If this trial proves successful, I will expand the research, so I have a rolling position in five biotech stocks awaiting approval/phase 3 readouts.

This week I am going to elaborate on the plan by looking at last month’s Phase 3 readout from Definium Therapeutics pivotal trial for its LSD drug to treat Generalized Anxiety Disorder or GAD.

My analysis will focus on statistics. I am not medically trained, but I have postgraduate qualifications in statistics and game theory, and I intend to use that knowledge to decide whether the data suggest the drug might pass its next milestone and become a blockbusting, cash-generating moneymaker.

I will be extremely skeptical, assuming the worst in everything and analyzing the statistics for errors or reasons not to invest; only if a drug candidate passes this analysis will I decide to invest.

Definium a Likely Bust?

Definium stock jumped from $24 to $36 when phase 3 results were released earlier this month, up from $13 at the start of the year. The company is now valued at $5.9 billion, up from $82 million when I first covered it in 2022.

Shares are up 267% since I first covered the company, and we have seen around 300% dilution.

That rate of wealth generation puts enormous pressure on management and can incentivize decisions that satisfy the market and lift the share price but may also create FDA regulatory issues and make the drug unlikely to be prescribed even if approved.

A key issue is trial design, especially for pivotal phase 3 trials. In this case, I think the trial design was flawed and focused on proving the drug’s efficacy relative to the competition on the company's chosen metric at the expense of delivering robust data that could lead to FDA approval and adoption.

The company can alter many parts of a trial design: which patients are admitted, what they receive, what the active arm is compared against, and what the endpoint of success is. This creates a realistic possibility of a cooked book that the FDA will see through and payment processors will not cover.

Defimium focused on showing that their drug DT120 had the largest placebo-adjusted change in the HAM-A patient test score relative to a wide array of already approved drugs. The HAM-A is a questionnaire administered before and after treatment; it measures how anxious a patient feels.

The placebo-adjusted score is the difference in improvement between patients taking the drug and those taking a placebo. GAD is notorious for high placebo responses, making a high placebo-adjusted score difficult to get. The market-leading Xanax managed a placebo-adjusted score of 2.6 against Definium’s 5.4, implying the Definium drug is perhaps three times as effective.

The markets and the press hailed the result as groundbreaking, but digging into the details raised concerns that made me skeptical of the drug.

Double Blinding

The gold standard for pivotal trials is the double-blind test; neither the medic nor the patient knows whether they have the real drug or a placebo.

Definium chose to use a completely inert placebo, a sugar pill. This means that the patients in the test arm taking the real drug went on a 6-hour psychedelic trip, and those taking the placebo would not have felt anything.

This was compounded by Definium allowing a high percentage of their trial participants to have had previous psychedelic experience, so the patients largely knew what they should experience, and when they did not get that, they knew they were in the placebo arm.

This is called functional unblinding, many people knew which arm they were in, consequently the response reported by the placebo arm was very low, far lower than in trials of other drugs for this condition. This low placebo response led to a high placebo-adjusted effect, not a high response to the drug itself.

If we ignore the placebo arm and look only at the active arm, we find that DT120 delivered a HAM-A drop almost identical to XANAX and significantly less than other approved competitors like Venlafaxine, which recorded a drop of 13.9 on the HAM-A score versus DT-120's drop of 11.

There are multiple examples of the FDA refusing to approve a drug due to functional unblinding, and a direct comparison was the FDA rejection of MDMA-assisted therapy from Lykos Therapeutics.

Comorbidity and Patient Selection

The FDA decides which patients a drug can be approved for; the simple rule is that it can only be approved for patients it was tested on, but the FDA has wide latitude.

37% of patients admitted to the Definium trial had a second condition of Major Depressive Disorder [MDD]; this type of issue is not uncommon, and companies must decide how they will deal with it. Often, companies present the FDA with segmented data showing how those with the comorbidity responded relative to those without.

Definium chose not to do this; they assessed patients with MDD using the accepted MADRS score, another questionnaire designed to give a reading of how depressed someone is.

The company has not released the MADRS change and has said it determined that some people were “too sad to go into the GAD study”, the company worked hard to ensure people were not depressed when they took the drug.

This kind of cherry-picking of patients presents a potential labeling issue; the FDA may only approve the drug for patients who do not have a high MADRS score, as that is the only patient cohort Definium tested on; in fact, they went out of their way to ensure this. A drug only approved for happy, anxious people does not seem like a true blockbuster possibility.

Definium is also claiming success in treatment-resistant GAD sufferers, but this will be a hard sell to payment firms. Definium has said that patients who had tried 1 or 2 previous treatments responded better than those who did not.

However, they did not collect complete data about what they had tried, if it was just a trial, how long they were on the drugs, or the reason for stopping treatment. Indeed, they said many people could not remember what they had been prescribed and for how long; for me, that's a tough sell.

In my mind, this was a poorly designed trial that maximized the reported drug effect by minimizing the placebo response and presenting incomplete information about prior treatment.

The difference is made clear when we compare the trial design to another psychedelic drug competitor that reported a much smaller placebo-adjusted effect in treatment-resistant depression.

The market was disappointed by the low placebo-adjusted score, and the share price did not immediately move; however, the trial design shows significant differences. Compass designed its trial to show physicians what it could do and to ensure the FDA would not have a problem with its drug application.

Compass Pathways ran a three-arm Phase 3 trial giving each arm a different dose of the same drug; patients received either 1 mg, 10 mg, or 25 mg. As a result, the test remained completely blinded, as all patients had some kind of reaction. Compass ensured that their patients had tried at least 5 other medications prescribed by a doctor and that they did not have prior psychedelic exposure.

The placebo-adjusted score they reported was between the 1mg arm and the 25mg arm; the test remained blinded, and the improvement in outcomes was noticeably better than any currently available treatment despite the low placebo-adjusted score.

Conclusion

I will not be buying Definium, but I do have several more drug candidates under review, and the three companies in the portfolio are due to receive either FDA approval or release phase 3 results in the next quarter. I looked through the relevant data in detail and think they have a high chance of a positive outcome and a substantial pop in share price.

Trade Results This Week

Another volatile week; a hawkish-sounding Fed speech moved markets lower on Friday. In the end, the portfolio fell 2.5%, all of it on Friday.

August has only one trading day left, and it has been a pretty good month. I am looking forward to September and the return of liquidity following the summer slowdown.

I did not make any trades this week, but I expect a busy September.

Earnings Season

The earnings season is now almost complete.

I closed the companies underperforming my thesis after completing a full check, and the scorecard for the remaining 25 stocks in the portfolio is.

I have not yet managed to add to all of the accumulate-ranked stops but intend to do so in the near future.

After closing four stocks in total following earnings, we now have a decent amount of cash in the account providing ammunition for the weeks to come.

