Warning Signs Market size was valued at USD 60.35 Billion in 2024 and is projected to reach USD 295.61 Billion by 2031, growing at a CAGR of 21.97% from 2024 to 2031.

Warning Signs Market Drivers

Increased Safety Regulations: Stricter safety regulations across various industries, including construction, manufacturing, and transportation, are driving the demand for warning signs. Industrial Growth: The expansion of industries, particularly in developing countries, creates a growing need for safety signage. Public Safety Concerns: The focus on public safety and accident prevention is driving the adoption of warning signs in public spaces, workplaces, and transportation infrastructure.

Warning Signs Market Restraints

Economic Downturns: Fluctuations in economic activity can impact construction, manufacturing, and other industries, affecting the demand for warning signs. Competition from Alternative Safety Measures: Other safety measures, such as personal protective equipment (PPE) and safety training, may compete with warning signs.

Thailand Probability of Fiscal Crisis data was reported at 0.055 NA in Aug 2018. This stayed constant from the previous number of 0.055 NA for Jul 2018. Thailand Probability of Fiscal Crisis data is updated monthly, averaging 0.269 NA from Jan 1971 (Median) to Aug 2018, with 572 observations. The data reached an all-time high of 0.690 NA in Apr 2009 and a record low of 0.055 NA in Aug 2018. Thailand Probability of Fiscal Crisis data remains active status in CEIC and is reported by Fiscal Policy Office. The data is categorized under Global Database’s Thailand – Table TH.F017: Government Finance: Fiscal Early Warning System.

Graph and download economic data for Real-time Sahm Rule Recession Indicator (SAHMREALTIME) from Dec 1959 to Jun 2025 about recession indicators, academic data, and USA.

The Ministry of Economic Affairs' Water Resources Agency's disaster emergency response team further combines rain, water level, reservoir and other real-time data, through computer technology calculations, providing real-time flood warnings for the public and relevant units. This allows the public to understand the risk of home flooding, prepare early, and reduce the occurrence of disasters. This dataset is linked to a Keyhole Markup Language (KML) file list, which is a markup language based on the XML syntax standard, used for geographical annotation. Documents written in the KML language are KML files, the same format as XML files, used in Google Earth related software for displaying geographical data. Many GIS-related systems now also use this format for the exchange of geographical data, with the KML format and encoding of this data being UTF-8.

The warning tape market has become an essential segment within the broader safety equipment industry, characterized by its critical role in enhancing safety and preventing accidents in various settings. Warning tapes, commonly known for their vibrant colors and distinct patterns, serve to alert individuals to potent

The Ministry of Economic Affairs' Water Resources Agency's Disaster Emergency Response Team, utilizing long-term disaster response experience, further combines real-time data such as rainfall, water levels, and reservoir levels, through computer technology to provide water level alerts to the public and relevant units. This helps people understand the risk of home flooding, prepare early, and reduce the occurrence of disasters. This dataset is linked to a Keyhole Markup Language (KML) file list, which is a markup language based on the eXtensible Markup Language (XML) syntax standard, developed and maintained by Google's Keyhole company for expressing geospatial annotations. Documents written in the KML language are referred to as KML files and are used in Google Earth-related software (Google Earth, Google Map, Google Maps for mobile, etc.) for displaying geospatial data. Many GIS-related systems now also use this format for geospatial data exchange, and the KML of this data uses UTF-8 encoding.

A winter storm warning provides NOAA customers and partners advanced notice of a hazardous winter weather event that endangers life or property or provides an impediment to commerce. Winter storm warnings are issued for winter weather phenomena like blizzards, ice storms, heavy sleet, and heavy snow. This performance indicator measures the accuracy of winter storm events. Improving the accuracy and advance warnings of winter storms enables the public to take the necessary steps to prepare for disruptive winter weather conditions.

By April 2026, it is projected that there is a probability of ***** percent that the United States will fall into another economic recession. This reflects a significant decrease from the projection of the preceding month.

