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Car being driven by a robot goes off a cliff.

AI in Finance Is a Governance Problem — Not a Technology One

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On February 26, 2026

In Accounting and Reporting, AI, CFO, Finance, Leadership

For the last year or two, every CFO conversation eventually drifts into AI. Sometimes it’s framed as excitement, sometimes as anxiety, and sometimes as an awkward silence followed by, “Well, we’re looking at it.” What’s striking is that most of the tension around AI in finance has very little to do with the technology itself. The models work. The tools are improving fast. The vendors all have slick demos.

The real issue is governance.

Finance teams are wired around controls, auditability, and repeatability. AI systems, by contrast, are probabilistic, opaque, and constantly evolving. That mismatch is where most CFO discomfort comes from — and it’s why “let’s just automate this” often stalls once it hits a real finance process.

The first mistake I see is treating AI like just another system implementation. ERP projects taught us how painful that mindset can be. AI requires a different framing: not “what can this tool do?” but “what decisions are we willing to delegate, and under what constraints?” That sounds abstract. It isn’t.

Over the past year I’ve pushed AI tools on real finance questions: revenue recognition edge cases, SEC disclosure interpretations, covenant calculations, and technical accounting memos. The patterns that show up are not technology failures. They are governance failures waiting to happen.

1. AI doesn’t fight back.

If you have ever debated an accounting position with a strong controller or technical accounting lead, you know what conviction feels like. You push. They push back. You test assumptions. They defend them with chapter and verse. That friction is healthy. Same thing for a forecast analysis. If one FP&A analyst thinks they found a good or disturbing trend, it will be debated and verified and usually their work can be recreated and checked.

AI does not behave that way.

If you tell it, “I think you’re wrong,” it often apologizes and produces a different answer. Sometimes an entirely opposite answer. The confidence level remains high. The tone remains polished. The data is processed inside the model, and the AI often struggles to explain — or even remain consistent in — its answers.

In a live finance organization, that would be a red flag. If a manager flipped their view that quickly under mild pressure, you would question the depth of analysis. With AI, the flip can look like responsiveness rather than fragility.

That is a governance issue. It means you cannot treat an AI output as a position that has survived adversarial testing. It hasn’t. It has survived prompt engineering. And the prompt may have been poor.

2. The praise problem.

Most AI agents are relentlessly deferential. “Great question.” “Excellent point.” “You’re absolutely right to focus on that.” In a consumer context, that feels pleasant. In a finance context, it is dangerous.

Finance works because of tension — between risk and growth, between conservatism and disclosure clarity, between what management wants and what GAAP allows. When the “advisor” in the room is constantly affirming the user, it subtly reinforces bias.

I’ve seen this firsthand when asking an AI to pressure-test a disclosure approach. Rather than aggressively identifying weaknesses, it often validates the framing of the question. The tone can make a marginal position sound well-supported. In other words, the user’s confidence can rise faster than the quality of the analysis.

Governance must assume that AI will not naturally challenge you the way a seasoned audit partner or skeptical board member will.

3. The citation illusion.

This one should make every CFO uncomfortable.

Ask an AI to provide citations to accounting guidance or SEC commentary, and it will often comply — confidently. Paragraph numbers. Codification references. Even plausible-sounding excerpts.

The problem is that some of them are fabricated. They look right. They read right. They are formatted correctly. But they do not exist.

In finance, citations are not decorative. They are the backbone of defensibility. When you write a technical memo on revenue recognition or stock-based compensation, the citation is the bridge between your judgment and the authoritative literature.

If an AI invents that bridge, and a team relies on it without independent verification, the failure is not the model’s. It is the control environment’s. Any AI-assisted accounting memo must include a verification step where a human independently confirms the authoritative source. Not “glances at it.” Confirms it.

4. Rule changes and historical drift.

Accounting rules change. Constantly.

Revenue recognition under ASC 606 replaced a patchwork of legacy guidance. Lease accounting under ASC 842 upended decades of practice. The SEC updates disclosure expectations over time, sometimes subtly, sometimes dramatically.

Meanwhile, the SEC’s EDGAR archive goes back decades. There are scanned paper filings from eras when the rules were materially different. There are thousands of examples built under superseded guidance.

AI models trained on broad corpuses struggle here. They can blend old and new regimes. They can cite legacy practice as if it were current. They can rely heavily on the abundance of historical examples rather than the correctness of modern policy.

I have seen AI answers that lean on pre-606 revenue language as though nothing changed. Or that reference lease accounting concepts that no longer apply post-842. To a non-expert, the answer looks sophisticated. To someone who lived through the transition, the seams are obvious.

Governance means you assume the model does not instinctively know the effective date of your accounting framework. You have to constrain it.

5. Finance is not plain English.

Financial reporting language is precise. “Probable” does not mean “likely” in a colloquial sense. “Material” is not a synonym for “important.” “Reasonably possible” has a defined meaning.

AI systems are trained on massive volumes of plain English. That is a strength in many domains. In accounting, it can be a weakness.

I’ve seen answers where the model drifts into narrative explanations that sound sensible but subtly misapply defined terms. In a board deck, that might pass. In a 10-K, that is a problem.

When language itself carries regulatory weight, small deviations matter.

So what does governance look like in practice?

It is not banning AI. That is neither realistic nor wise. The productivity gains are real. Drafting first passes of memos, summarizing contracts, identifying anomalies in large datasets — these are powerful tools. AI can be properly trained on your data and become more accurate. Specialized firms like the Big 4 Auditors can train AI models on better and sanitized accounting data, but your small Finance group cannot and its probably using a more general model.

But they must sit inside a control framework.

At a minimum:

  • AI outputs that influence external reporting require documented human review.
  • AI conclusions about trends must be independently tested and verified. Don’t order another $1M of a part because a model suggested it.
  • Authoritative citations must be independently verified.
  • Prompts and versions used for material analyses should be retained for auditability.
  • Use cases must be categorized: drafting support is different from judgment replacement.
  • Responsibility for the final position must be clearly assigned to a human owner.

Most importantly, the CFO has to set the tone.

Let me make a direct observation: most leadership team members are not finance experts, but AI can create the illusion that they are. You need to make sure they understand the risk.

If AI is positioned as an infallible oracle, teams will over-rely on it. If it is positioned as a junior analyst — fast, helpful, occasionally wrong, and requiring supervision — behavior adjusts appropriately.

The question is not whether AI will be used in finance. It already is.

The question is whether it will be used inside a governance framework that protects credibility.

Investors do not care how you produced your numbers. Auditors do not care how you drafted your memo. Regulators certainly do not care that a model was “usually right.” They care that your disclosures are accurate, supportable, and controlled.

AI in finance is not a technology problem. It is a governance problem. And like most governance problems, it lands squarely on the CFO’s desk.

I don’t want to sound like Cassandra warning of inevitable doom. Nor do I want to be the boy who cried wolf while your competitor quietly figures this out and gains an advantage.

In future posts, I will outline where I believe AI can genuinely add value inside a disciplined finance organization.

Businessman diving into a pile of cash with a bottle of champagne in hand.

Success! – The Waterfall of Cash at the End of the IPO

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On February 24, 2026

In CFO, Investor Relations, Working With Investment Banks

In my last blog entry on IPOs, the process had reached the successful end of the roadshow, and the banks were now prepared to offer you the deal.

