“A government big enough to give you everything you want is strong enough to take everything you have,” said Thomas Jefferson, the second US president and the man on the $2 and $10 bill.
The stock market, long a domain of human intuition, economic analysis, and the occasional gut feeling, is on the cusp of a profound transformation. Artificial intelligence (AI) is no longer a futuristic concept confined to science fiction; it is rapidly infiltrating the core mechanisms of trading, promising unprecedented speed, efficiency, and analytical power. As AI-driven trading systems become more sophisticated and widely adopted, the very fabric of the stock market – from price discovery and liquidity to volatility and risk management – is poised for a dramatic reshaping.
Currently, the integration of AI in stock trading is multifaceted. It ranges from sophisticated algorithms that execute trades at lightning speed based on pre-programmed rules to machine learning models that analyze vast datasets to identify patterns and predict market movements. Natural Language Processing (NLP) allows AI to decipher news sentiment and social media trends, while computer vision can even extract data from images to inform investment decisions. These technologies are empowering both institutional investors and retail traders with tools previously unimaginable.
One of the most immediate and noticeable effects of AI-driven trading is the acceleration of market activity. AI algorithms can process and react to information in milliseconds, far outpacing human traders. This speed allows for the exploitation of fleeting arbitrage opportunities and the rapid execution of complex trading strategies. High-frequency trading (HFT), a precursor to more advanced AI trading, has already demonstrated this capability, leading to increased trading volumes and potentially tighter bid-ask spreads in liquid markets. As AI evolves, its ability to analyze and act on more nuanced data will further amplify this effect, potentially leading to a market where price adjustments occur with breathtaking velocity.
Furthermore, AI promises to bring a new level of analytical rigor and efficiency to the market. Human analysts, while possessing valuable qualitative insights, are limited by the sheer volume of data they can process and the inherent biases in their decision-making. AI systems, on the other hand, can sift through massive datasets – including historical prices, financial statements, economic indicators, and alternative data sources – to identify subtle correlations and predict future trends with potentially higher accuracy. This data-driven approach can lead to more informed investment decisions, optimized portfolio allocation, and a more efficient allocation of capital across the market.
The ability of AI to perform real-time risk management is another significant potential impact. By continuously monitoring market conditions and analyzing vast amounts of data, AI algorithms can identify and react to potential risks far faster than human traders. This could lead to more proactive risk mitigation strategies, potentially reducing the likelihood and severity of market downturns. Moreover, AI can be used to build sophisticated risk models tailored to specific portfolios and market conditions, offering a more nuanced and dynamic approach to risk management compared to traditional methods.
However, the rise of AI-driven trading is not without its potential challenges and risks. One major concern revolves around the potential for increased market volatility. If numerous AI algorithms, relying on similar models and data, react in the same way to market events, it could lead to synchronized buying or selling frenzies, amplifying price swings and potentially triggering "flash crashes." The Bank of England recently warned that the "herding" behavior of AI-driven trading strategies could exacerbate market selloffs during times of turmoil. While AI can process information faster, its lack of human intuition and ability to understand unforeseen events could make it vulnerable to unexpected market shocks.
Another critical issue is the lack of transparency and explainability in some advanced AI models, often referred to as "black box" systems. If trading decisions are made by complex neural networks whose reasoning is opaque, it can be challenging to identify and correct errors or biases in the algorithms. This lack of transparency can also raise concerns about accountability in the event of significant market disruptions caused by AI trading systems. Understanding the logic behind AI-driven trades is crucial for both regulatory oversight and maintaining investor confidence.
Furthermore, the increasing reliance on AI could lead to a concentration of power in the hands of those with the most advanced technology and data resources. Large financial institutions and sophisticated hedge funds are likely to have a significant advantage in developing and deploying cutting-edge AI trading systems, potentially leaving smaller players and individual investors at a disadvantage. This could exacerbate existing inequalities in the market and raise questions about fair access and market participation.
The potential for algorithmic bias is another significant concern. AI models are trained on historical data, and if this data reflects existing market inefficiencies or biases, the AI systems may perpetuate or even amplify these biases in their trading decisions. Ensuring that AI algorithms are fair, unbiased, and aligned with ethical considerations is crucial for maintaining a healthy and equitable market.
Moreover, the regulatory landscape for AI-driven trading is still evolving. Existing regulations may not be adequate to address the unique challenges and risks posed by these advanced technologies. Policymakers will need to adapt and develop new frameworks to ensure market stability, prevent manipulation, and promote fair competition in an increasingly AI-driven environment. This includes addressing issues related to algorithmic transparency, accountability, and the potential for systemic risk.
Looking ahead, the future of AI in financial markets is likely to be characterized by further integration and sophistication. We can expect to see the development of even more advanced AI models that can process increasingly complex data, adapt to changing market conditions in real-time, and even generate novel trading strategies. The convergence of AI with other technologies, such as quantum computing and advanced communication networks, could further accelerate these trends.
