In May 2022, the value of a single LUNA (version 1.0) declined by over 50 percent per day, as prices fell significantly from one day to the next. This is a significant difference from earlier in the year, when the price of the Luna token within the Terra (Classic) network grew by roughly 100 percent between January and March 2022. This popularity was reflected in a ranking covering the world's most traded cryptocurrencies - where the relatively young crypto first showed in the top 10. The popularity of Terra and its cryptocurrencies LUNA and UST (TerraUSD) - from May 2025 referred to as Terra Classic - comes from its role in crypto lending and the interest rates promised by lending platform Anchor Protocol, a platform built off the Terra network.

In May 2022, over ***** billion Terra Classic – the 1.0 version of LUNA - tokens were issued and went into active circulation in a few days. The cryptocurrency’s built-in algorithm triggered this correction following the coin’s significant price drop that month. Terra’s algorithm would "burn" (permanently destroying) LUNA so that it created something else instead: TerraUSD (UST), a stablecoin within the same blockchain. This automated system was meant to keep the price of UST level, potentially avoiding economic sentiment. Because of this initial promise of stability, Terra and its two coins initially played a significant role in crypto lending. The poster child of algorithmic stablecoins Up until May 2022, TerraUSD (UST) was the biggest stablecoin that functioned with an algorithm. At the end of April 2022, the market cap of TerraUSD – now TerraClassicUSD – was *** times larger than what it was one month later, comparable in size to Binance USD. Algorithmic stablecoins are relatively new and, as most stablecoins, have an external asset as collateral. Several of the biggest stablecoins in the world, for example, are backed by real-world U.S. dollar assets, such as cash or securities. Others – such as DAI – rely on the backing of other cryptocurrencies, such as Ethereum (ETH). TerraUSD had little to no backing, relying on a closed ecosystem. Reset or revival: The LUNA (2.0) aftermath Terra got reset on May 28, 2022: A new *** coin released – taking over the Terra (LUNA) name - whilst the "original" crypto was abandoned and became Terra Classic (LUNC). TerraUSD (UST) remained but became TerraClassicUSD (USTC). Several of the *** LUNA holders, however, hoped for a different solution, rather seeing the (***) coin’s supply be bought back by the company who issued them. The company would then burn them, hopefully restoring the price of the original LUNA. Do Kown, the CEO of the Terra system, stated his company did not have the funds for such a big undertaking. He instead shared a blockchain address on Twitter where individuals could burn their tokens themselves. By June 2022, roughly **** LUNA tokens were destroyed that way – a burn rate of roughly ***** percent compared to the overall circulating supply.

This dataset contains the predicted prices of the asset Luna by Virtuals over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

In January 2022, the Luna token lost roughly one third of its market cap which it recovered and even increased in the following months. This development marked the continued fast growth of a cryptocurrency connected to a blockchain - Terra - that only officially launched in August 2021. Consequently, Terra (LUNA) ranked among the cryptocurrencies with the highest market caps worldwide.

Luna by Virtuals Ang pagsubaybay sa kasaysayan ng presyo ay nagbibigay-daan sa mga crypto investor na madaling masubaybayan ang performance ng kanilang pamumuhunan. Maginhawa mong masusubaybayan ang opening value, high, at close sa Luna by Virtuals sa paglipas ng panahon, pati na rin ang trade volume. Bukod pa rito, maaari mong agad na tingnan ang pang-araw-araw na pagbabago bilang isang porsyento, na ginagawang effortless na tukuyin ang mga araw na may significant fluctuations. Ayon sa aming data ng history ng presyo ng Luna by Virtuals, tumaas ang halaga nito sa hindi pa naganap na peak sa 2024-10-16, na lumampas sa $12.77 USD. Sa kabilang banda, ang pinakamababang punto sa trajectory ng presyo ni Luna by Virtuals, na karaniwang tinutukoy bilang "Luna by Virtuals all-time low", ay naganap noong 2024-10-16. Kung ang isa ay bumili ng Luna by Virtuals sa panahong iyon, kasalukuyan silang masisiyahan sa isang kahanga-hangang kita na 20,810%. Sa pamamagitan ng disenyo, ang 1,000,000,000 Luna by Virtuals ay malilikha. Sa ngayon, ang circulating supply ng Luna by Virtuals ay tinatayang 1,000,000,000. Ang lahat ng mga presyong nakalista sa pahinang ito ay nakuha mula sa Bitget, galing sa isang reliable source. Napakahalagang umasa sa iisang pinagmulan upang suriin ang iyong mga investment, dahil maaaring mag-iba ang mga halaga sa iba't ibang nagbebenta. Kasama sa aming makasaysayang Luna by Virtuals dataset ng presyo ang data sa pagitan ng 1 minuto, 1 araw, 1 linggo, at 1 buwan (bukas/mataas/mababa/close/volume). Ang mga dataset na ito ay sumailalim sa mahigpit na pagsubok upang matiyak ang consistency, pagkakumpleto, at accurancy. Ang mga ito ay partikular na idinisenyo para sa trade simulation at mga layunin ng backtesting, madaling magagamit para sa libreng pag-download, at na-update sa real-time.

This dataset contains the predicted prices of the asset Luna's Cat: Byte by Virtuals over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

This dataset contains the predicted prices of the asset SKI MASK LUNA over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

About this dataset

Context

The dataset tabulates the Luna County population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Luna County across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Luna County was 25,316, a 1.47% decrease year-by-year from 2022. Previously, in 2022, Luna County population was 25,693, an increase of 0.87% compared to a population of 25,471 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Luna County increased by 357. In this period, the peak population was 27,202 in the year 2008. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Luna County is shown in this column.
• Year on Year Change: This column displays the change in Luna County population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Luna County Population by Year. You can refer the same here

Graph and download economic data for All-Transactions House Price Index for Luna County, NM (ATNHPIUS35029A) from 1995 to 2024 about Luna County, NM; NM; HPI; housing; price index; indexes; price; and USA.

