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FRM二级
包含FRM二级传统在线课程、通关课程及试题相关提问答疑;
专场人数:1591提问数量:30363
11题跟第6题一样 题目问的不是reject or accept his claim 吗?不应该是reject the null and accept his claim 吗?求解答,很费解
查看试题 已回答An investment manager is given the task of beating a benchmark. Hence the risk should be measured A In terms of loss relative to the initial investment B In terms of loss relative to the expected portfolio value C In terms of loss relative to the benchmark D In terms of loss attributed to the benchmark 老师您好!能举个例子说明一下D选项为什么是绝对衡量指标吗?
查看试题 已回答这道题中说the probability of observing such a large alpha by chance is only 1%,是不是理解成投资者认为极大的超额收益偶然出现的概率只有1%?如果是这样,原假设是不是应该是alpha≠0?
A portfolio manager produced an alpha of 2.5% based on monthly returns over a 6 year period. Under the assumption of a normal distribution, the portfolio manager claims that the probability of observing such a large alpha by chance is only 1%. To test her claim, one would use a t-test using which level of confidence? 老师您好!我想问一下,就是这道题里他说观测到很大的α,是指单尾的1%还是双尾的1%。我认为是单尾的,所以在进行假设检验找临界值的时候,应该找98%的两个临界值。这样两边各留出1%,才能判断原假设:“α=0”是否是正确的。
查看试题 已回答John, a portfolio manager, claims to have consistently produced excessive returns (over and above the benchmark returns) 97.5% of the time due to her skill and not luck. To support her claim, she presents regression results based on 60 monthly observations as follows: alpha = 0.43%, standard error of alpha = 0.21% Would you reject the null hypothesis of true α = 0 and accept her claim of superior... 老师您好!我想问一下,这道题到底置信区间是多少?他说97.5%的概率下,他的优异表现是源自于能力不是运气。我的理解是,他的表现好,那么应该是单尾的97.5%,而右侧的尾巴是2.5%,而不看亏损的一侧。做假设检验时,95%的置信区间恰好表示了左右两边各2.5%的情况,因此,置信区间应该是-1.96到1.96。
查看试题 已解决精品问答
- 请问selection bias 与 self-selection bias 有什么区别?我看到一个老师回复的是:不同个体选择样本不同,这就是自选择偏差,是不同个体本身固有的差异。请问这里的不同个体是指不同的人吗?
- 请问,求组合标准差需要乘以权重,但是组合var,不需要权重,想不明白?麻烦仔细讲下
- 这里的cash 中性是只需要CAPM中的benchmark=0?还是这个benchmark怎么样?什么叫阿尔法不会产生active cash position?CAPM中阿尔法并不在基准中啊?
- 老师,这里benchmark的中性化,三个回归是什么逻辑?
- 最后一行的对比是啥意思,老师展开解释一下。增量收费和FRTB定义差异
- 老师,收益率的波动率(yield volatility)和基点波动率(basic volatility)能给讲一下么?尤其是前面的,后面的基点波动率我记得是公式dw前面的
- 能解释一下这道题吗?
- 这里severity modeling,对应GEV的fattail分布不是Frechet么,这里写的Weibull是瘦尾吧。