The rest of the article covers the earnings reports of the 3 companies in the portfolio that reported last week.

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Over the three years of this project to trade $250 a month into $100K my trading has been quite concentrated in a relatively small number of sectors

80% of all 125 trades fall into these three broad categories. From 2023 to 2025, they were very profitable, but the market has moved on, and they haven't delivered the same returns lately; indeed, the Electrification sector, which includes EVs, battery tech, electricity generation, and robots, seems to be stagnating a bit at the moment.

Just over 12 months ago I identified the medical field as an area prime for disruption and I have slowly increased my exposure in this sector.

With six out of six winning trades and all of these companies falling into my “Big Bagger” or better classification, meaning I am targeting more than 250% from them, the field has become of real interest.

Two of the trades are in a platform service provider that seems massively undervalued relative to the potential of its tech but the other four trades are in new drugs and that is an issue.

In the last few weeks, we have seen extraordinary volatility in this sector, with big wins and losses delivered at alarming speed.

Although I am not risk-averse, I am not a gambler either, but I think my background might give me an advantage in working out the chance of success for these stocks. I have a postgrad in mathematics specializing in game theory and probability, an MBA from Manchester Business School, and I once founded a tech start-up.

No other industry offers these binary dates of phase 3 trial releases and FDA decisions. Often we know in advance the likely date of these events and I have tried to put my skills to work looking for high probability candidates.

Of course there is no guarantee of success and inevitably I will suffer some losses, but with the percentage wins far outweighing the percentage losses and my belief that my background gives me an advantage in ensuring probabilities are in my favor, I think I have a good chance of delivering outsized returns from this sector in the coming year.

My long term win rate for this project is 56%. Applying this percentage to the CAPR and MRNA results implies my expected percentage win per trade is

Expectation Return = 0.56 x 182% - 0.44 x 86% = 64%

This is higher than my historical result of 46% (discussed July 26th Weekly)

The key to ongoing success is risk management. You can see from the size of the investments in the 6 positions that I do not take large positions; in fact, 3% of the portfolio is my maximum position size. Even if I do pick a CAPR the loss would be a 2.5% reduction in my portfolio.

The six current trades include three stocks heading towards key dates this year, two are FDA decisions and one a Phase 3 trial readout.

If I get two out of three right I will consider this a validation of the biotech thesis and start a biotech sector plan of having 4 or 5 stocks heading towards key catalysts, exit when they pass the hurdle and then look to add a replacement if I can find one that matches my criteria.

Results

It was a very busy week; I added one new name to the portfolio and closed 4 positions, putting cash back in the account after reviewing earnings announcements.

Only 9 of my 25 holdings posted a positive week, but two trades gained 41% and 35%, respectively, which offset losses in other holdings.

The trade portfolio fell 0.4% over the week, the S&P was down 0.9% and the NASDAQ 1.2% so it was a reasonable return. The monthly chart for the Trade account below shows the volatility we have seen, along with the outperformance relative to the main tech index.

The Invest Portfolio fell 2.4% but continues to outperform its benchmark.

Next Week

I have a space stock currently in the final stages of research and hope to buy next week. Space remains a good sector for me with two open positions both in profit.

I am not becoming a biotech investor just potentially increasing its profile in my portfolio if and only if the current trades deliver the expected returns.

Disclaimer: I'm not a financial advisor and don't offer investment advice. This newsletter is a diary of my high-risk trading in small-cap emerging stocks; past performance doesn't guarantee future returns. Make independent investment decisions based on your own research and risk tolerance; you are solely responsible for outcomes.

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The cash in the account will fall to $500 today after a $500 buy that's set for when markets open. I want to keep around $2,000 of cash, allowing me to take 4 trades a month

The longer-term Invest account doesn't have this limitation; I make far fewer investments than trades and fund each one with new money.

As a result, I have to be fairly ruthless and close trades when either they are failing to make the progress I require or the outlook is less appealing than it was.

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Of late, I have been following the Psychedelic drug market, and whilst reading one of the journals, I read an interview with a research scientist involved in the development of drug discovery platforms.

The expert name checked a company I was not familiar with saying he thought they had world leading technology, highlighting how they were able to quickly modify their existing molecules using a proven drug scaffold.

After a full deep dive into the stock, I decided to invest. The company meets many of my key criteria. With a market cap below $500 million, it has proven technology and has brought its first drug to market, delivering initial commercial success and building its name in its niche.

Right now it looks significantly undervalued, presenting an extremely high risk-reward setup with a good probability of success.

Like many of the companies I choose, it has balance sheet issues with an active going concern notice in the accounts and because its shares are trading for less than $1 it has received a NASDAQ delisting notice.

However, like the two Wall Street analysts that cover it, I value the shares at more than $10 and see immediate catalysts that could propel it close to that figure.

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Traders take high-risk bets, accepting some will lose, and as a result, profit is the difference between wins and losses. Traders are aiming for outsized returns higher than the NASDAQ or the S&P.

Investors take lower risk; they invest in companies expected to grow modestly and pay a reasonable dividend, resulting in a long-term return on investment greater than what a bank offers.

In my trading, I buy shares in companies before they have proven they can make a profit; some accelerate quickly toward profitability, some move on a slower-than-expected path, and some never make it.

We want to put money on the fast movers and none on those that will never make it, so we adjust portfolio holdings as information arrives.

Earnings season has a big impact: Trade 123 missed its revenue and EPS targets, and the price dropped 20% in one day; Trade 124 beat its earnings estimates, and the price jumped 24% in a day.

I need to review carefully to decide what to do with my money. I want to put as much as possible into high-potential, high-reward companies, so I analyze how they are doing. Here is the scorecard of my holdings so far in this earnings season

The second part of the decision is the potential reward.

Bagger Status: A New Criteria

I have decided to add a “Bagger status” to each of my holdings. It indicates what I am hoping for from the current position. Combining the classification and the bagger status will help drive my decisions about how to rotate money within the portfolio.

Performance Last Week

The Trade account had a mixed week, with exactly half the holdings making a profit and half taking a loss. Two big drops on poor earnings of 19% and 14% were overshadowed by two big wins on earnings beats and news reports of 59% and 27%.

The portfolio as a whole outpaced the NASDAQ and the S&P; the account is still below its May 2026 all-time high but is recovering from last month’s loss, posting a 16% gain so far in August.

The Invest portfolio did not do as well last week posting a drop of 0.8%, but this is a longer-term account and it should be judged over the longer term and over the last month it is beating the broader US markets

The rest of this article covers the earnings review of the five companies in the portfolio that reported earnings last week, along with portfolio updates.

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I will perform this categorization after every quarterly report, and the rating will be based on their performance relative to my original buy thesis.

A poor earnings report does not necessarily mean sell, and a good one does not mean buy. The categorization describes how the company is doing relative to the forecasts I laid out and the core reason I decided to buy in the first place.

