The Litecoin cryptocurrency peaked in both 2017 and 2020, reaching prices worth around 250 dollars, but did not reach this by 2022. As of November 13, 2025, one Litecoin token was worth 97.49 U.S. dollars. Litecoin's price was relatively volatile recently, revealing high price swings between months.What is a cryptocurrency?Cryptocurrencies are digital currencies that do not have a centralized regulating authority. The first of these, Bitcoin, introduced a technology called blockchain, in which a distributed ledger records every transaction on every bitcoin in circulation to prevent fraud. Litecoin also uses this technology. To accommodate the demands of constant ledger updates, users sell computational power in exchange for an amount of Litecoin, a process known as mining.More about LitecoinCryptocurrencies are still an emerging technology, and few are using them for transactions. As such, most users are speculators who look at the value of all coins in circulation as the market capitalization rather than money supply. Still, the average number of Litecoin transactions ranges in the tens of thousands, meaning that the cryptocurrency has a substantial financial footprint.

All-time high price data for Litecoin, including the peak value, date achieved, and current comparison metrics.

Litecoin's market cap in early 2020 was the highest ever-recorded, topping over *********** U.S. dollars and a value that had increased by 100 percent since ***********. Market capitalization figures are calculated by multiplying the total number of Litecoin in circulation by the Litecoin price. Compared to both the Bitcoin market capitalization as well as the Ethereum market cap, though, Litecoin's figures were significantly smaller.

Litecoin price data for 2025-11-23 including currency, value, high, low, open, close, and percentage difference.

The Litecoin (LTC) trading market, while smaller than Bitcoin's, exhibits significant growth potential. Analyzing the provided data (assuming a market size of, for example, $10 billion in 2025 and a CAGR of 15% – figures commonly observed in the cryptocurrency space), we project substantial expansion over the forecast period (2025-2033). Key drivers include the increasing adoption of cryptocurrencies as an alternative investment asset, the relatively low transaction fees compared to Bitcoin, and Litecoin's established presence within the broader cryptocurrency ecosystem. Emerging trends like decentralized finance (DeFi) and the growing integration of cryptocurrencies into traditional financial services further bolster the market's outlook. However, regulatory uncertainty remains a significant restraint, along with the inherent volatility of the cryptocurrency market and competition from other altcoins. Segment-wise, we can anticipate robust growth in both institutional and retail trading, with the former gaining traction as regulatory clarity improves and institutional investors become more comfortable with crypto assets. Major players like Binance, Coinbase (not explicitly listed but a significant player), and others mentioned will likely continue to dominate the market, although new entrants and innovative trading platforms could disrupt the landscape. Regional data would show variations, with regions having higher cryptocurrency adoption rates generally exhibiting larger market shares. The projection for the Litecoin trading market suggests a compound annual growth rate (CAGR) that, given the inherent volatility of cryptocurrencies, is likely to fluctuate year-on-year. However, a sustained period of growth is expected, driven by factors like increased institutional investment, the expanding utility of Litecoin within the DeFi space, and mainstream acceptance of cryptocurrencies. The market will also see increasing competition amongst exchanges, likely resulting in tighter margins and a push towards innovation in trading services. Geopolitical factors and regulatory changes across different jurisdictions will also significantly impact regional market shares, potentially leading to shifts in trading volume and market dominance. The long-term outlook for Litecoin trading hinges on the overall maturation of the cryptocurrency market and its broader integration into the global financial system.

Litecoin Trading Market Outlook

The global Litecoin trading market size was valued at approximately USD 2.5 billion in 2023 and is projected to reach around USD 10 billion by 2032, growing at a robust CAGR of 16.2% from 2024 to 2032. The primary growth factors driving this market include increased adoption of cryptocurrencies, advancements in blockchain technology, and the rise of decentralized finance (DeFi) platforms.

One of the significant growth drivers of the Litecoin trading market is the increasing acceptance of cryptocurrencies in various sectors. With more businesses and institutions embracing digital currency for transactions, Litecoin has seen a significant uptick in trading volumes. The ease of transaction, lower fees, and faster processing times compared to traditional banking systems are encouraging more users to adopt Litecoin, thereby boosting the trading market.

Another crucial factor contributing to the growth of the Litecoin trading market is the advancement in blockchain technology. Continuous improvements in blockchain security, scalability, and interoperability are making Litecoin a more attractive option for traders. Enhanced security measures are crucial in gaining the trust of both retail and institutional investors, while scalability ensures that the network can handle increasing transaction volumes without compromising speed. Interoperability with other blockchain networks further increases the utility and liquidity of Litecoin, making it a preferred choice for traders.

The rise of decentralized finance (DeFi) platforms is also playing a pivotal role in driving the Litecoin trading market. DeFi platforms offer various financial services like lending, borrowing, and trading without the need for traditional intermediaries like banks. The integration of Litecoin into these platforms has significantly boosted its trading volumes. Moreover, DeFi platforms provide a level of financial inclusivity and transparency that traditional financial systems cannot match, attracting a younger, tech-savvy demographic to Litecoin trading.

In terms of regional outlook, North America remains one of the most prominent markets for Litecoin trading, driven by technological advancements and high cryptocurrency adoption rates. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period. The increasing number of cryptocurrency exchanges and favorable regulatory frameworks in countries like Japan, South Korea, and Singapore are some of the key factors driving the market in this region. European markets, especially in countries like Germany and Switzerland, are also showing promising growth due to progressive regulatory stances and high levels of digital innovation.

Trading Type Analysis

Spot trading is one of the most prevalent forms of Litecoin trading. In spot trading, assets are exchanged instantly between buyers and sellers at the current market price. This type of trading is highly favored for its simplicity and immediacy, making it an attractive option for beginner traders. The ease of entry and straightforward mechanics make spot trading accessible to a broad audience, thus contributing significantly to the overall trading volume in the Litecoin market.

Margin trading, on the other hand, allows traders to borrow funds to increase their trading position, offering the potential for higher returns. This type of trading is more complex and involves a higher risk, attracting more experienced traders. The appeal of margin trading lies in its capability to amplify potential profits, although it also increases the risk of significant losses. The growing number of platforms offering margin trading services for Litecoin is expected to further propel its market growth.

Futures trading is another crucial segment within the Litecoin trading market. In futures trading, contracts are made to buy or sell Litecoin at a predetermined price at a future date. This type of trading is particularly popular among institutional investors looking to hedge against price volatility. The increasing participation of institutional investors in Litecoin futures trading is providing additional market liquidity and stability, which is beneficial for the overall market growth.

The growing sophistication of trading tools and platforms is also driving the popularity of different trading types. Advanced algorithms and AI-driven analytics are making it easier for traders to execute complex trades and manage risks more effectively. This is not only attracting more reta

Context

Real and up to date stock market exchange of cryptocurrencies can be quite expensive and are hard to get. However, historical financial data are the starting point to develop algorithm(s) to analyze market trend and why not beat the market by predicting market movement.

Content

Data provided in this dataset are historical data from the beginning of LTC-USD pair market on Kraken exchange up to the present (2021 December). This data comes frome real trades on one of the most popular cryptocurrencies exchange.

Trading history

Historical market data, also known as trading history, time and sales or tick data, provides a detailed record of every trade that happens on Kraken exchange, and includes the following information: - Timestamp - The exact date and time of each trade. - Price - The price at which each trade occurred. - Volume - The amount of volume that was traded.

OHLCVT

In addition, OHLCVT data are provided for the most common period interval: 1 min, 5 min, 15 min, 1 hour, 12 hours and 1 day. OHLCVT stands for Open, High, Low, Close, Volume and Trades and represents the following trading information for each time period: - Open - The first traded price - High - The highest traded price - Low - The lowest traded price - Close - The final traded price - Volume - The total volume traded by all trades - Trades - The number of individual trades

Don't hesitate to tell me if you need other period interval 😉 ...

Update

This dataset will be updated every quarter to add new and up to date market trend. Let me know if you need an update more frequently.

Inspiration

Can you beat the market? Let see what you can do with these data!

Introduction: The "Cryptocurrency Price Analysis Dataset: BTC, ETH, XRP, LTC (2018-2023)" is a comprehensive dataset that captures the daily price movements of six popular cryptocurrencies. It covers a period from January 1, 2018, to May 31, 2023, providing a valuable resource for researchers, analysts, and enthusiasts interested in studying the historical price behavior of these digital assets.

Description: This dataset contains a wealth of information for six major cryptocurrencies: Bitcoin (BTC), Ethereum (ETH), Ripple (XRP), and Litecoin (LTC). The data spans a time frame of over five years, enabling users to explore long-term trends, analyze volatility patterns, and gain insights into market dynamics.

Columns:

1. Crypto: This column specifies the name of the cryptocurrency (e.g., BTC, ETH, XRP, LTC).
2. Date: The date on which the price data was recorded.
3. Open: The opening price of the cryptocurrency at the beginning of the day.
4. High: The highest price reached by the cryptocurrency during the day.
5. Low: The lowest price reached by the cryptocurrency during the day.
6. Close: The closing price of the cryptocurrency at the end of the day.

Use Cases: The dataset offers numerous possibilities for analysis and research within the field of cryptocurrencies. Here are a few potential use cases:

1. Price Analysis: Researchers can investigate the historical price movements of each cryptocurrency to identify trends, patterns, and potential correlations between different assets.
2. Volatility Study: The dataset enables the study of volatility in cryptocurrency markets, helping users understand the frequency and magnitude of price fluctuations.
3. Market Performance: Analysts can analyze the performance of individual cryptocurrencies over time, comparing returns and risk measures to assess their investment potential.
4. Trading Strategies: Traders can utilize the dataset to develop and backtest trading strategies based on technical indicators, price patterns, or machine learning algorithms.
5. Sentiment Analysis: Combine this dataset with external sentiment data to explore the relationship between market sentiment and cryptocurrency price movements. By sharing this dataset on Kaggle, you are providing a valuable resource to the data science community, encouraging collaborative research, and enabling the development of innovative models and solutions within the cryptocurrency domain.

Please note that this dataset is for educational and research purposes only and should not be used for making financial decisions without thorough analysis and consultation with financial professionals.

Litecoin Transaction Market Outlook

The Litecoin Transaction market size is projected to grow from USD 2.5 billion in 2023 to USD 9.8 billion by 2032, with a compound annual growth rate (CAGR) of 16.5%. Key growth factors include increasing adoption of cryptocurrencies in various sectors and advancements in blockchain technology, promoting secure and fast transactions.

One of the primary growth factors driving the Litecoin transaction market is the increasing acceptance of cryptocurrencies among mainstream businesses and financial institutions. As more companies recognize the benefits of cryptocurrencies such as lower transaction fees and faster processing times, the demand for Litecoin and similar digital assets is expected to rise. Additionally, the widespread integration of blockchain technology in various industries is promoting a secure, decentralized system, further boosting the market.

Moreover, the regulatory environment surrounding cryptocurrencies is gradually becoming more favorable, encouraging market growth. Governments worldwide are acknowledging the importance of digital currencies and are working towards creating frameworks that support their use. This shift in regulatory stance is likely to increase investor confidence and spur further adoption of Litecoin, thus driving the market forward. Additionally, advancements in technology, such as improvements in the scalability and security of blockchain networks, are reducing barriers to entry for new users and enhancing the overall user experience.

The increasing penetration of internet and mobile devices is another significant factor contributing to the growth of the Litecoin transaction market. With the rise of e-commerce and digital payment platforms, consumers are increasingly seeking faster and more secure transaction methods. Litecoin, with its quick transaction speeds and low fees, fits this requirement perfectly, making it an attractive option for online shoppers and businesses alike. This growing trend is expected to continue driving the market's expansion over the forecast period.

From a regional perspective, North America currently holds the largest share of the Litecoin transaction market, driven by the high adoption rate of cryptocurrencies and advanced technological infrastructure. However, the Asia-Pacific region is anticipated to witness the fastest growth, attributed to the increasing number of internet users, rising popularity of digital payment systems, and supportive regulatory developments in countries such as Japan and South Korea. These factors collectively create a robust growth environment for the Litecoin transaction market in the region.

Transaction Type Analysis

The Litecoin transaction market can be segmented by transaction type into Peer-to-Peer Transfers, Merchant Services, Remittances, and Others. Each of these segments plays a crucial role in the overall market dynamics, with distinct characteristics and growth drivers. Peer-to-Peer transfers represent one of the foundational uses of Litecoin, enabling users to send and receive funds directly without intermediaries. This segment has been a significant contributor to the market due to the transparency and low transaction costs associated with Litecoin.

Merchant Services, another critical segment, involves the use of Litecoin for purchasing goods and services. With an increasing number of merchants accepting cryptocurrencies, this segment is poised for substantial growth. The low fees and quick transaction times offered by Litecoin make it an attractive option for both merchants and consumers. As more businesses integrate Litecoin payment options, this segment is expected to continue its upward trajectory.

Remittances represent a significant portion of the Litecoin transaction market, particularly in regions with high cross-border transfer volumes. Litecoin's low transaction fees and fast processing times make it an ideal solution for international money transfers. This segment's growth is bolstered by the increasing migration and the need for efficient remittance services. As more people become aware of the benefits of using Litecoin for remittances, this segment is likely to see accelerated growth.

The 'Others' category encompasses various niche applications of Litecoin transactions, such as charitable donations, tipping, and micropayments. These use cases, while smaller in volume compared to the primary segments, contribute to the overall diversity and robustness of the Litecoin transaction market. As innovative

Find my notebook : Advanced EDA & Data Wrangling - Crypto Market Data where I cover the full EDA and advanced data wrangling to get beautiful dataset ready for analysis.

Find my Deep Reinforcement Learning v1 notebook: "https://www.kaggle.com/code/franoisgeorgesjulien/deep-reinforcement-learning-for-trading">Deep Reinforcement Learning for Trading

Find my Quant Analysis notebook:"https://www.kaggle.com/code/franoisgeorgesjulien/quant-analysis-visualization-btc-v1">💎 Quant Analysis & Visualization | BTC V1

Dataset Presentation:

This dataset provides a comprehensive collection of hourly price data for 34 major cryptocurrencies, covering a time span from January 2017 to the present day. The dataset includes Open, High, Low, Close, Volume (OHLCV), and the number of trades for each cryptocurrency for each hour (row).

Making it a valuable resource for cryptocurrency market analysis, research, and trading strategies. Whether you are interested in historical trends or real-time market dynamics, this dataset offers insights into the price movements of a diverse range of cryptocurrencies.

This is a pure gold mine, for all kind of analysis and predictive models. The granularity of the dataset offers a wide range of possibilities. Have Fun!

Ready to Use - Cleaned and arranged dataset less than 0.015% of missing data hour: crypto_data.csv

First Draft - Before External Sources Merge (to cover missing data points): crypto_force.csv

Original dataset merged from all individual token datasets: cryptotoken_full.csv

crypto_data.csv & cryptotoken_full.csv highly challenging wrangling situations: - fix 'Date' formats and inconsistencies - find missing hours and isolate them for each token - import external data source containing targeted missing hours and merge dataframes to fill missing rows

see notebook 'Advanced EDA & Data Wrangling - Crypto Market Data' to follow along and have a look at the EDA, wrangling and cleaning process.

Date Range: From 2017-08-17 04:00:00 to 2023-10-19 23:00:00

Date Format: YYYY-MM-DD HH-MM-SS (raw data to be converted to datetime)

Data Source: Binance API (some missing rows filled using Kraken & Poloniex market data)

Crypto Token in the dataset (also available as independent dataset): - 1INCH - AAVE - ADA (Cardano) - ALGO (Algorand) - ATOM (Cosmos) - AVAX (Avalanche) - BAL (Balancer) - BCH (Bitcoin Cash) - BNB (Binance Coin) - BTC (Bitcoin) - COMP (Compound) - CRV (Curve DAO Token) - DENT - DOGE (Dogecoin) - DOT (Polkadot) - DYDX - ETC (Ethereum Classic) - ETH (Ethereum) - FIL (Filecoin) - HBAR (Hedera Hashgraph) - ICP (Internet Computer) - LINK (Chainlink) - LTC (Litecoin) - MATIC (Polygon) - MKR (Maker) - RVN (Ravencoin) - SHIB (Shiba Inu) - SOL (Solana) - SUSHI (SushiSwap) - TRX (Tron) - UNI (Uniswap) - VET (VeChain) - XLM (Stellar) - XMR (Monero)

Date column presents some inconsistencies that need to be cleaned before formatting to datetime: - For column 'Symbol' and 'ETCUSDT' = '23-07-27': it is missing all hours (no data, no hourly rows for this day). I fixed it by using the only one row available for that day and duplicated the values for each hour. Can be fixed using this code:

start_timestamp = pd.Timestamp('2023-07-27 00:00:00')
end_timestamp = pd.Timestamp('2023-07-27 23:00:00')

hourly_timestamps = pd.date_range(start=start_timestamp, end=end_timestamp, freq='H')

hourly_data = {
  'Date': hourly_timestamps,
  'Symbol': 'ETCUSDT',
  'Open': 18.29,
  'High': 18.3,
  'Low': 18.17,
  'Close': 18.22,
  'Volume USDT': 127468,
  'tradecount': 623,
  'Token': 'ETC'
}

hourly_df = pd.DataFrame(hourly_data)
df = pd.concat([df, hourly_df], ignore_index=True)

df = df.drop(550341)

• Some rows for 'Date' have extra digits '.000' '.874' etc.. instead of the right format YYYY-MM-DD HH-MM-SS. To clean it you can use the following code:

# Count the occurrences of the pattern '.xxx' in the 'Date' column
count_occurrences_before = df['Date'].str.count(r'\.\d{3}')
print("Occurrences before cleaning:", count_occurrences_before.sum()) 

# Remove '.xxx' pattern from the 'Date' column
df['Date'] = df['Date'].str.replace(r'\.\d{3}', '', regex=True)

# Count the occurrences of the pattern '.xxx' in the 'Date' column after cleaning
count_occurrences_after = df['Date'].str.count(r'\.\d{3}')
print("Occurrences after cleaning:", count_occurrences_after.sum()) 

**Disclaimer: Any individual or entity choosing to engage in market analysis, develop predictive models, or utilize data for trading purposes must do so at their own discretion and risk. It is important to understand that trading involves potential financial loss, and decisions made in the financial mar...

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

Context

Real and up to date stock market exchange of cryptocurrencies can be quite expensive and are hard to get. However, historical financial data are the starting point to develop algorithm(s) to analyze market trend and why not beat the market by predicting market movement.

Content

Data provided in this dataset are historical data from the beginning of LTC-ETH pair market on Kraken exchange up to the present (2021 December). This data comes frome real trades on one of the most popular cryptocurrencies exchange.

Trading history

Historical market data, also known as trading history, time and sales or tick data, provides a detailed record of every trade that happens on Kraken exchange, and includes the following information: - Timestamp - The exact date and time of each trade. - Price - The price at which each trade occurred. - Volume - The amount of volume that was traded.

OHLCVT

In addition, OHLCVT data are provided for the most common period interval: 1 min, 5 min, 15 min, 1 hour, 12 hours and 1 day. OHLCVT stands for Open, High, Low, Close, Volume and Trades and represents the following trading information for each time period: - Open - The first traded price - High - The highest traded price - Low - The lowest traded price - Close - The final traded price - Volume - The total volume traded by all trades - Trades - The number of individual trades

Don't hesitate to tell me if you need other period interval 😉 ...

Update

This dataset will be updated every quarter to add new and up to date market trend. Let me know if you need an update more frequently.

Inspiration

Can you beat the market? Let see what you can do with these data!

Context

Real and up to date stock market exchange of cryptocurrencies can be quite expensive and are hard to get. However, historical financial data are the starting point to develop algorithm(s) to analyze market trend and why not beat the market by predicting market movement.

Content

Data provided in this dataset are historical data from the beginning of LTC-AUD pair market on Kraken exchange up to the present (2021 December). This data comes frome real trades on one of the most popular cryptocurrencies exchange.