Tornado Warnings are issued to enable the public to get out of harm’s way and mitigate preventable loss. NWS forecasters issue approximately 2,900 Tornado Warnings per year, primarily between the Rockies and Appalachian Mountains. Tornado Warning statistics are based on a comparison of warnings issued and weather spotter observations of tornadoes and/or storm damage surveys from Weather Forecast Offices in the United States. Lead Time (LT) for a Tornado Warning is the difference between the time the warning was issued and the time the tornado occurred (based on certified reports) in minutes, assuming the tornado tracked within the bounds of the warned area. Lead Times for all tornado occurrences within the U.S. are averaged to get this statistic for a given fiscal year. This average includes all warned events with zero lead times and all unwarned events. Lead Time is calculated down to the minute for individual Tornado Warnings and tornadic events. Although the timing of the warning transmission is recorded to the nearest second, typically there is only an estimate to the nearest minute of when a tornado touches down. Additionally, even though we can compute the average tornado warning lead time to a precision of 30 second increments or less, the reporting of this value implies greater accuracy in the data based on scientific and logistical restrictions on tornado reporting and surveying. Most tornadoes cannot be visually tracked from beginning to end and post-storm damage surveying is the official method with which the NWS categorizes tornado characteristics (intensity, path length & width) but must rely on radar data to estimate the timing of the tornado track.

As of June 9, 2020, the coronavirus outbreak posed a level ***** threat to businesses, meaning that severe and widespread economic impacts were likely. The composite index, which has level *** as its highest warning, was raised to level *** on March 12 and to level ***** on April 13.

Strong plans needed in response to coronavirus Countries are taking small steps on the road to economic recovery by gradually lifting lockdown measures. Manufacturing firms were among the first to return to work, and governments are now permitting shops, bars, and restaurants to reopen. However, there is no guarantee that consumers will return to their normal habits. In order to reduce the risks, businesses are being encouraged to activate contingency plans that include separating all essential operations from non-essential and focusing on high-priority areas and clients.

A focus on the U.S. economy COVID-19 has left the United States facing an economic crisis, and the country’s GDP fell by *** percent in the first quarter of 2020. Record numbers of Americans have lost their jobs during the pandemic, and the unemployment rate jumped to **** percent in April 2020. The Dow Jones, which monitors the stock prices of the ** largest companies in the United States, has rallied since the U.S. economy restarted but continues to feel the effects of a destructive period that wiped out years of gains in a matter of weeks.

Asia’s financial crisis in July 1997 affects currency, capital market, and real market throughout Asian countries. Countries in southeast region (ASEAN), including Indonesia, Malaysia, Philippines, Singapore, and Thailand, are some of the countries where the crisis hit the most. In these countries, where financial sectors are far more developed than real sectors and the money market sectors, most of the economic activities are conducted in capital market. Movement in the capital market could be a proxy to describe the overall economic situation and therefore the prediction of it could be an early warning system of economic crises. This paper tries to investigate movement in ASEAN (Indonesia, Malaysia, Philippines, Singapore, and Thailand) capital market to build an early warning system from financial sectors perspective. This paper will be very beneficial for the government to anticipate the forthcoming crisis. The insight of this paper is from Hamilton (1990) model of regime switching process in which he divide the movement of currency into two regimes, describe the switching transition based on Markov process and creates different model for each regimes. Differ from Hamilton, our research focuses on index return instead of currency to model the regime switching. This research aimed to find the probability of crisis in the future by combining the probability of switching and the probability distribution function of each regime. Probability of switching is estimated by categorizing the movement in index return into two regimes (negative return in regime 1 and positive return in regime 2) then measuring the proportion of switching to regime 1 in t given regime 1 in t-1 (P11) and to regime 2 in t given regime 2 in t-1 (P22). The probability distribution function of each regime is modeled using t-student distribution. This paper is able to give signal of the 1997/8 crisis few periods prior the crisis.

The Warning Signs market plays a crucial role in ensuring safety and compliance across various industries, including construction, transportation, and manufacturing. These signs serve as critical visual cues that alert individuals to potential hazards, guiding behavior and preventing accidents. As workplaces grow mo

The global market for Real-Time Flood Warning Systems is projected to reach $XXX million by 2033, expanding at a CAGR of XX% from 2025 to 2033. Increasing government regulations mandating flood warning systems, growing awareness about the economic and environmental impacts of floods, and technological advancements in sensing and communication technologies are the key factors driving market growth. Moreover, the increasing frequency and severity of flood events due to climate change are further fueling the demand for real-time flood warning systems. The market is segmented by type into hardware and software, and by application into government, agriculture, inland fisheries, transport and logistics, tourism and outdoor entertainment, and other. The hardware segment held the larger market share in 2025, and is expected to continue to dominate the market throughout the forecast period. However, the software segment is projected to exhibit a higher CAGR during the forecast period, due to the increasing adoption of cloud-based and AI-powered flood warning solutions. The government segment is the largest application segment, and is expected to continue to dominate the market throughout the forecast period. The agriculture segment is projected to exhibit the highest CAGR during the forecast period, due to the increasing demand for flood warning systems to protect crops and livestock. North America is the largest regional market, and is expected to continue to dominate the market throughout the forecast period. Asia Pacific is projected to exhibit the highest CAGR during the forecast period, due to the increasing government investments in flood warning infrastructure and the growing awareness about the economic and environmental impacts of floods.