Today I am re-evaluating the portfolio's worst performer, down 71% since I bought. Earnings brought a number of surprises, so the company warranted a full re-evaluation. Should I average down or should I take my loss?

Disclaimer: I'm not a financial advisor and don't offer investment advice. This newsletter is a diary of my high-risk trading in small-cap emerging stocks; past performance doesn't guarantee future returns. Make independent investment decisions based on your own research and risk tolerance; you are solely responsible for outcomes.

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I revisited the semiconductor/photonics stocks following their steep pullbacks; some of these stocks have collapsed 75% in a fairly short time window. My “silicon” watchlist has 14 names on it; but even after the dramatic pullback, I can’t see that much value in any of them - perhaps 20% upside on a fundamental case, obviously far more on a retail/hype cycle case, but I am neither interested in 20% upsides nor hype cycles.

Photonics and silicon are not the only areas that stand to benefit from the AI spend; we have a battery storage stock already in the portfolio and one stock involved in cooling data centers.

Today I will buy an electricity generation company aiming to capture a piece of the market supplying electricity to datacenters behind the meter.

I looked at the companies I had bought before and compared them with new entrants; I decided to buy a new company for the portfolio that looks set for a substantial share price appreciation in the next 12 months. Earnings are due in a couple of days, and I have decided to buy in advance of the earnings, which does increase risk but is a common strategy of mine.

Disclaimer: I am not a financial advisor and do not provide investment advice. This newsletter details my personal high-risk trading in small-cap emerging stocks. Past performance doesn't guarantee future returns. Make independent investment decisions based on your own research and risk tolerance; you are solely responsible for outcomes.

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This week the portfolio ripped higher, delivering a 17% gain; the move higher was widespread across the holdings.

I published a piece last month A plumbing Problem, Not a Bear Market which talked about the driver of prices being buyers and sellers and a lack of buyers combined with a preponderance of sellers was leading to a short term price correction and not the start of a bear market.

Last week we got more evidence to support my view with the collapse of an AI Hedge Fund; it proves once again that if you want to make money in this market, you need to develop the skills, not write one on Claude.

The AI Hedge Fund Collapse

The article I linked earlier gave my view that the tech pullback was about liquidity and did not signal a bear market, despite share prices moving sharply lower at the time and a prevailing view that we were on the brink of collapse.

My belief was that sellers were flooding the market, having to raise capital for large bond issuances and mega IPOs, both of which they had to buy. There was an additional problem I was not aware of at the time: Situational Awareness.

Situational Awareness is an AI-driven fund that, after a collapse in value, was forced into a fire sale of its assets to cover massive leveraged losses in its AI infrastructure positions. Assets at the firm collapsed from $45 billion to $10 billion in a matter of weeks.

To cover its losses, Situational sold its entire holdings of tech shares at huge discounts, with Citadel being the main beneficiary.

Reuters reports that prior to the sale, multiple other hedge funds unloaded stocks in the exact positions held by Situational and noted it was the largest 3-day tech sell-off in history.

Goldman Sachs published this chart showing the size of this insider knowledge-fuelled stock dump.

Small traders like us don’t get that kind of inside info and have to hold through the periods of drawdown, but it is just part of the game. Unfortunately, many retail investors will have bought these stocks from the selling hedge funds at the highs just to sell them back to the same hedge fund at the lows.

For many companies, the drop was large; for instance, AXT Inc (AXTI), a semiconductor stock part of the Situational situation, fell from a high of $143 to a low of $36.50 - that’s a drop of 74% in a few weeks; that is a portfolio destroyer for most retail traders.

I use game theory to understand many situations; it is my area of expertise, and in classic game theory, the stock market is a “Bayesian Dynamic Game with Asymmetric Information”.

In other words, nobody knows everything, but the big players know more than most. It ensures the stock market moves money from the poor, who have little information, to the rich who have most.

Once you understand the nature of the game, develop the skills and experience to play it, you recognize it is not a zero-sum game, and you only need a tiny fraction of the available winnings to make a lot of money.

It is another example of why you need to follow the company, not the price; share price is dictated by buyers and sellers in the short term. The big players get information before the small players, giving them a short-term advantage, but if you can ignore this short-term market gyration, the company fundamentals always win out in the end.

It also shows the importance of experience. Situational is led by a 24-year-old trader using AI to choose stocks; he would not have seen a leveraged unwind before and assumed his AI modeling and research was real, although why people would invest $45 billion in such an inexperienced trader is a mystery to me. Situational, having sold all of its listed holdings, has continued to invest in private equity. Last week it made another $400 million bet in a private pre-revenue R&D company; I suppose, as there is no official valuation of these stocks, it allows Situational to avoid any further scrutiny of its holdings for several years.

No doubt this is uncomfortable reading for many, but the only way to win in this game is to put the hours in and do the research. Claude didn’t have the inside track on Situational, nor the understanding of what a liquidity trap feels like; a Claude trader is just another Situational situation waiting to happen, albeit on a small scale.

The biggest AI-led hedge fund has collapsed with the biggest AI-derived debts, at least the biggest so far.

Trade results

Both portfolios made good progress this week; some of the liquidity issues have no doubt been absorbed, and as earnings season gets underway, many people realize that the rumors of a recession and corresponding bear market are once again only rumors.

26 of our 27 holdings were in the green this week, with 12 stocks recording a double-digit percentage gain.

Trade Portfolio Results

Trade had a great week

With more companies due to report next week, we will see some more gains if and only if we have chosen well.

Invest Portfolio

Invest is now three months old; it is still a much smaller portfolio with only 11 holdings, but it did have last week’s biggest gainers, leading it to outperform once again. Monthly chart below

I added one position to both portfolios last week. I expect to add one to Trade on Monday and have a long prospect list that may lead to additional activity on both portfolios.

Earnings Report

Every quarter I am performing a detailed check of company performance measured against my original buy thesis. I want to make a decision: should I buy more, should I hold, or perhaps exit. Sometimes I need to completely re-evaluate as the outlook has changed dramatically.

This is the state of play so far

The portfolio is on a tear, and I think it is likely to continue, with 10 out of 12 companies meeting or exceeding the original buy thesis and only 1 lagging behind.

Next is a review of the companies reporting last week, with two companies added to the accumulate list.

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I will add ELVA to both the Invest account with a $500 position and the Trade account with a $400 position.

The $400 size is smaller than normal, reflecting the low cash position. I have only $2,100 in the account, and by dropping to $400, I will be able to fund the 5 trades I expect to take in the coming weeks.

I published an article on Seeki…

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Previously, I exited when the share price fell without regard to what was happening with the thesis; a detailed review of performance proved this to be an error. I closed some stocks that were down 30 or 40% only to see them move higher later when the thesis played out. I held some stocks to the -40% when the thesis had clearly failed much earlier.