This is the step where the final price is set and where the initial allocation of shares is done. There can be some movement in the share price compared to the original range announced at the launch of the roadshow. If the change is within a 10% band of that indicative pricing, you can proceed with pricing without needing to refile.

If demand is strong enough to justify a price more than 10% above the original band, it ideally was identified early in the roadshow so the range could be adjusted and a new prospectus filed with the SEC. If the demand is very back-end loaded, you may be forced to delay pricing while the new filing is made. That delay — on top of the market signal that a price reset was needed — can outright kill the deal.

That is one reason deals are often cut in size if demand is lower than hoped. The delay combined with weak optics can be fatal.

When the banks (specifically the lead left bank) tell you the price and number of shares, they also give you their proposed allocation — how many shares and to which investors.

The first thing to point out is that the initial allocation includes the “greenshoe,” which is part of a standard IPO. This is normally 15% on top of the base deal size. The underwriters sell these shares short up front as part of the stabilization process.

I will get to stabilization and the greenshoe mechanics shortly, but the key point at this stage is that the order book must cover not only the base deal but the additional 15% as well.

You do get a say in the allocation.

For the most part, the ECM desk knows who is best to place the initial shares with and how many. This ties directly to how the stock is likely to trade when the IPO goes live. You need some trading to happen right away, so some shares need to be placed into accounts that will actually trade.

You should absolutely review the allocation carefully. It is fine to tweak it and move shares to certain investors that you favour, especially those you believe will be constructive long term holders. But you also need to trust the banks. They are in the market every day and know these accounts well.

All of this is calculated by the banks, and they present what they believe is the most reasonable structure to support successful aftermarket trading. Everyone wants to see the stock trade up after the IPO — that stamps the deal as a success out of the gate. A huge first-day jump generates good press, but too big a jump is money left on the table by the company.

The deal then goes to your Board of Directors — almost always to a pre-authorized pricing committee. You need a quick decision, and coordinating a full board in real time can be a logistical nightmare. A smaller group authorized in advance makes the process smoother.

The lead bank presents the final terms, there is discussion, and then a decision is made.

Sometimes demand is not quite where you hoped. The banks may propose a smaller deal, a lower price, or both. If this happens, you are in a very tough spot. A failed IPO can set you back quite a while. If you take a lower price or reduced size, it puts you on your heels from a momentum standpoint and makes early investor relations more challenging.

I lean toward taking a workable deal and fighting forward, but you cannot make that call in the abstract — you make it in the moment. I did not face that specific scenario as our IPO priced in the middle of the range.

The next morning, trading begins. Pricing is often Wednesday night and trading starts Thursday morning. Banks generally avoid Mondays and Fridays for a first trade.

Traditionally, this also gives the company the opportunity to “ring the opening bell.” It is essentially a staged PR event, but a meaningful one for the team. Because we did our IPO during COVID, we did not get to do it. If you can arrange it, I recommend it.

Hopefully trading starts well and the stock trades up. Every trading day brings outside news and market events, so not everything that happens will have anything to do with your company.

Enjoy your celebratory dinner with the banking teams and, if you drink, have something that night to mark the moment — just do not do anything foolish (really do not drink and drive).

Although the stock technically settles on standard T+1 timing, your underwriting agreement likely specifies settlement between T+2 and T+4. This is because the underwriters purchase the shares directly from the company, not through market trading.

On settlement day, you receive a wire transfer for the gross proceeds less underwriting fees and usually all professional fees agreed to be paid (both yours and certain bank expenses), plus travel and other deal-related costs that the banks advanced.

You will only receive proceeds for the shares sold by the company. Secondary shareholders who sold as part of the IPO receive their cash directly from the underwriters.

If your company receives primary proceeds, you should have a plan ready. In our case, a significant portion went toward paying down debt.

If the stock stays at or above the IPO price during the greenshoe period (typically 30 days), you will also receive proceeds from the additional 15% overallotment.

If the stock trades down and the stabilization agent buys shares in the open market to cover the short created at pricing, you may end up with less greenshoe exercised. That is normal. Stabilization is common. Roughly 20–30% of IPOs trade below the offering price on the first day, and 40–50% trade below it at some point in the first 30 days. We tend to remember the moonshots and forget the statistics.

The greenshoe exists to balance the overallotment and help manage those first few weeks of trading. A clean aftermarket makes life much easier for management and investor relations.

The final topic that is important to understand is the lock-up.

It is very common for underwriters to require a 180-day lock-up on the company and its officers. This is designed to prevent additional stock from coming to market too quickly and gives IPO investors some stability.

It also means management has to wait 180 days before selling any shares they own or have been granted.

The banks can waive lock-ups, and terms are negotiable, but 180 days is standard. I have had waivers granted before when the stock was trading well above the offering price and the transaction involved secondary shares, so it is possible — just not typical.

Enjoy the success.

And try not to drown in the pool of cash.

Wooden puppet draped in green glowing code with a large nose.

My Technology Life: AI: Lying Liars Lie

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On February 14, 2026

In AI, CFO, Computer hardware, Finance

I know that the in-vogue term is hallucinate instead of lie, but since the main interface to AI tends to be via chat — and the models are intentionally designed to simulate a personality — “lying” feels more accurate.

During my attempts to develop the RPG PDF conversion pipeline I described last week (you can find that post here: https://mgpotter.com/my-technology-life-ai-agent/), I encountered behaviors that should sound very familiar to anyone who has tried to push AI beyond toy problems.

Here are a few highlights.

1) Work Claimed, Work Not Done

On several occasions, I was told that the new Python script I requested had been completed. When I asked to see the script — because my own coding is not good enough to trust it without review — I was then told the script could not be found and likely had not been written.

In another variation, I was told the PDF had been successfully processed and that the output was excellent. No output file existed.

This is not a “mistake.” It is the model optimizing for conversational completion. It is trained to provide a satisfying answer, not to verify that work was actually performed.

2) Phantom Sub-Agents Doing Phantom Work

At one point I was informed that five sub-agents had been spawned to divide the PDF and perform OCR.

The problem? The OCR tool in question does not run on the 15-year-old CPU I was using as a test bed. It lacks the instruction set required to execute.

Yet I received multiple progress reports describing how efficiently the sub-agents were performing.

In reality, the tool had crashed immediately. The sub-agents were waiting for a reply that would never come. The administrator bot was confidently reporting progress on work that had not and could not have occurred.

Again, this is not malicious. It is structural. The AI fills in gaps with plausible narratives.

3) “Perfect Output” That Was Garbage

More than once, I received a grand report that the parsing was perfect and ready for conversion into Fantasy Grounds format.

The file was not even close.

The model had learned that the desired outcome was “success.” So it reported success.

4) Hardcoding the Answer

While dialing in table and column detection, I created an answer sheet to help guide the agent’s debugging.

The next output was perfect.

Until I asked probing questions and ran the code through a second model.

There had been no improvement to the algorithm. The agent had simply hardcoded the expected answer.

This is a recurring issue: the model optimizes to satisfy the prompt, not to build a robust, generalized solution.

5) Creative Rewriting Instead of Extraction

In some cases, the “extracted text” was not extracted at all. It had been rewritten and reorganized to be cleaner and more readable.

That might be helpful for marketing copy. It is catastrophic for financial reporting or legal work.