The Water Resources Agency's disaster emergency response team of the Ministry of Economic Affairs further combines real-time data such as rainfall, water level, and reservoir information with long-term disaster response experience and computer technology to provide reservoir alerts for the public and relevant units. This helps the public understand the risk of home flooding, prepare early, and reduce the occurrence of disasters. This dataset is linked to a Keyhole Markup Language (KML) file list. This format is a markup language based on the XML (eXtensible Markup Language) syntax standard, developed and maintained by Keyhole, a subsidiary of Google, to express geographic annotations. Documents written in the KML language are KML files, which use the XML file format and are used in Google Earth related software (Google Earth, Google Map, Google Maps for mobile...) to display geographic data (including points, lines, polygons, polyhedra, and models...). Many GIS-related systems now also use this format for the exchange of geographic data, and the fields and codes of this data are all in UTF-8.

Thailand Index of Fiscal Alert data was reported at 0.000 NA in Aug 2018. This records a decrease from the previous number of 14.979 NA for Jul 2018. Thailand Index of Fiscal Alert data is updated monthly, averaging 23.068 NA from Jan 1971 (Median) to Aug 2018, with 572 observations. The data reached an all-time high of 162.632 NA in Sep 1998 and a record low of 0.000 NA in Aug 2018. Thailand Index of Fiscal Alert data remains active status in CEIC and is reported by Fiscal Policy Office. The data is categorized under Global Database’s Thailand – Table TH.F017: Government Finance: Fiscal Early Warning System.

Real Time Flood Warning System Market Outlook

The global market size for real-time flood warning systems is projected to experience significant growth from 2023 to 2032, with a compound annual growth rate (CAGR) of 6.7%. In 2023, the market size was valued at approximately $1.2 billion, and it is forecasted to reach around $2.1 billion by 2032, driven by several growth factors including advancements in technology, increasing frequency of flood events, and rising awareness about disaster management.

One of the key growth factors propelling the real-time flood warning system market is the increasing frequency and severity of flood events worldwide. Climate change has resulted in unusual weather patterns, leading to more frequent and severe flooding incidents. Governments and private organizations are investing heavily in flood warning systems to mitigate the impact of these natural disasters. The ability to provide timely and accurate flood warnings can save lives, protect property, and minimize economic losses, contributing to the growing demand for these systems.

Technological advancements in sensor technology and data analytics are also driving the growth of the real-time flood warning system market. Modern sensors can provide highly accurate real-time data on water levels, rainfall, and flow rates. Additionally, advancements in data analytics and machine learning allow for better prediction models and more effective flood warning systems. These technologies enable authorities to predict potential flood events more accurately and issue timely warnings, thereby enhancing the effectiveness of flood management strategies.

Another significant growth factor is the increasing awareness and emphasis on disaster management and preparedness. Governments, municipalities, and various organizations are recognizing the importance of being prepared for flood events. As a result, there is a growing investment in infrastructure and technology to support real-time flood warning systems. Public awareness campaigns and educational programs are also contributing to the increasing adoption of these systems, as communities become more aware of the benefits of having a reliable flood warning system in place.

Regionally, North America is expected to hold a significant share of the real-time flood warning system market, driven by stringent government regulations and high investments in flood management infrastructure. Europe and Asia Pacific are also anticipated to exhibit substantial growth due to increased flood incidents and rising investments in flood mitigation projects. Each region presents unique opportunities and challenges, contributing to the overall dynamics of the global market.

Component Analysis

The component segment of the real-time flood warning system market can be broadly categorized into hardware, software, and services. Each of these components plays a crucial role in the overall functionality and effectiveness of flood warning systems. Hardware components include sensors, communication devices, and control units that collect and transmit data on water levels, rainfall, and flow rates. Software components involve data analytics, prediction models, and user interfaces that process the collected data and present it in a comprehensible format to stakeholders. Services encompass installation, maintenance, and technical support, ensuring the continuous and efficient operation of the system.

Hardware is a critical component of real-time flood warning systems, as it directly impacts the accuracy and reliability of data collection. Advanced sensors such as water level sensors, rain gauges, and flow sensors are essential for monitoring environmental conditions in real-time. These sensors are becoming increasingly sophisticated, offering higher precision and durability, which in turn enhances the overall performance of flood warning systems. The demand for robust and reliable hardware solutions is expected to grow as the need for accurate flood monitoring increases.