I have no doubt the new policy will be more profitable in the medium term, but it is likely to add to drawdown in the shorter term. This quarter has been particularly hard for the new policy as the markets generally have fallen and shown volatility in advance of the Q2 earnings season, which has just got going.

The policy puts far greater emphasis on a company's business performance and much less on its share price performance. Consequently, at each earnings release I will be completing a detailed review of how the company is doing relative to the original thesis.

The review will put each company into one of four classifications:

Classification 1: Accumulate

In this instance the company is out performing the original thesis, perhaps exceeding revenue targets or beating the timeline for commercialization. In these cases, I will look to add to the position.

Classification 2: Hold

The company will be meeting all parts of the thesis as expected; I will consider adding to the position when funds are available or following pullbacks.

Classification 3: Re-evaluate

This class is for companies that are meeting parts of the thesis but not all of it. Perhaps technical achievements have been met but revenues delayed. Or revenue targets hit, but a new product has failed to launch.

Classification 4: Opportunity Cost

In this case, the company has failed to fulfill the thesis, and I must consider the opportunity cost of holding the stock. Generally, the money invested in these stocks will be rotated into other companies that fall into Class 1.

The remainder of this article will be looking at the companies that reported in the last week, putting them into one of the four classifications.

Last Week’s Performance

After a good start to the week, the portfolio continued to show its high beta, selling off dramatically with the markets on Tuesday and Wednesday. The invest portfolio continues to do marginally better in these difficult market conditions

Trade Portfolio

Invest Portfolio

I expect a busy August as earnings release season continues and the thesis-based policy identifies some positions to trim and some to increase. I am still waiting to buy one eVTOL company and one battery company but will wait for their earnings to be published first.

Disclaimer: I'm not a financial advisor and don't offer investment advice. This newsletter is a diary of my high-risk trading in small-cap emerging stocks; past performance doesn't guarantee future returns. Make independent investment decisions based on your own research and risk tolerance; you are solely responsible for outcomes.

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The Aussie ASX exchange, where I prefer to buy, ha…

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It means this weekly update will just be on results; I thought I would provide a deeper dive into closed Trades.

It has been a poor few months for the account as a whole, and subscribers naturally get concerned, so I thought a detailed breakdown would give me a chance to talk about strategies, risk management, and what we are likely to see going forward.

The Trade account started on August 1st 2023 so is coming to the end of year three, that gives me quite a lot of data to work with.

Firstly, some raw figures

The raw figures look great, For every dollar I lost on a bad trade I made $2.54 on a good one.

The problem is the wins and the losses don’t come evenly spread. They arrive in clumps and are of all different sizes. I had one period with 10 consecutive wins.

Of course everyone loves patches like that, but if I have patches of ten consecutive wins I will inevitably have streaks of 10 consecutive losses.

That has not happened yet, but this current period is the closest I have come.

The losing period also includes my biggest ever loss, 59% on ASX:DRO for $381.

It is interesting to read comments when I report winning and losing results. When it is a winning run, many people say it is fake; some suggest I have inside information, and others that my actions are manipulating the market.

When I report losses, nobody doubts them; people come up with narratives to explain why. I have read that large funds are purposefully taking the opposite side of my trades, that I don’t have any risk management or should use technical analysis rather than fundamentals.

When you have ten wins in a row, people think you are a superstar and never lose, and when you only win one out of ten, people think the opposite.

Of course it’s just probability: I win 56% of the time, and because I invest in very risky small-cap stocks, the size of my wins relative to the size of my losses is very high. The strategy is to actively seek out small companies with the potential to become big companies; we know they won’t all make it, but when they do, we get a decent win.

Will the next trade be a win? I have no idea; perhaps it will be Trade 102, currently in profit 117% ($696), or perhaps it will be Trade 107, currently underwater 43% (-$162).

Stop Loss and Take Profit

I used to close trades at set figures, max 30% - 40% loss and 200% profit. Analyzing data as it arrived showed that to be a poor strategy; of course, I would have avoided an additional 19% loss on trades 79 and 88, as well as an additional 17% on trade 81; however, I did miss out on huge gains on several trades.

Trade 6 is an example; it was in ELVA, and I bought it at $2.80, selling at $2 because of my fixed stop loss rule. Today, ELVA is at $12 - that single trade missed more profit than all of the losing trades lost in the image above. Sadly, trade 6 is not the only example; there have been several.

I abandoned the stop loss and take profit rules, replacing them with a company-by-company decision process. I exit when the thesis fails and take profit when the target is hit.

For ELVA, I set a target of $14, which was hit earlier this year. I missed a 400% win and booked a 30% loss when I exited due to a made-up percentage-based rule, even though I knew from my fundamental company analysis the thesis was still valid.

The change in strategy has led to increased drawdown as I hold trades through the current market pullback and risk-off scenario, but I believe it will lead to much bigger profits over the medium term.

Individual subscribers can of course choose to exit on any strategy they prefer, my service tells you what I am doing, why I am doing it and what the results are.

Failed Thesis

What do I mean by a failed thesis? Probably best explained by some concrete examples.

In my trade alert on ARBE, I noted that in an interview the CEO had said they would sign 4 OEM contracts in 2024. That was a key part of the thesis, by mid 2025 they still had not signed any. That is a clear failure of the thesis.

Vertical Aerospace. In the buy article, I predicted that the VX4 might get certified in late 2027/early 2028 and thought that might be a matter of months after the market leaders. Late last year, they announced they were going for certification with a new aircraft, not the VX4, pushing certification back into 2029 at the earliest. Another big fail.

NetPower, in that trade article I predicted their first plant would be operational in 2027, and it would need CAPEX of around $600 million, making it a cost-effective solution. Last year the company doubled the likely cost of the build and said they were delaying the first site whilst focusing on selling turbines to datacenters.

That is what I mean by a failed thesis; the core reason for the investment is no longer valid. With these small companies, this happens quite a lot: the engineering can be too difficult, the competition moves forward, regulation changes, or the proposed customers decide to stay with their current supplier.

When I write a trade alert, I am predicting the future for these small companies; it is impossible to do that with any certainty.

Target Prices

When I write a trade alert, I try to work out what the value of the company would be if the thesis plays out. So the company does complete the engineering, they do get the customers and the margins do appear. I regularly review these after earnings calls but tend not to change them that much.

History shows I only win 56% of the time, will that change with the new strategy? I hope so; the data shows that 8 of my 34 losers have since returned to profit, and three of them hit their target.

Of the 42 open trades in the account 4 of them are showing a loss of 50% or greater, these trades would have closed under the old system the additional drawdown incurred is dwarfed by the profit missed.