However, the complete automation of trading with no human oversight remains a distant prospect. Most experts believe that a "human-in-the-loop" approach will persist, where human traders and analysts work in collaboration with AI systems, leveraging the strengths of both. Humans can provide crucial contextual understanding, ethical judgment, and the ability to adapt to truly novel and unforeseen events, while AI provides the analytical power, speed, and efficiency to enhance decision-making and execution.
In conclusion, AI-driven trading holds immense potential to transform the stock market, offering benefits such as increased speed, efficiency, analytical power, and enhanced risk management. However, it also presents significant challenges related to market volatility, transparency, algorithmic bias, and regulatory oversight. Navigating this algorithmic tide will require a careful and thoughtful approach, balancing the benefits of AI with the need to maintain a stable, fair, and transparent market for all participants. As AI continues to evolve, its impact on the stock market will undoubtedly be profound, reshaping the landscape of finance in ways we are only beginning to understand. The key lies in harnessing the power of AI responsibly, ensuring that it serves to enhance, rather than destabilize, the intricate ecosystem of the global stock market.
Mad Hedge Technology Letter
April 11, 2025
Fiat Lux
Featured Trade:
(WALMART IS THE NEW TECH UNICORN)
(WMT), (AMZN)
Walmart’s (WMT) shares are up year to date and that is quite an achievement in the stock trading environment we are in.
This company is pretty much an e-commerce company in 2025, and its future is bright.
Walmart isn’t a traditional tech company, but it is turning into the closest competitor to Amazon.com (AMZN).
The company from Arkansas has pivoted hard to the e-commerce side of business pumping billions into developing its infrastructure.
Like many CEOs, management has understood for quite some time that the future is e-commerce and the delivery of products to people’s homes.
Walmart’s management saw this trend early and pounced on it and at one point during this year during the Trump rally, shares of WMT were up 60%.
That meant it was on track to have its best year since 1999 because the market came crashing down to reality. Back then, the retailer was building a bunch of superstores and making a bigger name for itself in Canada and Mexico.
Roughly 60% of Walmart’s business is groceries and consumers have relied on WMT to deliver competitive pricing during a high inflation environment. It’s improved its delivery and curbside pickup services, and that’s made it an attractive option.
WMT quickly has evolved into a digital package of services that is a worthy rival to Amazon.
The website, the app, and the annual membership have brought in new customers.
WMT has attracted the $100,000 per year household which they never did before and they will continue to deliver earnings to WMT as inflation and interest rates stay sky high.
Walmart has created an artificial intelligence (AI) agent for its merchants called Wally to help “get to the root cause of issues related to things like out of stocks or overstocks with more accuracy and speed.”
Walmart expanded its store-fulfilled delivery to reach 93% of U.S. households with same-day delivery, its chief financial officer said.
Sam’s Club ecommerce sales grew 24%, including triple-digit growth in club-fulfilled delivery.
Walmart Inc. announced 16% growth in its global online sales for its fiscal Q4 2025, which ended Jan. 31, 2025.
That’s about four times faster than the retailer’s overall Q4 revenue growth rate. Meanwhile, although Walmart didn’t specify its year-over-year ecommerce growth for the full 12-month period, Walmart said it grew revenue in that time frame.
Walmart’s fiscal 2025 marked the 10th consecutive year in which it grew its total annual revenue. Moreover, it has only had one year-over-year annual decrease — in 2016 — since at least its fiscal 2009.
Although, the recent short-term price action has been brutal to say the least, once all the bad news is priced into the stock, I do see the stock rallying to the upside.
Meanwhile, WMT becomes more and more like a tech company and pushes competitors like Amazon to raise its level of services to customers.
In the crush of higher inflation, WMT has delivered value to a higher income bracket in the United States and I believe that will continue as we me further into 2025 and 2026.
In the next few years, we will also see $200,000 per year salaried consumers grace the aisles and digital services of WMT to the benefits of the underlying stock.
Global Market Comments
April 11, 2025
Fiat Lux
SPECIAL VOLATILITY ISSUE
Featured Trade:
(TESTIMONIAL)
(MAKING VOLATILITY YOUR FRIEND),
(VIX), (VXX), (XIV),
(THE ABC’s OF THE VIX),
(VIX), (VXX), (SVXY)
Ingenious writing John in your Monday morning strategy letter. I forwarded it to all my family and kids, and made my 16-year old read it out loud to my wife. I made sure he understood what he was reading. I got choked up by the whole article.
Go Ukraine!
Best regards,
Greg
Las Vegas, NV
With the Volatility Index back down to a bargain of $16, I am getting deluged with emails from readers asking if it is time to start hedging portfolios one more time and buying the iPath S&P 500 VIX Short Term Futures ETN (VXX).
