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7

http://replication.uni-goettingen.de/ (The below text was added by Jan Höffler who founded the wiki.) This site is a replication project for papers, so far mainly in economics but open to any field. It serves as a database of empirical studies, the availability of replication material for them and of replication studies. It can help teaching replication ...


5

Quandl has a python api: https://www.quandl.com/help/api and free stock fundamentals (some) https://www.quandl.com/help/api-for-stock-data


4

Yes, Thomson Reuters RIC codes are case-sensitive. I believe the confusion comes from the fact that some frontends will 'assist' you if you misspell and automatically convert. That's just a trick. This doesn't change the fact that at the API level it is case-sensitive. In other words: if you are doing your own application you should definitely think of RIC ...


4

You don't have to scrape that data to get it via Python if you work with Intrinio's API. Here is a Python SDKs that will make it easy for you: Historical financial statements and dividend yield, marketcap, etc: https://github.com/nhedlund/intrinio Specifically, you can make a curl request for historical marketcap like this: curl "https://api.intrinio.com/...


3

The main problem of linking Compustat with IBES is not the fact that Compustat's cusip is 9 character, whereas IBES is 8-character. The main issue is that Compustat Cusip is header (most recent), whereas IBES Cusip is historical (as of date). Therefore matching through Cusips is likely to be correct for many cases but not all. The standard way of doing the ...


2

You can get stock price data using the following packages. Generally, scraping is not legal and using the API is the best and faster way to get the data. I have shown below three ways to get the stock price data: Yahoo finance Quandl Yahoo Finance import matplotlib.pyplot as plt import fix_yahoo_finance as yf data = yf.download('AAPL','2016-01-01','...


2

You could consider he fairly-recently started ReScience initiative which has exactly this in mind: ReScience is a peer-reviewed journal that targets computational research and encourages the explicit replication of already published research, promoting new and open-source implementations in order to ensure that the original research is reproducible. As ...


2

You could restate your problem as: $$ \min_x \quad Var \left (-\sum_{i=0}^n x_iR_i \right) $$ $$ \text{s.t.} \quad x_0 = -1, \quad \sum_{i=1}^n x_i = 1, \quad \text{non-negativity of }x_1:x_n $$ where $R_i$ are the expected returns of asset $i$ and $x_i$ are your solution variables. The objective function can be expressed as: $$ \min_x \quad - \sum_{i,j} ...


2

Since I don't have SAS, I wrote a python script to create the mapping table between Compustat and IBES via CRSP. The code is available on my GitHub: https://github.com/snauhaus/link_compustat_ibes It does not require any input other than valid WRDS login credentials.


1

I have only read your code but it seems to me that DELTA_VOL is way too low. This causes vol1 and vol2 to be very close which doesn’t ensure the value your looking for is included in the initial bracket.


1

There is no internal function in python to get the duration (like excel for example ), although it's not that hard to program. You basically need daycounts, rates and discount factors. As noob2 mentioned, it's possible to get it with QuantLib although there is a learning curve until you're comfortable with building the needed objects. Here is a simple ...


1

This depends on quite a few other inputs. If you're comparing deltas, what's the volatility of the underlying and the moneyness of the derivative (whether call, put, or something more exotic). I've done valuations that need 10 million simulations (5x out of the money options with 10 years until expiration) and others where 10,000 is perfectly sufficient (at ...


1

You could use the database at ISIN.com of as part of Refinitiv's reference data (if you were purchasing that). However, every firm I have worked at generally downloads that data or keeps their own cross-reference table -- since they also included market data codes (e.g. RIC, Bloomberg ID, FactSet Exchange Symbol) in the table. Note that the cross-reference ...


1

Your question is not clear enough. Go long on 3 highest returns... since when? During the past month? If so, at the end of each month you need to compute the average return on each index, and then find the minimum and maximum returns. As simple dummy example, I will generate a matrix of 10 stocks and 30 daily returns. Then I will average those and find ...


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