Until I get the hard data, I will continue with the current position size rules; they are what keep me in the game and allow me to get money onto stocks that I think will deliver an outsized return, but I know nearly half of them will not deliver and that I need to make funds around 4 trades a month.

Risk management

My risk management is all about position size, and position size is the key to success.

I know this strategy is high risk- that’s just the nature of the companies I buy and I am not going to bet my house on any of them.

The risk profile was the reason I began this project, investing only $250 a month. I figured almost everybody could afford that figure, and few people would suffer a loss they could not afford.

When the account was large enough (due to booked profits) I moved to a position size of 3% of equity. 3% of equity is now $600.

Cash Constraints

The cash in the account is a limiting factor; to take 4 trades at $600 a month, I need $2,400 available, but I only deposit $250, and the remainder has to come from closing positions.

At times this can become an issue, and I am forced to close trades prematurely if I feel a better opportunity is available.

One such situation exists at the moment; one of the battery stocks I follow has developed a technical milestone that gives it a substantial and sustainable competitive advantage that I believe will lead to substantial growth in revenue in the short term, likely selling out capacity in 2027 and for the next several years. The potential here is immediate, but I have another battery stock where the potential is more distant; it is likely another 18 months before we see any real revenue growth. The thesis on the current position is not broken; if I had the money, I would keep the position, but I don’t, so I will be forced to close the position to fund the new one.

This a rotation of capital into a more near term potential.

I have two other prospects that I want to take in the very near term, an eVTOL company I have been mentioning for months and a small environmental company. I think I can fund these two out of existing cash without the need to rotate.

Final Thoughts

On average over the last three years, winners have returned 110%, and losers have lost 34%.

If I apply these figures to the current position size of $600 it means my average win will be $660 and my average loss $204.

If the win rate of 56% remains unchanged in the future, my expectation for every trade is a profit of $280 regardless.

Of course all of this assumes the future will be similar to the past, we know the market is more difficult, geopolitical and trade disputes seem common but good companies are good companies and as long as I keep betting on them the portfolio should continue to perform in a similar way to the past- or maybe a little better if the new exit rules bring the benefits I hope for.

Disclaimer: I'm not a financial advisor and don't offer investment advice. This newsletter is a diary of my high-risk trading in small-cap emerging stocks; past performance doesn't guarantee future returns. Make independent investment decisions based on your own research and risk tolerance; you are solely responsible for outcomes.

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key Takeaway

When markets open today, I will add PONY to the Invest portfolio with a $500 investment and increase the size of my position in the trade portfolio by $250

I wrote an article on SeekingAlpha about PONY.AI in June titled “Buying the Wuhan Whiplash.”

The core argument of the piece was that the price drop we have seen in recent months related ent…

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I think it is an opportunity to add to positions or open new ones at good prices. I am continuing the process of analyzing companies on an individual basis. I will look to close when a thesis breaks, or I need to reallocate the capital, and will look to add when companies improve their competitive position.

Today I will add to one of the small caps that has just passed a significant milestone; it has received its first commercial order- a major step for any tech company and the customer seems to be an extremely solid partner that offers the chance of a significantly enhanced revenue ramp-up.

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The last four months’ returns show this extreme volatility, with a second consecutive loss so far in July pushing the portfolio as a whole into negative territory.

Over the longer term, returns remain very solid with an annualized IRR of 80% (below the 100% target but still good).

As I have explained in previous issues, I am a perma-bull; this chart from last month’s issue is the basis for this view. (the DOW for the last 100 years)

Since its inception in 1896, the world’s oldest index, the DOW, has been on a relentless move higher. Even the great depression of the 1930s did not make a new low, and the only other major pullback, the 2008 credit crunch-a global financial crisis- hardly made a dent in the path higher.

However, this is a view and not a belief; I don’t think I have any beliefs (apart from soccer being a rubbish sport that is), and I will drop the view depending on the evidence. If I decide a significant deep correction is likely, I will exit my positions and book the unrealized loss; if I do not, I will continue to exit on a company-by-company fundamentals basis.

My strategy is high risk; I buy small-cap emerging technology companies. I use fundamentals to buy them and have moved to using fundamentals to decide an exit; if the thesis holds, so will I.

Right now I think there is an 80% chance the market will continue higher, which is down from last month’s 90%, but I remain confident that the market and my portfolio are going higher over the short to medium term.

A Brewing Economic Collapse

There are always a number of proponents who believe a full-blown economic collapse is either here already or just around the corner. They believe stocks are overvalued and a correction is due. They have been proven to be correct maybe four times in the last 140 years.

We are all aware of the current geopolitical problems, the oil price issue, and inflation moving higher; these issues lead to narrative-driven reasons for a pullback.

However, narratives don’t drive stock markets; they are fundamentally driven by the supply and demand of capital.

What drives markets

There is a set amount of money available to be invested in stocks and a certain amount of stocks available to be purchased.

If there is more money available than stocks to buy, it forces prices higher; however, the reverse is true: if there is not enough money around to buy the stocks people are trying to sell, stock prices fall. In this situation, my small-cap, high-risk stocks fall the most

Cash availability

The amount of cash available is generally modeled as the M2 money supply, and it is always growing, but its rate of growth, to a large extent, depends on the Fed.

The US Treasury is issuing record volumes of debt to fund the multi-trillion-dollar fiscal deficit, but the money supply is not growing at the same pace.

During quantitative easing, the FED increases the amount of money in the system by buying government bonds and debt from banks, which gives the banks enough capital to buy the new bonds without having to liquidate holdings elsewhere. This substantially increases the amount of money in the system; however, at the moment the Fed is not buying, requiring private balance sheets to carry 100% of the load.

Indeed, the FED is tightening; it is not buying additional bonds and is letting its current holdings of bonds mature without replacing them, reducing its balance sheet.

When institutional investors need to free up billions to buy 5% Treasuries or mega-tech shares, they trim their highest-risk, least-liquid assets first (small caps) to derisk their books, amplifying small-cap losses relative to large caps.

In addition, large investors take the opportunity to reduce some of their longer-term holdings and higher-risk bets to buy these high-yield, highly secure Treasuries. To buy this new paper, they liquidate a portion of their holdings to reallocate the funds.

Mega IPOs

At the same time as the increase in government debt, we have seen a near-explosion in the amount of shares available for purchase. Mega IPOs like SpaceX, which alone absorbed $75 billion, are coming to the market in droves.

Portfolio managers do not keep $75 billion in cash just waiting for an opportunity; they had to sell something to participate in the deal.

SpaceX was not the only driver of new shares; in fact, it wasn’t even the largest. Alphabet raised $85 billion, along with most other big tech firms; even the South Korean chip maker SK Hynix took $26 billion out of the US markets for its new ADR offering.

This new issuance is overwhelming investors, and when added to the record issue of treasuries, there just isn’t enough cash to go around.

