diff --git a/vnpy/pricing/bs.py b/vnpy/pricing/bs.py
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+++ b/vnpy/pricing/bs.py
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+# encoding: UTF-8
+
+'''
+Black-Scholes期权定价模型，主要用于标的物为股票的欧式期权的定价
+
+变量说明
+s：标的物股票价格
+k：行权价
+r：无风险利率
+t：剩余到期时间（年）
+v：隐含波动率
+cp：期权类型，+1/-1对应call/put
+price：期权价格
+
+出于开发演示的目的，本文件中的希腊值计算基于简单数值差分法，
+运算效率一般，实盘中建议使用更高速的算法。
+
+本文件中的希腊值计算结果没有采用传统的模型价格数值，而是采用
+了实盘交易中更为实用的百分比变动数值，具体定义如下
+delta：当f变动1%时，price的变动
+gamma：当f变动1%时，delta的变动
+theta：当t变动1天时，price的变动（国内交易日每年240天）
+vega：当v涨跌1个点时，price的变动（如从16%涨到17%）
+'''
+
+from __future__ import division
+
+from scipy import stats
+from math import (log, pow, sqrt, exp)
+
+cdf = stats.norm.cdf
+
+
+# 计算希腊值和隐含波动率时用的参数
+STEP_CHANGE = 0.001
+STEP_UP = 1 + STEP_CHANGE
+STEP_DOWN = 1 - STEP_CHANGE
+STEP_DIFF = STEP_CHANGE * 2
+
+DX_TARGET = 0.00001
+
+
+#----------------------------------------------------------------------
+def calculatePrice(s, k, r, t, v, cp):
+    """计算期权价格"""
+    # 如果波动率为0，则直接返回期权空间价值
+    if v <= 0:
+        return max(0, cp * (s - k))
+
+    d1 = (log(s / k) + (r + 0.5 * pow(v, 2)) * t) / (v * sqrt(t))
+    d2 = d1 - v * sqrt(t)
+    price = cp * (s * cdf(cp * d1) - k * cdf(cp * d2) * exp(-r * t))
+    return price
+
+#----------------------------------------------------------------------
+def calculateDelta(s, k, r, t, v, cp):
+    """计算Delta值"""
+    price1 = calculatePrice(s*STEP_UP, k, r, t, v, cp)
+    price2 = calculatePrice(s*STEP_DOWN, k, r, t, v, cp)
+    delta = (price1 - price2) / (s * STEP_DIFF) * (s * 0.01)
+    return delta
+
+#----------------------------------------------------------------------
+def calculateGamma(s, k, r, t, v, cp):
+    """计算Gamma值"""
+    delta1 = calculateDelta(s*STEP_UP, k, r, t, v, cp)
+    delta2 = calculateDelta(s*STEP_DOWN, k, r, t, v, cp)
+    gamma = (delta1 - delta2) / (s * STEP_DIFF) * pow(s, 2) * 0.0001
+    return gamma
+
+#----------------------------------------------------------------------
+def calculateTheta(s, k, r, t, v, cp):
+    """计算Theta值"""
+    price1 = calculatePrice(s, k, r, t*STEP_UP, v, cp)
+    price2 = calculatePrice(s, k, r, t*STEP_DOWN, v, cp)
+    theta = -(price1 - price2) / (t * STEP_DIFF * 240)
+    return theta
+
+#----------------------------------------------------------------------
+def calculateVega(s, k, r, t, v, cp):
+    """计算Vega值"""
+    vega = calculateOriginalVega(s, k, r, t, v, cp) / 100
+    return vega
+
+#----------------------------------------------------------------------
+def calculateOriginalVega(s, k, r, t, v, cp):
+    """计算原始vega值"""    
+    price1 = calculatePrice(s, k, r, t, v*STEP_UP, cp)
+    price2 = calculatePrice(s, k, r, t, v*STEP_DOWN, cp)
+    vega = (price1 - price2) / (v * STEP_DIFF)
+    return vega
+
+#----------------------------------------------------------------------
+def calculateGreeks(s, k, r, t, v, cp):
+    """计算期权的价格和希腊值"""
+    price = calculatePrice(s, k, r, t, v, cp)
+    delta = calculateDelta(s, k, r, t, v, cp)
+    gamma = calculateGamma(s, k, r, t, v, cp)
+    theta = calculateTheta(s, k, r, t, v, cp)
+    vega = calculateVega(s, k, r, t, v, cp)
+    return price, delta, gamma, theta, vega
+
+#----------------------------------------------------------------------
+def calculateImpv(price, s, k, r, t, cp):
+    """计算隐含波动率"""
+    # 检查期权价格必须为正数
+    if price <= 0:
+        return 0
+    
+    # 检查期权价格是否满足最小价值（即到期行权价值）
+    meet = False
+    
+    if cp == 1 and (price > (s - k) * exp(-r * t)):
+        meet = True
+    elif cp == -1 and (price > k * exp(-r * t) - s):
+        meet = True
+    
+    # 若不满足最小价值，则直接返回0
+    if not meet:
+        return 0
+    
+    # 采用Newton Raphson方法计算隐含波动率
+    v = 0.3     # 初始波动率猜测
+    
+    for i in range(50):
+        # 计算当前猜测波动率对应的期权价格和vega值
+        p = calculatePrice(s, k, r, t, v, cp)
+        
+        vega = calculateOriginalVega(s, k, r, t, v, cp)
+        
+        # 如果vega过小接近0，则直接返回
+        if not vega:
+            break
+        
+        # 计算误差
+        dx = (price - p) / vega
+        
+        # 检查误差是否满足要求，若满足则跳出循环
+        if abs(dx) < DX_TARGET:
+            break
+        
+        # 计算新一轮猜测的波动率
+        v += dx
+        
+    # 检查波动率计算结果非负
+    if v <= 0:
+        return 0
+    
+    # 保留4位小数
+    v = round(v, 4)
+    
+    return v
+    
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