The SPAC bubble burst in the second quarter of 2021 after four consecutive quarters of growth, though the number of SPAC IPOs rose to 175 in the fourth quarter of 2021. However, the peak of the SPAC boom was reached when SPACs raised capital in 300 IPOs in the first quarter of 2021. In April 2021, the U.S. Securities and Exchange Commission (SEC) brought in new accounting rules for SPACs, which likely played a role in the drop in new SPAC IPO filings.

What are SPAC IPOs?

A special purpose acquisition company (SPAC) is a corporation formed for the sole purpose of raising investment capital through an initial public offering (IPO). The value of SPAC IPOs globally reached a record-high in February 2021, amounting to over 35 billion U.S. dollars. IPO underwriters are necessary to act as brokers between the issuing company and the investing public, and are usually investment banks. They essentially help the issuing company sell its initial set of shares. As of September 2021, the largest underwriters of SPAC IPOs globally were Citigroup, Goldman Sachs, and Credit Suisse.

SPAC IPOs in the United States

The number of SPAC IPOs in the United States has increased significantly in recent years. As of October 2021, SPACs had raised capital in a record number of IPOs. At the same time, the value of SPAC IPOs raised in the U.S. also peaked - amounting to a value of over 130 billion U.S. dollars. When compared to Europe, the vast majority of global proceeds from SPAC IPOs was raised in the United States.

Data on quarterly SPACs, both relative to total IPOs (spacprop) and the SPAC volume (nspac).

Data includes financial information about companies that made IPO during 2021.

Sweden Share Trading: OMX: SPAC List: Turnover Velocity data was reported at 217.071 % in Jul 2024. This records a decrease from the previous number of 237.403 % for Jun 2024. Sweden Share Trading: OMX: SPAC List: Turnover Velocity data is updated monthly, averaging 29.629 % from Mar 2021 (Median) to Jul 2024, with 41 observations. The data reached an all-time high of 727.024 % in Mar 2021 and a record low of 9.437 % in Aug 2022. Sweden Share Trading: OMX: SPAC List: Turnover Velocity data remains active status in CEIC and is reported by Nasdaq Stockholm. The data is categorized under Global Database’s Sweden – Table SE.Z004: OMX Nasdaq Stockholm: Share Trading.

There is no description for this dataset.

Sweden Share Trading: OMX: SPAC List: Market Capitalization data was reported at 2,515,000.000 SEK th in Jun 2024. This records a decrease from the previous number of 2,585,000.000 SEK th for May 2024. Sweden Share Trading: OMX: SPAC List: Market Capitalization data is updated monthly, averaging 6,625,500.000 SEK th from Mar 2021 (Median) to Jun 2024, with 40 observations. The data reached an all-time high of 7,979,200.000 SEK th in Oct 2021 and a record low of 2,400,000.000 SEK th in Oct 2023. Sweden Share Trading: OMX: SPAC List: Market Capitalization data remains active status in CEIC and is reported by Nasdaq Stockholm. The data is categorized under Global Database’s Sweden – Table SE.Z004: OMX Nasdaq Stockholm: Share Trading.

Sweden Share Trading: OMX: SPAC List: Number of Listed Companies data was reported at 1.000 Unit in Jun 2024. This stayed constant from the previous number of 1.000 Unit for May 2024. Sweden Share Trading: OMX: SPAC List: Number of Listed Companies data is updated monthly, averaging 3.000 Unit from Mar 2021 (Median) to Jun 2024, with 40 observations. The data reached an all-time high of 4.000 Unit in Mar 2022 and a record low of 1.000 Unit in Jun 2024. Sweden Share Trading: OMX: SPAC List: Number of Listed Companies data remains active status in CEIC and is reported by Nasdaq Stockholm. The data is categorized under Global Database’s Sweden – Table SE.Z004: OMX Nasdaq Stockholm: Share Trading.

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.

