One of the questions that may be posed when musing over your stock portfolio is about stock dividends. Often, the information provided by brokerages is misleading or incomplete. For example, our brokerage, Schwab, only aggregates dividends and provides simplistic results, such as the dividend return is the total amount of dividends divided by the cost of stocks. This neglects the compounding effect of using a stock’s DRIP (Dividend Reinvestment Program).
To address this situation, I am going to use actual numbers from a stock in our portfolio, Trinity Capital, with ticker symbol TRIN. In this example, I want to know what is provided in the following Prompt and provide results in a table format that follows. Note that instead of a static $1970.13 in quarterly dividends, the last quarter in 2026 TRIN paid out $2252.04 in dividends with a total payout of $10,488.41.
Prompt: Current date 10/31/2025. We own 3863 shares of BDC TRIN, which are in their DRIP. Calculate quarterly dividends and construct a table with values of dividend, # shares DRIP, total number of shares held, and total dividends paid to date, all through the last payment in December 2026.
Here is the table limited to only the months in which TRIN pays its regular dividends—December, March, June, and September. It includes dividend paid, the number of new shares added via DRIP, total shares after reinvestment, and cumulative total dividends paid through the last payment in December 2026.
TRIN DRIP Table (Dividend Months Only: Dec, Mar, Jun, Sep)
Month
Dividend
Shares DRIP
Total Shares
Cumulative Div Paid
2025-12
1970.13
131.3420
3994.3420
1970.13
2026-03
2037.11
135.8077
4130.1497
4007.24
2026-06
2083.90
138.9269
4269.0766
6091.14
2026-09
2145.23
143.0152
4412.0918
8236.37
2026-12
2252.04
150.1363
4562.2281
10488.41
Only dividend-paying months are listed, matching TRIN’s expected payout pattern.
“Shares DRIP” is the rounded estimate of new shares bought using the dividend (assumes a $15 share price).
Dividends and share totals are cumulative and project only regular quarterly payouts. Supplemental or variable dividends are not included.
These updated values illustrate your DRIP growth and total dividends by each quarter through the end of 2026.
Monte Carlo methods originated in the mid-20th century, although early concepts date to the 18th century. The pivotal modern development happened during World War II with Stanislaw Ulam, who, while working at Los Alamos National Laboratory on nuclear weapons research, conceived random sampling as a way to solve complex neutron diffusion problems that defied standard mathematical analysis.wikipedia+6
Early Mathematical Roots
The initial concept can be traced to experiments like Buffon’s needle in the 18th century, where French scientist Georges Louis LeClerc (Comte de Buffon) used repeated random trials to estimate mathematical values, notably Pi.pmc.ncbi.nlm.nih+1
In the 19th century, simulation and randomization methods continued to develop in statistics and probability studies, such as smoothing mortality tables and generating distributions with dice and cards.pmc.ncbi.nlm.nih
World War II and the Manhattan Project
The method’s breakthrough came in the 1940s at Los Alamos. Stanislaw Ulam, recovering from illness and playing solitaire, realized some problems—like predicting the likelihood of winning the game or neutron movement in reactors—could be addressed by simulating many random outcomes and observing their frequencies.oakleyj.github
Ulam shared his idea with John von Neumann, who recognized its power and helped formalize the computational implementation. The approach was first coded for the ENIAC electronic computer in 1948.lanl+1
The term “Monte Carlo” was coined by Nicholas Metropolis, inspired by both the randomness of the method and the famed Monte Carlo Casino, symbolizing luck and probabilistic games.investopedia+1
Key Contributors
Stanislaw Ulam: Conceived and refined the central concept.oakleyj.github
John von Neumann: Helped formalize and implement the numerical technique.aws.amazon+1
Nicholas Metropolis: Named the method and contributed to coding and applications.metaplane+1
Monte Carlo methods revolutionized simulation and modeling, becoming foundational in physics, finance, engineering, and data science.investopedia+2
What Are Monte Carlo Simulations?
Monte Carlo simulations are mathematical techniques that use random sampling from defined probability distributions to create a wide range of possible scenarios for a given problem. Instead of relying on single-point predictions, the process repeats thousands—even millions—of iterations, each drawing random values for input variables. This results in a comprehensive picture of potential outcomes and their likelihoods.investopedia+3
How Do They Work?
