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如何使用VIX计算标普500指数的预期范围


For OS: Windows XP, Windows Vista, Windows 7, Windows 8, Windows 10, Windows 11

S&P 500 VIX Mid Term Futures Index (200%) – ETF Tracker

The index offers exposure to 如何使用VIX计算标普500指数的预期范围 a daily rolling long position in the fourth, fifth, sixth and seventh month VIX futures contracts and reflects the implied volatility of the S&P 500 Index at various points along 如何使用VIX计算标普500指数的预期范围 the volatility forward curve. The Index futures roll continuously throughout each month from the fourth month VIX futures contract into the seventh month VIX futures contract.

ETFs Tracking Other Mutual Funds

We’re sorry, there are no active ETFs associated with this index.

Sort By: Largest in Assets Highest YTD Returns Lowest Expense Ratio

ETFs Tracking Other Volatility

ETF Database staff has allocated 如何使用VIX计算标普500指数的预期范围 each ETF in the ETF database, as well as each index, to a single ‘best-fit’ ETF Database Category. Other ETFs in the Volatility ETF Database Category are presented in the 如何使用VIX计算标普500指数的预期范围 following table.

* Assets in thousands of U.S. Dollars.

ETFs Tracking Other Volatility

Historical return data for other ETFs in the Volatility ETF Database Category is presented in the following 如何使用VIX计算标普500指数的预期范围 如何使用VIX计算标普500指数的预期范围 table.

ETFs Tracking Other Volatility

Fund flow information for other ETFs in the Volatility ETF Database Category is presented in the following table.

ETFs Tracking Other Volatility

Expense information for other ETFs in the Volatility ETF Database Category is presented in the following table.

ETFs Tracking Other Volatility

Dividend information for other ETFs in the Volatility ETF Database Category is presented in the following table.

ETFs Tracking Other Volatility

Holdings data for other ETFs in the Volatility ETF Database Category is presented in the following table.

ETFs Tracking Other Volatility

Tax Rate data for other ETFs in the Volatility ETF Database Category is presented in the following table.

ETFs Tracking 如何使用VIX计算标普500指数的预期范围 Other Volatility

Technical information for other ETFs in the Volatility ETF Database Category is presented in the following table.

ETFs Tracking Other Volatility

Links to analysis of other ETFs in the Volatility 如何使用VIX计算标普500指数的预期范围 ETF Database Category is presented in the following table.

ETFs Tracking Other Volatility

Links to a 如何使用VIX计算标普500指数的预期范围 proprietary ETF Database rating for other ETFs in the Volatility ETF Database Category is presented 如何使用VIX计算标普500指数的预期范围 in the following table.

看跌/看涨比(PCR)

Noldo

Plots the CBOE Put Call Ratio and marks up locations of extremities. Useful as a factor of confluence in identifying extremities in the market.如何使用VIX计算标普500指数的预期范围

SPX: Put/Call-Ratio-Buschi

English: This script shows the Put/Call-Ratio as seen on the Cboe-Website: www.cboe.com A higher Put/Call-Ratio means a higher trading volume of puts compared to calls, which is a sign of a higher need for protection in the market. For best reflection of the Cboe's data, which is shown in 30 minutes intervals, a 30 min-chart is recommended. 30 min-data as.

PC: Put/call ratio cross - buy and sell SPY

When 50DMA and 200DMA cross on PC, algo trades SPY 如何使用VIX计算标普500指数的预期范围 accordingly

CBOE: CBOE PCR Factor Dependent Variable Odd Generator

This script is the my Dependent Variable Odd Generator script : with the Put / Call Ratio ( PCR ) appended, only for CBOE and the instruments connected to it. For CBOE this script is more accurate and faster than Dependent Variable Odd Generator. And the stagnant market odds are better and more realistic. Do not use for timeframe periods less than 1 day. Because.

NDX: I11L Long Put/Call Ratio Inversion

The Strategy uses the Put/Call Options Ratio Inversaion as a Signal and Implements simple Money Management rules. It is adjusted for the NDX and for the SPX in the 30min Range. The Oscilation has to be finetuned to reflect the correct 如何使用VIX计算标普500指数的预期范围 Reversal point. A good indicator of the correct Reversal Point is a solid range of good backtesting results..