The chart highlights a steady expansion in stock issuance since 2022, but keep in mind that the 2026 data reflects only the first six months of the year. If this pace persists through December, annual issuance will cross $600 billion for the first time in history.

Bears will argue that such record supply is a classic warning sign of an overextended market topping out. The problem with that narrative is that historical data doesn’t back it up—surging equity issuance has rarely derailed a bull market on its own.

Looking at the chart, 2007–2008 saw high issuance right before the Great Financial Crisis, but the next major high in 2013 was followed by years of continued market gains. Similarly, when issuance set a record peak in 2021, the market rallied aggressively right through it. The subsequent drop in 2022 was driven by runaway inflation and aggressive Fed rate hikes, not the volume of new paper hitting the street. Heavy issuance creates a temporary liquidity bottleneck as investors digest new supply, but it doesn’t cause structural bear markets.

Stock prices are high with the S&P 500 dividend yield just above 1%, but markets don't fall because of high valuations.

If all the money raised for the AI build is spent on the AI build it will quickly come back through the cycle. The cash being absorbed by Alphabet, SK Hynix and the rest isn’t disappearing; it will be paid to suppliers, energy firms and chipmakers; it will turn into next quarter's earnings and future dividends.

Historically it has been rising interest rates, new regulations and underappreciated risks that bring down a bull market. In this market, earnings have been strong, and the economy is showing little sign of cooling. The private credit issue people discuss seems not to be of the scale of the subprime mortgage debacle, and I cannot see this administration allowing a prolonged increase in rates or putting new regulations on the flow of money.

Conclusion

At the moment, the evidence points to a ‘digestion phase’ rather than an economic collapse. When unprecedented levels of government debt and mega-equity issuances hit the market at once, money gets pulled from secondary stocks to fund primary bids. Once this wave of new paper is absorbed, liquidity balance will be restored, and high-growth small caps will have a runway to lead the next leg up.

Of course, I could be wrong, and that is why I make this assessment every month. The financial world is fluid, and we have to be prepared to change with it, but we should base those changes on the evidence, not speculation and “belief”.

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Trade Review: ASP Isotopes (ASPI)

Key Takeaway: I will allow ASPI to run despite significant losses at the moment.

Less than a month ago, this position was in profit; the share price has fallen by 47% in 30 days…

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I had said many times that Amazon was its biggest customer, although Electrovaya had never publicly stated it to be so, it was clear from the description they gave, “ A Fortune 100 e Retailer with operations in multiple countries,” that it narrowed it to a field of 1.

The $280 million deal included a large slice of warrants for Amazon; it is a textbook play for Amazon. They have been extracting warrants from smaller suppliers for decades, and analyzing the deals has become a standard question for MBA students. (you can read the question here from 2022) Is the deal a good one? is the usual question, and the answer is, it depends. The deal is always good for Amazon, but not always for the supplier.

First, a word on results

Tech generally is having a poor month, and our small-cap tech stocks are taking a beating. Only 6 of our 25 holdings posted positive results last week. The pullback across the sector has been sharp, prompting me to consider closing some positions to preserve cash. Of course, the last thing I want to do is sell near a price bottom, and with earnings season just getting started, these decisions are incredibly difficult.

The Trade and Invest portfolios lost 7.1% and 7.4% respectively last week, with almost the entirety of those losses hitting us on Thursday, which goes down as the portfolio’s worst single day on record. The Nasdaq 100 fell 4.2% over the week. While a 7.1% drop is painful, it puts our downside beta at roughly 1.7 times the index. Keeping our beta under 2 during a full-blown small-cap tech rout is a decent relative performance on a down week, though it admittedly does little to hide the immediate sting of the loss.

I did not execute any new trades or investments during the week.

Looking ahead, I have one high-conviction stock ready to buy early next week. It is a tight, $50 million market-cap operation that justifies a small bet. The position offers significant potential for outsized rewards. The thesis is supporteed by the proven track record of some heavily invested institutional managers, innovative tech in a high growth area and multiple evaluations. I have mentioned this stock a couple of times (you might remember me describing it as a 6-employee operation a while back, but it has grown a bit since then).

Amazon Supplier Warrants

In late 2021, when the Harvard question was first written, Amazon had $3.4 billion in supplier warrants; today, it has moderated to $2.7 billion, but the policy continues.

Recent examples related to AI build include.

It is hard to understand how a big order from Amazon might not be great for any company, but history shows us that companies entering these deals show mixed results for their shareholders. For some, it is the start of great things, for others, it brings no change, and for the rest it is the start of a significant stock decline.

Here are 4 examples (only chosen because I already had the data)

The stocks are universally up in the first few days after the release, but over the next 12 months, the return for shareholders was mixed. PLUG showed a 10% loss that loss is from the pre 70% spike, and it got much worse when they had to report negative equity because of incorrect accounting regarding the warrants. ASTG is the only real gainer; the stock rose 20% immediately and another 20% in the following 12 months to make 40% overall.

The problem is that the warrants must be reported as contra revenue, i.e., they must be deducted from revenue.

I will use the ELVA deal to try to explain this, the impact is different in every case; however, the basic maths and the areas that need looking at are unchanged.

Dilution

Electrovaya has 49.5 million shares outstanding, if Amazon exercised its right to buy all 13.88 million shares it would represent 21.9% dilution for existing shareholders.

It also brings about a hit to earnings per share

The deal attacks this formula from the top and the bottom, total shares jump by nearly 14 million, and the top line net Income shrinks because of the contra revenue.

Customer Illusion

Amazon was already Electrovaya’s biggest customer, responsible for a big chunk of its revenue. So this deal isn’t tying in a new customer, it is locking in an existing one. A defensive move to stop Amazon from going elsewhere, and they had to give up 21.9% of the company to do it.

Paper v Cash Margin Trap

Here, we have to look at GAAP rules versus cash movement. If a battery costs $60 to make and Amazon pays $100 for it, Electrovaya gets the $100 and takes home $40 in cash to run the business.

The accounting reality is different because of the non-cash warrant charge; Electrovaya has to write off a portion of the $100 revenue on paper. On the GAAP income statement, it might look like they only got $50 in revenue for a battery that cost $60 to make, resulting in a negative net profit margin.

This is exactly what happened to PLUG and CLNE; they generated record amounts of cash, but the earnings report was a disaster because of millions of dollars of revenue being deducted due to the warrants.

Other Issues

Continuing on the margin theme, the guaranteed volumes do allow Electrovaya to spread the cost of its new facility and the manufacturing lines of its recently constructed New York facility over more batteries, helping to keep COGS down.

It has great marketing potential, as now the wider market knows they supply Amazon with batteries for material handling trucks inside its warehouses. That should make it a bit easier to get some new customers.

