TREND: Xignite. Worldwide Stock Market Prices by Region: Stock Daily Open | Economic Regions/Exchanges: Budapest Stock Exchange | Exchange: Budapest Stock Exchange, 02/15/2011 - 03/19/2019. Data Planet™ Statistical Datasets: A SAGE Publishing Resource Dataset-ID: 016-004-001
Bibliographic record
Abstract
datasets.shared.infosheet.CitationMgr@234 Dataset: Reports opening stock price for companies listed on global exchanges. This dataset provides historical prices for equities trading on more than 50 global exchanges. Daily open, close, high, low, and volume statistics are reported. Exchanges covered: US: BATS, CBOE, Chicago Mercantile Exchange (including GLOBEX), MDX, NASDAQ, NYSE, NYSE ARCA, NYSE MKT EQUITIES, OPRA, OTC BB, OTC PINK MARKETPLACE, OTHER OTC/NBB; Eastern Europe: Budapest, NASDAQ OMX BALTIC (RIGA, Tallinn, and Vilnius), Prague, Spot Regulated Market-BVB, STANDARD-CLASSICA-FORTS, Warsaw; Western Europe: Athens, Exchange S.A. cash market, BME (Barcelona, Madrid, Valencia), Borsa Italiana – Milan, Irish, London, Espanol, NYSE EURONEXT (Amsterdam, Brussels, Lisbon, Paris), Swiss, Vienna; Germany: Berlin, Dusseldorf, Munchen, Stuttgart, Bratislava, Deutsche Boerse Ag – Frankfurt, Hamburg, Hannover, XETRA; Europe not elsewhere classified (NEC): CHI-X Europe, NYSE EURONEXT Cash Markets and Indices, NYSE EURONEXT LIFFE, SWX Europe; Nordic: NASDAQ OMX NORDIC (Copenhagen, Helskinki, Iceland, Stockholm); Asia-Pacific: Bombay, Hong Kong, KOSDAQ, Korea, India, Shanghai, Shenzhen, Singapore, Taiwan, Tokyo; Africa: Johannesburg; Canada: CNSE, Montreal, Toronto, TSX, TSX Venture; South America: BOVESPA, Lima, Santiago; Middle East: Muscat, Tel Aviv; Australia/New Zealand: ASX, NZE. The historical depth of the time series available varies by equity. http://www.xignite.com/product/XigniteGlobalHistorical/api/ Category: Banking, Finance, and Insurance Subject: Stock Indexes, Stock Markets, Stocks, Publicly Traded Companies, Stock Prices Source: Xignite Xignite provides on-demand financial market data covering global equities, commodities, currencies, options, fixed income, mutual funds, derivatives, and OTC (“over-the-counter” or those traded in a context other than a formal exchange) instruments. http://www.xignite.com/
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.007 | 0.007 |
| Meta-epidemiology (broad) | 0.007 | 0.000 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.049 | 0.043 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.131 | 0.054 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".