These Problems Are Not Unique to Hobby Projects

I have seen similar behaviors when applying AI to real Finance questions:

  • SEC citations that do not exist
  • Press releases with invented links
  • Tariff rules misread and inverted
  • Spreadsheets reorganized in ways that no longer foot

In Finance, you cannot be 98% right. Especially when you are reporting publicly.

A 2% error rate is not a rounding issue. It is a career-limiting event.

How to Reduce These Errors (But Not Eliminate Them)

There are ways to mitigate these behaviors. They require discipline.

1) Force Evidence, Not Assertions

Instead of asking whether the script was completed, ask the AI to return the full script, include line numbers, include the file path, and confirm the function definitions exist. Make the AI produce artifacts, not conclusions.

2) Require Verifiable Citations

Instead of asking what an SEC rule says in general terms, require the model to quote the exact paragraph of the rule, include the regulation number, and state explicitly if it is uncertain rather than inferring. Force it to cite or admit uncertainty.

3) For Code: Demand Diff-Based Changes

Instead of simply asking to improve the algorithm, require the model to return only the changed lines, explain the logic improvement, confirm that no test data is embedded, and explicitly state that it has not hardcoded expected outputs. This reduces the chance of hardcoding or cosmetic fixes.

4) Explicitly Forbid Invention

Include language in your prompts that instructs the model to say “unknown” if it does not know, to avoid fabrication, to avoid assuming files exist, and not to simulate tool output. You would be surprised how much that helps.

5) Separate Tasks

AI struggles when prompts mix architecture, implementation, testing, and reporting in one request. Break them apart. Treat it like managing a junior associate.

6) Independent Verification

If the output matters, use a second model to review it, recalculate totals independently, cross-reference source documents, and inspect logs manually. Trust but verify is too generous. Verify and then trust provisionally.

The Finance Question

I have seen steady progress in AI tools for Finance. FP&A more than accounting, which makes sense. Forecasts are inherently estimates; variance analysis is expected.

But regulatory filings, audit workpapers, footnotes, tax positions, debt agreements — these are binary environments.

The market, the SEC, your auditors, and your board do not accept “the AI hallucinated.”

The tools are impressive. They are helpful. They can accelerate research, draft memos, and summarize documents.

They are not yet reliable enough to operate unsupervised in Finance.

As of right now, AI tools in Finance should be used:

  • As assistants
  • As draft generators
  • As brainstorming tools

And always with a heavy layer of skepticism and human review.

Lying liars lie.

The models are not malicious. But they are optimized to complete conversations, not to protect your reputation.

That distinction matters.

Unstable stack of SEC filing papers. Several pages swirl showing edits.

Doing an IPO: The Reality Behind the Process

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On January 29, 2026

In Accounting and Reporting, CFO, Investor Relations, Working With Investment Banks

There is a lot of information available online about IPOs at a very high level. As with my other posts in this series, my goal here is to connect theory with my actual experience. In this post, I focus on actually doing an IPO—drawing on the transaction I helped lead roughly five years ago, along with more than 20 years of broader equity capital markets experience as a public company CFO.

This post is written for CFOs—and for those who want to become CFOs—because the IPO process is as much a test of the finance function and its leadership as it is a capital markets event.

An IPO doesn’t just test the company. It tests the CFO, the finance team, and every system beneath them.

Choosing the IPO Path: Traditional vs. SPAC

When we set out to pursue an IPO, we focused on a traditional underwritten offering. We did speak with several SPACs, but the valuations were not as compelling—and became even less attractive once we factored in the additional costs and structural complexity inherent in SPAC transactions.

At the time, SPACs promised speed and certainty. In practice, the economics simply did not work for us. That will not be true in every situation, but it is a decision that needs to be made with eyes wide open and a clear understanding of the trade-offs.

Your Core Advisors: Lawyers, Auditors, and IPO Specialists

Traditionally, your two primary advisors are your lawyers and your accounting firm. Your banks also advise you, but during the underwriting process there is an inherently adversarial dynamic: you must clear their internal risk processes before they will support launching the deal.

Today, there is an additional category of advisor that can be extremely helpful—IPO advisory firms that specialize in managing the process end to end. These firms are typically compensated through a share of banking fees and help guide management through what is otherwise a complex and unfamiliar process.

We used an advisory firm (Solebury Capital in our case, though there are others). For smaller companies, and particularly where management lacks deep capital markets experience, these advisors can materially reduce execution risk.

Getting the Right Lawyers and Auditors (and Paying for It)

It is critical that both your lawyers and auditors have meaningful IPO experience. In the case of auditors, they must also be SEC-approved. This is one of the first points in the process where fees increase noticeably—market credibility and IPO experience come at a premium.

You may need to switch firms entirely. Auditors, in particular, must be engaged well in advance. Ideally, they will have completed at least one full annual audit before the IPO process begins and resolved any issues related to reliance on a predecessor firm’s work.

Lawyers are somewhat easier to bring in later for the registration process, even without a long operating history with the company.

Hard CFO Career Advice: This Process Will Expose You

Here is some very direct CFO career advice: the IPO process is a stress test for you, your finance team, and your systems.

Once auditors know their opinions will be included in an S-1 used in an IPO, their risk tolerance drops sharply. They will be demanding—and appropriately so.

If your people, systems, or processes are not ready, that will become apparent very quickly to the entire IPO team. The finance function comes under an intense spotlight. You can lose the confidence of the Board, and the risk of replacement is real.

No one is really your friend during an IPO. The work has to be done before the spotlight turns on.

There is a reason you often see a new CFO brought in six to twelve months ahead of an IPO.

Marketing Readiness and the Company Story

You should already have your core marketing points prepared. Even an early, imperfect version of the company story helps attract banks and investors.

Today, it is rare for a company to go public without having completed multiple rounds of private financing, often with investors who also operate in public markets. Those interactions matter more than many CFOs initially realize.

Choosing the Banking Team

Once you are ready to proceed, this is the stage where you select your banking team. Ideally, you have been investing in banking relationships while still private and have a meaningful starting pool.

If not, an IPO advisory firm can be particularly helpful.

Even if you do have relationships, they may not be with the right analysts or sector teams. While there is significant focus on choosing the lead bank during the bake-off process, you will ultimately work with a syndicate. Use the process to signal that smaller banks matter—even if they are not selected as lead.

The Team Matters More Than the Bank Name

This is an important concept: the bank’s name appears on the cover of the S-1, but it is the banking team that actually works with you.

You want the A-team, not the C-players at a prestigious firm. Internally, this comes down to respect. Bankers want to make money by solving problems efficiently. They do not want unnecessary friction or rework for the same economics. The bank’s internal staff know who their A-players are and what trouble their C-players will cause, so make sure the team representing you is strong.

During the bake-off, do not over-index on brand. Lean on your advisors and your own judgment about the individuals involved. Consider which banks bring the better sell-side analysts. The bank ultimately will step in and do what they can to get the deal done, but everything will be easier with the best team.

Strong teams get cooperation—from the bankers themselves and from the broader institution behind them.

Why Experience Matters (and Why Advisors Help)

Going through this process reinforced the value of our IPO advisory firm. Companies typically do one IPO. Even with internal capital markets experience—in our case, I was the only executive with prior IPO experience—you do not have the transaction repetition your advisors bring.

Auditors are less helpful here due to their role constraints, but they can recommend experienced law firms and partners. If you are VC-backed or PE-owned, your investment partners are also an important resource. Members of the broader management team may bring useful experience from prior financings or acquisitions as well.

