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Donna Cournoyer

Hold ’em, Don’t Fold ’em

Kenny Rogers revealed his ideas about what to do at the poker table when he sang; “you got to know when hold ‘em, know when to fold ‘em, know when to walk away, and know when to run.”

Roger’s wisdom may ring true for gamblers, but it is much less useful for investors. John C. Bogle’s ideas and approach to investing are more apt to yield positive long-term results.

One of the four “investment giants” of the twentieth century (according to Fortune Magazine), Bogle was a founder of The Vanguard Group and was known for doing well by Main Street.

He had a strong conviction that focusing on the long term was the best approach for individual investors.

Bogle appreciated the classics, and was fond paraphrasing Shakespeare’s MacBeth, asserting: “the daily machinations of the stock market are like a tale told by an idiot, full of sound and fury, signifying nothing.”

He went on to say: “Don’t let all the noise drown out your common sense and your wisdom. Just try not to pay that much attention, because it will have no effect whatsoever, categorically, on your lifetime investment returns.”

During periods such as April, when the ebbs and flows of the financial markets are extreme, it’s important to remember Bogle’s words of wisdom.

In theory, it’s easy to get on board with what Bogle is saying.

In practice, however, it is difficult to “not to pay that much attention” when stock prices are gyrating and when you are witnessing daily declines in your portfolio’s value.

Since April’s mini-panic has subsided, investors may have an easier time considering the following, which support the “hold, don’t fold” principle:

  1. Large stock market declines are typically closely followed by large stock market rallies.
  2. Selling during today’s downswing can be detrimental, because it increases the chances that you’ll miss the benefits of tomorrow’s upswing
  3. Bear markets are infrequent (but not rare) and are typically unpredictable. Preparing for a rough ride in the near-term, while anticipating a smooth ride over the long-term, is a prudent approach.

Below are charts, with additional commentary, that illustrate these points.

Worst Days and Best Days Tend to Cluster Together

This chart shows the worst 50 days and the best 50 days in the stock market from 1997 through 2024, courtesy of Goldman Sachs Asset Management.

Source: Goldman Sachs Asset Management

GSAM says the time between the worst day in a drawdown and the best day of the subsequent recovery is often as little as 2-8 days.

If this chart were to be extended into 2025, early April would have featured prominently, when large company US stocks fell by nearly 5% on 4/3 and 6% on 4/4 – then shot up by 9% on 4/9.

If you’re tempted to sell stocks after a big market decline, keep this chart in mind. If you sell on the downswing, you’re likely to miss the upswing.

The 10 Best Days of Each Year Make All the Difference

Here’s another lens on the good days / bad days concept: since 1990, missing just the ten best trading days each year would have turned the S&P 500’s average positive return of +15.1% into an annual loss of -18.0%, on average.

Source: Goldman Sachs Asset Management

The chart above extends back to 2000, and shows actual annual returns in dark blue, paired with what annual returns would have been if investors missed the ten best trading days of the year.

The lesson: hold through the downs and the ups. Selling when the market is down means you run the risk of missing recoveries, which can be detrimental to your long-term wealth.

As hard as it may be psychologically to persevere when the outlook is gloomy and stock prices are falling, it most often is the right thing to do.

Markets Reward Long-Term Investors

The next two images show that being in the markets for the long haul is the best way to handle volatility, which is a feature of the stock market.

This table, courtesy of Capital Group, maps out the nine largest market declines during the past two decades, and puts what just occurred in April, labeled “Trump Tariff Tremor” into context.

Source: Capital Group

The events in purple font are corrections, where the stock market (S&P 500 Index of large company US stocks) has declined by between 10% to 20%.

Most of the time in instances where the market corrects, the decline is quick and sharp, and stocks recover quickly.

The “Trump Tariff Tremor” in black font a significant event, and the market activity was in line with other corrections. While stocks haven’t fully recovered to their most recent peak, the upswing from the April 8 “bottom” has been 14% as of May 2.

The events in green font are more severe bear markets, where the stock market has declined by more than 20%.

Recovery typically takes some time after the bottom of a bear market is reached. But in both types of down markets – Corrections and Bear Markets – long-term investors are rewarded for staying the course.

The last chart, also courtesy of Capital Group, is a complement to the previous table and shows the path of the S&P 500 Index of large-company US stocks for the past 20 years.

Source: Capital Group

The shaded areas map out the bear markets in green and the corrections in purple.

Through it all, the US stock market return has averaged about 9.25% per year. A $1,000 investment on January 2004, would have appreciated to approximately $5,888 over the twenty-year period.

Hopefully, this data can help you recognize the trees (short-term), enable you to see the forest (long-term), and support your resolve to stay committed to your investment strategy and your financial plan.

-RK

April 2025 Market Recap: Trade Policy U-Turn

For drivers, a car U-turning on busy roadway is universally viewed as negative. For investors, the recent policy U-turn by the Trump administration on its busy tariff agenda was universally viewed as positive.

As the tariff announcements came fast and furious in early April, the financial markets took another leg down.

During four trading days early in the month (April 3rd – 8th) US large company stocks dropped by 12%.

This downdraft, on top declines registered in the first quarter, brought the cumulative drop in stocks close to a bear market – down 19% from the most recent high on February 19.

Then, President Trump said he’d pause tariffs on dozens of countries for 90 days after coming under intense pressure from business leaders and investors to reverse course.

On April 9, the stock market delivered a 1-day rally of 9% following that announcement.

As of the end of April, here’s how the situation stood with regard to tariffs:

  • A 90-day pause on so-called “reciprocal” tariffs (apart from a 10% universal tariff)
  • Further tariff exceptions for computers, smartphones and electrical equipment
  • Some short-term exclusions from the 25% tariffs on imported vehicles and auto parts under consideration
  • Conversely, the Administration has ratchetted up tariffs on China to 145%
  • New levies on imported pharmaceuticals, lumber and semiconductors are expected in coming months

Beijing’s countermove was to raise tariffs on all US goods imported into China to 125%.

Financial market participants are now interpreting the situation as less of a global trade war, and more of a tariff showdown between the US and China.

