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april@madhedgefundtrader.com

They’re Not Making Americans Anymore

Diary, Homepage Posts, Newsletter

You can count on a bear market hitting some time in 2038, one falling by at least 25%.

Worse, there is almost a guarantee that a financial crisis, severe bear market, and possibly another Great Depression will take place no later than 2058 and would take the major indexes down by 50% or more.

No, I have not taken to using a Ouija board, reading tea leaves, nor examine animal entrails in order to predict the future. It’s much easier than that.

I simply read the data that was just released from the National Center for Health Statistics, a subsidiary of the federal Centers for Disease Control and Prevention (click here for the link).

The government agency reported that the US birth rate fell to a new all-time low for the second year in a row, to 60.2 births per 1,000 women of childbearing age. A birth rate of 125 per 1,000 is necessary for a population to break even. The absolute number of births is the lowest since 1987. In 2017, women had 500,000 fewer babies than in 2007.

These are the lowest number since WWII, when 17 million men were away in the military, a crucial part of the equation.

Babies grow up, at least most of them. In 20 years, they become consumers, earning wages, buying things, paying taxes, and generally contributing to economic growth.

In 45 years, they do so quite substantially, becoming the major drivers of the economy. When these numbers fall, recessions and bear markets occur with absolute certainty.

You have long heard me talk about the coming “Golden Age” of the 2020’s. That’s when a two-decade-long demographic tailwind ensues because the number of “peak spenders’ in the economy starts to balloon to generational highs. The last time this happened was during the 1980’s and 19990’s stocks rose 20-fold.

Right now, we are just coming out of two decades of demographic headwind, when the number of big spenders in the economy reached a low ebb. This was the cause of the Great Recession, the stock market crash, and the anemic 2% annual growth since then.

The reasons for the maternity ward slowdown are many. The Great Recession certainly blew a hole in the family plans of many Millennials. Falling incomes always lead to lower birth rates, with many Millennial couples delaying children by five years or more. Millennial mothers are now having children later than at any time in history.

Burgeoning student debt, which just topped $1.5 trillion is another. Many prospective mothers would rather get out from under substantial debt before they add to the population.

The rising education of women is another drag on childbearing and is a global trend. When spouses become serious wage earners, families inevitably shrink. Husbands would rather take the money and improve their lifestyles than have more kids to feed.

Women are also delaying having children to postpone the “pay gaps” that always kick in after they take maternity leave. Many are pegging income targets before they entertain starting families.

As a result of these trends, one in five children last year were born to women over the age of 35, a new high.

This is how Latin Americans moved from eight to two-child families in only one generation. The same is about to take place in Africa, where standards of living are rising rapidly, thanks to the eradication of several serious diseases.

The sharpest falls in the US have been with minorities. Since 2017 the birth rates for Hispanics have dropped by 27% from a very high level, African Americans 11%, whites 5%, and Asians 4%.

Europe has long had the same problem with plunging growth rates but only much worse. Historically the US has made up for the shortfall with immigration, but that is now falling thanks to the current administration policies. Restricting immigration now is a guarantee of slowing economic growth in the future. It’s just a numbers game.

So watch that growth rate. When it starts to tick up again it’s time to buy….in about 20 years. I’ll be there to remind you with this newsletter.

As for me, I’ve been doing my part. I have five kids aged 15-34, and my life is only half over. Where did you say they keep the Pampers?

 

I’m Doing My Part

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april@madhedgefundtrader.com

February 4, 2025

Biotech Letter

Mad Hedge Biotech and Healthcare Letter
February 4, 2025
Fiat Lux

 

Featured Trade:

(TOO RICH TO FAIL, TOO EXPENSIVE TO SUCCEED)

(MRNA), (TSLA), (NVS), (SNY), (JNJ), (BNTX), (RHHBY), (REPL), (CRSP), (ORCL)

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april@madhedgefundtrader.com

Too Rich To Fail, Too Expensive To Succeed

Biotech Letter

Last weekend, while organizing my home office, I stumbled across an old COVID vaccination card. Remember those? It got me thinking about Moderna (MRNA), the biotech darling that went from relatively unknown to household name faster than you can say "messenger RNA."

Now, in early 2025, this once up-and-coming company is already facing what my grandmother would call "champagne problems" - too much cash to be broke, but burning through it faster than a Tesla (TSLA) on Ludicrous mode.