AI-powered price forecasts for LUNA stock across different timeframes including weekly, monthly, yearly, and multi-year predictions.

About this dataset

Context

The dataset tabulates the Luna Pier population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Luna Pier across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Luna Pier was 1,353, a 0.44% decrease year-by-year from 2022. Previously, in 2022, Luna Pier population was 1,359, a decline of 1.09% compared to a population of 1,374 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Luna Pier decreased by 131. In this period, the peak population was 1,541 in the year 2007. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Luna Pier is shown in this column.
• Year on Year Change: This column displays the change in Luna Pier population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Luna Pier Population by Year. You can refer the same here

The number of LUNA burned jumped significantly in October 2022, after Binance burned *** billion tokens or **** percent of the coin's circulating supply. This according to data from within the Terra blockchain, specifically an old address shared by LUNA CEO Do Kwon where users could send tokens to see them burned (permanently destroyed). The address was shared after The circulating supply of Terra (LUNA) - renamed Terra Classic (LUNC) since late May - grew by trillions as the cryptocurrency's algorithm tried to account for a significant price fall. Several crypto holders hoped that Do Kwon's company would buy the LUNA token back from them and remove them from the supply entirely - meaning Terra's price would be restored. The CEO shared his company would not be able to do such a thing - citing it was too vast of an undertaking - but provided an option for those who wanted to burn coins either way. By the end of June 2022, over one billion tokens - or ***** percent of all the LUNA/LUNC that exists - had been sent to that address by the end of June 2022. The price of Terra (LUNA) did recover on certain days, but was not close to the parity it originally desired.

This dataset contains the predicted prices of the asset Luna The Panthera over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

This dataset contains the predicted prices of the asset Diamond Luna over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

This dataset tracks annual reduced-price lunch eligibility from 1999 to 2023 for Luna Elementary School vs. Texas and Garland Independent School District

This dataset tracks annual reduced-price lunch eligibility from 2005 to 2023 for Luna Middle School vs. Texas and Northside Independent School District

This dataset contains the predicted prices of the asset Eris Amplified Luna over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

This dataset tracks annual reduced-price lunch eligibility from 2013 to 2023 for Uplift Education - Luna Preparatory - Primary vs. Texas and Uplift Education School District

This dataset contains the predicted prices of the asset Baby Luna by Virtuals over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

Cryptocurrency historical datasets from January 2012 (if available) to October 2021 were obtained and integrated from various sources and Application Programming Interfaces (APIs) including Yahoo Finance, Cryptodownload, CoinMarketCap, various Kaggle datasets, and multiple APIs. While these datasets used various formats of time (e.g., minutes, hours, days), in order to integrate the datasets days format was used for in this research study. The integrated cryptocurrency historical datasets for 80 cryptocurrencies including but not limited to Bitcoin (BTC), Ethereum (ETH), Binance Coin (BNB), Cardano (ADA), Tether (USDT), Ripple (XRP), Solana (SOL), Polkadot (DOT), USD Coin (USDC), Dogecoin (DOGE), Tron (TRX), Bitcoin Cash (BCH), Litecoin (LTC), EOS (EOS), Cosmos (ATOM), Stellar (XLM), Wrapped Bitcoin (WBTC), Uniswap (UNI), Terra (LUNA), SHIBA INU (SHIB), and 60 more cryptocurrencies were uploaded in this online Mendeley data repository. Although the primary attribute of including the mentioned cryptocurrencies was the Market Capitalization, a subject matter expert i.e., a professional trader has also guided the initial selection of the cryptocurrencies by analyzing various indicators such as Relative Strength Index (RSI), Moving Average Convergence/Divergence (MACD), MYC Signals, Bollinger Bands, Fibonacci Retracement, Stochastic Oscillator and Ichimoku Cloud. The primary features of this dataset that were used as the decision-making criteria of the CLUS-MCDA II approach are Timestamps, Open, High, Low, Closed, Volume (Currency), % Change (7 days and 24 hours), Market Cap and Weighted Price values. The available excel and CSV files in this data set are just part of the integrated data and other databases, datasets and API References that was used in this study are as follows: [1] https://finance.yahoo.com/ [2] https://coinmarketcap.com/historical/ [3] https://cryptodatadownload.com/ [4] https://kaggle.com/philmohun/cryptocurrency-financial-data [5] https://kaggle.com/deepshah16/meme-cryptocurrency-historical-data [6] https://kaggle.com/sudalairajkumar/cryptocurrencypricehistory [7] https://min-api.cryptocompare.com/data/price?fsym=BTC&tsyms=USD [8] https://min-api.cryptocompare.com/ [9] https://p.nomics.com/cryptocurrency-bitcoin-api [10] https://www.coinapi.io/ [11] https://www.coingecko.com/en/api [12] https://cryptowat.ch/ [13] https://www.alphavantage.co/

This dataset is part of the CLUS-MCDA (Cluster analysis for improving Multiple Criteria Decision Analysis) and CLUS-MCDAII Project: https://aimaghsoodi.github.io/CLUSMCDA-R-Package/ https://github.com/Aimaghsoodi/CLUS-MCDA-II https://github.com/azadkavian/CLUS-MCDA