This “less bad” news was enough to allow the stock market to turn back up during the second half of April.

When all was said and done (or, perhaps more aptly put, after all that was said), here’s how things shook out in the financial markets for the full month of April:

Note: Foreign Stocks = MSCI EAFE Index; Tech Stocks = Russel 1000 Technology Index; Bonds = Bloomberg US Aggregate Bond Index; US Large Co = S&P 500 Index; US Small Co = Russell 2000 Index

Year-to-date through April 30, here are returns for the above asset classes:

  •  Foreign stocks, +12%
  • Tech stocks, -10.4%
  • Bonds, +3.2%
  • US Large Co, -5.1%
  • US Small Co, -11.6%

Positive momentum pushed the stock market up further during the first two days in May.

By the close of trading on Friday, May 2, the S&P 500 index of large company US stocks had rallied for nine straight trading sessions and had reclaimed all losses registered in April.

The quick recovery from April’s intense bout of crisis-like volatility indicates that investors seem believe the American economy isn’t about to slide into recession, and that it will take a much bigger shock to push stocks into a bear market.

-RK

Reading Room: Who Is Government?

Michael Lewis was 26 years old when he wrote about his experience as a bond salesman at Salomon Brothers. Liar’s Poker is considered one of the books that defined Wall Street during the “greed is good” era of the 1980s.

Since then, he’s authored more than 30 books on the topics of finance, economics, and sports. He has a unique ability to take complex topics and break them down into stories about relatable people.

His latest work is: Who Is Government?: The Untold Story of Public Service.

In a departure from his typical solo approach to writing, Lewis enlists six of his author friends to write a chapter for the book (Lewis himself writes two).

Each chapter is a story about a specific individual, working in a non-glamorous area of government, doing amazing things. Through these stories, the reader is able to develop a better understanding of how government works for the people, through people committed to the idea of public service.

In a recent podcast, Lewis said “all these people (profiled in the book) have found the secret to living a meaningful life. They could all be far wealthier working outside the government, but they choose to work inside the government because they have a sense of mission.”

-RK

Choosing the Right College Before the Decision Deadline

The following article was contributed by our colleague and college financial advisor Donna Cournoyer 

May 1, commonly known as National College Decision Day, marks the deadline for high school seniors across the U.S. to commit to the college they plan to attend in the fall. With multiple acceptance letters in hand, this decision can feel both exciting and overwhelming.

Here are some key considerations to help students and families make a confident choice.

1. Revisit Your Priorities
Start by reflecting on what matters most to you. Academic programs, campus culture, location, extracurricular opportunities, class sizes, and internship pipelines can all make a big impact on your college experience. While prestige and high rankings are nice, make sure the school aligns with your goals and values.

2. Compare Financial Aid Offers and Merit Scholarships Awarded
Cost is a major factor for many students. Lay out all the financial aid packages you’ve received, including scholarships, grants, loans, and work-study options. Calculate the net cost (not just the tuition sticker price) and consider long-term debt implications.

Merit scholarships (non-financial need funds) are especially important if you do not qualify for financial aid. If you are considering a school that does not offer merit scholarships, be sure to know the full price you will be responsible for.

Be sure to have a four-year financing plan in place, not just a way to “make it through paying for year one”.

3. Attend Accepted Student Events
Many colleges offer virtual or in-person events for admitted students during April. These are great opportunities to ask questions, meet future classmates, and get a real feel for the campus environment.
Have your questions ready and seek out those who can help to give you important information to help you make this decision.

4. Talk to Current Students and Alumni
Hearing honest perspectives from current students or recent graduates can offer insights you won’t find with college brochures and marketing materials. Those leading the tours are going to “sell” you on choosing their school, usually no matter the cost.

Be sure to ask about academic rigor, social life, career support, and anything else important to you.

5. Trust Your Gut
At the end of the day, this is your decision. You might not have all the answers, and that’s okay. Consider where you felt the most comfortable, excited, or inspired. Your instinct can be a powerful guide.

Final Tip: Don’t Miss the Deadline

Once you’ve made your choice, be sure to submit your enrollment deposit by May 1 to secure your spot. Also, notify the schools you’re not attending so they can offer spots to wait-listed students.

Choosing a college is a milestone—and while it’s a big decision, it’s just the beginning of an exciting new chapter. Take a deep breath, weigh your options, and take the next step with confidence. By this time, you have put in the hard work both in high school and in your college search.

Finally, celebrate your decision. This is a major milestone! Enjoy the remainder of senior year and rest up this summer (maybe work to earn a few extra dollars) so that you are ready for move-in day this fall.

Additional Pointers for Parents

Right now, you are not alone. Many families across the country are working together to help their high school seniors make one of the most important decisions of their academic journey: choosing which college to attend. As a parent, your guidance, support, and perspective can play a vital role.

Here’s how you can help your student make a thoughtful, confident choice:

  • Now is the time to remind your student about their priority list and to help them focus on where they will thrive. While attending a school of prestige has certain attractions, the reality is that most of the time, other schools on their list will offer everything your student needs to have a great career and make connections that will last a lifetime.
  • Hopefully you have already had a conversation about finances. However, now is a good time to review with your student their financial responsibilities, including costs, loans, etc. It’s also important to discuss what you are willing to finance as their parent. Be sure it is a realistic plan and makes sense for all of you. If it is not a smart decision financially, it may be wise to consider another choice.
  • Offer support, give guidance and perspective, but give your student space to use their own judgement. Your reassurance can go a long way to helping them feel confident and excited about the way forward.

Best of luck to students and parents in making the big decision!

Trade Walls Go Up

In this article:

  • Review of recent government policy actions
  • Recap of financial market performance as of early April
  • Crisis case study
  • Ideas for investors facing financial market disruption

Policy Action Review

“Liberation Day” arrived on April 2, when President Trump announced his newest round of tariffs during a Rose Garden press conference.

The president also presciently warned “there may be short-term pain.” Indeed. US stockholders were collectively liberated from about $5 trillion in the most recent two trading days, according to Reuters news agency.