First, let's talk about this biotech's cash burn. In just nine months of 2024, Moderna torched through over $4 billion - that's the same amount they burned in all of 2023, suggesting their cash cremation rate is actually accelerating.

This acceleration in spending wouldn't be as worrying if they had endless reserves, but their current position shows $7 billion in cash and $2 billion in non-current investments.

The math isn't complex: at this burn rate, their runway is shorter than many investors realize.

The recent Health and Human Services (HHS) grant of $176 million in July 2024 for bird flu research barely registers on their financial statements.

While we've seen about 70 bird flu cases in the U.S. with one fatality in an elderly patient with underlying conditions, this isn't going to be another COVID-style revenue stream.

I've analyzed enough pharmaceutical companies to know that betting on another pandemic windfall is like expecting lightning to strike twice in the same spot.

What really interests me is Moderna's position in the competitive landscape. I spent last week analyzing patent data and geographic reach metrics across the industry.

First, you've got the old-guard pharma giants like Novartis (NVS), Sanofi (SNY), and Johnson & Johnson (JNJ), who have been at this game since before mRNA was a gleam in a scientist's eye.

Then, there are companies like BioNTech (BNTX) and Roche (RHHBY) with significantly higher geographic reach, while Replimune Group (REPL) and CRISPR Therapeutics (CRSP) demonstrate superior application diversity.

In comparison, Moderna's position in this landscape shows relatively low scores on both metrics - not exactly what you want to see from a company burning cash at this rate.

Stéphane Bancel, Moderna's CEO, recently outlined their pipeline: 2 approved medicines, 7 Phase 3 trials, and 45 candidates in development. They're also targeting $1.1 billion in annual R&D cost reductions by 2027.

But here's what keeps bothering me: their SG&A expenses have ballooned to nearly 10 times their pre-COVID levels, yet management is focusing on R&D cuts instead of addressing this administrative bloat.

The insider trading patterns since early 2024 haven't exactly inspired confidence either.

When I see heavy selling from insiders while a company is promising future breakthroughs, I can't help but remember all the biotech stories I've covered where the promise didn't match the reality.

Speaking of promises, Oracle's (ORCL) Larry Ellison recently made headlines talking about 48-hour personalized cancer vaccines using AI and robots.

While the technology sounds promising, I'm more interested in the practical path to profitability. Moderna isn't alone in this race, and their well-capitalized competitors have the luxury of funding similar development programs while maintaining positive cash flow.

Given Moderna's cash burn trajectory, their next three quarters will be telling.

I'll be watching that $4 billion nine-month burn rate closely, along with their progress on cost reductions - particularly those inflated SG&A expenses that management seems reluctant to address.

I'm keeping my old vaccination card as a reminder of Moderna's impressive COVID-19 achievement, but I'm not ready to bet on lightning striking twice.

Sometimes the hardest part of investing is knowing when to appreciate history without banking on its repeat performance.

 

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april@madhedgefundtrader.com

February 4, 2025

Jacque's Post

 

(SPECIAL ISSUE: TAKING PROFITS AND SLIMMING DOWN OUR PORTFOLIO)

February 4, 2025

 

Hello everyone

 

Today, I’m listing stocks I’m recommending you sell.  Sell at best price.

If you are reluctant to sell out of the whole stock, then look at selling between 50% - 75% of the stock.    

Update on tariffs:  China has issued retaliatory tariffs – up to 15% -  against the U.S.  They are due to take effect on February 10.  Next week should be interesting.

 

Here’s the List of Stocks

1/ Johnson & Johnson (JNJ)

Purchase Date:  10/25/23

Purchase Price:  $150.00

Sell Date:  02/03/25

Sell Price:  $151.87

+/- +$ 1.87

+/-% +1.87%

 

2/ Snowflake (SNOW)

Purchase Date:  11/24/23

Purchase Price:  $171.33

Sell Date:  02/03/25

Sell Price:  $182.54

+/- +$ 11.21

+/-% +6.54%

 

3/Palo Alto Networks (PANW)

Purchase Date:  01/06/23

Purchase Price:  $315.00

Sell Date:  02/03/25

Sell Price:  $182.79

+/- -$132.21

+/- % -41.97%

 

4/ Advanced Micro Devices (AMD):

Purchase Date:  01/06/23

Purchase Price:  $150.00

Sell Date:  02/03/25

Sell Price:  $114.27

+/- -$35.73

+/-% - 23.82%

 

5/ Arista Networks (ANET)