ASCBW A SPAC II Acquisition Corp. Warrant

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

Sweden Share Trading: OMX: SPAC List: Avg Daily: Number of Trade data was reported at 209.130 Unit in Jul 2024. This records a decrease from the previous number of 382.778 Unit for Jun 2024. Sweden Share Trading: OMX: SPAC List: Avg Daily: Number of Trade data is updated monthly, averaging 272.762 Unit from Mar 2021 (Median) to Jul 2024, with 41 observations. The data reached an all-time high of 1,489.000 Unit in Mar 2021 and a record low of 136.045 Unit in Jan 2024. Sweden Share Trading: OMX: SPAC List: Avg Daily: Number of Trade data remains active status in CEIC and is reported by Nasdaq Stockholm. The data is categorized under Global Database’s Sweden – Table SE.Z004: OMX Nasdaq Stockholm: Share Trading.

February 2021 was the strongest month yet for SPAC acquisitions globally when the value of these deals exceeded 100 billion U.S. dollars. In contrast, the total value of SPAC acquisitions amounted to 152 billion U.S. dollars for the entire year of 2020. A special purpose acquisition company (SPAC) is a company with no business operations which is set up for the sole purpose of raising capital through an initial public offering with the goal of buying an existing company. Historical data shows that the average initial returns after SPAC IPOs can vary, though have been generally positive over the past two decades.

This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.

Using a sample of 200 SPAC mergers announced in the 2006-2023 period, this study investigates the short-term stock price reaction of the publicly listed rivals of the target firms around the announcement of a deal. The results provide evidence of significant negative valuation changes for rival firms, especially those with higher industry relatedness to the target firms. Collectively, the findings indicate that the industry dynamics surrounding SPAC merger announcements are driven by competitive effects.

Sweden Share Trading: OMX: SPAC List: Turnover data was reported at 166,769.740 SEK th in May 2022. This records an increase from the previous number of 87,439.486 SEK th for Apr 2022. Sweden Share Trading: OMX: SPAC List: Turnover data is updated monthly, averaging 166,769.740 SEK th from Mar 2021 (Median) to May 2022, with 15 observations. The data reached an all-time high of 536,597.811 SEK th in Mar 2021 and a record low of 87,439.486 SEK th in Apr 2022. Sweden Share Trading: OMX: SPAC List: Turnover data remains active status in CEIC and is reported by Nasdaq Stockholm. The data is categorized under Global Database’s Sweden – Table SE.Z004: OMX Nasdaq Stockholm: Share Trading.

Sweden Share Trading: OMX: SPAC List: Avg Daily: Turnover data was reported at 17,981.573 SEK th in Jul 2024. This records a decrease from the previous number of 23,808.910 SEK th for Jun 2024. Sweden Share Trading: OMX: SPAC List: Avg Daily: Turnover data is updated monthly, averaging 6,630.290 SEK th from Mar 2021 (Median) to Jul 2024, with 41 observations. The data reached an all-time high of 28,978.629 SEK th in Apr 2023 and a record low of 2,467.575 SEK th in Aug 2022. Sweden Share Trading: OMX: SPAC List: Avg Daily: Turnover data remains active status in CEIC and is reported by Nasdaq Stockholm. The data is categorized under Global Database’s Sweden – Table SE.Z004: OMX Nasdaq Stockholm: Share Trading.

Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

All but seven special purpose acquisition company (SPAC) IPOs completed globally in the first quarter 2021 were completed in the United States. The seven remaining deals were closed in Europe, and took place across only four stock exchanges. Special purpose acquisition companies are public companies with neither a specific business plan, nor a product or service to sell.

Customs records of are available for SPAC VIET NAM CO.,LTD. Learn about its Importer, supply capabilities and the countries to which it supplies goods

Market value analysis based on 14 actual sales showing current worth and pricing trends

The datasets for this investigation consist of microtremor array data collected at: 1) 18 sites in Salt Lake and Utah valleys, Utah, and 2) two sites as part of the Frontier Observatory for Research in Geothermal Energy (FORGE) near Milford, Utah. Each of the 18 sites in the Salt Lake and Utah valleys were acquired with four-sensor arrays with three-component (3C) sensors having flat response from 0.033 Hz to 50 Hz. The data acquired as part of the FORGE investigation used both 3C broadband and 5-Hz geophone sensors. Additional information on these datasets can be found in the supporting documentation provided in this data release as well as in the paper by Zhang and others (2019) that utilized these data.

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.

ASPA ABRI SPAC I INC. Common Stock

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