Question

求高手翻译啊，急！！！！

Figure 2.3 shows how the trading strategy performs over several trials.
Clearly the strategy is profitable, but how the strategy performs in comparison to the S&P index has yet to be seen. Not surprisingly different trials of the strategy yield different results. This will be especially true for lower sample size values. This is because low sample sizes allow a greater diversity of stocks into the portfolio. Though profitable, the wide variation in expected returns is enough to deter investors. To remedy this we increase the sample size to narrow the range of possible stocks that may comprise our portfolio. The results are seen below in figure 2.4, 2.5 & 2.6. As expected, variation in expected returns shrinks as a result. Additionally, expected returns also increases as a result of this change. The increased sample size has decreased the randomness of the portfolio constituents and

makes the portfolio more reliant on the true extreme value distribution.
The increase in returns suggests three things. The first is that higher sample sizes yield higher returns. The second is that higher samples sizes yield lower variation in expected returns. And finally, that this trading strategy is significantly better than a random portfolio of stocks. However, the opposite extreme for sample size is displayed in figure 2.7. Here the sample size is 300. The result is a significant drop in returns. We conclude that at either extremes of sample size, returns decline. Thus there is some sample size within this range that maximizes returns. According to our trials, this optimal sample size is 100. Next we investigate the effect of changing the long/short ratio. As a general rule more weight is typically given to long positions based on the reasoning that stock prices normally trend upwards. In the previous exercise the long/short ratio was 9, that is 90% of the portfolio was invested in long positions and the last 10% in short positions. Figure 2.8 demonstrates that

Answer 1

图2.3展示了交易策略执行几个试验。
清晰的策略是有利可图的,但是如何执行的策略与标准普尔指数还有待观察。不足为奇的试验产量不同策略不同的结果。这将是尤其是对于降低样品的尺寸值。这是由于样本数低允许一个更加多样化的股票的投资组合。虽然有利可图,差异很大预期收益足以吓阻的投资者。为了弥补这个不足,我们增加样本大小缩小可能的范围的股票,可以由我们的投资组合。结果在图如图2.4、2.5和2.6。正如人们所预料的那样,在预期收益缩变化的结果。此外,预期收益也会增加由于这种改变。增加样本容量下降的随机性成分、组合

使投资更加依赖真正的极值分布。
建议增加收益的三件事。首先,更高的样本数产量更高的回报。第二个是更高产量降低样品尺寸变化对预期收益。最后,这种交易策略显著优于随机组合的股票。然而,另一为样本大小显示在图2.7。这里的样本大小是300。结果是一个显著下降的回报。我们认为在任何一个极端的样本量,返回下降。因此有一些样本大小的范围之内,最大限度的回报。根据我们的实验,该最优样本大小是100。接下来我们的影响进行长焊缝/短改变的比率。作为一个通用规则更重要的是给仓位通常基于推理的股票价格趋势向上通常。在前一项练习长焊缝/短的,比9的90%投资于长期的投资组合的最后10%位置和短的位置。图2.8显示

Answer 2

图2.3显示了交易策略进行了多次试验。
显然，策略是有利可图的，但如何在战略相比，标准普尔指数的表现还有待观察。毫不奇怪的策略不同的试验产生不同的结果。这将特别适用于较低的采样大小值。这是因为低样本量允许进入的股票投资组合更多元化。虽然盈利，在预期收益的巨大差异，就足以阻止投资者。为了解决这个问题，我们增加样本规模缩小的可能，可能包括我们的股票投资组合的范围。结果看到下面的图2.4，2.5和2.6。正如预期，在预期收益的变化，结果缩小。此外，预期收益也增加了作为这种变化的结果。增加的样本量已减少了随意性和投资组合成分

使投资组合更真实的极值分布的依赖。
在返回的增加表明三件事情。首先，样本量较高的回报率更高。二是高规格的样品在预期回报率较低的变化。最后，这种交易策略是显着高于随机的股票投资组合更好。然而，相反的极端样本大小显示在图2.7。在这里，样本大小为300。其结果是在收益大幅下降。我们得出结论，无论是在极端的样本量，效益下降。因此，有一些在此范围内的样本大小，最大化的回报。根据我们的试验中，这个最佳的样本量为100。接下来我们探讨改变长/短率的影响。作为一般规则更多的重量通常给予的理由是，股票价格向上的趋势，通常长职务。在前面的练习长/短的比例为9，即90％是投资组合中多头头寸和空头头寸在过去的10％。图2.8表明，
朗读

Answer 3

急还不给点分？还让别人给你免费翻译？

Answer 4

这玩意谁能用时间翻译啊。。。