After stocks fell sharply on April 3 and 4, the onset of a new bear market (typically defined as a 20% market decline from the recent peak) which was hard to imagine just weeks ago, now looks much more likely.

This time around, government policies have precipitated financial market disruption and are expected to cause widespread economic dislocation.

A summary of the Trump Tariffs:

  • 10% baseline on all imports, effective April 5
  • Assess higher country-specific tariffs for the “worst-offending” trading partners, effective April 9
  • Combining the new tariffs with those that have already been announced moves the average effective tariff rate up to about 22%
  • Canada and Mexico were notably excluded from the most recent round of tariffs
  • Aluminum, steel, and autos are also exempt as they are already covered by targeted tariffs
  • Energy, minerals, copper, pharmaceuticals, semiconductors, and lumber were excluded, but are expected to be affected at some point by sector-specific tariffs

The new tariff regime is roughly equivalent to the high tariff levels of the early 1900s, a time when the US economy was far smaller and much less integrated with the global economy.

Tariffs likely will present a sizable shock to both prices and economic growth.

The estimated impacts to economic growth and inflation are:

Source: Apollo

These impacts, assuming the announced tariffs remain in place for some time, mean that economic growth in the US for 2025 is likely to be in the neighborhood of 1% (not a recession) and inflation will probably be in the neighborhood of 4%.

Following the announcements on Wednesday, professional forecasters began to raise the probability that the US economy will fall into recession.

For example, Goldman Sachs puts the risk of US recession at 35%, while JP Morgan now places the odds of a recession at 60%.
Despite recession odds climbing significantly, most Wall Street economists continue to support a base-case scenario of modest economic expansion in 2025.

However, because the tariffs were far steeper than expected, the reaction in the financial markets was pronounced and negative.

Financial Market Assessment

So, just how bad has damage been in the financial markets? For stocks, the short answer is: pretty bad.

The policy-driven Liberation Day was followed by investor-driven “Hibernation Days”: the broad-based S&P 500 index of large-company US stocks, for example, fell by more than 10%. US stocks are now within spitting distance of a bear market.

Bonds have provided a counterweight in balanced portfolios, with many bond funds registering price appreciation. The Bloomberg Aggregate US Bond Index (investment grade bonds) increased in value by about 0.5% during the past two days.

Below is a table of historical asset class returns, ranging from very short-term (last two days), to the long term (previous 10 years).

Source: Morningstar

How much worse could it get?

The answer depends largely upon the extent of the economic damage, which likely will be a function of the extent and duration of the new tariff regime.

Since 1950, there have been 56 pullbacks of 10% or more, according to a recent article in Barrons. Twelve months after those corrections, stocks were higher 49 times.

Of the seven they failed to rebound, six of them came during a recession. In the median recession, stocks have fallen by 25%.

The most recent “worst” recession / bear market combination occurred during the Global Financial Crisis of 2007 – 2009. The unemployment rate reached 10%, and the US stock market declined by approximately 56%.

The second worst recession / bear market combination in recent times occurred in 2000 – 2002, following the “dot-com” bubble. The unemployment rate reached 6%, and the US stock market declined by approximately 49%.

Crisis Case Study
The Trump Tariff War may turn out to be a seismic event. It may be the start of a reordering that will change economic and political relationships for decades. It might cause inflation to spike, companies to retrench, consumer and business confidence to crater, and workers to lose jobs.

Trump Tariffs may bring on an epic bear market in stocks, and stocks could stay in the gutter for an extended period. Or maybe they won’t.

In an optimistic scenario:

  • foreign countries decide to negotiate rather than retaliate
  • inflation rises incrementally rather than exponentially
  • US companies decide to reshore operations that are currently located offshore
  • foreign companies locate more of their operations in the US
  • more jobs are created for US workers (who are also consumers)
  • business and consumer spending goes up rather than down
  • the economy continues to expand rather than contract

To expect that all this happens immediately seems a bit pie-in-the-sky. But it also can’t be ruled out.

In a less optimistic scenario, but still positive scenario President Trump may decide on a different course of action (history shows that Trump can change his mind). A new, new tariff regime may be less onerous, and the economic growth and inflation impact may be less severe than feared.

It’s fair to say that the current tariff regime is unprecedented in the US – at least in terms of the last hundred or so years. The range of potential outcomes from the new trade regime is wide, where “crisis and crash” must also be considered.

In the two worst-case scenarios referenced in the previous section (dot-com bubble and Global Financial Crisis), the issues affecting the US economy were multi-layered and deep.

In the case of the dot.com bubble, the speculative frenzy for buying “lottery ticket” stocks of unprofitable companies associated with the internet reached a fever pitch and pushed stock prices in general far beyond rational levels.

Also, widespread corporate accounting fraud precipitated widespread business failures which exacerbated the stock market crash.

In the case of the Global Financial Crisis (GFC), the combination of speculative frenzy in the US housing market; overextended homeowners; loosened US financial institution regulation; wildly extended bank balance sheets around the world; fraudulent activity at US rating agencies; and failure-to-act government were all factors in the stock market crash.

In today’s situation, stock prices are generally regarded as being high relative to history, but not wildly overvalued, so the condition of speculative excess seems to be absent.

Also, the traditional US banking system appears to be stable and sound. The regulatory screws were turned tightly post GFC, which has helped to keep bank risk taking in check.

So, the Trump tariff situation strikes me to be more of a single-event flashpoint.

For a case study in what can happen during a crisis caused by a single-event flashpoint, consider the situation in 2020:

  • On February 4, 2020, the City of Boston reported the first case of the “novel coronavirus” in Massachusetts, which also happened to be the eighth case of the infection reported in the US
  • On March 10, Massachusetts Governor Charlie Baker declared a state of emergency
  • In late March 2020, the S&P 500 index of large-company US stocks plunged to its lowest point during the pandemic, declining by a third from its record high of a month earlier.
  • Covid had been in the public consciousness for several weeks, and the magnitude of the health crisis was just sinking in.
  • No one knew how deadly, or how long-running, the pandemic would be.
  • A recession was just starting, and the severe economic contraction would extend into the summer.
  • No one knew when we would have an effective vaccine (turns out, we got one by year end)
  • Investors were panicking.
  • Yet stocks began to turn around on March 24 (gaining almost 10% on that day alone).
  • By August 18, the stock market was back at a record high.
  • The first COVID-19 vaccine received approval in December 2020
  • For the full year of 2020, stocks posted a gain of 18%

The pandemic was a health catastrophe, and many folks unfortunately are still dealing with related illness and personal loss.