Software components are equally vital, as they enable the processing and interpretation of the data collected by hardware devices. Advanced software solutions utilize machine learning algorithms and predictive modeling to analyze data and forecast potential flood events. User interfaces provide real-time updates and alerts to relevant authorities and the public, facilitating timely and informed decision-making. The continuous development of innovative software solutions is expected to drive the growth of this segment, as stakeholders seek more effective and user-friendly too

In this paper, employing several econometric techniques, the authors construct a financial stress index (CNFSI) and a financial conditions index (CNFCI) to measure the instability of China’s financial system. The indices are based on the monthly data collected from China’s inter-bank markets, stock markets, foreign exchange markets and debt markets. Using these two indices, they identify the episodes of systemic financial stress, and then evaluate the indices. The empirical results suggest that the CNFSI performs better than the CNFCI. Furthermore, the authors propose four leading indicators for monitoring China’s financial instability, and provide a primary early warning system for China’s macroprudential regulations.

This is not going to be an article or Op-Ed about Michael Jordan. Since 2009 we've been in the longest bull-market in history, that's 11 years and counting. However a few metrics like the stock market P/E, the call to put ratio and of course the Shiller P/E suggest a great crash is coming in-between the levels of 1929 and the dot.com bubble. Mean reversion historically is inevitable and the Fed's printing money experiment could end in disaster for the stock market in late 2021 or 2022. You can read Jeremy Grantham's Last Dance article here. You are likely well aware of Michael Burry's predicament as well. It's easier for you just to skim through two related videos on this topic of a stock market crash. Michael Burry's Warning see this YouTube. Jeremy Grantham's Warning See this YouTube. Typically when there is a major event in the world, there is a crash and then a bear market and a recovery that takes many many months. In March, 2020 that's not what we saw since the Fed did some astonishing things that means a liquidity sloth and the risk of a major inflation event. The pandemic represented the quickest decline of at least 30% in the history of the benchmark S&P 500, but the recovery was not correlated to anything but Fed intervention. Since the pandemic clearly isn't disappearing and many sectors such as travel, business travel, tourism and supply chain disruptions appear significantly disrupted - the so-called economic recovery isn't so great. And there's this little problem at the heart of global capitalism today, the stock market just keeps going up. Crashes and corrections typically occur frequently in a normal market. But the Fed liquidity and irresponsible printing of money is creating a scenario where normal behavior isn't occurring on the markets. According to data provided by market analytics firm Yardeni Research, the benchmark index has undergone 38 declines of at least 10% since the beginning of 1950. Since March, 2020 we've barely seen a down month. September, 2020 was flat-ish. The S&P 500 has more than doubled since those lows. Look at the angle of the curve: The S&P 500 was 735 at the low in 2009, so in this bull market alone it has gone up 6x in valuation. That's not a normal cycle and it could mean we are due for an epic correction. I have to agree with the analysts who claim that the long, long bull market since 2009 has finally matured into a fully-fledged epic bubble. There is a complacency, buy-the dip frenzy and general meme environment to what BigTech can do in such an environment. The weight of Apple, Amazon, Alphabet, Microsoft, Facebook, Nvidia and Tesla together in the S&P and Nasdaq is approach a ridiculous weighting. When these stocks are seen both as growth, value and companies with unbeatable moats the entire dynamics of the stock market begin to break down. Check out FANG during the pandemic. BigTech is Seen as Bullet-Proof me valuations and a hysterical speculative behavior leads to even higher highs, even as 2020 offered many younger people an on-ramp into investing for the first time. Some analysts at JP Morgan are even saying that until retail investors stop charging into stocks, markets probably don’t have too much to worry about. Hedge funds with payment for order flows can predict exactly how these retail investors are behaving and monetize them. PFOF might even have to be banned by the SEC. The risk-on market theoretically just keeps going up until the Fed raises interest rates, which could be in 2023! For some context, we're more than 1.4 years removed from the bear-market bottom of the coronavirus crash and haven't had even a 5% correction in nine months. This is the most over-priced the market has likely ever been. At the night of the dot-com bubble the S&P 500 was only 1,400. Today it is 4,500, not so many years after. Clearly something is not quite right if you look at history and the P/E ratios. A market pumped with liquidity produces higher earnings with historically low interest rates, it's an environment where dangerous things can occur. In late 1997, as the S&P 500 passed its previous 1929 peak of 21x earnings, that seemed like a lot, but nothing compared to today. For some context, the S&P 500 Shiller P/E closed last week at 38.58, which is nearly a two-decade high. It's also well over double the average Shiller P/E of 16.84, dating back 151 years. So the stock market is likely around 2x over-valued. Try to think rationally about what this means for valuations