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My understanding is that ^GSPC is Yahoo Finance's 'proprietary' ticker for the S&P 500 index. I have no idea why Yahoo Finance chose not to or was forbidden from using the common SPX ticker. It's worth noting that I have had reason to source the free daily, monthly or weekly ^GSPC data from Yahoo Finance a number of times over the years.
2015年6月6日 · ^GSPC is a price index, not a total return index, so it does not include dividends. SPY is an ETF that holds the underlying stocks. When it receives a dividend it keeps it in a cash account (which of course affects the NAV and market value of SPY shares) until the end of the quarter.
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2017年5月18日 · Since Yahoo has decided to yank their API for the foreseeable future, I'm attempting to switch to Google finance. I'm having trouble downloading a .csv file for GSPC (S&P 500), despite there clearly being a website and table set up for it. The website is here:
(SOLVED: Solution is below the second graph) The API results on GSPC: Same period in the interactive chart of ^GSPC: SOLVED Apparently, Yahoo Finance API has different results for ^GSPC and GSPC.
Basically the Total Return Index assumes reinvestments compared to "regular" indices. "A total return index is an index that measures the performance of a group of components by assuming that all cash distributions are reinvested, in addition to tracking the components' price movements.1 While it is common to refer to equity based indices, there are also total return indices for bonds and ...
I would like to calculate the Yearly Sharpe Ratio on MSCI World index I have monthly values of the index that falls back up to Jan/1970, hence about: 44 years, 528 months In order to calculate Sh...
I'm basically running some code as follows. Basically I'm just retrieving pairs of stocks (laid out as Row 1-Stock 1,2, Row 2-Stock 1,2 and so on, where Stock 1 and 2 are different in each row) fro...
2020年5月2日 · I want to download historical data for different indices. I am using Python for this. I used the following code. import pandas_datareader.data as web start = datetime.datetime(1960, 1, 1) end =
2019年5月23日 · I was wondering how one should choose parameters such as "frequency" of returns (daily, monthly etc.), "time frame" (1 or 3 or 5 years of historical data etc), benchmark (same of the portfolio or the specific one of the market of each asset etc. - i.e. AAPL.US