The basic workflow involves:
Defining uncertain variables (such as market returns, costs, project delays).mastt+2
Assigning each variable a probability distribution that reflects its possible range (e.g., normal, triangular, uniform).mastt
Running thousands of iterations, each randomly sampling values from these distributions.lumivero+1
Aggregating all results to produce a probability distribution of outcomes.lumivero+1
For example, in finance, if one wants to forecast retirement portfolio sustainability, a Monte Carlo Simulation would vary market returns, inflation rates, interest rates, and more, then review the range and probability of possible outcomes.emoneyadvisor+2
Real-World Applications
In finance, Monte Carlo methods help analyze:
Portfolio return variability and risk
Retirement income sustainability projectionsanalytica+1
Stock option pricing by simulating asset price paths and payoffsinvestopedia+1
Asset-liability modeling in pensions and insurance
Risk assessment, including “Value at Risk” and stress testinginteractivebrokers+1
Beyond finance, these methods are widely used for:
Project cost, schedule, and risk modeling in engineeringlumivero+1
Reliability and efficiency forecasts in manufacturinglumivero
Estimating solutions to complex mathematical problems, such as approximating Pi or infinite seriesmetaplane
A Simple Example: Predicting Stock Price
First, I’m going to outline the problem we are going to use Monte Carlo techniques to address, then write a Perplexity Prompt to actually use Monte Carlo to solve, and lastly, the results provided by Monte Carlo. At this point, you may be asking yourself Why? It falls in the “because I can class” and also to point out some of the less evident things Perplexity can do for you, if you are so inclined.
I have been tracking and buying a significant position in a stock with the ticker TRIN. It is a BDC company with a current 13.1% simple annualized return, pays dividends quarterly, at $0.51 per share. Recently, the stock dropped 4.5% in a single day, which I viewed as a buying opportunity. I had been buying TRIN at over $15.00, and accordingly, it was now in the $14.40 vicinity. I bought 1000 shares at 14.005.
Let’s assume TRIN’s price fits a triangle distribution. The triangular distribution is a continuous probability distribution shaped like a triangle, defined by three parameters: the minimum value aa, the maximum value bb, and the mode (or most likely value) cc, where a<ba<b and a≤c≤ba≤c≤b. It’s widely used when limited data is available, as it allows for the estimation of these three values, making it popular in project management, risk analysis, and Monte Carlo simulation work.wikipedia+4
You can generally get C-level executives to estimate next year’s sales as worst case, best case, and most likely after pounding heads for a while. Same thing for other estimates, which is the power of the triangle distribution. For TRIN, let’s assume the lowest price to expect is $14.00, the highest 18, and the most likely 16. We have everything we need to run a Monte Carlo simulation except the number of iterations. Let’s arbitrarily set this at 100.
Prompt: Run a Monte Carlo using the following: a triangular distribution with lowest value 14, highest 18, and most likely 16, using 100 iterations. Place the results in a table along with the probabilities of each histogram bin you provide.
Here is the extended table including the probability values for each bin in the Monte Carlo simulation from a triangular distribution with minimum 14, mode 16, and maximum 18, based on the PDF integration over each bin’s interval:
Bin Range
Count
PDF Value (Height)
Probability (Area of bin)
14.0–14.8
10
0.125
0.100
14.8–15.6
18
0.3125
0.225
15.6–16.4
38
0.5
0.320
16.4–17.2
22
0.3125
0.225
17.2–18.0
12
0.125
0.130
Explanation:
Count: Number of samples in the bin from the simulation.
PDF Value: The height of the triangular probability density function at the midpoint of the bin.
Probability: The integral (area) of the PDF over the bin range, representing the probability that a random variable falls within that interval.
These probability values sum approximately to 1 (due to rounding), confirming that the bins collectively cover the entire probability space for this distribution. This table reflects how the triangular distribution assigns higher probabilities near the mode and lower toward the minimum and maximum values, aligning with the Monte Carlo simulation output.statology+2
And that, kind folks, is how you make Perplexity do weird statistical stuff for you!
I am a mess. In the past, I have experienced “good days” for weeks at a time. Lately, I’m lucky if the cycle is every other day. I’m not inferring that the “bad days” are bad, it’s just as if my “git up and go” got up and went. Lethargic explains it probably best.
In my defense, I’m certain age has something to do with it, but not all. I have lots of things going on. I’ve just recently reached the stage where my Spinal Cord Stimulator (SCS) installation has settled down to a manageable level. Dialysis is always a 20-pound gorilla sitting on my shoulders. Something I haven’t blogged about is even a heavier weight: skin cancer has taken over my head, breaking out all over the place with scabs and now bleeding wounds that my wife has to bandage every night to keep blood off our sheets, etc. This state is partially my fault, as I postponed continued surgery while having the SCS installed. Then there’s the heart. Upon leaving my last cardiologist appointment, I was admonished “to not do anything stupid,” meaning really, really pace myself. As a rather active dude my entire life, this is just about untennable, but it is now wearing on me.