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资产组合优化原理与实例 Portfolio Optimization

置顶 微岩 于 2016-03-07 18:36:24 发布 21834 收藏 49

在前一片文章(SkLearn 对上证50成分股聚类 )中简单介绍了投资组合优化理论,在此进一步介绍下该理论,以及如何进行Portfolio Optimization。

1. Markowitz投资组合理论

Markowitz投资组合理论是投资组合优化的理论基础。
马克维茨被公认为是现代投资组合理论的开创者,他与夏普、米勒共同获得1952年的诺贝尔经济学奖。
1952年他在自己著名的论文《资产选择:有效的多样化》中首先提出了投资组合理论。马克维茨的理论主要包括“均值方差分析理论”和“有效边界模型”,他用期望收益率表示收益,用方差表示风险。该理论证明了“通过证券组合只能消除非系统风险,而不能消除系统性风险”。

2. 投资组合优化的目标

3. 如何进行投资组合优化

这里就需要用到Markowitz投资组合理论。
均值方差分析理论解释了为什么要建立投资组合
有效边界模型理论解释了如何进行投资组合优化

3.1 均值方差分析理论

也就是说通过分散投资降低方差即投资风险。
以期望收益E来衡量证券收益,以收益的方差 δ 2 表示投资风险
min δ 2 ( r 如何使用VIX计算标普500指数的预期范围 p ) = ∑ ∑ w i w j c o v ( r i , r j )

E ( r p ) = ∑ w i r i

r i 、 r j ——第i种、第j种资产的收益;

w i 、 w j ——资产i和资产j在组合中的权重;

δ 2 ( r p ) ——组合收益的方差即组合的总体风险;

c o v ( r , r j ) ——两种资产之间的协方差。

3.2 有效边界模型

3.3 2项资产的投资组合优化

资产AB
投资比例x1x2
回报率r1r2
风险δ1δ2
协方差 ρ

令投资总数为为单位1:
r = x 1 r 1 + ( 1 − x 1 ) r 2 …………(1)

x 1 = r − r 2 r 1 − r 2 ……………………(2)

v a r = x 2 1 δ 2 2 + ( 1 − x 1 ) 2 δ 2 2 + 2 x 1 x 2 ρ …………(3)

δ 2 = ( r − r 2 r 1 − r 2 ) 2 δ 2 2 + ( r − r 1 r 2 − r 1 ) 2 δ 2 2 + 2 x 1 x 2 ρ …………(4)

最后我们的到了 δ 2 如何使用VIX计算标普500指数的预期范围 和r的关系公式:公式(4),并且从(4)可以看出该公式是一个一元二次公式。

如图中曲线即为我们需要的投资边界(Efficient Portfolio Frontier),该曲线右边是我们可以采用的投资组合,曲线左边是在该投资模型下不可能取得的投资组合。
只有在该曲线上的投资组合才是最优投资组合。

3.3 3项资产的投资组合优化与切线模型

(1)3项资产的投资组合
在引入一项投资资产(石油):

(2)切线模型
然后引入一种无风险资产,视该资产的风险为零,收益( r f )固定。
如此可以一条直线并与未引入无风险资产的曲线相切。
该切线组合极为最优组合,是一般投资经理应该选择的投资组合。
切线斜率:

资产池:
海螺水泥, 中国中车, 光大银行, 中国石油, 中信证券, 中国船舶, 国金证券, 青岛海尔
采用2015年1年期国债作为无风险资产,年华收益率为3.14%

日回报率:
0.0015 0.0012 0.0024 0.0044 -0.0005 0.0054 0.0015 0.0057
风险:
0.如何使用VIX计算标普500指数的预期范围 0199 0.0168 0.0223 0.0328 0.0144 0.0882 0.0187 0.0351
协方差矩阵:
0.0004 0.0001 0.0001 0.0003 0.0001 0.0002 0.0002 0.0002
0.0001 0.0003 0.0001 0.0002 0.0001 0.0000 0.0001 0.0001
0.0001 0.0001 0.0005 0.0003 -0.0000 0.0007 0.0003 0.0002
0.0003 0.0002 0.0003 0.0011 0.0001 0.0006 0.0003 0.0006
0.0001 0.0001 -0.0000 0.0001 0.0002 0.0001 0.0001 0.0001
0.0002 0.0000 0.0007 0.0006 0.0001 0.0078 0.0004 0.0004
0.0002 0.0001 0.0003 0.0003 0.0001 0.0004 0.0003 0.0003
0.0002 0.0001 0.0002 0.0006 0.0001 0.0004 0.0003 0.0012

切点:
(风险,日回报率) = 0.02125, 0.0039
对应组合: