Ukraine's commerce and industry sectors were estimated to suffer the highest losses from the Russian invasion that started on February 24, 2022, at around 214 billion U.S. dollars. The estimate includes the period from February 24, 2022, to June 30, 2026. Furthermore, the Ukrainian agricultural sector's losses were calculated at approximately 73 billion U.S. dollars over the same period. In total, monetary losses of the country were estimated at 589 billion U.S. dollars.

Following the announcement of sweeping tariffs on all countries by Donald Trump, ************* became the day with the third-highest point losses for the Dow Jones Industrial Average in history. Worse than the loss experienced on that day were only the losses that occurred following the beginning of the COVID-19 pandemic. The Dow Jones Industrial Average posted significant points losses due to the global impact of the coronavirus pandemic in 2020. With stocks falling sharply, the Dow recorded its worst single-day points drop ever, plunging ***** points – nearly ** percent – on **************.

The DXY exchange rate rose to 99.4202 on December 2, 2025, up 0.01% from the previous session. Over the past month, the United States Dollar has weakened 0.45%, and is down by 6.53% over the last 12 months. United States Dollar - values, historical data, forecasts and news - updated on December of 2025.

Graph and download economic data for Consumer Price Index for All Urban Consumers: Purchasing Power of the Consumer Dollar in U.S. City Average (CUUR0000SA0R) from Jan 1913 to Sep 2025 about urban, consumer, CPI, inflation, price index, indexes, price, and USA.

United States - Domestic Finance Companies, Reserves for Losses, Flow was 74.88000 Mil. of $ in April of 2025, according to the United States Federal Reserve. Historically, United States - Domestic Finance Companies, Reserves for Losses, Flow reached a record high of 9155.96000 in January of 2020 and a record low of -8997.23000 in October of 2009. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Domestic Finance Companies, Reserves for Losses, Flow - last updated from the United States Federal Reserve on November of 2025.

Series Name: Direct economic loss in the housing sector attributed to disasters (current United States dollars)Series Code: VC_DSR_HOLHRelease Version: 2021.Q2.G.03 This dataset is part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 1.5.2: Direct economic loss attributed to disasters in relation to global gross domestic product (GDP)Target 1.5: By 2030, build the resilience of the poor and those in vulnerable situations and reduce their exposure and vulnerability to climate-related extreme events and other economic, social and environmental shocks and disastersGoal 1: End poverty in all its forms everywhereFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

Total cryptocurrency losses were valued at over ** billion U.S. dollars between 2021 and 2024, although most of these came from early in the period mentioned. This is according to data from web 3 crowdsourced security platform Immunefi. While the source does not clearly state how it estimated its figures, it claims most losses occurred in Q2 2021 - citing the fraud cases of Africrypt, with a *** billion U.S. dollar loss, and Thodex, with a *** billion U.S. dollar loss. Much like the annual value of cryptocurrency losses from REKT Database, Immunefi seems to rely on publicly available data, and community reporting. This is not unusual for digital assets, as they are decentralized - meaning these are not tracked "officially" by government or regulatory bodies.

View monthly updates and historical trends for S&P 500 Market Cap. from United States. Source: Standard and Poor's. Track economic data with YCharts analy…

Series Name: Direct economic loss attributed to disasters (current United States dollars)Series Code: VC_DSR_GDPLSRelease Version: 2021.Q2.G.03 This dataset is the part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 1.5.2: Direct economic loss attributed to disasters in relation to global gross domestic product (GDP)Target 1.5: By 2030, build the resilience of the poor and those in vulnerable situations and reduce their exposure and vulnerability to climate-related extreme events and other economic, social and environmental shocks and disastersGoal 1: End poverty in all its forms everywhereFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

As of June 17, 2024, the most shorted stock was for, the American holographic technology services provider, MicroCloud Hologram Inc., with 66.64 percent of their total float having been shorted. This is a change from mid-January 2021, when video game retailed GameStop had an incredible 121.07 percent of their available shares in a short position. In effect this means that investors had 'borrowed' more shares (with a future promise to return them) than the total number of shares available for public trading. Owing to this behavior of professional investors, retail investors enacted a campaign to drive up the stock price of Gamestop, leading to losses of billions when investors had to repurchase the stock they had borrowed. At this time, a similar – but less effective – social media campaign was also carried out for the stock price of cinema operator AMC, and the price of silver. What is short selling? Short selling is essentially where an investor bets on a share price falling by: borrowing a number of shares selling these shares while the price is still high; purchasing the same number again once the price falls; then returning the borrowed shares at a profit. Of course, a profit will only be made if the share price does fall; should the share price rise the investor will then need to purchase the shares back at a higher price, and thus incur a loss. Short selling can lead to some very large profits in a short amount of time, with Tesla stock generating over one billion dollars in short sell profits during the first week of March 2020 alone, owing to the financial crash caused by the coronavirus (COVID-19) pandemic. However, owing to the short-term, opportunistic nature of short selling, these returns look less impressive when considered as net profits from short sell positions over the full year. The risks of short selling Short selling carries greater risks than traditional investments, and for this reason financial advisors often recommend against this strategy for ‘retail’ (i.e. non-professional) investors. The reason for this is that losses from short selling are potentially uncapped, whereas losses from traditional investments are limited to the initial cost. For example, if someone purchases 100 dollars of shares, the maximum they can lose is the 100 dollars the spent on those shares. However, say someone borrows 100 dollars of shares instead, betting on the price falling. If these shares are then sold for 100 dollars but the price subsequently rises, the losses could greatly exceed the initial investment should the price rise to, say, 500 dollars. The risks of short selling can be seen by looking again at Tesla, with the company causing the greatest losses over 2020 from short selling at over 40 billion U.S. dollars.

