This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

ALT ANALYTICA LIMITED

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

South Africa Index: FTSE/JSE: Alt X 15 data was reported at 290.239 NA in Nov 2018. This records a decrease from the previous number of 297.999 NA for Oct 2018. South Africa Index: FTSE/JSE: Alt X 15 data is updated monthly, averaging 504.890 NA from Oct 2007 (Median) to Nov 2018, with 134 observations. The data reached an all-time high of 2,080.730 NA in Dec 2007 and a record low of 290.239 NA in Nov 2018. South Africa Index: FTSE/JSE: Alt X 15 data remains active status in CEIC and is reported by Johannesburg Stock Exchange. The data is categorized under Global Database’s South Africa – Table ZA.Z001: Johannesburg Stock Exchange: Index.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Altimmune (ALT) Poised for Breakout: Is This the Next Biotech Giant?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

South Africa Index: FTSE/JSE: Alt X data was reported at 988.679 04Mar2006=100 in Nov 2018. This records a decrease from the previous number of 996.746 04Mar2006=100 for Oct 2018. South Africa Index: FTSE/JSE: Alt X data is updated monthly, averaging 1,295.804 04Mar2006=100 from Apr 2006 (Median) to Nov 2018, with 152 observations. The data reached an all-time high of 4,813.280 04Mar2006=100 in Oct 2007 and a record low of 857.340 04Mar2006=100 in Feb 2013. South Africa Index: FTSE/JSE: Alt X data remains active status in CEIC and is reported by Johannesburg Stock Exchange. The data is categorized under Global Database’s South Africa – Table ZA.Z001: Johannesburg Stock Exchange: Index.

Explore the historical Whois records related to alt-sector.net (Domain). Get insights into ownership history and changes over time.

South Africa Market Cap: FTSE/JSE: Alt X data was reported at 5,148.140 ZAR mn in Nov 2018. This records an increase from the previous number of 5,145.869 ZAR mn for Oct 2018. South Africa Market Cap: FTSE/JSE: Alt X data is updated monthly, averaging 7,110.670 ZAR mn from Mar 2006 (Median) to Nov 2018, with 153 observations. The data reached an all-time high of 20,152.351 ZAR mn in Dec 2016 and a record low of 1,697.735 ZAR mn in Apr 2006. South Africa Market Cap: FTSE/JSE: Alt X data remains active status in CEIC and is reported by Johannesburg Stock Exchange. The data is categorized under Global Database’s South Africa – Table ZA.Z004: Johannesburg Stock Exchange: Market Capitalization: by Index.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

ALT:TSXV Alturas Minerals Corp.

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

South Africa TRI: FTSE: Alt X data was reported at 1,877.365 NA in Jun 2022. This records a decrease from the previous number of 1,885.611 NA for May 2022. South Africa TRI: FTSE: Alt X data is updated monthly, averaging 1,821.158 NA from Mar 2021 (Median) to Jun 2022, with 16 observations. The data reached an all-time high of 2,021.409 NA in Mar 2022 and a record low of 1,518.190 NA in Jul 2021. South Africa TRI: FTSE: Alt X data remains active status in CEIC and is reported by FTSE Russell. The data is categorized under Global Database’s South Africa – Table ZA.Z002: Financial Times Stock Exchange: Enhanced ICB Framework: Total Return Index.

Explore historical ownership and registration records by performing a reverse Whois lookup for the email address alt.cq-5o8xk9vf@yopmail.com..