The period of a half-decade ago also serves as a reminder for why it’s so important to stick to your financial plan and your investment strategy.

Covid crushed consumer and business confidence and tore through the social and economic fabric of the US. Financial market deterioration was sharp and swift, registering a 34% stock market decline in a matter of weeks during February and March 2020.

But recovery was sharp and swift, too, with stocks reversing the decline by August 2020, and ultimately gaining 18% for the full year of 2020.

Market Disrupted. Now What?

What should investors do? Looking before leaping is always advisable. So is pausing before pressing the “sell” button.

Reducing risk by selling stocks may bring temporary relief to emotional stress and pain caused by a sudden drop in stock prices, but it has seldom proven an effective approach for building wealth over the long term.

Prudent action can take a few forms during financial disruption, including:

  • Tax loss harvesting:fo r individual or joint brokerage accounts subject to capital gains tax, a stock market downturn might cause prices of some individual stock or stock fund holdings to fall below cost. Selling holdings below cost creates a capital loss, which can be used to offset capital gains realized in other parts of the portfolio. Or, if no realized gains are available to offset, a realized loss can be used to offset taxable income, subject to an annual limit, and carries forward for use in future year.
  • Roth Conversions: a Roth conversion involves taking a distribution from a traditional IRA, paying income tax on that distribution, and immediately depositing or “converting” that distribution into a Roth IRA. If a conversion takes place during a low point in stock prices (instead of during a high point), stock fund shares will have a lower value, so more shares can be moved from Traditional IRA to Roth IRA for the same tax bill. When the markets recover, the subsequent share appreciation in the Roth IRA occurs tax free.
  • Rebalancing: If you believe that corrections are temporary, and that over the long-term stock prices will rise, then a stock market drop can be viewed as an opportunity. The idea of rebalancing is simple: investors choose a target asset mix (such as: 60% stocks and 40% bonds). When asset price changes pull actual portfolio weights away from target weights, investors sell the assets that have gone up in price and buy the assets that have gone down in price. This rebalancing brings the portfolio back into line with its target. When stock prices fall, rebalancing allows investors to buy long-term appreciating assets at a discount.

When investors are faced with economic crises (whether pandemic-induced or policy-inflicted) and financial market turmoil, advice such as “keep calm”, “try going for a walk”, and “don’t look at your account statements” probably falls flat.

However, sticking to your plan is not the same thing as sticking your head in the sand. It is important to be aware of what’s going on, to try to understand how the landscape might be different in the future, and to adjust your financial situation accordingly.

Taking prudent action may mean stress-testing your financial plan to account for a new economic environment and to give you confidence that things will be OK over the long term. Or it may mean reviewing your investments to see how changes in the financial markets might affect the prospects of future returns. It might even mean asking for an interpretation of a new technological development that is causing confusion or concern.

Susan, Donna, Alex and I are here to help with any of these issues, or other items that may affect your personal financial situation.

I’ll leave you with this closing thought: it will take much more than a draconian new set of trade policies to take down US consumers, US businesses, and the US financial markets. We may feel pain from self-inflicted wounds (in the words of JP Morgan analyst Bruce Kasman, “there will be blood”), but the damage is much more likely to be terminable (and manageable) rather than terminal.

March 2025 Market Recap: Q1 Market Review: Mixed Picture

Given the developments that have occurred in early April – implementation of draconian trade policy and a sharp drop in stocks – the first quarter of 2025 already seems like ancient history.

The three main developments during the January – March 2025 period were:

Stocks reached new all-time highs in mid-February, but didn’t stay at those lofty levels for long as tariff concerns set in

  1. Foreign stock returns exceeded US stock returns by the widest margin in some time, helped by a weakening US dollar
  2. Bonds provided ballast for portfolios by delivering positive returns

Here’s a snapshot of quarterly stock and bond performance for the last four quarters:

Note: US Large Co = S&P 500 Index; US Bonds = Bloomberg US Aggregate Bond Index

-RK

Is This AI or Just a Fantasy? – AI Explained

Our colleague and Operations Manager Alex Kania explains how a newer development in Artificial Intelligence, called a Large Language Model, works- and how you can make I work for you 

If the first two decades of this millennium were defined by the emergence and increasing relevance of the internet into public life, the next decades may well be defined by the explosion of Artificial Intelligence.

In a few short years, “AI” (Artificial Intelligence) has transformed from sci-fi speculation to a normal part of many people’s personal and professional lives.

Advocates see this as a transformative tool which could usher in the greatest technological change since the industrial revolution.

Opponents see it as an existential risk factor comparable to nuclear weapons. Skeptics see it as a glorified party trick bandied about to boost share prices while failing to offer anything truly transformative.

I’ll leave it up to you to decide who is right.

In the article that follows, I explain how this current crop of (at times) shockingly human-like services like ChatGPT actually works, and how you might use them.

What do we mean by “AI,” anyway?

AI is a fairly loaded term which conjures images of an impossibly intelligent computer system far beyond our fleshy comprehension. The reality is actually much more mundane – “AI” is a fairly nebulous term which simply refers to a machine which can accomplish a task or tasks typically associated with human intelligence.

This leads to a paradox where once a task becomes more associated with machines than human intelligence, it definitionally ceases to be “AI.” Searching a database, for example, is now almost exclusively thought of as a job for computers, but was once (not too long ago, so I’m told) performed by humans.

In some sense, then, AI has been here for at least the past 20 years – but this is not what’s driving the current “AI Boom.”

Rather, concurrent increases in computational power and development of more sophisticated means of representing language has led to the development of tools that can (seemingly) read and write like people, powered by something called a “Large Language Model.”

What is a Large Language Model?