The global insurance industry had lost *** billion U.S. dollars due to the COVID-19 pandemic as of May 2020. Estimates for the total losses the market will experience in 2020 range from ** to *** billion U.S. dollars according to Willis Towers Watson, whereas Bank of America's estimates range from ** to ** billion U.S. dollars.

This dataset provides a comprehensive overview of the financial losses due to various types of cybercrime in all 50 states and Washington D.C. in the United States for the years 2020 and 2021. The dataset is curated with detailed attention to demographic and regional variances, as well as the types of cybercrime that occurred. The data for individual crimes was extracted from the Internet Crime Complaint Centre, a unit under the FBI (Federal Bureau of Investigation).

The columns in this dataset are:

• s/n: Serial Number.
• State: The US state in which the cybercrimes occurred.
• Year: The year of the cybercrimes (2020 or 2021).
• Population: The population of the state for the given year.
• Totalcrime_count: The total count of all cybercrimes in the state for the given year.
• Totalcrime_loss: The total financial loss (in US dollars) due to all cybercrimes in the state for the given year.
• Bec_count: The count of Business Email Compromise (BEC) incidents in the state for the given year.
• Bec_loss: The total financial loss (in US dollars) due to BEC in the state for the given year.
• Romance_counts: The count of romance scam incidents in the state for the given year.
• Romance_loss: The total financial loss (in US dollars) due to romance scams in the state for the given year.
• Creditcard_count: The count of credit card fraud incidents in the state for the given year.
• Creditcard_loss: The total financial loss (in US dollars) due to credit card fraud in the state for the given year.
• Databreach_count: The count of data breach incidents in the state for the given year.
• Databreach_loss: The total financial loss (in US dollars) due to data breaches in the state for the given year.
• GovtImp_count: The count of government impersonation fraud incidents in the state for the given year.
• GovtImp_loss: The total financial loss (in US dollars) due to government impersonation fraud in the state for the given year.
• Age<20_count: The count of cybercrime victims under the age of 20.
• Age<20_loss: The total financial loss (in US dollars) for victims under the age of 20.
• Age<29_count: The count of cybercrime victims between the ages of 20 and 29.
• Age<29_loss: The total financial loss (in US dollars) for victims between the ages of 20 and 29.
• Age<39_count: The count of cybercrime victims between the ages of 30 and 39.
• Age<39_loss: The total financial loss (in US dollars) for victims between the ages of 30 and 39.
• Age<49_count: The count of cybercrime victims between the ages of 40 and 49.
• Age<49_loss: The total financial loss (in US dollars) for victims between the ages of 40 and 49.
• Age<59_count: The count of cybercrime victims between the ages of 50 and 59.
• Age<59_loss: The total financial loss (in US dollars) for victims between the ages of 50 and 59.
• Age>60_count: The count of cybercrime victims aged 60 and above.
• Age>60_loss: The total financial loss (in US dollars) for victims aged 60 and above.

This dataset is ideal for those who wish to investigate trends in cybercrime across different US states, the financial impact of various types of cybercrime, or the impact of cybercrime on different age groups. It can also be used to generate insights for developing strategies to combat cybercrime, implementing protective measures, and raising awareness about this growing issue. The crime data contained herein was extracted from the Internet Crime Complaint Centre, a unit under the FBI, which ensures its authenticity and reliability.

When converted to the value of one US dollar in 2020, goods and services that cost one dollar in 1700 would cost just over 63 dollars in 2020, this means that one dollar in 1700 was worth approximately 63 times more than it is today. This data can be used to calculate how much goods and services from the years shown would cost today, by multiplying the price from then by the number shown in the graph. For example, an item that cost 50 dollars in 1970 would theoretically cost 335.5 US dollars in 2020 (50 x 6.71 = 335.5), although it is important to remember that the prices of individual goods and services inflate at different rates than currency, therefore this graph must only be used as a guide.

