Finally,it establishes prediction model and applies it to the stock data. Experimental result indicates that SVM is an effective method for complicated time series prediction.
对股票数据进行建模和预测,结果表明支持向量机对复杂时间序列具有较好的预测效果。
参考来源 - 基于支持向量机的复杂时间序列预测研究 in C·2,447,543篇论文数据,部分数据来源于NoteExpress
Finance获取股票数据。
这里我使用两家公司31天的股票数据。
In this case, I take stock data from a 31-day period for two companies.
因此,股票数据不可能一直是正确的。
This is since 1802-- now how many countries do you think have uninterrupted stock market data since 1802?
西格尔使用的数据始于1802年...,你们想想现在有多少的国家,存有从1802年以来,股票市场的完整数据呢
So in fact, it is the case, if you look at data, and by the way, that's the way I ended up setting a lot of these parameters and playing with it, was comparing what my simulation said to historical stock data.
所以实际上,在这个例子中,如果你看到数据,顺便说一下,这就是我设置很多变量,然后编程的方式,也就是把我的仿真程序得到的结果,和历史股票数据进行比较。
Here is the price-earnings ratio for the U.S. stock market from 1881 to the present-- this is also on that spreadsheet that you have on the website.
这是美国股票市场的市盈率,从1881年至今,这份数据也在网站上的电子数据表上
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