A large language model or (“LLM”) is a computer program which can process natural language. Models designed to generate output text to respond to the user are considered “generative,” since they generate text as a response, although LLMs also encompass models designed for other functions like classifying text or generating code from a text input.

LLMs earn the name “large” because they are trained on *enormous* collections of text – scanning through millions of books, articles, and websites.

By digesting this vast data, an LLM builds up a statistical model of language, which it uses to produce new sentences that sound fluent and human-like. Think of an LLM as a super-advanced version of the autocomplete feature on your phone.

Just as your phone might suggest the next word when you’re texting, an LLM can predict words to continue a sentence in a sensible way.

The difference is that an LLM’s abilities go far beyond a simple text suggestion – it can generate paragraphs of text, answer complex questions, write stories or essays, and even carry on a dialogue.

Modeling Language

A model is a simplified representation of something designed to preserve some key elements.

For example, a model train preserves the appearance of a train while eliminating or changing other attributes (like changing the size and eliminating the ability to carry passengers).

Modeling language in this context means simplifying it to a series of statistical interrelations between symbols with no preservation of the deeper understanding of the world language represents.

In some sense, language is a model of our experience of the world, shaving off qualia but maintaining enough of some underlying essence to allow for communication.

LLMs are effectively working with a model of a model – although this can produce some very human-like results, it’s important to remember these systems have no deep understanding of language beyond their encoded statistical maps.

One way to think of it is like a very well-read parrot that has seen every possible context for words – it doesn’t know facts or truth per se, but it knows how words are usually used together. As a result, it can produce remarkably coherent sentences on almost any topic.

How Does an LLM Decide What to Say?

When you ask an LLM a question or give it a prompt, how does it come up with a response? It all boils down to prediction.

The model looks at your input and internally tries to predict a suitable next word, then the next, and so on, one word at a time. Each word is chosen based on probabilities the model has learned.

Essentially, the LLM asks itself: “Given everything I’ve seen (in the prompt and in my training), what word is most likely to come next?”, and it outputs that. Then it repeats the process for the following word, continuing until it produces a complete answer.

Here’s an analogy: imagine the AI is continuing a text that it “thinks” you want to see. If you start a sentence, it will finish it in a way that fits the style and context. The LLM doesn’t have a database of perfect answers; instead, it generates answers on the fly by stringing together likely words.

For example, if the prompt is “The actress that played Rose in the 1997 film Titanic is named…” the model will recognize this as a question about a known fact. It will consider the patterns in its training data and likely predict “Kate” then “Winslet” as the next words, forming the answer “Kate Winslet.”

The model arrives at this by having “read” many movie articles and knowing that “Rose…Titanic…is named” is often followed by that name. In essence, the LLM is doing an educated guess based on learned patterns.

It’s important to note that the model isn’t retrieving this answer from a stored fact lookup; it’s generating a response from what it learned.

If your prompt were slightly different or if there were ambiguity, the model’s guess for the next word could be different.

The decision process is statistical: the LLM has a sort of internal compass that was calibrated during training to point to likely continuations.

Because it has so many parameters (like millions or billions of “neurons” adjusting to text patterns), it can capture subtle relations – like understanding that “Rose”, “Titanic”, and “actress” together are likely talking about Kate Winslet. That’s how it determines what to say next.

Another way to think about it: the LLM generates text kind of like how we form sentences when speaking off the cuff.

We don’t plan every word in advance; our brains produce words that make sense as we go.

Similarly, the LLM produces one word at a time in a fluid manner. It doesn’t have a conscious plan or an agenda – it’s just following the direction given by the input and its training.

This is why sometimes the outputs can surprise even the creators of the model: it’s not using a simple script, it’s dynamically weaving a response from learned language patterns.

When AI Gets It Wrong: “Hallucinations” in LLMs

Now that we’ve established LLM “predict” instead of “think”, it may be easier to understand how and why they get things wrong.

LLMs generate text by probability, not by querying a database of verified truths. If the prompt leads into territory the model is uncertain about, it will still produce an answer because that’s what it’s designed to do – generate a continuation.

Unlike a human, LLMs don’t say “I don’t know” unless specifically trained to. They just keeps writing something that sounds right. For users, the key takeaway is: LLMs do not guarantee accuracy. They can embed plausible-sounding falsehoods in their answers.

This is why using an LLM can feel like conversing with a very knowledgeable but sometimes overconfident person who occasionally “bluffs” an answer when unsure.

In practical terms, when you use an LLM (like asking for medical advice, legal information, historical facts, etc.), it’s wise to treat the responses with a healthy dose of skepticism. Use them as a helpful draft or a starting point, but verify critical details from trusted sources.

The technology is improving, and newer models are trying to reduce these hallucinations, but no LLM is 100% reliable on facts.

LLM vs Search Engine: What’s the Difference?

It’s easy to confuse using an LLM with using a search engine like Google, since both can answer questions. However, they work very differently.

Search engines (Google, Bing, etc.) are tools that find and retrieve information. When you search, the engine looks through its indexed web pages for your keywords and returns a list of links to webpages, images, or documents that might contain the answer.

Essentially, a search engine is like a librarian – you ask for information, and it hands you a stack of books or articles (the search results) where you might find what you need. It’s then up to you to read and extract the answer. Traditionally, search engines don’t generate new text; they give you existing content from the web, along with its source.

LLMs (ChatGPT/Bard and similar) are tools that generate content. You ask a question or give a prompt, and the LLM directly produces an answer in natural language. It does not give you a list of sources or direct excerpts unless specifically designed to do so.

Instead, it creates a response on the fly. Using the librarian analogy, an LLM is like a knowledgeable person you ask a question to, and they speak an answer back to you in full sentences, as if they’re explaining or teaching.

The answer is synthesized from what the model “knows” (from its training data), not quoted from a specific webpage.

It’s worth noting that the lines are blurring: modern search engines are integrating AI (Google now often shows AI-generated answers or summaries at the top of search results) to give more direct answers, and many LLM-based services can cite sources or even search the web when generating answers.