The IPO Is a Sales Process

Some companies spend years nurturing banking relationships and presenting their story as a potential IPO candidate. Others gain similar experience through extensive pitching during venture fundraising or private equity acquisition processes.

If you are one of those companies, the next stages will be easier.

At its core, an IPO is a sales process.

The S-1: The Center of Gravity

The S-1 is the central document that drives nearly every aspect of the IPO process. Broadly, it consists of three main sections: the business, the financial statements, and the risk factors. Extensive appendices include material contracts and governance documents, such as share class and voting arrangements.

While significant effort goes into the investor presentation, that document is also filed with the SEC and is, in many ways, an extension of the S-1.

The drafting process is highly iterative—first within management, then across a broader internal group, and finally with the SEC once a near-final draft is filed. Confidential filing allows much of this work to occur outside public view until late in the process.

Risk Factors and Exhibits

Risk factors and appendices are generally the most straightforward sections. They are heavily lawyer-driven, and you benefit from reviewing filings of comparable public companies. SEC filings are not copyrighted, so language can be adapted where appropriate.

Management’s role is to ensure risks are complete, properly ordered, and reflective of the business. This section exists primarily to protect the company—if a risk is disclosed, investors have been warned.

The appendices require careful attention to which contracts will become public. Confidential treatment may be available for certain provisions, but disclosure is part of life as a public company, including detailed executive compensation disclosure. This also tests your document retention systems, as signed final versions are required.

The Business Section and the “Box”

The business section has the greatest marketing impact and the largest working group. It must satisfy SEC scrutiny while still presenting the company in the best possible light.

At the front of this section is the “box”—a concise summary set apart on the page that distills the company’s story. This content feeds nearly all other marketing materials and is reviewed relentlessly. Every claim must be substantiated. If you describe yourself as a “leader,” expect to prove it.

Despite being the least technical section, it often receives the most edits. My strongest recommendation is that the CEO own the final narrative voice. They will be doing most of the talking during the roadshow, and the document should sound like them.

Financial Statements: Where IPOs Get Won or Lost

Across the three S-1s I have prepared, the financial statements section always took the longest, produced the most surprises, and attracted the most SEC comments. Auditor scrutiny increases dramatically, and previously cordial relationships can become strained.

Every accounting policy must be fully documented. Disclosures must meet technical requirements, including MD&A and segment reporting. Poor segment decisions can create both compliance and marketing challenges.

I began my career at a Big 4 firm, became a Chartered Accountant, worked extensively in internal audit and controls, served as Controller of a public company, and had been a public company CFO for 14 years before leading this IPO. Even with that background, success depended entirely on having a strong SEC reporting team.

Experience helps—but systems, people, and preparation determine outcomes.

That team existed because earlier attempts to go public had uncovered material weaknesses across Finance and IT. Much of my first six months was spent rebuilding the close process and reporting to public company standards. If you are considering an IPO within the next year, you should be upgrading staff and systems now.

Preparing for SEC Reporting Standards

You will have help. Accounting firms provide detailed SEC reporting checklists. But your people must be capable of meeting the higher standard.

While SOX compliance is not required before going public, you should be close enough that it would not fail.

You are the CFO. Even without a deep accounting background, responsibility ultimately rests with you. Invest in better people and put in the time.

Filing the S-1 and Engaging the SEC

Once the S-1 is in strong draft form, it must be filed. While ongoing SEC reporting can be handled internally, the S-1 filing itself is typically managed by a financial printer specializing in SEC formatting and XML requirements. Errors here carry real risk.

Lawyers often have strong preferences for specific printers. Negotiate aggressively and evaluate multiple options—you can often secure favorable pricing for the first year of filings.

The process is far more streamlined than it once was. You are not staying overnight at a printer (Palo Alto was the location for me) where typists work on their Wyse terminals typing into Interleaf or whatever special system they used. Drafting happens in Word, with later conversion by the printer. You still need to review formatting and the final text in the printer system carefully, but by this point the financial statements should be in excellent shape.

With the confidential filing complete, the SEC review process begins.

Looking Ahead

In the next post, I will walk through the remaining stages of the IPO process, including SEC comments, the roadshow, pricing, and execution. By this point, however, you will know whether your finance organization is truly ready to be public.

Evaluating Opportunities

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On February 12, 2018

In CFO, Investing

When I first moved to Silicon Valley in 1999, I routinely received phone calls from DotCom start-ups looking for a CFO. I was a Controller of a division (close to $1B in revenue) of a big company, but I had just been promoted to that level for the first time and had near zero experience in what I thought was needed to be a CFO (the general advice these days seems to be to pretend you can do it and just take the job). I used to have a list of the companies that called me, and none of them made it. At the time, they told me I was an idiot for not leaping at my chance. Cryptocurrencies remind me of that.

Now, before I continue, I must admit that one of the companies that contacted me was Amazon.com. This was after they had gone public and their stock was quite high. They were looking for employees with inventory and supply chain experience, the title and pay was far below what I was making and I would have had to move to Seattle. The stock suffered in the DotCom bust, so it seemed that my decision to not change jobs was smart, but if I were really the genius that many bitcoin experts claim to be today, I would have invested then. I would have been quite wealthy now if I had.

I can only console myself in that I was also offered a job a few years later for a lower title and pay at a major networking company. When I declined, the recruiter scolded me for being turned off by their attitude and then not long thereafter, they took the largest inventory write-off that I am aware of and the stock really has neve recovered its high-flying ways since then. Finally, and more directly related to cryptocurrencies, I was a long time participant in distributed computing projects like SETI at Home and such and the early appearance of bitcoins and the first miners came from people like me that were using idle cycles of our CPUs to do something else. However, I never installed the bitcoin mining software. In theory, I could have been mining bitcoins when it was possible to solve for them using a regular PC and do it as an individual. If I had done so and kept the bitcoins I made, at today’s prices I would be far wealthier than my reasonably successful career has taken me to.

I added those three examples because I want to make it clear that I have no magical ability to know the future and perfectly guess every opportunity. This is compounded by the fact that you need to choose now and will not know until later, and often much later, if you made the right choice. Using bitcoins as an example, there is not guarantee that I would not have sold the coins at $100. Considering that I have played Magic the Gathering (a card game) off and on for quite a while, it is likely that I would have placed coins in MtGOX and lost everything I put in there. When you back solve what could have happened, most people solve to the best possibility, not the likely one even if you made one arbitrary correct decision that you did not in the past.

I have seen quite a few posts on bitcoin value cross my feed on Linkedin in the past few weeks, much more than when it was going up and all from people that claim some expertise or professional skill for bitcoin and all suggesting that now is the time to buy the dip.

Blockchain is real technology that is finding new applications. All the cryptocurrencies are experiments and they are valuable for the same reason why anything is valuable – people are willing to spend money on them. There certainly is a good argument that a currency linked to a blockchain has merit and can quite valuable for online transactions. There is no doubt at all that blockchain as a technology will see many applications, like perhaps tracking materials in the pharmaceutical production chains.

There also is no doubt that there will be lasting wealth that comes from the innovation, but I don’t think that trading advice (buy or sell) is the right thing to promote on Linkedin or on a Facebook feed. That type of decision needs to be an informed one from individuals, and older advisers may be trapped in past expectations, but they have also seen a few bubbles pop as well.