Purchase Date:  01/06/24

Purchase Price:  $62.00 (Stock split June 6, 2024)

Sell Date:  02/03/25

Sell Price:  $111.50

+/- +$53.50

+/- % +86.29%

 

6/ Black Rock (BLK)

Purchase Date:  01/08/24

Purchase Price: $782.00

Sell Date: 02/03/25

Sell Price:  $1,013.75

+/- +$231.75

+/-% +29.63%

 

7/ Realty Group (O)

Purchase Date:  02/21/24

Purchase Price:  $52.00

Sell Date:  02/03/25

Sell Price:  $54.49

+/- +$2.49

+/- % + 4.78%

 

8/Prologis (PLD)

Purchase Date:  02/21/24

Purchase Price: $134.00

Sell Date: 02/03/25

Sell Price:  $117.84

+/- -$16.16

+/- % -12.05%

 

9/ Caterpillar (CAT)

Purchase Date:  04/22/24

Purchase Price:  $354.56

Sell Date: 02/03/25

Sell Price:  $361.55

+/- +$6.99

+/- % +1.97

 

10/ Eaton Corporation (ETN)

Purchase Date:  04/22/24

Purchase Price: $303.02

Sell Date: 02/03/25

Sell Price: $315.55

+/- +$12.39

+/- % +4.08%

 

11/ General Motors (GM)

Purchase Date:  05/15/24

Purchase Price:  $45.03

Sell Date:  02/03/25

Sell Price:  $47.90

+/- +$2.87

+/- % +6.37%

 

12/ Apple (AAPL)

Purchase Date: 11/24/23

Purchase Price:  $190.00

Sell Date: 02/04/25

Sell Price:  $228.01

+/- +$38.01

+/- % +20%

 

13/ Microsoft (MSFT)

Purchase Date:  01/05/24

Purchase Price:  $372.00

Sell Date:  02/03/25

Sell Price:  $410.92

+/- +$38.92

+/-% +10.46%

 

14/ iShares Biotechnology ETF (IBB)

Purchase Date:  01/31/24

Purchase Price:  $137.49

Sell Date:  02/03/25

Sell Price:  $137.85

+/- +$0.36

+/- % +0.26%

 

15/ SPDR S&P Biotech ETF (XBI)

Purchase Date:  01/31/24

Purchase Price:  $90.80

Sell Date:  02/03/25

Sell Price:  $91.42

+/- +$0.62

+/- % +0.28%

 

Percentage gain/loss = + 94.69%

Dollar gain/loss = + $211.86 (if you had bought one stock/share of each of the above)

12 stocks = + gains

3 stocks = - loss

 

 

 

Cheers

Jacquie

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april@madhedgefundtrader.com

February 4, 2025

Diary, Newsletter, Summary

Global Market Comments
February 4, 2025
Fiat Lux

 

Featured Trade:

(LEARNING THE ART OF RISK CONTROL)

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Mad Hedge Fund Trader

Learning the Art of Risk Control

Diary, Homepage Posts, Newsletter

Now that you know how to make money in the market, I’m going to teach you how to hang on to it. There is no point in booking winning trades only to lose money by making careless beginner’s mistakes. So today, I am going to talk about risk control.

The first goal of risk control is to conserve whatever capital you have. I tell people that I am too old to start over again as a junior trader at Morgan Stanley if I lose all my money. With my attitude, nobody would hire me anyway. So, I’m pretty careful when it comes to risk control.

The art of risk control is to make sure your portfolio is profitable, no matter what happens to the market. You want to be a winner, whether the market goes up, down, or sideways. This is what I do.

Remember, we are not trying to beat an index here. Our goal is to make actual dollars at all times, to keep the P&L chart always moving from the lower left to the upper right. You can’t eat relative performance, nor can you use it to pay your bills.

The second goal of a portfolio manager is to make your portfolio bomb-proof. You never know when a flock of black swans is about to alight on the market, or a geopolitical shock comes out of the blue causing markets to crash.

The biggest mistake I see beginning traders make is that they are in too much of a hurry to get rich. As a result, they make too much money too soon. I can’t tell you how many times I have heard of first-time traders losing all their money on their first trade, well before they got a handle on the basics.

I’m usually right 80% to 90% of the time (this year it’s 95%). That means I’m wrong 10% to 20% of the time. If you bet the ranch on one of my losing trades, you’ll get taken to the cleaners. Never bet the ranch.