But fundamentally, an LLM is not searching the live internet when you ask it something (unless explicitly connected to a search tool). It relies on its pre-existing training data and any provided information to craft a response.

This means LLMs might not have the latest information, whereas a search engine is continuously updated by crawling new web content.

What Can LLMs Help With in Everyday Life?

Summarizing Information: If you have a long article or report and you want just the key points, an LLM can summarize the text for you in a few paragraphs or bullet points. This is like having a speedy reader digest content and present the highlights.

It’s useful for skimming news, research papers, or even simplifying a dense legal document into plain language.

Explaining or Tutoring: LLMs can explain complex topics in simpler terms. Curious about a scientific concept or a piece of history? You can ask an LLM to explain quantum physics as if you’re 5 years old, or to summarize the causes of World War I in a concise way.

Planning and Advice: While they’re not perfect, LLMs can help generate plans or give advice on everyday matters.

For example, trip itineraries (“Plan a 3-day visit to Paris with a focus on art museums”), meal planning (“What’s a healthy dinner idea with chicken and broccoli?”), or personal to-do lists (“Help me create a weekly schedule for my study routine”).

The LLM will generate a structured suggestion that you can then adjust to your needs. They can even play role-based scenarios – like acting as a personal coach giving you motivation tips or a historical figure answering in character, which can be both fun and educational.

Keep in mind though, while LLMs can assist with tasks, they are not perfect and can occasionally produce odd or incorrect results (remember the hallucinations). So for critical tasks, you wouldn’t rely on the LLM alone.

But for every-day, low-stakes tasks, they can save you time and effort by handling the heavy lifting of drafting text or searching through information. In fact, studies have shown that using LLMs can streamline many routine tasks, freeing up time for more important things.

What LLMs Can I Use Today? Do I Have to Pay?

Numerous LLMs are publicly accessible, either directly or through products built on top of them. Some (like ChatGPT, Gemini, Copilot) are directly aimed at end-users and have easy chat interfaces.

Others are more behind-the-scenes but might surface in apps you use. The good news is you don’t need to be a programmer or a tech guru to try them – if you can use a web browser or install an app, you can likely access an LLM.

For the big names, just visit their official websites and they’ll guide you on how to start. (As with any online service, be mindful of official links to avoid scams.)

One great thing about the AI boom is that many LLM services offer free access, at least for basic usage. For instance, ChatGPT has a free version that anyone can use, as does Google’s Gemini and Anthropic’s Claude.

You might wonder why they’re free – often it’s because companies are gathering feedback, improving the AI, or integrating it with their services, so they want as many people as possible to use it.

That said, there are usually paid options or subscriptions for heavy users or for accessing more advanced features.

Using ChatGPT as an example: OpenAI offers a subscription called ChatGPT Plus (roughly $20 a month) which gives access to their most advanced models (GPT-4, which is more powerful than the free version’s GPT-3.5), and also provides faster responses and priority access even when demand is high.

But if you’re a casual user, the free ChatGPT service is quite capable on its own for light use and trying things out. The paid tier is more for enthusiasts or professional use where the small improvements in quality and speed matter.

Is Your Personal Information Safe with LLMs?

If by “safe” we mean confidential – you should assume that what you type into an online LLM might be seen by humans running the service or at least by the AI company’s algorithms.

It’s not broadcast publicly (other users won’t see your specific chats), but it’s also not 100% private like talking to a lawyer or doctor under privilege.

A good rule of thumb is not to share anything with an AI chatbot that you wouldn’t share in an email to a stranger.

Keep your inputs fairly generic and non-sensitive. Asking it to draft a generic business plan is fine; asking it to analyze your personal medical records is not a good idea.

On the flip side, companies are aware of these concerns. They do implement security measures: for instance, OpenAI claims conversations are encrypted in transit and at rest, and only authorized personnel can access data.

They also have policies against the AI requesting personal data from users. So, it’s not that using an LLM is dangerous, it’s just that you are your own best gatekeeper – you decide what to divulge.

In summary, personal information is as safe as you make it when using an LLM. The AI itself isn’t malicious or trying to steal info, but the infrastructure around it means your data isn’t totally private.

Treat an AI chat like a semi-public space: enjoy the conversation, get help with tasks, but don’t spill secrets. If you stick to that guideline, using LLMs can be very safe.

More Reading on AI and LLMs

Alex utilized a range of sources when preparing the article on Artificial Intelligence and Large Language Models. You might enjoy diving deeper into the subject, so we’ve included links to the sources below.

US Department of Education Shakeup: The Effects

Our colleague and college specialist Donna Cournoyer shares her thoughts on the shake up at the Department of Education, and what it means for colleges and universities, and students

When the new administration took office on January 20, they swiftly took action, making big changes to multiple US government agencies, including the US Department of Education.

Layoffs, mass firings, and talk of eliminating some departments altogether. The US Department of Education is at the top of that list.

Linda McMahon was confirmed on March 3 as the next Secretary of Education, seemingly with the sole purpose of dismantling the entire US Department of Education.

As of March 6, President Trump is expected to issue an executive order soon- aimed at abolishing the Education Department, according to people briefed on the matter, as reported in the Wall Street Journal.

However, it appears that eliminating the department would take an act of Congress.

 Background

What is the US Department of Education?

Federal agency created by Congress in 1979

  • Responsible for overseeing education policies and programs across the country
  • Employs more than 4,000 people
  • Annual budget of $79 Billion
  • Overseen by the US Secretary of Education

Main Roles of the US Department of Education

 Funding for US Public Schools

While most funding comes from state and local governments, the US Department of Education provides between 6-13% of funding for public schools, according to a 2018 report from the U.S. Government Accountability Office.

  • Title I-Helps serve lower-income communities. In 2023, the Education Department received more than $18 billion for Title I.
  • IDEA (Individuals with Disabilities Education Act)-Provides money to help districts serve students with disabilities. In 2024, the department received more than $15 billionfor IDEA.

Created by separate acts of Congress, Title I was signed into law in 1965, and IDEA signed into law in 1975. It is highly unlikely that these acts would be undone. An act of Congress would be needed, and they have broad bipartisan support.