Trading history

Historical market data, also known as trading history, time and sales or tick data, provides a detailed record of every trade that happens on Kraken exchange, and includes the following information: - Timestamp - The exact date and time of each trade. - Price - The price at which each trade occurred. - Volume - The amount of volume that was traded.

OHLCVT

In addition, OHLCVT data are provided for the most common period interval: 1 min, 5 min, 15 min, 1 hour, 12 hours and 1 day. OHLCVT stands for Open, High, Low, Close, Volume and Trades and represents the following trading information for each time period: - Open - The first traded price - High - The highest traded price - Low - The lowest traded price - Close - The final traded price - Volume - The total volume traded by all trades - Trades - The number of individual trades

Don't hesitate to tell me if you need other period interval 😉 ...

Update

This dataset will be updated every quarter to add new and up to date market trend. Let me know if you need an update more frequently.

Inspiration

Can you beat the market? Let see what you can do with these data!

Daily historical price data for Litecoin including high, low, open, close, and percentage difference over the most recent 24 days.

Context

Real and up to date stock market exchange of cryptocurrencies can be quite expensive and are hard to get. However, historical financial data are the starting point to develop algorithm(s) to analyze market trend and why not beat the market by predicting market movement.

Content

Data provided in this dataset are historical data from the beginning of LTC-GBP pair market on Kraken exchange up to the present (2021 December). This data comes frome real trades on one of the most popular cryptocurrencies exchange.

Trading history

Historical market data, also known as trading history, time and sales or tick data, provides a detailed record of every trade that happens on Kraken exchange, and includes the following information: - Timestamp - The exact date and time of each trade. - Price - The price at which each trade occurred. - Volume - The amount of volume that was traded.

OHLCVT

In addition, OHLCVT data are provided for the most common period interval: 1 min, 5 min, 15 min, 1 hour, 12 hours and 1 day. OHLCVT stands for Open, High, Low, Close, Volume and Trades and represents the following trading information for each time period: - Open - The first traded price - High - The highest traded price - Low - The lowest traded price - Close - The final traded price - Volume - The total volume traded by all trades - Trades - The number of individual trades

Don't hesitate to tell me if you need other period interval 😉 ...

Update

This dataset will be updated every quarter to add new and up to date market trend. Let me know if you need an update more frequently.

Inspiration

Can you beat the market? Let see what you can do with these data!

BackgroundThough mass evacuation may increase the need for long-term care (LTC) services, how the need for LTC services increases and how the public LTC system affects it is not well understood. We evaluated changes in public LTC benefits for the people living in the mandatory evacuation areas established after the 2011 Fukushima nuclear disaster and examined the roles of the universal LTC insurance system in Japan.MethodsIn order to evaluate the effect of the mandatory evacuation on LTC benefits, we examined the trends of LTC benefits in the Fukushima evacuation group and the nationwide non-evacuation group. We first decomposed per-elderly-individual benefits at the municipality level into the LTC certification rate and per-certified-individual benefits, and then implemented difference-in-differences analysis using these variables as outcomes.ResultsPer-elderly-individual benefits significantly increased from 2012 onward in the evacuation group, and this was explained by an increase in the certification rate rather than in per-certified-individual benefits. Increases in per-elderly-individual benefits and the certification rate in the post-disaster period were observed in all but the highest care level, and the corresponding outcomes for the highest care level decreased immediately after the disaster. We also found that the increase in the certification rate had been mostly realized by an increase in the number of certified individuals.ConclusionsThe increase in LTC benefits can be associated with the impact of the increase in the number of people newly certified to receive LTC benefits after the mandatory evacuation. In order to cope with the increase in utilization of long-term care and associated costs after disasters in aging societies, both formal long-term care services and social support for informal care for evacuees should be considered important.

Litecoin reached its all-time high price on May 10, 2021.

Litecoin price data for 2025-12-01 including currency, value, high, low, open, close, and percentage difference.

Litecoin price data for 2025-11-30 including currency, value, high, low, open, close, and percentage difference.

Litecoin price data for 2025-11-29 including currency, value, high, low, open, close, and percentage difference.