If you do, you are turning a calculated list into random risk, or throwing darts at a dartboard and hoping for the best. It is akin to buying a lottery ticket. I often tell clients they have gambling addictions. Make sure you’re not one of them. You can’t trade yourself back from zero with no money.

If you can master the skills I'm teaching you, you can make a living at this FOREVER! So, what’s the hurry? As my old trading mentor used to tell me, the late Barton Biggs of Morgan Stanley, “Invest in haste, repent in leisure,” a time-tested nostrum that is always true in this business.

I recommend that you use NO real money on your first few trades. Start with paper trading only. All of the online trading platforms offer wonderful tools that allow you to practice trading before you try the real thing. If you lose in their “pretend money”, no harm, no foul. They don’t want you to go broke either. Broke customers don’t pay commissions. They also sue.

The more time you spend learning to trade, the more money you will get out of it. Remember, work in, money out. Spend at least an hour or two getting to know your own trading platform well.

Once you start trading will real money it will become a totally different experience. Your heart rate steps up. Your hands get sweaty. You start checking your watch. It’s a lot like going into combat. In fact, combat veterans make great traders, which is why the military recruits so actively from the military. I think all these instincts trace back to our Neanderthal days when our main concern was being chased by a saber-toothed tiger.

The time to learn a trading discipline is NOW. All of a sudden, your opinions, your ego, and your savings are on the line. It’s crucial for you to always start small when using real money.

That way, making a beginner’s mistake, like confusing “BUY” and “SELL” (I see it every day) will only cost you a cup of coffee at Starbucks, and not your kid's college education, your house, or your retirement. It won’t take long for you to grow from one contract to thousands, as I have done myself for many years.

It’s all about finding your comfort level and risk tolerance. You never want to have a position that is so large that you can’t sleep at night, or worse, call me in the middle of the night and ask what to do with it. My answer is always the same. Cut your position in half. If you still can’t sleep, cut it in half again.

I make a bold prediction here. The more experience you gain, the faster your risk tolerance goes up.

I’ll give you one more piece of advice. Take your broker's technical support phone number and paste it to the top of your computer monitor. You don’t want to go look for it when you can’t figure out how to get out of a position, or your platform breaks. These are machines. It happens. As they teach in flight school, it’s not a matter of if but when a machine breaks.

There’s one more thing. When you’re ready to commit real money, don’t forget to take your account off of paper trading. The profits you make there can’t be spent.

Risk management is an important part of the position sheet I update every day.

Take a look below at a past position sheet I sent out during sharply rising markets.

 

 

The important thing to look at here is my long/short balance. On the left is the position name and on the right is the position weighting. I usually run 10% positions so I don’t have all my eggs in one basket. Maybe twice a year, I’ll run a 20% position in a single stock, and once a year I’ll have a 30% weighting. Above that, I start to lose sleep.

I have further subdivided the portfolio into “RISK ON” and “RISK OFF.” “RISK ON” means the world is getting better, while “RISK OFF” means the world is getting worse. The long positions have positive numbers, while the short positions have negative ones.

I like to balance “RISK ON” and “RISK OFF” to remove overall market risk from the portfolio. When markets are rising, I turn positive. When markets are falling, I tilt negative. At the bottom, I have my total net exposure. On this particular day, I was running 60% in long and 20% in shorts, for a total net position of 40% long. This is an aggressively bullish portfolio.

When I’m bullish, the net position is positive. When I’m bearish the net position is negative. When I have no strong views, the net position is zero. That way, if nothing happens you still get to rake the money in.

I have no positions at all only a few days a year. I only play when the risk/reward is overwhelmingly in my favor, and sometimes that is just not possible.

One more warning to the wise. There are literally hundreds of gurus out there marketing services promising 100% a year, if not 100% a month, or even 100% a day. They are all fake, created by 20-year-old marketing types who have never worked in the stock market, or even traded. Unfortunately, I work in an industry where almost everyone else is a crook.

I have worked in the markets for more than 50 years and have seen everything. Ray Dalio is the top-performing hedge fund manager in history and he only averages 35% a year.  The number of real traders who are right more than 80% of the time you can almost count on one hand. If returns sound too good to be true, they never are.

I want to offer special caution about naked put shorting strategies which are promoted by 90% of these letters. This is where a trader sells short a put position without any accompanying hedge, hence the word “naked.” This is an unlimited-risk position.