• Introduction This is the Khmer ALT of the Asian Language Treebank (ALT) Corpus. English texts sampled from English Wikinews were available under a Creative Commons Attribution 2.5 License. Please refer to http://www2.nict.go.jp/astrec-att/member/mutiyama/ALT/index.html for an introduction of the ALT project. Khmer ALT has been developed by NICT and NIPTICT. The license of Khmer ALT is Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) License https://creativecommons.org/licenses/by-nc-sa/4.0/ * Contents - data_km.km-[tok|tag].nova : tokenized/POS-tagged Khmer sentences by the nova annotation system # based on the following two guildelines # http://www2.nict.go.jp/astrec-att/member/mutiyama/ALT/Khmer-annotation-guideline.pdf # http://www2.nict.go.jp/astrec-att/member/mutiyama/ALT/Khmer-annotation-guideline-supplementary.pdf * Disclaimer [1] The content of the selected English Wikinews articles have been translated for this corpus. English texts sampled from English Wikinews were available under a Creative Commons Attribution 2.5 License. Users of the corpus are requested to take careful consideration when encountering any instances of defamation, discriminatory terms, or personal information that might be found within the corpus. Users of the corpus are advised to read Terms of Use in https://en.wikinews.org/wiki/Main_Page carefully to ensure proper usage. [2] NICT bears no responsibility for the contents of the corpus and the lexicon and assumes no liability for any direct or indirect damage or loss whatsoever that may be incurred as a result of using the corpus or the lexicon. [3] If any copyright infringement or other problems are found in the corpus or the lexicon, please contact us at alt-info[at]khn[dot]nict[dot]go[dot]jp. We will review the issue and undertake appropriate measures when needed.

Clinical characteristics of the participants according to the ALT level.

Femoral neck bone mineral densities for participants with and without NAFLD, stratified by gender and menopausal status, race/ethnicity, age, and BMI.

指数：富时/JSE指数：Alt X在11-01-2018达988.67904Mar2006=100，相较于10-01-2018的996.74604Mar2006=100有所下降。指数：富时/JSE指数：Alt X数据按月更新，04-01-2006至11-01-2018期间平均值为1,295.80404Mar2006=100，共152份观测结果。该数据的历史最高值出现于10-01-2007，达4,813.28004Mar2006=100，而历史最低值则出现于02-01-2013，为857.34004Mar2006=100。CEIC提供的指数：富时/JSE指数：Alt X数据处于定期更新的状态，数据来源于Johannesburg Stock Exchange，数据归类于Global Database的南非 – 表 ZA.Z001：约翰内斯堡证券交易所：指数。

TRI：富时：Alt X在06-01-2022达1,877.365NA，相较于05-01-2022的1,885.611NA有所下降。TRI：富时：Alt X数据按月更新，03-01-2021至06-01-2022期间平均值为1,821.158NA，共16份观测结果。该数据的历史最高值出现于03-01-2022，达2,021.409NA，而历史最低值则出现于07-01-2021，为1,518.190NA。CEIC提供的TRI：富时：Alt X数据处于定期更新的状态，数据来源于FTSE Russell，数据归类于全球数据库的南非 – Table ZA.Z002: Financial Times Stock Exchange: Enhanced ICB Framework: Total Return Index。

市价总值：富时：Alt X 15在06-01-2022达4,045.402百万南非兰特，相较于05-01-2022的3,450.101百万南非兰特有所增长。市价总值：富时：Alt X 15数据按月更新，03-01-2021至06-01-2022期间平均值为3,435.201百万南非兰特，共16份观测结果。该数据的历史最高值出现于06-01-2022，达4,045.402百万南非兰特，而历史最低值则出现于07-01-2021，为2,277.000百万南非兰特。CEIC提供的市价总值：富时：Alt X 15数据处于定期更新的状态，数据来源于FTSE Russell，数据归类于全球数据库的南非 – Table ZA.Z003: Financial Times Stock Exchange: Enhanced ICB Framework: Market Capitalization: by Index。

(NA: Not Applicable).

Clinical, biological, and hemodynamic characteristics of the hypertensive population according to the stiffness index (negative or positive).

Baseline characteristics by ALT quartile in males.

Performance of serum liver fibrosis indexes in predicting SPH.

Exclusion criteria for patient selection prior to index date of statin prescription.