I assume one way or another, this will pass, for the better or worse. In the meantime, we’re enjoying 80+ degree weather here in North Texas. And even with its bumps, life is good!
Since going on Peritoneal Dialysis, my albumin lab reading has consistently been low, in the 3.4-3.5 range. This is considerably below the bottom target of 5.0 and has consistently been a subject of discussion within my dialysis team. We have tried drink additives, energy bars, and IPN without any noticeable increase in my albumin readings. It’s as if it’s stuck on the 3.4-3.5 range.
Costco has a protein drink that tastes like chocolate milk that has 30 grams of protein in it. I have been attempting to down two servings of this per day in an attempt to increase my albumin. This provides two-thirds of my daily requirement for protein, according to my team’s dietitian, wherein I require 90 grams.
So the question arises, how is my albumin reading impacted by this somewhat large intake of protein? Is it impacted immediately, or over time? To answer this line of questioning, I turned to Perplexity with the following prompt and results. Seems like good whiskey, it takes time.
Prompt: My albumin is 3.4. I am increasing my daily protein intake by 60 grams. How long does it take for this to affect my labs?
Increasing dietary protein intake can positively influence serum albumin levels, but the response in lab results is gradual due to albumin’s long half-life in the blood (about 20 days). Most studies show that, even with significant increases in daily protein (such as 60 extra grams), short-term changes in serum albumin—within 7 to 14 days—are typically small or undetectable, with more noticeable improvements usually observed after several weeks or longer.
Timeline for Albumin Changes
Serum albumin changes slowly because it is a stable protein with a half-life of approximately 20 days. This means any gradual increase from higher protein intake will usually take at least 2–4 weeks to show up in repeat lab tests, especially if low albumin is due to inadequate nutrition and not from other factors like inflammation or chronic illness.
Factors Affecting Albumin Response
Protein Dosage: While albumin synthesis increases with more dietary protein, results plateau at moderate amounts (around 20g per meal); going higher may not speed up albumin increases beyond what the body can utilize immediately.
Other Conditions: Acute or chronic inflammation, kidney or liver disease, and fluid status can independently lower or mask increases in serum albumin.
Individual Differences: Age, overall health, and baseline nutritional status can affect how quickly serum albumin responds to dietary changes.
Practical Considerations
Most nutritional interventions recommend reevaluating albumin labs after at least 3–4 weeks of consistent increased protein intake.
If low albumin is related to protein-energy malnutrition, steady intake of 60 extra grams per day could support a gradual rise over several weeks, but significant jumps in lab values are uncommon in just one to two weeks.
In summary, with an extra 60 grams of protein daily, expect subtle albumin changes to appear after about 2–4 weeks, longer if underlying inflammation or illness is present.
A couple of days ago, I used Perplexity to ascertain which, if any, stocks to buy. Today, I ran our portfolio through Perplexity to obtain recommended stocks to sell, if any, which is named “Rationalizing your portfolio.”
This is the Prompt followed by the analysis Perplexity provided:
Prompt: Of the stocks in our portfolio that we manage, which, if any, should we sell?
Ticker
Recommendation
Key Rationale
AIRO
Hold
Bullish long-term forecasts
DPRO
Hold
Analyst consensus “Strong Buy”
RCAT
Hold/Review gains
Mild uptrend, no strong sell signal
SPAI
Consider Sell
Short-term bearish, downside risk remains
UMAC
Hold
Strong buy, bullish forecasts
DRSHE
Consider Sell
Negative forecasts despite strong business growth
ONDS
Hold/Review
Flat or declining forecasts, watch for sustained weakness
DX
Consider Sell
BDC weakness, poor price performance vs. peers
HRZN
Consider Sell
NAV decline, sector & asset quality risks
OBDC
Hold
Stable vs. sector, no glaring red flags
TRIN
Hold
Positive relative performance, among top BDC picks
Based on Perplexity’s recommendations, I sold the four stocks it recommended to sell. This morning in Monday’s WSJ, I read an article about how foreign stocks are outperforming U.S.-based stocks. I then used Perplexity and requested a listing of ETFs that are invested in foreign stocks. The one that stood out was Vanguard’s VYMI, which I used the proceeds from the previous sales to purchase 480 shares of.
Before making the buying decision, I asked Perplexity if VYMI was a good replacement for the BDCs we had just sold, based on its recommendation, and received the following advice, located in the PDF below. You know what’s really neat about this: anyone can do it!