You might take in a $1 premium with this approach, but if the market turns against you, and implied volatilities go through the roof, your losses could balloon exponentially to $100 or more, wiping you out. The newsletters recommending these have absolutely no idea when or if this is going to happen.

I call this the “picking up the pennies in front of the steamroller strategy.” No professional trader worth his salt will put money into it. It is banned by most investing institutions. And only a few brokers will still let you do this, and then only with 100% margin requirements, because when losses exceed 100% of capital, they’re left carrying the bag.

Many of those strategies you see being hawked online look great on paper but can’t actually be executed. In other words, you just paid thousands of dollars for a service that is utterly useless. Sounds like a “No Go” to me.

Stop losses are an important part of any trading strategy.  No one is right 100% of the time. If they claim so they are lying. The best way to avoid a big loss is to take a small one.

There are many possible places to use stop losses. I use 2% of my total capital. If I start to lose more than that I am out of there. It’s easy for me to do this because 90% of the time the next trade will be a winner and I’ll make back all the money I just lost.

Others use a 10% decline in the underlying stock as a good arbitrary point to limit losses. Others rely on Fibonacci levels (I’ll get to him later). Many traders rely on key moving averages, like the 50-day or the 200-day.

The problem with this is that high-frequency traders have access to the same charting data as you do. They’ll program their algorithms to quickly take a stock through your stop loss level, buy your stock for cheap, and then take it right back up again to book a quick profit. You are left with a “SELL” confirmation in your inbox and no position in a rising market. No wonder people think Wall Street is rigged.

Another concept is the “trailing stop”. That’s when after an initial rise, you place a stop-loss order at your cost. That way you CAN’T lose money. This is known as “playing with the house's money.” This approach has one shortfall. You can’t place stop losses in the options market that are executed automatically. The same is true for options spreads.

In this case, you use what is known as a “pocket stop loss” where you set your mental level on when to get out. Also, these are not automatic, they do establish a trading discipline. Caution: You can’t execute a pock-stop loss when you’re playing gold or on a one-week cruise in the Caribbean.

So, there you have it. By managing your risk prudently, you can tip the risk/reward balance in your favor.

I hope this helps.

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Mad Hedge Fund Trader

February 4, 2025 - Quote of the Day

Diary, Newsletter, Quote of the Day

“In the US, you had ten bad years in a row (during the Great Depression) and it still turned out to be a pretty good century, said Lloyd Blankfein, CEO of Goldman Sachs.

 

Elderly Couple

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Douglas Davenport

How AI is Revolutionizing Risk Assessment in the Insurance Industry

Mad Hedge AI

The insurance industry is undergoing a seismic shift as artificial intelligence (AI) transforms the way insurers assess and manage risks associated with properties, particularly those vulnerable to natural disasters, climate change, and other hazards. From predictive analytics to real-time monitoring, AI is enabling insurers to make faster, more accurate, and data-driven decisions, helping them navigate an increasingly complex risk landscape.

The Growing Need for Advanced Risk Assessment

Climate Change and Natural Disasters

Climate change is driving a surge in the frequency and severity of natural disasters, including hurricanes, wildfires, floods, and earthquakes. According to the National Oceanic and Atmospheric Administration (NOAA), the number of billion-dollar weather and climate disasters in the U.S. has risen dramatically over the past few decades. This trend is global, leaving insurers grappling with higher claims and greater financial exposure.

Traditional risk assessment methods, which rely heavily on historical data, are struggling to keep pace with these evolving risks. AI, however, offers a solution by analyzing vast amounts of real-time data and identifying patterns that traditional methods might miss.

Urbanization and Property Density

Urbanization is compounding the problem, with more properties being built in disaster-prone areas. Coastal cities, for instance, face heightened risks from hurricanes and rising sea levels. The increasing density of properties in these regions means that a single catastrophic event can result in massive losses for insurers.

AI is helping insurers better understand these risks by integrating data from satellite imagery, weather forecasts, and building codes. This allows for more informed underwriting and pricing decisions, ensuring that insurers can manage their exposure effectively.

Regulatory and Consumer Pressures

Regulators and consumers are demanding greater transparency and accuracy in risk assessment. Insurers are under pressure to offer affordable yet comprehensive policies while maintaining financial stability to pay out claims. AI is helping insurers meet these demands by providing more precise risk assessments, enabling better pricing and underwriting decisions, and ensuring compliance with regulatory requirements.