Tracking of Student Achievement Through the “Nation’s Report Card”

The department oversees the National Assessment of Educational Progress (NAEP) known as the “Nation’s Report Card”.

  • Congress mandated this assessment in 1969, and tests students in reading, math, science and other subjects
  • It also offers insights into attendance, economic conditions, and students’ educational backgrounds
  • Educators, policymakers, and researchers use this data to work toward improving the K-12 education across the US

Oversight of Federal Grants and Federal Student Loans for College Students

The department manages federal aid programs, including Pell Grants and student loans which helps students afford higher education.

Key Functions Include:

  • Managing the federal student loan portfolio, approximately $1.6 Trillion, including oversight of outside contracted companies who manage the loans.
  • Managing the FAFSAapplication (Free Application for Federal Student Aid) which determines eligibility for grants, loans, and work-study programs for college students.
  • More than 17 millioncurrent students and new applicants fill out the FAFSA each year.
  • FSA (Federal Student Aid) provides approximately $120.8 billion in grant, work-study, and loan funds each year to help students, and their families, afford a college education.
  • This includes $33 Billion in Pell Grants for low/middle-income undergraduates.
  • The FSA also prevents fraud and abuseby ensuring that schools and borrowers comply with federal regulations to prevent financial mismanagement.

Data Collection on Colleges and Students

Through the IPEDS (Integrated Postsecondary Education Data System), the US Department of Education gathers independent research, statistics, and evaluations of colleges throughout the country. Schools are required to complete detailed reports each year.

  • This information helps students and parents analyze and compare different schools through admissions statistics, academic outcomes, graduation rates, need-based eligibility data and more.

Although the current administration has said it would close the Department of Education, and return “all education, and education work and needs back to the states”, it is already up to the states and local agencies to determine what is taught in classrooms. The department does not dictate what is taught at K-12 schools, colleges, or universities.

Recent Changes to the Department of Education Since the Inauguration and Their Potential Implications

Repayment of Federal Student Loans

If federal student loans face disruptions, students may have to move to private lenders, where they may be subject to higher interest rates and fewer repayment or forgiveness options.

  • The current administration has already paused applications for some income-driven repayment plans.
  • If the administration moves the loan repayment for the $1.6 Trillion in loans to another agency, such as the Treasury department, (an idea that has been discussed) it likely won’t be a quick or smooth process.
  • The future of the loan repayment plans is unsure, students could see a higher monthly payment if the plan options change.
  • One extreme possibility is the privatization of the entire student loan system, which would have wide-spread financial implications for loan holders.

University Research Funding Proposed Cuts

The current administration has proposed significant reductions in federal funding for university research, particularly targeting the National Institutes of Health (NIH).

Legal Actions have been initiated. A federal judge in Massachusetts issued a preliminary injunction blocking the implementation of the 15% cap on indirect cost reimbursements.

Despite the legal challenges, this has created widespread concerns among research institutions.

  • Stanford Universityhas implemented a hiring freeze with leadership citing the potential NIH funding reductions and increased taxes on large private university endowments as factors necessitating these precautionary measures.
  • Rice University anticipates that this will jeopardize critical projects, including innovative cancer treatments and detection technologies. They warn that without sufficient support for indirect costs, they may be faced with difficult choices of raising tuition or halting certain research endeavors altogether.

These proposed cuts pose significant challenges to universities, and could disrupt essential research, lead to job losses, and potentially affect the ability of the US to have a competitive edge in global scientific and technological arenas.

Other broader implications beyond individual universities, is a growing concern that reduced research investment could hinder scientific innovation and diminish the US global leadership in technological advancement.

Some analysts caution that this may allow other nations, notably China, to surpass the US in critical areas like artificial intelligence and quantum computing.

Federal Grants and Loans- Eligibility and Processing at Colleges and Universities

  • The FAFSA has already gone through a horrible two years of a new form rollout. Changing oversight of this form, (a possibility) or eliminating the US Department of Education, would likely result in more upheaval of the application process for college students.
  • Eligibility –It is unsure at this point if any actions will be taken to change how eligibility is calculated by the FAFSA form.

 Federal Employee Layoffs or the Elimination of the US Department of Education

  • Fewer employees at the department and FSA (Federal Student Aid) could mean a disruption of the processing and flow of Federal aid including federal grants and student loans.
  • Note that federal aid resources such as Pell Grants and student loans are established by Congress, and an executive order to end them is not a legal option and highly unlikely.
  • If the processing of federal aid changes hands, this may cause significant challenges for the timely disbursement and processing of aid for students.

Final Thoughts

As an insider in the Higher Education sphere for much of my career, I understand the processes and intricacies of how colleges and universities operate on many levels.

Colleges are run like a business and rely on tuition to meet budgetary needs. Any federal cuts can have significant impacts.

Endowments (the funds collected from donors) are designed to be a permanent source of income and are used to make long-term investments.

These funds are used to sustain the operating costs and to offer discounts on tuition to attract students to enroll. If other funding is reduced, more strain may be put on endowments going forward.

Financial aid offices coordinate the awarding and disbursement of funds through many systems to get the funds for students disbursed in a timely manner while also complying with federal regulations.

During a time when colleges are still rebounding after the pandemic, and enrollment is on a steady decline due to a shrinking birth rate.

Along with FAFSA application issues, the upheaval caused by the current administration’s decisions, particularly to the US Department of Education, will likely creating more challenges.

Since the Covid-19 pandemic, seventy-four colleges have closed, merged, or announced plans to close, according to bestcolleges.com.

Institutions may become even more unaffordable, research and learning opportunities may be of less quality, and the already complicated, opaque process of applying to college is likely to become even more challenging and complicated.

The biggest immediate effect for students likely will have to do with financial aid.

Many fewer employees at the Department of Education (or of its demise) will make the processing and disbursement of federal funds challenging and likely create disruption and delays. Exactly how this plays out is yet to be seen.

As students and families approach applying to college (and for those in college), it is a good practice to remain informed, particularly as significant changes are likely on the horizon.

Seeking professional advice when possible and keeping calm as you approach college planning will pay off when it comes time to make the four-year commitment, and decide on financing options.

