.get("price_sdr"), "price_cny": data.get("price_cny"), "price_eur": data.get("price_eur"), "price_gbp": data.get("price_gbp"), "price_jpy": data.get("price_jpy"), "mint_ratio_usd": data.get("mint_ratio_usd"), "gold_backing_usd": data.get("gold_backing_usd"), "gold_price_usd": data.get("layers", {}).get("gold_layer", {}).get("gold_price_usd"), "weights": { "fx": data.get("layers", {}).get("fx_layer", {}).get("weight_pct"), "au": data.get("layers", {}).get("gold_layer", {}).get("weight_pct"), "com": data.get("layers", {}).get("commodity_layer", {}).get("weight_pct"), }, "timestamp": data.get("timestamp") } self.send_response(200) self.send_cors_headers() self.end_headers() resp = json.dumps({"success": True, "data": simple}, ensure_ascii=False) self.wfile.write(resp.encode('utf-8')) elif path in ['/price/refresh', '/api/xtzh/price/refresh']: # 强制刷新缓存 _cache['timestamp'] = 0 data = get_cached_price() self.send_response(200) self.send_cors_headers() self.end_headers() resp = json.dumps({"success": True, "data": data, "refreshed": True}, ensure_ascii=False) self.wfile.write(resp.encode('utf-8')) else: self.send_response(404) self.send_cors_headers() self.end_headers() resp = json.dumps({ "error": "Not found", "endpoints": ["/health", "/price", "/price/simple", "/price/refresh"] }) self.wfile.write(resp.encode()) def run_server(port=8709): """启动 HTTP 服务器""" server = HTTPServer(('0.0.0.0', port), XTZHPricingHandler) logger.info("XTZH AI 定价服务 v2.0 启动,端口: " + str(port)) logger.info("API: http://0.0.0.0:" + str(port) + "/price") logger.info("算法: NAC Constitutional Weighted Pricing v2") logger.info("公式: P_XTZH = (w_fx×V_fx + w_au×V_au + w_com×V_com) / 10000") # 预热缓存 logger.info("预热缓存,首次计算 XTZH 价格...") get_cached_price() server.serve_forever() if __name__ == '__main__': run_server(8709)