On the negative side, Electrovaya has two other major customers. Home Depot and Del Monte- you can be certain their buying teams read the Amazon headline and will be using it to negotiate better terms of their own.

The Amazon Squeeze Play

Amazon has mastered the art of the commercial squeeze play. They provide the large volumes needed to justify big capital expenditures, like the New York Electrovaya build-out, but they charge a high price for doing so.

For Electrovaya, the cash flow from the orders is real, and the operational scaling is a long-promised corporate goal. For Amazon, they get the batteries they were going to buy anyway, but stand to make a big profit from the warrants. For the Electrovaya investors, the 12 months following an Amazon announcement can be a sobering reminder of the effect of accounting drag and massive shareholder dilution.

These Deals Last

The four deals I highlighted from 2016 to 2021 with PLUG, CLNE, SPTN and ATSG led to ongoing deep relationships. Plug signed a massive second deal to supply 11,000 tons of liquid Hydrogen. CLNE booked $47 million in ongoing Amazon warrant charges in Q1 2026, and the Spartan deal continues and looks set to cross $8 billion in 2027. Even though it is now private following a $3.1 billion private equity buyout, ATSG remains the foundational operator for the Amazon airfleet.

So the pattern seems to be a short-term pop, 12 months of consolidation flowing into a long-term sticky relationship with Amazon.

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I do not have any medical training, but have a postgraduate qualification in game theory and statistics, so I am well qualified to report on the statistics, if not the pharmacology.

Phase 3 tests are the final trials before going for drug approval, the FDA has previously rejected psychedelic drug approvals (notably Lycos) despite the outstanding top line result because of the construction of the trial and the effect of unblinding.

This week I will explain why I think Compass Pathways phase 3 data paves the way for acceptance, despite its low topline that left the market unimpressed and why Definiums phase 3 gives me cause for concern despite the amazing top line which excited the market leading to the companies market cap growing by $700 million.

First Last Week’s Performance

A large discussion took place in the chat section of my subscription service this week regarding the results the Trade portfolio has delivered so far in 2026. Recent subscribers noted that they are only at break-even on their investments, with some pointing out that some stocks have fallen by as much as 50%. Other subscribers pointed to the huge gains delivered in 2024 and 2025 and highlighted recent stocks that have made large gains.

The truth is, any experienced trader knows that slower periods are an inevitable part of the game. This recent stretch is actually our second major period of near-breakeven performance. The first was a grinding 6-month stretch spanning the end of 2023 and the beginning of 2024.

When you are heavily positioned in high-risk, high-reward small and micro-cap tech stocks, breaking even during a macro lull is not really a failure. With some stocks down 50%, the portfolio and careful position sizing have allowed me to preserve capital. I am using this quieter window to build and scale positions in small companies that, I believe, have outsized growth potential. History rhymes here: it was precisely during the last slow period that we quietly accumulated the positions that went on to book massive, portfolio-defining gains once the market turned.

Over the week

• The short-term Trade portfolio (now three years in with a 81% Annualized rate of return and YTD of -2%) fell 3.5%

• The longer-term Invest portfolio (now three months old with a total return of 9.3%) fell 4%.

I made one trade during the week, increasing the position size of a microcap I first bought last September. I did not add to the Invest portfolio.

Psychedelic Drug Therapy

Definium released its first phase 3 with its LSD candidate for major depressive disorder, and Compass Pathways gave the 6-month readout from its second phase 3 trial for its Psilocybin compound for patients with treatment-resistant depression.

Top Line Results

The accepted measure of efficacy is a reduction in MADRS score. MADRS stands for Montgomery-Asberg Depression Rating Scale. It is a 10-item diagnostic questionnaire used by clinicians to measure the severity of depression. A trained clinician evaluates the patient, making it an observer-rated scale. The scale measures cognitive symptoms of depression (not physical) like sadness, tension, and pessimism over the previous week.

Each of the ten items is scored on a scale of 0-6, for a maximum score of 60; higher scores indicate greater depression.

Definium reported a placebo-adjusted drop in MADRS of 8.1, and Compass reported a drop of 3.8. The market wrongly assumed that this meant Definium's drug is twice as effective as Compass's. I hope I can explain why the market got this wrong.

TRIAL DESIGN & PATIENT POPULATIONS

Compass Pathways (COMP360): Compass has reported on two pivotal Phase 3 trials, COMP005 and COMP006, evaluating COMP360 (synthetic psilocybin) in a highly chronic and severe Treatment-Resistant Depression (TRD) population. Compass defined TRD as having failed at least five previous lines of treatment, and every single patient met this severe bar. In the newly released COMP006 trial, the mean duration of patients' current depressive episode was a grueling 45.5 months for the 25 mg arm, and 57.4% of participants had been in their current episode for more than 2 years. COMP005 used a single-dose design (258 patients), while COMP006 used a multi-dose design (581 patients), comparing 25 mg, 10 mg, and 1 mg doses administered 3 weeks apart.

Definium Therapeutics (DT120/MM120): Definium released results from its first Phase 3 “Emerge” trial evaluating DT120 (an LSD Orally Dissolving Tablet) in a relatively small sample size of just 149 patients with standard Major Depressive Disorder (MDD). Although Definium noted that 53% of the trial population (79 patients) had tried at least two antidepressants (narrowly qualifying under some broader definitions of TRD), the cohort's baseline health was fundamentally different from Compass's. Their mean episode duration was only 8.9 months, 75% had current episodes under 1 year, and zero participants had a current episode exceeding 2 years. Definium utilized a completely inert placebo (a sugar pill), whereas the active arm received a heavy 100 µg dose of active LSD. The trial evaluated this single dose against a placebo in Part A, followed by an open-label extension in Part B, in which up to three additional doses could be administered by Week 28.

Efficacy Comparison

While Definium’s raw signal is stronger, clinical experts caution that MDD populations typically show much higher responsiveness than highly chronic TRD populations. This key baseline discrepancy is a primary driver of the efficacy gap.

Key Points

The Placebo Effect vs. Blinding Success:

The placebo effect for Definium was substantial, with a 5.2-point reduction on the MADRS scale. This directly points to their less chronic patient population, where effectively taking nothing still had a major positive impact on how depressed they felt.

Conversely, look at Compass. Their control arm recorded a massive -6.8 drop. Remember, these control patients did not receive a sugar pill; they took a micro-dose (1mg) of active psilocybin. Because this small amount triggered identical, transient side effects (nausea, mild headaches, light visual alterations), the patients were truly blind to which arm they were in, and reported safety concerns were functionally identical. While this compressed Compass’s headline “placebo-adjusted” number down to -3.8, it is an astronomical victory for FDA approval because it proves robust blinding.