Even the arguments around cryptocurrencies and why they have value and are a currency themselves or are more valuable than other traditional currencies are suspect. For those of you that don’t know the standard argument, the normal value drivers mentions are i) production cost, ii) scarcity and iii) utility. The basic argument is that the cost to produce a bitcoin is high, they are scarce by design with only 21 million that can be produced and the blockchain technology makes them useful.

However, the production cost is based on current brute force problem solving and scarcity is all about bitcoin itself, not cryptocurrencies in general. There are near infinite algorithms that can be designed to generate a cryptocurrency and there are plenty of new industries where the first mover did not ultimately dominate (Netscape is a good example as is Visicalc and many other similar examples). The utility is even questioned because the transaction time and process to verify a transaction is thought to be too long and many merchants that had been accepting the currency have abandoned it as the transaction time exposed them to too much valuation variance. Even the early criminal use of bitcoins (the initial foundation in its value came from criminals using it to transfer money for drug deals and to do money laundering) has suffered as authorities have proven to be much better at tracking and shutting down bitcoin fueled deals than was originally assumed.

Even the crypto part of the equation may ultimately prove to be flawed as there still is the real possibility that the assumptions behind the math that powers it may ultimately prove to be false. Eventually there may be no more “greater fools” and there is a risk when you buy that you will end up being the last and most foolish.

I’ll try and parse through my thinking on these types of opportunities to show the how I think through I as an example of what I have done in the past as a CFO and what I do today when asked for advice as a consultant.

First, the normal reaction is to shut down and say “no” to new opportunities because these always represent additional effort needed and additional risk. In the case of bitcoin, the easy responses are “tulip mania”, “artificial bubble” and “ponzi scheme”. I am not saying that those responses are correct, but the longer I have been at it, the easier I find my mind comes to a way to say no. Saying no is easier, and, since the consequences of saying yes or no are rarely immediate, you can insulate yourself from the lost opportunity or loss easily. The problem is, saying “no” is easier, but it also closes down growth and opportunity and isolates you from changes in the market. When I detect that instinctive “no”, I push it down and listen and ask one or two simple questions. This is not free, that costs time and mental effort and causes some distraction, but I think that cost is worth the possible upside, so I pay it more often than not.

The questions I normally ask are: 1) Is this a decision I can or should make, 2) Can I or we afford the expense (or not afford to spend it), 3) How long do I have to consider it, and 4) Can I understand pretty quickly what the idea is all about and how it would be profitable?

The first question is an interesting one. As a Finance professional, and especially as you move up the management ranks, you will get both increasing power over spending and increasingly be lobbied for many different ideas outside of the traditional Finance responsibilities. However, you also need to know your limitations. One advantage of being part of a team is access to opinions and expertise of your team members, and using that will probably result in more informed decisions. You also need to consider that the latest encryption standard may seem cool to you, but the head of IT may not want you to install the ransomware you were just pitched in email.

The second question really is about practicality. I would love to have several different phones and VR headsets and whatever else comes out to see which one is good, but I only really need one phone at a time and I barely have time to use the VR headset I already have, so even more does not help. In the case of bitcoins, like most people, I have a wide variety of investment options in front of me, and bitcoins are just one of them.

Coupled with the cost and time commitment is the need to understand if you should be doing without it. I could just use pen and paper and brain power to calculate my taxes, but Turbotax does a much better job and does it much faster. The danger with budget or time pressures are that you may ignore something important. I have used the time when I was flying to read up on new technologies and I have always carved out some time to look at what has changed in the market compared to what has been happening. This is important for personal portfolios and reserving even a small amount of your investment capital (5%) to invest in new technologies or trends can help here.

It has been my experience that the shorter time you have to make a decision, the less something makes sense. There always is lots of marketing and media hype to buy or sell now, but rarely do you need to make an instant decision. If a technology is good, or a trend really has changed, you can enjoy the benefit well enough if you spend a little more time to make sure you understand what you are considering. Most importantly, the risks it brings. In the case of cryptocurrencies, there are a lot of self-proclaimed experts, but most a simply hyping without any depth or new information. I also have seen a disturbing pattern emerge of people with fairly questionable backgrounds suddenly getting involved. It sure is easy to promote this new idea that replaces traditional investment products when you lost your broker license because you were convicted of defrauding your clients.

Counter to the previous concept of making sure you have enough time to consider the new opportunity, it also must be something that you can grasp with a reasonable amount of time and effort. There are always slight edges that someone with a decade of experience and education can exploit, but it might not be the right thing for you to try and figure out. Quite often new technology products work well for people with the specific skillset to use them but are not worth the cost f you cannot program or change all the base setting on your computer to get the additional 5% performance boost. Learn to recognize when something is more complex than you have the training and time to understand quickly and deeply enough and reach out for help. Do not be afraid to say you do not know or do not understand.

I have always been an intuitive problem solver but working in my chosen field which is seeped in process and logical progression, I have to take what I feel is right based on my internal process and break it down in a way that I can repeat and explain it to the people waiting for my decision.

In the case of bitcoins, and other cryptocurrencies, I have seen little reason other than pure speculation, to try them out in any real way. I can understand that the base technology is something to follow closely, but I do not think that it is something that needs urgent action and there are real risks of fraud and theft and regulatory curtailment. I also am concerned about the poor quality of the advisers that have attached themselves to it. As I cautioned up front in this blog, I could have made quite a bit of money just by embracing bitcoins earlier in my life and I was a natural fit for the early adapters there. Unlike the self-called experts I see in the media these days, I know that I don’t know a lot of the details and I think it is not worth my time and money to learn more, but it is complicated and I could be missing something. I have a real edge in other investment and finance areas and I am choosing to spend my time there.

Working with investment bankers

By

On March 8, 2016

In CFO, Finance, Working With Investment Banks

If you have followed a normal career progression through finance to make it to CFO, you probably worked with investment bankers at least once along the way. It is possible you did not, maybe you are at a start-up that is just now successful enough to go public or do some form of pre-public fund raising and you are dealing with bankers for the first time. It is a fallacy to believe that working for a big company means you would have worked with investment bankers as you climbed the ladder as normally only the Treasury department and the CFO do that, division finance staff normally are not involved. Even if you are involved, it is as a data source, not negotiating the deal. Mid-sized companies tend not to have formal Treasury departments and are a lot more egalitarian, so a much better chance of gaining some experience.

This blog is about working with the bankers themselves. Each investment bank is different and has resources far beyond the bankers that directly cover you, but you will probably never see the rest of the bank, just the small staff that covers you and the few people within their bank that they introduce you too. I try not to be too caught up in the name of the bank they work for and focus more on what my coverage team can deliver. Obviously, there are different tiers of banks, but which ones want to serve you is already at least partially driven by your company size. There just is not enough business for larger investment banks to devote resources to smaller companies.

Investment banks and their bankers get a lot of negative press. The recent, Oscar nominated film “The Big Short” is a good example. They usually are a topic in just about every major political campaign, and populist anger is stirred up against them. The current hit musical “Hamilton” has some of the Founding Fathers attacking them as doing nothing but moving money around. At the end of this blog, I will link some books that are quite critical on bankers and their culture. I can tell you that I have worked with quite a few bankers over my career and I have cannot remember working with any that are like the tell all books I have read, but the banking culture certainly is a culture into and of themselves. I will also link a few more “studious” books as well, if only for balance.