How AI is Transforming Risk Assessment

Data Collection and Integration

AI excels at collecting and integrating data from diverse sources, including:

  • Satellite Imagery: AI analyzes satellite images to assess property conditions, identify hazards, and monitor changes over time, such as erosion or deforestation.
  • Weather Data: Real-time weather data from satellites, IoT devices, and weather stations helps insurers predict extreme weather events and their potential impact.
  • Social Media and News Feeds: AI scans social media and news articles to identify emerging risks like wildfires or civil unrest.
  • Building and Infrastructure Data: AI evaluates building materials, construction methods, and infrastructure to assess vulnerability to hazards.
  • Historical Claims Data: AI identifies patterns in past claims to predict future risks.

By integrating these data sources, AI provides a comprehensive and accurate risk assessment for each property.

Predictive Analytics

Predictive analytics is one of AI's most powerful tools. By analyzing historical data, AI can forecast the likelihood of future events and their potential impact. For example, AI can predict hurricane landfalls and estimate property damage based on factors like wind speed, storm surge, and building resilience. This allows insurers to adjust premiums, recommend mitigation measures, and prepare for potential claims.

AI is also being used to assess long-term climate risks, such as rising sea levels and changing precipitation patterns, helping insurers plan for future challenges.

Machine Learning and Risk Modeling

Machine learning algorithms analyze large datasets to identify complex relationships between variables, enabling the development of sophisticated risk models. These models consider factors like geographic location, building characteristics, and environmental conditions, and are continuously updated with new data.

For example, machine learning can identify properties at higher risk of water damage due to flooding or plumbing issues, allowing insurers to adjust premiums or recommend specific mitigation measures.

Real-Time Monitoring and Alerts

AI enables real-time monitoring of properties through IoT sensors that track conditions like temperature, humidity, and water levels. If a sensor detects a potential hazard, such as a sudden increase in water levels, the system can alert both the insurer and the property owner.

AI also assesses the impact of natural disasters as they unfold by analyzing data from social media, news feeds, and satellite imagery. This helps insurers prioritize claims and allocate resources more effectively.

Automated Underwriting and Pricing

AI automates underwriting and pricing by analyzing property data to determine appropriate premiums and coverage. It can also flag high-risk properties for further review, ensuring that underwriters focus on the most complex cases.

Customer Engagement and Risk Mitigation

AI-powered chatbots provide policyholders with personalized recommendations on reducing risks, such as maintaining properties or installing protective measures. AI also delivers real-time updates on emerging risks, such as approaching wildfires, helping policyholders take proactive steps to protect their properties.

Case Studies: AI in Action

Lemonade: AI-Powered Insurance

Lemonade, a tech-driven insurer, uses AI to assess risks and process claims in real-time. Its AI system analyzes property data to determine premiums and coverage, while its chatbot, Maya, engages with customers, answers questions, and even helps file claims.

Zurich Insurance: AI for Flood Risk Assessment

Zurich Insurance has developed an AI-powered flood risk assessment tool that uses satellite imagery, weather data, and machine learning to predict flooding likelihood and potential damage. The tool helps underwriters assess risks and provides policyholders with mitigation recommendations.

Allstate: AI for Wildfire Risk Assessment

Allstate's AI tool predicts wildfire risks by analyzing factors like temperature, humidity, wind speed, and vegetation density. It helps underwriters evaluate properties in wildfire-prone areas and provides real-time updates to policyholders.

Challenges and Ethical Considerations

Data Privacy and Security

The use of AI requires collecting and analyzing vast amounts of sensitive data. Insurers must implement robust data protection measures to safeguard this information and comply with privacy regulations.

Bias and Fairness

AI systems can produce biased results if trained on unrepresentative data. Insurers must ensure their AI models are trained on diverse datasets to avoid bias and ensure fairness.

Transparency and Explainability

The complexity of AI algorithms can make it difficult to explain how risk assessments are made. Insurers must prioritize transparency to build trust with regulators and policyholders.

Regulatory Compliance

AI-driven risk assessment must comply with regulations on data privacy, fairness, and transparency. Insurers must stay ahead of evolving regulatory requirements to avoid legal and reputational risks.

The Future of AI in Risk Assessment

Integration with IoT and Smart Homes

The integration of AI with IoT devices and smart home technology will enhance real-time risk monitoring. Smart sensors can detect leaks, smoke, or unusual activity, helping prevent damage and reduce claims.

AI-Driven Climate Risk Models

As climate change intensifies, insurers will rely on AI-driven climate risk models to assess long-term risks and develop strategies to mitigate them.