True Dose-Response and Durability:

Compass reported remarkable durability in the active 25mg arm, with nearly 40% of patients maintaining a clinically meaningful response through 26 weeks after just two fixed doses. Crucially, the data showed a clear dose-response differentiation: the 25mg arm consistently outperformed the mid-tier 10mg arm, while the 1mg control arm experienced a significant drop-off in sustained efficacy over time. For a population this deeply chronic, a 40% disease-modification rate without continuous daily dosing strongly implies that Compass’s drug is a functional cure for a significant segment of patients. Definium’s data show immediate relief, but the long-term erosion of effect suggests it functions more as a short-term reset; achieving high response and remission at Week 28 required scheduled re-dosing across multiple open-label sessions.

Safety

Compass Pathways COMP360: The Phase 3 program confirmed a clean, highly manageable safety profile. The incidence of Serious Adverse Events (SAEs) over the 26-week period in COMP006 did not differ meaningfully between the 25 mg arm (5.7%) and the 1 mg control arm (6.3%), indicating a lack of dose-dependent severe toxicities. No new, unexpected safety signals emerged in this large trial of over 800 patients. Compass did report a suicide in its 25mg arm, which took place 80 days after treatment, and the patient's clinician does not believe it was treatment affected.

Definium Therapeutics DT120: Definium reported an unremarkable safety profile, reinforcing the clinical consensus that LSD is extremely physiologically safe when administered in a controlled setting. A notable progress in Definium’s clinical development is the switch from its Phase 2b capsule formulation to the Phase 3 Orally Dissolving Tablet (ODT) formulation. The ODT formulation demonstrated reduced gastrointestinal side effects compared to the capsule, which has been a historical tolerability concern for oral LSD. Key metrics such as exact SAE rates, common TEAE percentages, and discontinuation rates were not provided in the topline Emerge results.

Trial Logistics

Dosing Session Duration: A major historical barrier for LSD was its extremely long session time (typically 8 to 12 hours). In its Phase 2b capsule-based study, only 45% of patients in the 100 µg arm met safe discharge criteria at 8 hours. However, in the Phase 3 Emerge trial utilizing the ODT formulation, participants cleared the 8-item End of Session Checklist in an average of 5.8 hours (with >50% clearing at 5 hours, and 100% by 8 hours).

This represents a major step forward, aligning LSD’s monitoring footprint with that of psilocybin. However, clinical experts note that psilocybin still maintains a slight logistical advantage: in real-world settings or future trials, up to half of psilocybin patients could be safely discharged at the 4-hour mark. Compass did not have an end-of-session checklist, which may have been an error, but it will not affect approval.

The defining difference in execution is the role of therapy. Compass incorporates a structured, multi-session psychological support model (preparation, in-session monitoring, and integration). Definium implemented a pure ‘drug-only’ protocol with zero preparation or integration sessions. Although about a quarter of Definium’s participants engaged in outside, non-study therapy, statistical analysis showed that outside therapy was not a major driver of the response.

The Durability & Re-dosing Challenge

While both drugs demonstrate rapid onset, their long-term clinical pictures diverge. Compass’s COMP006 showed strong durability, with 39% of the 25 mg arm maintaining response at 26 weeks following just two initial doses.

Conversely, clinicians have highlighted a notable ‘erosion in effect over months’ for DT120. In the Emerge trial, achieving and maintaining high response rates at Week 28 required up to three additional open-label doses in Part B. This strongly suggests that a meaningful fraction of responders to LSD will require scheduled re-dosing on the order of every few weeks.

The high results from the placebo arm of the LSD trial point to the more moderate depression of the cohort chosen. The small number of patients only 149 v Compass 800 patients does give a concern. The market-leading Spravato had to do five additional phase 3 trials to match its initial positive outcome, whereas Compass has matched on consecutive trials. I suspect Definium may need to run a second phase 3 due to the small number of patients and the high placebo response rate.

Conclusion

The market’s euphoric reaction to Definium—which added $700 million to its market cap—ignores critical regulatory history. When the FDA evaluates psychedelic drugs for approval, their primary concern is functional unblinding. They previously rejected Lycos’s MDMA approval precisely because patients in a pure-placebo trial immediately knew whether they were tripping, rendering the topline data statistically suspect. Definium knows this is a weakness in their trial design. In their ongoing Phase 3 trial for anxiety (the Panorama study), they introduced a mid-tier 50 µg active control arm specifically to stop participants from accurately assessing the dose they were getting. The fact that they didn’t or couldn’t deploy a balanced active control in the Emerge depression trial means the data is highly susceptible to expectation bias.

By using a pure placebo in a tiny sample size of 149 patients, Definium achieved a flashy, headline-grabbing -8.1 MADRS drop, but they left themselves open to FDA scrutiny regarding trial construction and expectation bias.

The market-leading depression treatment, Spravato, was forced by regulators to run five additional Phase 3 trials to replicate its initial success because its early sample cohorts were too narrow. Given the small patient count and high placebo response in the Emerge trial, I highly suspect Definium will be forced to execute a secondary, much larger Phase 3 trial before the FDA even considers an NDA.

By implementing an active 1mg control, Compass successfully mitigated the unblinding problem, resulting in consecutive, highly reproducible Phase 3 successes across more than 800 patients with severe chronic conditions. Their -3.8 score is scientifically airtight, and their 26-week durability data positions COMP360 as a robust, defensible, first-in-class cure for the hardest-to-treat patients on earth.

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Today, the market has moved on; competition has diminished as key players pivot elsewhere or continue to lag in commercial development; and, at the same time, the TAM has grown significantly as the industry body has made a clear commitment to reduce its landfill use by 50% in a decade.

Today, I review market changes and the clear progress the company has made towards the targets I set for reinvestment, and explain why I am doubling my investment.

Disclaimer: I’m not a financial advisor and don’t offer investment advice. This newsletter is a diary of my high-risk trading in small-cap emerging stocks; past performance doesn’t guarantee future returns. Make independent investment decisions based on your own research and risk tolerance; you are solely responsible for outcomes.

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Although I never trade on technicals, they do alert me when I need to check a thesis. The game of every trader is to buy low and sell high, technicals let me know when price is low and then I have to decide if the fundamentals mean it is likely going higher.

This week, 19 technical alerts triggered, 5 had already been looked at last week, so I started with 14 companies to consider. 9 made it to an initial filter stage of reviewing recent press releases and reading earnings calls, and 4 made it to a deep dive. Of those 4, one was deferred until earnings, which are due next week. I have decided to buy one today, and the other two have been discounted.

The company that passed all the checks spans multiple market verticals I am interested in and, crucially, has confirmed orders and profitable operations. The pullback may just be presenting an opportunity.

Disclaimer: I'm not a financial advisor and don't offer investment advice. This newsletter is a diary of my high-risk trading in small-cap emerging stocks; past performance doesn't guarantee future returns. Make independent investment decisions based on your own research and risk tolerance; you are solely responsible for outcomes.

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