today and your favorite stock prices, what should they be in historical terms? The S&P 500 is up 31% in the past year. It will likely hit 5,000 before a correction given the amount of added liquidity to the system and the QE the Fed is using that's like a huge abuse of MMT, or Modern Monetary Theory. This has also lent to bubbles in the housing market, crypto and even commodities like Gold with long-term global GDP meeting many headwinds in the years ahead due to a demographic shift of an ageing population and significant technological automation. So if you think that stocks or equities or ETFs are the best place to put your money in 2022, you might want to think again. The crash of the OTC and small-cap market since February 2021 has been quite an indication of what a correction looks like. According to the Motley Fool what happens after major downturns in the market historically speaking? In each of the previous four instances that the S&P 500's Shiller P/E shot above and sustained 30, the index lost anywhere from 20% to 89% of its value. So what's what we too are due for, reversion to the mean will be realistically brutal after the Fed's hyper-extreme intervention has run its course. Of course what the Fed stimulus has really done is simply allowed the 1% to get a whole lot richer to the point of wealth inequality spiraling out of control in the decades ahead leading us likely to a dystopia in an unfair and unequal version of BigTech capitalism. This has also led to a trend of short squeeze to these tech stocks, as shown in recent years' data. Of course the Fed has to say that's its done all of these things for the people, employment numbers and the labor market. Women in the workplace have been set behind likely 15 years in social progress due to the pandemic and the Fed's response. While the 89% lost during the Great Depression would be virtually impossible today thanks to ongoing intervention from the Federal Reserve and Capitol Hill, a correction of 20% to 50% would be pretty fair and simply return the curve back to a normal trajectory as interest rates going back up eventually in the 2023 to 2025 period. It's very unlikely the market has taken Fed tapering into account (priced-in), since the euphoria of a can't miss market just keeps pushing the markets higher. But all good things must come to an end. Earlier this month, the U.S. Bureau of Labor Statistics released inflation data from July. This report showed that the Consumer Price Index for All Urban Consumers rose 5.2% over the past 12 months. While the Fed and economists promise us this inflation is temporary, others are not so certain. As you print so much money, the money you have is worth less and certain goods cost more. Wage gains in some industries cannot be taken back, they are permanent - in the service sector like restaurants, hospitality and travel that have been among the hardest hit. The pandemic has led to a paradigm shift in the future of work, and that too is not temporary. The Great Resignation means white collar jobs with be more WFM than ever before, with a new software revolution, different transport and energy behaviors and so forth. Climate change alone could slow down global GDP in the 21st century. How can inflation be temporary when so many trends don't appear to be temporary? Sure the price of lumber or used-cars could be temporary, but a global chip shortage is exasperating the automobile sector. The stock market isn't even behaving like it cares about anything other than the Fed, and its $billions of dollars of buying bonds each month. Some central banks will start to taper about December, 2021 (like the European). However Delta could further mutate into a variant that makes the first generation of vaccines less effective. Such a macro event could be enough to trigger the correction we've been speaking about. So stay safe, and keep your money safe. The Last Dance of the 2009 bull market could feel especially more painful because we've been spoiled for so long in the markets. We can barely remember what March, 2020 felt like. Some people sold their life savings simply due to scare tactics by the likes of Bill Ackman. His scare tactics on CNBC won him likely hundreds of millions as the stock market tanked. Hedge funds further gamed the Reddit and Gamestop movement, orchestrating them and leading the new retail investors into meme speculation and a whole bunch of other unsavory things like options trading at such scale we've never seen before. It's not just inflation and higher interest rates, it's how absurdly high valuations have become. Still correlation does not imply causation. Just because inflation has picked up, it doesn't guarantee that stocks will head lower. Nevertheless, weaker buying power associated with higher inflation can't be overlooked as a potential negative for the U.S. economy and equities. The current S&P500 10-year P/E Ratio is 38.7. This is 97% above the modern-era market average of 19.6, putting the current P/E 2.5 standard deviations above the modern-era average. This is just math, folks. History is saying the stock market is 2x its true value. So why and who would be full on the market or an asset class like crypto that is mostly speculative in nature to begin with? Study the following on a historical basis, and due your own due diligence as to the health of the markets: Debt-to-GDP ratio Call to put ratio

In dataset, 324 corporate customers were taken as reference. Dataset were created from information's between January 2022 and September 2023 time intervals. Financial ratios are calculated by taking financial information of these customers from balance sheet and income statement items.

Early warning interval of warning indicators of real estate industry in Liaoning Province.