-DC

Tariff Beauty: In the Eye of the Beholder

For some, tariff “is the most beautiful word in the dictionary.” But not for all. Beauty is in the eye of the beholder.

Below is a table that summarizes the tariffs that have been announced so far (courtesy of Apollo) along with their corresponding dates of implementation:

A month ago, President Trump announced that he would impose sweeping tariffs on imports from Canada, Mexico, and China. Soon after, a last-minute deal was reached to delay the Canada and Mexico tariffs for 30 days.

During the first week of March, when the tariffs were scheduled to come into effect, the tariffs on Canada and Mexico were watered down with a 30-day reprieve for automakers.

Also, broader exemptions for other products that are imported from America’s neighbors were permitted after lobbying from business groups that warned of rising prices.

This fluid situation around tariffs may be a feature stemming from the administration’s approach to negotiation, and the backtracking could be a realization that tariffs likely will cause domestic production and supply disruptions, push up inflation, and weigh on economic growth.

The administration’s main economic goals of applying tariffs appear to be to:

  • address unfair trade practices
  • correct significant trade imbalances
  • rebuild the US manufacturing sector

And trade policy that relies on tariffs as a cornerstone is high risk.

In a recent article, JP Morgan Asset Management’s Chief Global Strategist highlighted that tariffs have undesirable consequences including that they:

  • Raise prices
  • Slow economic growth
  • Cut profits
  • Increase unemployment
  • Worsen inequality
  • Diminish productivity
  • Increase global tensions

Economists at major banks and research firms have begun to increase the odds that more tariffs will be implemented (and not just threatened) and applied for longer.

On Monday, March 10 the chief economist at Goldman Sachs published a report that factors in new, more adverse trade policy assumptions. He made a significant downgrade to his US growth forecast for 2025 (by nearly 1 percentage point) – though he still expects the US economy to expand this year.

Moody’s Analytics has estimated that if the US were to impose universal tariffs on all goods entering America, it could slow US economic growth by 3 percentage points by 2026, which likely would push the economy into a recession.

At this point, I don’t believe a tariff-induced US recession is the likely outcome, in part because tariffs still appear to be more malleable than ironclad, but also because the US economy has proven to be resilient and remains on a sound economic footing.

But it’s also quite possible that continued tough talk toward trading partners coupled with policy action that sticks will bite. A meaningful slowdown in the quarters ahead may be in the cards as well as more unsettling moves in stocks.

For all investorsholding to a stress-tested financial plan with an appropriate investment strategy and asset-allocation target is the time-tested way to weather financial market swings, irrespective of what headline or new development is causing the volatility.

And specifically for retirees who depend on portfolio withdrawals, verifying that enough cash is on hand to avoid having to sell stocks if stock volatility persists for an extended period, is always good practice.

-RK

February 2025 Market Recap: Turbulence Part Deux

Our January Market Update highlighted “beneath the surface” turbulence in the financial markets. In February, that turbulence emerged, pushing stock prices lower – and pressure accelerated into early March.

The US stock market hit a new all-time high on February 19. But the mood in the US financial markets, which had been generally positive since election day, shifted due to investors’ nervousness driven by:

  1. The lofty prices of big tech stocks
  2. The possibility of slower economic growth
  3. Repercussions related to trade policy and tariffs

Since mid-February, technology shares have been leading the way lower for US stocks. From the February peak to the close of trading on March 10, the Nasdaq 100 technology-focused stock index declined by 12.9%.

Declines in the broader stock market have been less pronounced. The S&P 500 Index of large company stocks has declined by 8.6% from the mid-February peak.

Interestingly, foreign-company stocks have held up relatively well, with the benchmark MSCI EAFE Index of 21 developed countries (excluding the US and Canada) rising by about 1% since February 19.

The repercussions related to trade policy and tariffs are unclear at this point because the policies themselves are unclear, with the administration taking an on-again, off-again approach to both policy formulation and implementation.

However, consumers’ concerns amped up in February. Worries about the future direction of the US economy were displayed in two monthly surveys:

The University of Michigan’s Index of Consumer Sentiment for February declined sharply from the January reading, and inflation expectations took a big step up from January. This monthly survey polls at least 500 individuals each month from across the US.

A separate survey of consumers, conducted by The Conference Board (which interviews approximately 300 consumers each month) showed similar results: a steep decline in consumer confidence, marking the third straight decline, and an increase in inflation expectations.

Below is a chart showing the Consumer Confidence Index, published on The Conference Board’s website. The blue line shows the history of the Consumer Confidence Index. The grey bars indicate periods of economic recession.

According to The Conference Board, a reading below 80 generally indicates a potential recession is ahead, based on consumers’ short-term outlook for income, business, and labor market conditions. Currently, the data is healthy distance from signaling recession.

A senior economist of global indicators at The Conference Board had this to say about February’s survey: “References to inflation and prices in general continue to rank high in write-in responses. Most notably, comments on the current administration and its policies dominated the responses.”

Without clarity on policies that will affect jobs and the cost of goods and services, consumer concern likely will stay high, and consumer activity may downshift.

Because consumers make up the largest component of the US economy – consumer spending accounts for roughly two-thirds of Gross Domestic Product, or GDP – financial market participants smell trouble, which has pressured stocks.

For the month of February, large-company foreign stocks (MSCI EAFE Index) came out on top and gained 3.1%. US investment-grade bond returns (Bloomberg Aggregate Bond Index) also were appealing, with a gain of 2.2%.

Large-company US stock returns, measured by the S&P 500 Index, declined by 1% in February. Technology shares, measured by the Nasdaq 100 Index fell by 2.7%, and Small-Company US Stocks fell by 4.8% (CRSP US Small-Cap Index).

Here’s a snapshot of February market performance (note that returns from the first week of March are excluded from the chart below):

Note: Foreign Stocks: MSCI EAFE International Index; US Small Co: CRSP US Small Cap Index; US Large Co = S&P 500 Index; US Tech Stocks: Nasdaq 100 Index; US Bonds = Bloomberg US Aggregate Bond Index

-RK