The past couple of days I have used Perplexity to research promising companies operating in the warfare realm, including defense drones and anti-drone space. For today, I used Perplexity to construct a matrix, AKA a table, of these companies with actual holdings. The first five operate in the defense category, and the second two in the anti-drone space, and the remaining are BDCs with pay high dividends. The data is as of about the market close on Wednesday, 10/22/2025. See below:
The four Business Development Companies (BDCs) have been added to the existing portfolio — Ellington Financial (DX), Horizon Technology Finance (HRZN), Blue Owl Capital Corporation (OBDC), and Trinity Capital (TRIN). Their market data, including share count, cost, and current price, was sourced as of October 22, 2025.perplexity+3
Updated Portfolio:
Ticker
Name
Shares
Cost
Market Price
Value
Gain
Gain %
AIRO
AIRO Group Holdings
100
$1,878.40
$17.50
$1,750.00
-$128.40
-6.84%
DPRO
Draganfly Inc.
200
$1,725.95
$9.42
$1,884.00
$158.05
9.16%
RCAT
Red Cat Holdings
100
$868.00
$11.57
$1,157.00
$289.00
33.29%
SPAI
Safe Pro Group Inc.
100
$764.00
$6.81
$681.00
-$83.00
-10.86%
UMAC
Unusual Machines Inc.
100
$977.59
$12.76
$1,276.00
$298.41
30.52%
DRSHE
DroneShield Ltd.
500
$1,602.50
$2.22
$1,110.00
-$492.50
-30.73%
ONDS
Ondas Holdings Inc.
100
$761.52
$9.45
$945.00
$183.48
24.09%
DX
Ellington Financial
1,224.258
$14,820.97
$10.01
$12,254.78
-$2,566.19
-17.31%
HRZN
Horizon Tech. Finance Corp.
1,370.636
$11,169.87
$5.88
$8,062.14
-$3,107.73
-27.83%
OBDC
Blue Owl Capital Corp.
514.1934
$7,260.00
$12.96
$6,666.16
-$593.84
-8.18%
TRIN
Trinity Capital Inc.
568.5004
$9,148.15
$16.35
$9,296.78
$148.63
1.63%
Totals
Total Invested: $52,977.95
Current Portfolio Value: $45,082.86
Total Gain/Loss: -$7,895.09
Total Return: -14.91%
The BDCs really got hammered today, reducing overall returns greatly.
This past Monday, October 20, 2025, The Wall Street Journal ran an article on page A18 titled “Global Startups Race to Develop Systems to Fight Drone Threats,” which got my attention. Up to now, my investments have been on the delivery side in such companies as AIRO, DPRO, SPAI, RCAT, & UMAC. Overall, in a short period, these stocks have produced decent market returns. The lead sentence in the cited article states, “Startups from Silicon Valley to Europe and beyond are racing to develop cheap, reliable systems to counter hostile drones (that) appear over airports and global shipping lanes far from the battlefield in Ukraine.”
Can you smell the investment opportunities? I can and did. I turned to Perplexity with the following prompt and results:
Prompt: Small new startups publicly traded in the anti-drone sector.
Several small, publicly traded startups are emerging in the anti-drone (counter-UAS) sector in 2025, focusing on detection, jamming, and AI-driven defense solutions for both military and civilian markets. These firms stand out for their niche technologies and relatively low market capitalization compared to major primes.
Small Publicly Traded Anti-Drone Companies
Company
Exchange / Ticker
Headquarters
Key Technology Focus
Notable Developments
DroneShield Ltd
OTCMKTS: DRSHF
Sydney, Australia
RF and radar-based detection, jamming rifles (DroneGun Mk4), AI-driven DroneSentry fusion system
Recent $32 million Asia-Pacific defense contract; active field use in Ukraine exoswan+1
Dedrone Holdings
Private (seeking listing)
U.S. / Germany
AI-based and sensor fusion counter-UAS networks
Recently integrated with U.S. federal and airport defense systems; potential IPO candidate marketsandmarkets+1
Ondas Holdings
NASDAQ: ONDS
U.S.