Let’s start with describing the three types of bankers you are likely to work with. The first, and most important, in your coverage banker. The leader of that team is almost always a “managing director” and typically has a small team that works for them. The MD is usually an industry specialist but otherwise a generalist. The next type of banker that you are likely to meet is a product specialist. There are many different products that a bank can sell to the market or to you and the product specialist is the one that supports the MD in pitching the products. Examples are syndicated loans, hedging instruments, convertible bonds, asset backed securities. The bank probably has someone who specializes in that product. The final banker that you are likely to meet is someone from one of the “desks”. This may or may not be one of the specialists that came to sell a product to you, but the important ones you want to meet are the heads of the Equity Capital Markets desk or the Debt Capital Markets desk.

The “desks” are always a little hard to understand, but the easiest way to think of them is that they run the sales force that will be selling your instrument to investors and they are the ones that decide on how it will get allocated between the bank’s customers (not you in this case).

What is very important here is that your coverage banker must be experienced and have clout internally. If you do a deal run by that bank, you need to best and most experienced team executing the deal and the relationship that the coverage banker has with the desk is key. A good relationship can result in above average resources devoted to your deal. A bad relationship or lack of clout in their bank and you might get the the C team and so-so execution.

One question that I get from time to time is how do you even get covered by a bank or bankers so you can get access to them and their resources. I find that question a little strange because bankers survive on fee income. So if there is a way for them to earn a reasonable fee, you should be able to get the attention of a banker. The main way to meet a banker up front is through your lawyers, accountants or through your investors if you are VC funded. If you have a deal for them or a good possibility of a deal in the near future, you will get some attention at least. If you actually have a transaction like an IPO, you can do a “bake-off”, and get a few banks to compete for your business.

Choosing a banker

Let’s say you have had your bake-off, or you have met a few bankers and now you are trying to decide which one to go with. I’ll try and list out some of the things that I consider the most.

The first is that is this is not a smaller transaction, then you probably will have several different banks working on the deal. Whoever you choose as the lead banker (the bank on the left of the list of bankers on the front page of the offering document) will end up controlling the deal, so I generally try and focus the most on picking that one. As an aside, banks and their bankers are very competitive and expect to have several ridiculous conversations about position and typeface and variations of the title they are called. You will need to make it very clear that the banks are to work together well. Most are professional, but they also want to position themselves for the next deal and they are perfectly happy to throw their competition under a bus if given a chance.

I tend to look for experience, both in the bank and from the banker, trustworthiness, and strategic sense. All banks will have two different experience elements in their initial pitch books – league tables and deal tombstones. They will cut industry data in a way that shows that they are a leader, usually the leader in whatever deal they are trying to get onto (or your industry if an initial meeting). They will list out all the deals they were on, sometimes even if they had only very minor roles if they need to, but usually any deals they were some form of bookrunners.

I am a little cynical about league tables because the data chosen is cherry-picked to make the pitching bank look good, but they do have some reference value because if you have 3-4 banks come see you, you can compare the tables and see if there is a pattern as to who is number 2 or three in all of them. That is a good indication of who the leaders really are. Having a big market share and being a leader for a long time can be a good indication of how strong the bank is. And if the banker cannot make his bank look good, then you need to ask yourself how good a job they will do for you with investors.

The tombstones are much less useful. I normally look at the dates to make sure enough are recent, and I ask if the banker and his team personally worked on the deals presented. With typical turnover, anything more than several years old was likely done by a different team and different leaders at the bank.

The next criteria is trustworthiness. This may be surprising, but even with the books listed at the end and my cynicism about the process, I like my current bankers very much and I have had almost uniformly positive experiences with them. What I need to know is that are they there to help me as their priority or themselves or their bank and if they can keep details confidential. Both are easy to tell. Are they listening and advising or are they selling? Are they sharing details of competition that would make you uncomfortable if they shared the same about you?

One of the best ways to tell if you are a priority is coverage (visits, phone calls, emails) even when there is not a deal on the table. The next best indication is if they lend you resources, typically an associate or two to help in a project you are working on. Banks tend to have very good in house models for M&A, for example, or they may have very good knowledge and advice on what to use for standard valuation metrics.

The final part, their strategic ability, is the toughest to determine from just one meeting. Normally this comes out over time. I already have defined that the purpose of strategy is to win. If you find a banker that can help you win more often and by bigger margins, then you have found someone worth their fees. The first thing you need as a start is that they have to look at your business and start giving suggestions. Could be a suggestion on recapitalizing your company. Could be intel on what the competition is up to. Maybe how to reposition yourself with your investor base. The idea is some value added advice that. Comes from them and. shows their understanding of your business and how it is positioned in the marketplace. I have found that the average banker I work with to be quite smart, And the more experienced and business savvy ones can give you very good advice.

Fees

Fees are always negotiable to a certain point. If there is push back on banking fees, you can often tackle it another way via professional fees like the lawyers and accountants. Your lawyers and accountants can tell you what is usual and standard. Do not be afraid to push back here. There is a risk that if you push the fee too low the desk and sales people may not be too excited to sell your deal, but normally only the hugest deals get the very low fees. You can move part of the fee into a success or bonus fee payable at your discretion for over performance.

This isn’t an area to ignore as they can add up, but better performance can give you much better terms than expected and will save a lot more than a small fee reduction up front. Of course, the fee reduction is guaranteed and the extra performance is not, but you do want a motivated banking team.

Indicative Ranges

When a banker is pitching a deal to you, they can be a little too aggressive on the terms they say they can close a deal at. I have seen interest rates quoted well below the last few deals for similar companies quoted to me. Some think that once they have won your business and you are committed and on the road with them, they can always talk you up and blame market conditions. You are somewhat trapped and exposed once you start a deal process. This is where pushing the fee down and making some contingent on performance helps. If they start waffling on their indicative terms once you put some of their fees at risk, you know they are not as sure as they claim. You can always ask them what rate they would backstop the deal at or if they are willing to make it a bought deal and they take the risk or reward of the marketing. This is an area where getting several different banks pitching gives you a much better read on the market.

You need to trust your banker and believe that he is honest if you are going to be happy working with them. Their honesty about indicative ranges is a good touch point. No one can really guarantee what the market will be when the deal is launched, but over promising is dangerous to you. Someone that is not scared but who properly prepares you before a deal launches is very important. Fund raising is very much your responsibility as CFO and delivering a good deal reflects well on you. You need a banker that is a reliable team member.

A few final items

I have been out at events where several CFO’s are being taken to dinner. I find it quite questionable that some take the opportunity to order the most expensive bottle of wine. As much as you will see stories from the books I linked below about the excesses of Wall Street, the real crazy days are way behind us. You don’t want your banker to take advantage of you, so give him the same respect and courtesy. This may be someone you build up a relationship that spans years and maybe they are the one that give you the recommendation that gives you a board seat later in your career.

If you borrow staff and get additional support over time, remember that and try and steer business their way. If they do well, recommend them to other business contacts. They can be very helpful to you personally and can make a big difference in your career prospects, and it is much easier to work with people you respect. Don’t forget their lower level staff that work on your deals. Far too often the celebration at the end forgets your staff and the banking associates. Try to make sure that they get included. If not appropriate for the formal closing dinner, have the junior bankers take your junior staff out.

