Windows 11, version 22H2 also delivers critically important new security features. For example, available on new Windows 11 devices, or with clean installations of Windows 11, Smart App Control enables you to confidently download any app you need without worry by blocking untrusted or unsigned applications, script files, and malicious macros from running on Windows 11.
Metastock 11 Setup Key Download
Refinitiv XENITH has an auto-upgrade mechanism built into the application, meaning when a new version is released as long as the application is open(ed) the application will upgrade to the latest version within the release window. In the event that release window is missed the latest release can be downloaded from the My Downloads page on www.MetaStock.com.
This is a very basic guide on the format symbols must be in when using the Refinitiv DataLink data service. If you have additional questions on symbol formats that this FAQ did not cover please contact MetaStock Support at 1-80-506-0999 or by email at support@metastock.com.
Downloader uses the DataLink data feed as its source to download data. To configure Downloader to collect data from the DataLink data feed the username and password must be entered into "Vendor Options". The DataLink/Maintenance ID login information can be found on the My Downloads page of www.metastock.com.
Legacy Downloader versions 11 or before will also need to set the port number according to the subscriptions used. Please contact Support at support@metastock.com or 801-506-0999 to obtain the correct Port Number.
MetaStock 12 and prior, as well as DownLoader 11 and prior, have the last update for the day available after the close when the last snapshot is taken. For instance, the US Stock Exchanges will update at 4:30 PM EST. The data is then updated with corrections within the next 4 to 5 hours. This means US Stock Exchange data is corrected by approximately 9:00 PM EST. If data collection is done previous to the corrections, the corrections will be picked up during the next day's download.
The manual for Don Fishback's ODDS Compression for Options Add-on is available as a download from www.metastock.com/mydownloads. It is also installed in C:\Program Files (x86)\MetaStock Add-ons\Don Fishback.
Exchange fees are never pro-rated. Exchange pricing is mandated by exchanges, and are subject to change without prior notice. For questions please contact MetaStock Sales at 1-800-882-3040 or by email at Sales@metastock.com.
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In the previous article we learnt how to setup a prototyping environment for algorithmic trading using Jupyter Notebooks. We used Yahoo data with Pandas DataReader. In this article we will be looking at another free market data provider Stooq.
Stooq is a Polish website that has been partly translated into English. At the time of writing Stooq offer OHLCV data on 21,332 Global securities and ETFs, 1980 currency pairs and 132 crytpocurrencies. They also offer data on global indicies, commodites and bonds. Much like Yahoo, all the data on offer is accessed through a web interface and the OHLCV data can be download in CSV format. There is no API for Stooq. For stocks listed on US exchanges it is also possible to obtain some fundamentals such as price earnings and market value, although there are no historic downloads available for these. You can search for a ticker and download all current data relating to it via the symbol page or you can access current and historic data here.
Stooq offer historic daily, hourly, and minutely data on indicies, ETFs, stocks, bonds, forex and cryptocurrencies. In order to obtain the data you need to download by region and then by frequency. ETFs and Stocks are downloaded by specific region, whilst cyrptocurrencies, forex, indicies and bonds data are available within the region named world. Once you have selected your preferred data set by clicking on the links in the ASCII column you need to complete the CAPTCHA and confirm your download. You will receive a zip file containing the information for your selected time frequency. For this tutorial we will be using the daily data from the U.S region.
Stooq sub-divide the data from each region to the exchange level then they split stocks and ETFs. For exchanges with a high volume of stocks the files are further sub-divided to allow a maximum of 2000 stocks per directory. This makes accessing the information more challenging, however the Stooq website provides information on the preffered directory structure for the download as shown in the figure below.
Once you have downloaded and unzipped the file from Stooq you will need to open Jupyter notebook. As discussed in the last article you will need to do this from your base anaconda environment. We previously installed and configured Ipykernel so you will be able to access the correct kernel for you virtual envronment directly through Jupyter. Create a new notebook and select the required kernel, if you are following along with the article series this will be called py3.8.
It is a good idea at this point to familiarise yourself with the location of your downloaded data. You will need to input the path to the directory into Pandas. The Pandas read_csv() is an incredibly versitile function. It allows you to read .csv and .txt files directly into a DataFrame for further analysis. You can define a lot of the structure of your DataFrame within this function. You can select a row for column headers and a column to use as the index. You can skiprows or footers, limit the number of rows to be read, you can also infer datetimes. There is even the option to pass a dictionary of column names with values that are functions to apply to the columns. More information can be found here.
Accessing data on a single stock is great but how do we access data on multiple stocks and analyse them all in one place? The structure of the Stooq download does make this a more complicated task. While you can generally tell which region or exchange a stock is located in you can't necessarily guarantee which subfolder it will be in. In the case of AAPL it was located under us/nasdaq stocks/1/ but it is prohibitive to spend time searching for stock tickers in all of the subfolders. Luckily for us Python 3.5+ comes with glob, a Unix style pathname pattern expansion. Glob allows us to recursively search through subdirectories on a given path for a particular file.
Now that we have our imports we will define the ticker names of the top ten S&P500 constituents. In practice this could be any grouping of stocks you require as long as they are all contained within the US region in the Stooq download. We now create a tuple containing our stock tickers. The reason for this is that we plan to create a dictionary of DataFrames, a tuple is immutable so it ensures that the order of the tickers will not change. Although it is true that Python 3.7 provides dictionaries that maintain their order this behaviour is undocumented and may not be guaranteed. A dictionary is a key value pair mapping, as such it does not have an order. Using a tuple will make sure that we maintain the order of our tickers within the dictionary.
Stooq also provide point in time cross sectional snap shots of their database. This takes the form of CSV downloads for daily data containing over 12,000 global securities, indicies and currencies. For hourly and 5 minutely data they offer price information for 66 currency pairs and 56 indicies. To access current data or data for a specific date you select the date and then specify different combinations of daily, hourly or 5 minutely data.
In this article we have introduced the Stooq historical market data vendor. We have looked at the available data, how to download it and reshape it to suit our requirements. There is an extensive offering of data available for download at different time frequencies. However, there is no API and the data files, once unzipped, take up a large amount of space. The Close price provided has been adjusted and, as far as we are aware, there is no separate unadjusted data. There are also some differences in ticker nomenclature compared to industry norms. If you are simply looking for data to experiment with Stooq offer a large history of diverse data that can be accessed and wrangled to suit most needs. In later articles we will be considering the data vendors AlphaVantage and Tiingo. 2ff7e9595c
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