Weather catastrophes caused economic losses of *** billion U.S. dollars worldwide in 2021. Sudden cataclysmic disasters cause devastation on impact. Some weather and climate-related extreme events are storms, floods, heat waves, cold waves, droughts, and forest fires. Climate-related hazards pose risks to human health and can lead to substantial economic losses. Global natural disaster economic loss The economic damage caused by disasters varies based on geography and affects natural resources. Capital assets and infrastructure, along with the loss of life, disrupt the economic structure. In 2021, the economic loss due to natural disasters globally was about *** billion U.S. dollars, and flooding generated the highest loss that year. Billion-dollar natural disaster events in the United States The United States experienced nearly two dozen billion-dollar disasters in 2021. At an economic loss of around ** billion U.S. dollars, Hurricane Ida, a Category * storm that landed on the Louisiana coast in August, was the costliest.

The NZD/USD exchange rate fell to 0.5730 on December 2, 2025, down 0.11% from the previous session. Over the past month, the New Zealand Dollar has strengthened 0.39%, but it's down by 2.68% over the last 12 months. New Zealand Dollar - values, historical data, forecasts and news - updated on December of 2025.

In 2024, the economic losses due to natural disasters worldwide amounted to about *** billion U.S. dollars. Natural disasters occur as a result of natural processes on Earth. Many different types of natural disasters can occur, including floods, hurricanes, earthquakes, and tsunamis. Natural disasters in 2024 Tropical cyclones generated the highest amount of economic losses in 2024 with *** billion U.S. dollars worldwide. Hurricanes Helene and Milton were the most destructive events worldwide that year with over 100 billion U.S. dollars in economic losses. Flooding events ranked second in the costliest events in 2024, with flooding in Valencia, Spain, and South and Central China being the worst examples. Asia hardest hit by natural disasters A highly destructive force, Asia is one of the most susceptible regions to natural disasters. The repercussions of natural disasters are not only physical, but also economic. Costs may be high – depending on the severity – as areas affected by natural disasters might need to be rebuilt. Lower income countries are more likely to be affected by natural disasters for a multitude of reasons, including a lack of developed infrastructure, inadequate housing, and lack of back-resources.

In a 2020 survey, ** percent of supply chain decision-makers in the automotive and transportation industry responded they had lost ** to 100 million U.S. dollars due to supply chain issues related to the COVID-19 pandemic.

The damage to housing facilities from the Russian invasion of Ukraine was estimated at 57.6 billion U.S. dollars between February 24, 2022, and December 31, 2024. A further 36.7 billion U.S. dollars were recorded in losses from damages to transportation. The total war damage to Ukrainian sectors was estimated at 176 billion U.S. dollars over that period. War impact on the Ukrainian economy Ukraine’s gross domestic product (GDP) fell by 29 percent in 2022 as a result of the Russian invasion and was expected to grow by four percent in between 2023 and 2024. On the one hand, the country suffers from damage to its infrastructure which would require time and financial resources to be restored. On the other hand, the war threatens Ukraine’s international trade. The military actions disrupt the routes used for transporting goods for exports and imports. In July 2022, a deal has been signed between Russia and Ukraine in Istanbul to provide for a corridor for Ukrainian grain exports via the Black Sea; however, it was suspended a year after. Which are the largest industries in Ukraine? Wholesale and retail trade occupied the largest share of the GDP of Ukraine, at nearly 14 percent in 2021. Agriculture, having ranked second with over 10 percent, was another major sector, especially important for export trade. The value added by agriculture, forestry, and fishing reached over seven percent of Ukraine’s GDP in 2023.

Global commercial aviation generated an estimated profit of **** billion U.S. dollars in 2024, marking the second year of worldwide recovery following the pandemic downturn between 2020 and 2022. North American carriers led the industry with profits of 11.5 billion dollars, the highest regional margin, while their African counterparts reported 0.2 billion dollars in profit.
Middle Eastern airlines before and in the aftermath of COVID-19 The Middle Eastern airline companies have an ambitious plan to shift the center of global air transport towards their local region. The region’s largest carriers – Emirates, Etihad, and Qatar – exert high effort to position their respective countries as central hubs for intercontinental travel. Yet, the dynamics of global commercial airlines create a fiercely competitive environment difficult to resist. Up until around 2016, the region was consistently the fastest growing but the emergence of the coronavirus pandemic further worsened the profitability scenario in the Middle East. In 2020, the Middle Eastern airline groups incurred a net loss of just under ***** billion U.S. dollars. Reasons for low profits in the Middle East Analysts provide several reasons for the low profits of Middle Eastern airlines. One reason is a decline in demand relative to capacity. For example, Qatar Airways increased their available seat kilometers in 2019, while the number of passengers they carried slightly increased. Regional geopolitical tensions is one reason often given for this decline, both through direct effects (such as the Qatar blockade which commenced in 2017) and the indirect effect of leading passengers to not want to travel through the region. Other analysts argue that the large Middle Eastern airlines are simply less concerned with profits than their western counterparts, as they are owned by oil-funded governments who are more focused on gaining market share than profitability. Regardless of reasons, airlines in the Middle East are significantly less profitable than the industry average.

In 2021, X's (formerly Twitter) annual net loss amounted to *** million U.S. dollars. Overall, this is a significant decrease from the previous year, in which the micro blogging and social network company saw losses of almost *** billion U.S. dollars.