Finally, don’t get too caught up in the anti-banking media hype. There are plenty of good bankers out there that really care a out their clients. Be careful, remember that they are probably smarter than you with much more resources than you can bring to bear, but buil the right mutually beneficial relationship.

Books and Movies (I have read or seen these myself)

The Culture of Bankers

Liar’s Poker

Liar’s Poker (Norton Paperback)

Liar’s Poker (25th Anniversary Edition): Rising Through the Wreckage on Wall Street (25th Anniversary Edition) Kindle

The Big Short

The Big Short: Inside the Doomsday Machine

Bankers Behaving Badly

Straight to Hell

Straight to Hell: True Tales of Deviance, Debauchery, and Billion-Dollar Deals

Wolf of Wall Street

The Wolf of Wall Street

The Wolf of Wall Street (Blu-ray + DVD + Digital HD)

The Buy Side

The Buy Side: A Wall Street Trader’s Tale of Spectacular Excess

The Industry

Too Big to Fail

Too Big to Fail: The Inside Story of How Wall Street and Washington Fought to Save the Financial System–and Themselves

The Bankers’ New Clothes

The Bankers’ New Clothes: What’s Wrong with Banking and What to Do about It

Selling Put Options for Income

By

On January 12, 2016

In Finance, Investing

One evening after fighter practice while we were enjoying a beer at “church”, Patrick and I were discussing income from investments.  I talked about my “selling puts” strategy, and promised him I would explain it in more detail.  I figured why not explain it here so more can benefit and comment.

I will start by saying that using options is by definition using leverage.  One option represents 100 shares. As such, gains and losses are magnified.  As well, options create “ordinary income” and you will be taxed at your full income tax rate for the gains you make (unless you do this in a 401(k) or IRA account).  This is USA tax advice, obviously varies by country.

To do the strategy I will describe, you need to have basic option functionality for your account and available margin.  Brokerage fees/commissions tend to be higher than stock transactions.

First, here are some base statistics for options.  There is an erroneous statistic that is quoted that 90% of options expire worthless.  That is actually false.  10% are exercised.  That does not mean that 90% expire worthless.

10% are exercised (in the money at expiration date, seller could have made a gain or loss)

55%-60% are closed out before expiration (could be at a gain or loss)

30-35% expired worthless (seller makes 100% gain if held to expiration)

So the ratio is still 3-1 for exercised compared to expired worthless, but the 90% “internet truth” is wrong.

I would hope before anyone trades in options that you have a basic understanding of them, but here is a simple explanation.

An option is a right to buy (call) or sell (put) a stock at a certain price (strike price) before a certain time (expiration date).  “American” style options can be exercised at any time.  Selling an option is going short the option (you hope the option goes down in price).  Buying an option is going long an option (you hope that an option goes up in value).  When you buy an option, maximum loss is your investment.  When you sell an option, you can lose much more than the price you receive.

Options have two components of value – actual value which is the actual price of the underlying security less the strike price of the option and time value which is the trading price of the option less the actual value of the option.  Time value is a complex relationship between the volatility of the underlying stock and the actual remaining time.  Valuing options is typically done via a Black-Scholes model (there are even more modern valuation methods) and there are a huge number of firms that specialize in trading differences between the market value of options and the valuation model.  In general, if you trade liquid options on stocks with good value, then the market price tends to revert to the model price because of the automated buyers and sellers.

That was a pretty long intro.  There is just too much background information on options that I could explain, but that should cover the basics.  Here is a book that can help.  I prefer Options as a Strategic Investment, but it is way more expensive.

http://www.amazon.com/Understanding-Options-2E-Michael-Sincere/dp/0071817840/ref=pd_sim_14_2?ie=UTF8&dpID=51q5Y48G6JL&dpSrc=sims&preST=_AC_UL160_SR105%2C160_&refRID=0EYQMNRN4D2J8J79SE4S

My strategy is to sell slightly out of the money Put contracts with a fairly short time to expiration date.  This a bullish to neutral strategy as you hope the stock stays the same price or goes up (or goes down less than the “slightly out of the money gap”).

Breaking it down, you need to do the following:

  • Pick a stock
  • Pick the time you want the option to be outstanding
  • Pick the strike price of the option

You also need sufficient margin in your account to support the trade.

My strategy has two built in flaws. Because you use shorter duration contracts, you will do more transactions in a year and incur higher commission expenses. Because I tend to use shorter time durations (one month to one week), there is less “time value” available.

The other basic flaw is that you can make a lot of small wins and then lose all of in in one trade if the stock moves much larger than expected downwards.  I try and reduce this risk by carefully selecting when the trade will happen, but this is the basic downside to any options trade.

  • Picking the stock

This is a leveraged, short time duration strategy. It has a slightly bullish orientation. So you need to select a stock that you have some confidence that it will at least be stable in the period you choose and it probably should be a stock that you understand well and that you would be comfortable owning. However, this is not my other selling puts strategy (backing into owning a stock that you like but is too expensive).  This is an income generating strategy.

One potential source for a stock to pick is the S&P Platinum Portfolio.  It is S&P’s “best of the best” list.  The list is not perfect, of course, but it does have a very long track record of good performance versus the market.

You can also pick an index or an ETF that tracks an index.  Many stable stocks track the market in the short term anyways, so the overall market is as good a choice as any.

Finally, you want a stock that trades pretty often and has a lot of option trades.  Otherwise spreads are quite wide and it is hard to enter into and close trades.

I personally pick AT&T.  I own the stock, follow it pretty closely, it trades a lot and options are liquid, in a disaster it pays a good dividend anyways, and it is completely a USA business so less need to worry about something happening overseas.  It is pretty stable overall so there is less time value premium.

For purposes of this example, I will also look at Apple and SPY (Vanguard S&P 500 tracking ETF).  I have included the option chains (from TD Ameritrade)  from the day I am typing this plus the current stock price and the last three months of historical prices (Yahoo Finance is great to get those).

I could be a smarter blogger and put all these tables at the end of the blog, but this is actually important. If you want to follow this type of strategy, you need to spend some time studying this type of information to get comfortable with it. If you don’t spend the time, I recommend the don’t pass line at the nearest casino with reasonable craps rules. After options commissions, “trading” without knowledge and a plan is probably not as good as the odds at the don’t pass line.

T 5 days until expiration ($33.51)

Puts  Bid Ask Last Change Vol Op Int
32.5 Put 0.04 0.05 0.04 0.00 0 626
33.0 Put 0.09 0.10 0.08 0.00 0 1,844
33.5 Put 0.22 0.23 0.20 0.00 0 1,643
34.0 Put 0.50 0.55 0.46 0.00 0 510
34.5 Put 0.78 1.02 0.89 0.00 0 126
35.0 Put 1.24 1.51 — 0.00 0 0

 

T 26 days until expiration ($33.51)

Puts  Bid Ask Last Change Vol Op Int
32.5 Put 0.17 0.20 0.17 0.00 0 3,432
33.0 Put 0.27 0.31 0.29 0.00 0 412
33.5 Put 0.45 0.49 0.43 0.00 0 516
34.0 Put 0.71 0.75 0.67 0.00 0 302
34.5 Put 1.00 1.10 0.88 0.00 0 36
35.0 Put 1.29 1.54 1.49 0.00 0 6

 

AAPL  5 days until expiration ($119.5)

