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So first, I choose a volatility randomly, from some distribution of possible volatilities 2 from to, in this case, 0.2.
来决定的一个值，所以首先我先随机选择一个浮动值，从可能的浮动值中的分布进行选择,在这个例子中就是0。
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If I wanted every stock to have the same volatility, I could just do that, if you will, at the time I wrote my program.
如果我希望每只股票的浮动值都相同，在我编写程序的时候，如果你愿意的话，我会这么做。
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Systematically, investors are buying after things have gone up, selling after they've gone down, and the problem is most severe in those funds that show the greatest volatility.
投资者都一窝蜂似的,上涨之后才买进,下跌之后才卖出,对于波动最大的那些基金,问题更严重
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There's a lot of volatility in exchange rates.
汇率的波动毫无定数可言。
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uniform So here, I'm going to look at the thing random dot uniform, for example, between minus volatility and plus volatility.
所以在这里，我会看到random。,比方说，在-浮动性值+浮动值之间。
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And then I could also do a Gaussian one here, with the mean of and the standard deviation of volatility divided by 2.
然后我在这里再写一个高斯分布的函数，它的浮动值的平均值和,标准偏差值都除了2。
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With a different volatility for the stocks because that was also selected randomly, plus some market bias.
或者均匀分布的一个随机值,因为数值选择上的随机性，再加上市场偏好。
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minus volatility to plus volatility it will return any value in here.
浮动值到+浮动值之间等概率地,去返回一个值。
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But notice the previous line, where I am computing volatility.
但是请注意前面这个语句，我用这个语句计算了浮动值。
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And then I'll create this function, d1 this distribution d 1, which will, whenever I call it, give me a random, a uniformly selected value between minus and plus volatility.
然后我会创建这个函数，这个概率分布，每次我调用这个函数的时候，他会给我返回一个随机的，按照均匀分布,从正负浮动值之间选择的值。
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