Collaboration with Governments and NGOs

Insurers are increasingly partnering with governments and NGOs to address climate risks. AI provides the data needed to develop effective policies and mitigation strategies.

Personalized Insurance Products

AI enables insurers to offer tailored policies based on specific property risks, such as flood or wildfire coverage, ensuring that policyholders receive the protection they need.

Conclusion

AI is revolutionizing the insurance industry by enabling more accurate, efficient, and scalable risk assessment. From predictive analytics to real-time monitoring, AI is helping insurers navigate the growing risks posed by climate change and natural disasters. While challenges remain, the potential benefits of AI are immense, promising a more resilient and sustainable future for the insurance industry. As AI technology continues to evolve, its role in risk assessment will only grow, reshaping the industry for years to come.

https://www.madhedgefundtrader.com/wp-content/uploads/2025/02/Screenshot-2025-02-03-164141.png 587 914 Douglas Davenport https://madhedgefundtrader.com/wp-content/uploads/2019/05/cropped-mad-hedge-logo-transparent-192x192_f9578834168ba24df3eb53916a12c882.png Douglas Davenport2025-02-03 16:47:562025-02-03 16:49:04How AI is Revolutionizing Risk Assessment in the Insurance Industry
april@madhedgefundtrader.com

February 3, 2025

Tech Letter

Mad Hedge Technology Letter
February 3, 2025
Fiat Lux

 

Featured Trade:

(TARIFFS COME FOR TECH STOCKS)
(NVDA), (META)

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april@madhedgefundtrader.com

Tarrifs Come For Tech Stocks

Tech Letter

Tech stocks have felt the full effect of the volatile nature of the new federal government in charge in Washington.

Tech stocks aren’t looking too pretty today. 

The new admin levied a 25% tariff on goods from Mexico only to give the Mexicans a 1-month reprieve.

Like a game of high-stakes poker, but Trump is wielding the American economy at the poker table with reckless abandon.

Tech stocks whipsawed and most stocks opened up in the red, however, a stock like Meta was able to ride out the instability by surging at the open.

Not all tech stocks are created equal.

If many investors thought Trump wouldn’t follow through with his sabre-rattling, then think again.

He is hell-bent on going full throttle and pushing allies to the brink whether they can tolerate it or not.

The surge in interest rates because of the perception of higher inflation and higher geopolitical risk was the reason tech stocks were jolted at the beginning of this week.

Indeed, tech stocks are in for a sideways correction if American government policy becomes constantly aggressive and brutal.

Tech stocks will have a narrow path to go higher, but not like the prior 10 years when stocks were cheered higher by almost everyone.

Trump said this will boost US manufacturing.

The tariffs will grow the US economy, protect jobs, and raise tax revenue, he argues.

Canada’s Trudeau declared retaliatory 25% tariffs on $107 billion dollars worth of US goods on Saturday.

Mexican President Claudia Sheinbaum has directed the Secretary of Economy to impose a plan including "tariff and non-tariff measures in defense of Mexico's interests".

Together, China, Mexico, and Canada accounted for more than 40% of imports into the US last year.

Most goods from Mexico don’t affect tech stocks such as fruits like avocado, vegetables, tequila, and beer.

Canadian goods such as steel, lumber, grains, and potatoes are also likely to get pricier.

It is expected that the car manufacturing sector could see the brunt of the effects of the tariff.

It’s not like Trump is only going after Mexico and Canada, he also has the U.K. and Europe in his crosshairs.

Do tariffs cause inflation?

In the short term, tariffs will hit consumers in the U.S. with corporations front-running price increases by passing on the higher inputs to the end buyer.

The market also senses higher inflation and interest rate yields will get bid up, which is negative for tech stocks.

It is naïve to think that tech stocks will go up in a straight line like the past 10 years – they certainly will not.

If the government is hell-bent on this type of tactic, global markets will feel the pain.

Even if this doesn’t directly affect tech stocks, the American consumer will not go unscathed.

Interest rates exploding higher will certainly mean tech stocks opening up Monday mornings 3% down.

That is not a good starting point for the week and explains why the bellwether Nvidia (NVDA) is down 15% year to date.

Then throw in the chaos from the Deepseek fiasco that threatens the valuations of many AI stocks.

It’ll be tough sledding from here on out and tech investors need to be mindful to not get caved in out of nowhere. 

 

 

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