Wireless data and counter-drone communications tech via subsidiary Airobotics
Expanding presence in Israel’s anti-drone urban defense systems theglobeandmail
Red Cat Holdings
NASDAQ: RCAT
Puerto Rico, USA
Small tactical drones and anti-UAS integration
Works with U.S. DoD and public safety clients, expanding into counter-UAS software fusion theglobeandmail
ZenaTech
NASDAQ: ZENA
U.S. (Defense startup)
AI-based radar and jamming solutions for battlefield use
Identified as one of the fastest-growing drone-defense equities in 2025 theglobeandmail
Private Startups Poised to Go Public
Some defense-focused startups are not yet listed but are considered potential IPO candidates or acquisition targets:
Aurelius Systems – specializes in smart radar for small UAV interception.militarystartups
BlueHalo – works on directed-energy and C-UAS systems; may pursue public listing after latest funding round.militarystartups
Epirus – developer of high-power microwave counter-drone systems, noted for rapid DoD prototype adoption.militarystartups
Guardian RF – passive RF-based detection, funded through Y Combinator, potentially seeking future listing.ycombinator
Market Drivers
According to MarketsandMarkets, the anti-drone sector will grow from $4.48 billion in 2025 to $14.5 billion by 2030, a 26.5% CAGR, driven by AI-enabled tracking, radar fusion systems, and increased defense spending in the Americas region.marketsandmarkets
For investors, DroneShield (DRSHF) and Ondas (ONDS) are the leading small-cap public equities in this niche, while Dedrone, Epirus, and BlueHalo remain top private contenders likely to influence the market soon.
Based on this analysis, I bought 500 shares of DRSHF & 100 shares of ONDS. Wish me luck!
One of the “pleasures” we can enjoy while on dialysis is analyzing our stock portfolios, given that we hold such securities. We can do it all alone, with help from our friends (always someone around who thinks they have a hot tip), with the aid and attendance of professionals, or a combination of all of the above. Personally, we have professionals manage about 90% of our portfolio of investments, and we manage the remaining 10%.
At our point in life, we are interested in stocks that throw off great dividends and are relatively lower risk. There is a not well-known segment of stocks named Business Development Companies, or BDCs for short. By law they pay a major portion of their profits in dividends. Suggest doing a Google search on BDCs for more information.
I used Perplexity to map out the 15 highest dividend-paying BDCs to provide insight into expected returns. BTW, some pay monthly and some quarterly dividends. See table below:
Here is the updated table of major Business Development Companies (BDCs) sorted by highest total return or dividend yield as of October 2025. The returns reflect annualized yields and current prices from the most recent SureDividend and Fidelity data.
The recently installed Spinal Cord Stimulator is doing a great job. I was having recurring leg cramps at night, but turning the stimulator power to 4 from 5 at night has really worked well to mitigate this problem. I have been able to drive our truck over 100 miles without my feet going to sleep, my walking gait has improved, and I have feeling in my legs once again. What’s not to like about it? I am going two weeks between battery charging, FYI,
Had our new all-around domestic person in yesterday to do yard work for us. She is fast, efficient, and accomplished, completing in four hours what would have taken me several days. Well worth it. For instance, I’m not allowed on ladders anymore, so I had her change a burned-out LED flood light on our garage corner. I barely took a breath, and she had it done. Same with weeding and other chores I presented her with. We’re lucky to have her. She also walks Dickens three times a week.
I’m having one of those two steps back days when all around me things are breaking or need fixing. Some examples: I’m trying to intake more protein, so last night I started to cook hamburgers on the grill outside. The grill has never presented any problems, but last night, while it was lit, it was not heating up enough to cook the burgers. I was tired and it was late, so I brought them inside where we finished cooking them in our little oven. Luckily, they were precooked Angus burgers so all we had to do was essentially reheat them. I tore the grill down after checking for gas, which was ok, fired it up again, and it was good to go.
I’m keeping a log of all food intake for three days in prep for our dialysis team meeting on Thursday. During this meeting, the subject of discontinuing IPN will be at the forefront, and what to do in its demise. The team dietitian has requested the data on meals and provided me with a rich source of protein-rich foods for those of us on dialysis. This listing is provided below in PDF format.
My wife’s email stopped working all of a sudden. We use a source named bananic.com and “own” the domain names feeser.net, along with feeser.me. Our email addresses are our first names followed by feeser.net. Mine, running off of Gmail as a front end, never has any problems. I’m running hers out of Thunderbird, and therein lies the problem. I finally got the server settings tweaked so that she can receive emails, but not send them. I’ll keep plugging away at it.
My wife has several projects that she has brought to the fore as follows:
Our front door leaks air around the top. We had a replacement door estimate, and it was $29,906. Ha to that. We have a builder friend of our son coming in tomorrow to do a look-see and possibly rehang the door or replace it.
Our front porch is developing small cracks, and our driveway has several large ones. We are still seeking estimates to recoat both of these.
We have funkey gates across the front of our single garage roll-up door because HOA restrictions in Pecan don’t allow garage doors to be seen from the street. The gates are sagging and need to be replaced.
We have a brick extension installed off our back patio, which is starting to settle in places. We have the guy who installed them under contract to come back, remove the brick and necessary materials, and relevel the entire extension.