The answer is not yet, but soon, possibly very soon. And here is the anomaly in the market today. Volatility is not reflecting actual short-term movements in the S&P 500.
While we have seen several 200-point moves in the market in the past three weeks, the volatility Index (VIX) has spent only hours over the $20 level. That is because the ($VIX) measures anticipated 30-day volatility, and for the past 30 days, the overall net move in the market has been zero.
They are inquiring at absolutely the wrong time.
And here is the problem. When the (VIX) rises, it usually spikes straight up, and then right back down again. This time, it spiked but has since hung around the $20 level rather than collapse back down. That suggests that there is another leg up to go in volatility until it hits $50 or more before it takes a much-deserved break. That means the stock market has one more sharp selloff left before we hit bottom and bounce.
Markets can ignore trade wars, rising interest rates, rocketing interest rates, and international political instability (Gaza, Ukraine) for a while, but not forever. When the time DOES come to pay the piper, prices will fall and volatility will rocket.
So I am more than usually interested in hedging the downside risk for my trading book. A good rule of thumb is to let the (VIX) sit at a bottom for a week, and then go buy the (VXX). Two weeks is even better. That way, you can ignore expensive and unnecessary time decay.
Which all brings me to the subject at hand.
If you are new to the service and have no longs, you probably should skip this trade and just watch it as a learning experience.
This can also be a great hedge for any long positions we may want to add in the coming weeks, such as in “trade peace” or technology plays.
As I never tire of telling people, no one ever complains when they buy fire insurance and their house doesn’t burn down.
If you are new to this service, don’t freak out. My daily research newsletters are not always about exploring the esoterica of options, or volatility trading.
I’ll let you know when I’m ready to pull the trigger with a Trade Alert.
I am always trying to get better prices.
If you are new to the (VIX) game, please read the educational piece below.
I am one of those cheapskates who buy Christmas ornaments by the bucket load from Costco in January for ten cents on the dollar because my 11-month theoretical return on capital comes close to 1,000%.
I also like buying flood insurance in the middle of the summer drought, when the forecast in California is for endless days of sunshine. That is what we had at the end of July when the (VIX) was plumbing the depths of $12.
Get this one right, and the profits you can realize are spectacular.
It gets better.
If the bottom in volatility exactly coincides with the peak in the stock market that it measures, volatility could be headed back up to the 30% handle, and maybe more.
I double dare you to look at the charts below and tell me this isn’t happening.
Watch carefully for other confirming trends to affirm this trade is unfolding. Those would include a strong dollar, and a weak Japanese yen, Euro, and rising fixed-income instruments of any kind.
Notice that every one of these is happening this week!
Reversion to the mean, anyone?
You may know of this from the many clueless talking heads, beginners, and newbies who call (VIX) the “Fear Index”.
For those of you who have a PhD in higher mathematics from MIT, the (VIX) is simply a weighted blend of prices for a range of option contracts on the S&P 500 index (SPX).
The formula uses a kernel-smoothed estimator that takes as inputs the current market prices for all out-of-the-money calls and puts for the front-month and second-month expirations.
The (VIX) is the square root of the par variance swap rate for a 30-day term initiated today. To get into the pricing of the individual options, please go look up your handy dandy and ever-useful Black-Scholes equation.
You will recall that this is the equation that derives from the Brownian motion of heat transference in metals. Got all that?
For the rest of you who do not possess a PhD in higher mathematics from MIT, and maybe scored a 450 on your math SAT test, or who don’t know what an SAT test is, this is what you need to know.
When the market goes up, the (VIX goes down. When the market goes down, the (VIX) goes up. Period. End of story. Class dismissed.
The (VIX) is expressed in terms of the annualized monthly movement in the S&P 500 (SPX) which, with the (VIX) today at $10, is at $72.54.
So for example, a (VIX) of $10 means that the market expects the index to move 2.89%, or $72.54 S&P 500 points, over the next 30 days.
You get this by calculating $10/3.46 = 2.89%, where the square root of 12 months is 3.46.
The volatility index doesn’t really care which way the stock index moves. If the S&P 500 moves more than the projected 2.89% in ANY direction, you make a profit on your long (VIX) positions.
I am going into this detail because I always get a million questions whenever I raise this subject with volatility-deprived investors.
It gets better.
Futures contracts began trading on the (VIX) in 2004, and options on the futures since 2006.
Since then, these instruments have provided a vital means through which hedge funds control risk in their portfolios, thus providing the “hedge” in hedge fund.
“You always sound smarter when you’re a bear than when you’re a bull,” said Adam Parker formerly of Morgan Stanley.
When John identifies a strategic exit point, he will send you an alert with specific trade information as to what security to sell, when to sell it, and at what price. Most often, it will be to TAKE PROFITS, but, on rare occasions, it will be to exercise a STOP LOSS at a predetermined price to adhere to strict risk management discipline. Read more