A record 500,000 more house sellers than buyers exists, surpassing levels seen during the 2008 housing crisis, with buyer sentiment at its lowest since 1980.
The Federal Reserve’s near-zero interest rates during COVID-19 lockdowns caused house prices to soar 40% in just 2 years, with average mortgage rates dropping to 2.7%.
Rapid Fed rate hikes tripled mortgage rates to over 7%, creating a frozen market with both buyers and sellers on strike for years.
Sellers are flooding the market at the highest pace since COVID, driven by loss of hope for cheap mortgages and declining work-from-home opportunities (from 1 in 3 workers in 2020 to 1 in 7 today).
A potential 5-10% hit in house prices could result in $20,000 to $40,000 losses for median homeowners, potentially doubling if paired with a recession, significantly impacting Americans’ retirement savings.
AI’s effect on economic growth is projected to compound massively over time, potentially providing a 0.5-0.8% boost to GDP according to IMF and PWC estimates, which could dramatically alter the global economy’s trajectory in the next 20 years.
The adoption of AI is expected to follow an S-shaped curve, similar to electricity in the early 1900s, with slow initial uptake followed by rapid acceleration, leading to significant increases in global GDP.
AI’s capacity to replace numerous jobs may result in increased structural unemployment, potentially reaching 20% in the US by 2030 as workers struggle to adapt to the new skill requirements.
Stock market performance in the AI era will likely be more influenced by traditional economic cycles than direct AI impact, with investors who hold through tech-induced downturns potentially benefiting from subsequent asset price booms.
While AI’s initial impact on real GDP may be minimal, its long-term effects could drive the stock market to unprecedented heights, mirroring the massive boom following the electricity-powered second industrial revolution.
Martin Armstrong’s computer model predicts a terrifying Iran war in August 2023, followed by civil unrest and global economic collapse in 2027, based on historical patterns of war and economic cycles.
The model forecasts a panic cycle in 2026, the first in 40 years, indicating a severe economic downturn and warns that China and Russia are aware of the neocons’ objective of world domination.
Iran’s closure of the Strait of Hormuz would not affect China, which has a completed railroad from China to Iran and buys 80% of Iran’s oil, but would impact other Sunni states like UAE and Saudi Arabia.
Armstrong’s model predicts a low point in global markets in August 2023 before a turnup in 2027, based on consistent historical patterns showing global economic collapse following war and civil unrest.
Russia is described as the richest country in the world due to its vast natural resources, contradicting common perceptions of its economic status.
The neocons in the US intelligence community, led by Netanyahu, convinced Trump to attack Iran, potentially leading to civil unrest and terrorism in the US and Europe, as well as a proxy war with Russia in Ukraine.
The globalist model in Europe, originally planned for worldwide implementation, is now failing and being rejected by populist revolts.
Armstrong’s computer model has accurately forecasted global events in the past, including the collapse of Russia and the 2014 Ukraine war, lending credibility to its current predictions.
The Romanian election interference was related to NATO building the largest base in Europe in Romania to attack Russia, highlighting geopolitical tensions.
The EU is described as having zero free speech and interfering in elections to ensure their preferred candidates win, raising concerns about democratic processes in Europe.
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