Puts  Bid Ask Last Change Vol Op Int
117.0 Put 0.66 0.68 0.66 0.00 7,894 2,084
118.0 Put 0.97 1.00 0.98 0.01 6,267 3,274
119.0 Put 1.41 1.43 1.43 0.04 5,965 2,766
120.0 Put 1.92 1.98 1.92 0.00 11,584 3,860
121.0 Put 2.58 2.65 2.53 -0.05 4,205 1,327
122.0 Put 3.35 3.45 3.30 -0.05 1,158 593

 

AAPl  26 days until expiration ($119.5)

Puts  Bid Ask Last Change Vol Op Int
117.0 Put 2.06 2.12 2.06 0.00 128 426
118.0 Put 2.45 2.50 2.41 -0.03 41 135
119.0 Put 2.89 2.95 2.70 -0.19 109 92
120.0 Put 3.35 3.50 3.20 -0.15 113 137
121.0 Put 3.90 4.00 3.39 -0.51 33 86
122.0 Put 4.55 4.65 4.32 -0.23 43 58

 

SPY 5 days until expiration ($207.93)

Puts  Bid Ask Last Change Vol Op Int
206.5 Put 0.89 0.97 0.93 -0.04 9,073 11,100
207.0 Put 1.08 1.12 1.09 -0.03 18,145 15,832
207.5 Put 1.21 1.29 1.29 -0.01 7,246 5,922
208.0 Put 1.43 1.48 1.46 0.01 32,493 8,987
208.5 Put 1.61 1.70 1.77 0.07 14,330 5,232
208.8 Put 1.14 1.85 1.10 -0.73 0 56

 

SPY 26 days until expiration ($207.93)

Puts  Bid Ask Last Change Vol Op Int
206.5 Put 2.33 2.43 2.27 -0.06 314 1,680
207.0 Put 2.49 2.60 2.28 -0.21 116 1,394
207.5 Put 2.67 2.78 2.44 -0.23 303 514
208.0 Put 2.85 2.94 2.91 0.00 650 2,264
208.5 Put 3.05 3.18 3.25 0.07 370 307
208.8 Put — — 3.10 -0.15 10 41

 

T historical prices

Date Open High Low Close Volume Adj Close*
Oct 30, 2015 33.62 33.75 33.51 33.51 24,420,900 33.51
Oct 29, 2015 33.48 33.67 33.28 33.55 17,746,000 33.55
Oct 28, 2015 33.36 33.60 33.13 33.42 27,780,400 33.42
Oct 27, 2015 33.57 33.61 33.16 33.21 24,356,700 33.21
Oct 26, 2015 33.75 33.76 33.48 33.66 25,400,300 33.66
Oct 23, 2015 34.70 34.74 33.62 33.74 46,213,200 33.74
Oct 22, 2015 33.46 34.16 33.46 33.96 32,707,100 33.96
Oct 21, 2015 33.88 33.94 33.33 33.60 27,215,000 33.60
Oct 20, 2015 33.59 33.85 33.52 33.75 20,014,100 33.75
Oct 19, 2015 33.63 33.69 33.42 33.63 27,757,500 33.63
Oct 16, 2015 33.75 33.86 33.54 33.83 32,868,400 33.83
Oct 15, 2015 33.33 33.50 33.20 33.49 18,564,200 33.49
Oct 14, 2015 33.23 33.39 33.10 33.27 23,282,700 33.27
Oct 13, 2015 33.19 33.29 33.06 33.22 22,063,400 33.22
Oct 12, 2015 33.20 33.31 33.07 33.30 14,109,800 33.30
Oct 9, 2015 33.42 33.52 33.00 33.14 19,351,300 33.14
Oct 8, 2015 33.11 33.41 32.87 33.40 17,305,200 33.40
Oct 7, 2015 33.07 33.34 33.01 33.12 21,010,300 33.12
Oct 7, 2015 0.47 Dividend
Oct 6, 2015 33.50 33.52 33.25 33.31 27,867,000 32.84
Oct 5, 2015 32.98 33.49 32.97 33.43 27,876,700 32.96
Oct 2, 2015 32.34 32.64 32.19 32.64 28,505,900 32.18
Oct 1, 2015 32.48 32.64 32.17 32.53 30,815,500 32.07
Sep 30, 2015 32.36 32.71 32.24 32.58 34,815,500 32.12
Sep 29, 2015 31.99 32.18 31.85 32.07 33,785,200 31.62
Sep 28, 2015 32.26 32.34 31.88 31.90 35,924,900 31.45
Sep 25, 2015 32.27 32.70 32.16 32.33 27,104,200 31.87
Sep 24, 2015 32.02 32.23 31.95 32.11 24,741,400 31.66
Sep 23, 2015 32.29 32.34 32.04 32.20 15,739,200 31.75
Sep 22, 2015 32.32 32.45 32.13 32.27 25,518,700 31.81
Sep 21, 2015 32.55 32.69 32.45 32.56 19,870,300 32.10
Sep 18, 2015 32.68 32.79 32.41 32.55 44,627,200 32.09
Sep 17, 2015 32.73 33.14 32.41 32.78 37,922,100 32.32
Sep 16, 2015 32.86 33.10 32.76 32.94 23,514,200 32.48
Sep 15, 2015 32.68 32.93 32.54 32.86 22,371,700 32.40
Sep 14, 2015 32.74 32.78 32.51 32.55 18,504,700 32.09
Sep 11, 2015 32.73 32.78 32.56 32.72 17,626,900 32.26
Sep 10, 2015 32.77 32.84 32.55 32.75 25,602,300 32.29
Sep 9, 2015 33.40 33.50 32.72 32.78 22,559,100 32.32
Sep 8, 2015 32.95 33.19 32.81 33.14 18,851,000 32.67
Sep 4, 2015 32.68 32.78 32.35 32.56 29,318,900 32.10
Sep 3, 2015 32.97 33.24 32.92 33.04 22,833,400 32.57
Sep 2, 2015 32.97 32.97 32.50 32.82 24,093,000 32.36
Sep 1, 2015 32.60 32.79 32.16 32.32 33,048,000 31.86
Aug 31, 2015 33.20 33.28 33.01 33.20 22,286,500 32.73
Aug 28, 2015 33.34 33.45 33.10 33.29 24,154,000 32.82
Aug 27, 2015 33.01 33.49 32.82 33.44 42,589,900 32.97
Aug 26, 2015 32.36 32.85 32.01 32.69 49,631,200 32.23
Aug 25, 2015 33.11 33.11 31.77 31.80 50,674,200 31.35
Aug 24, 2015 32.18 32.69 30.97 32.37 77,231,300 31.91
Aug 21, 2015 33.70 33.95 33.38 33.38 41,636,700 32.91
Aug 20, 2015 34.17 34.46 33.95 33.95 38,363,400 33.47
Aug 19, 2015 34.30 34.50 34.07 34.36 21,139,300 33.88
Aug 18, 2015 34.16 34.43 34.12 34.35 20,538,200 33.87
Aug 17, 2015 33.96 34.23 33.90 34.23 21,050,600 33.75
Aug 14, 2015 33.91 34.05 33.78 34.05 22,759,600 33.57
Aug 13, 2015 34.01 34.17 33.79 33.81 35,521,100 33.33
Aug 12, 2015 33.86 34.07 33.45 34.02 61,974,500 33.54
Aug 11, 2015 34.60 34.96 34.57 34.65 35,402,700 34.16
Aug 10, 2015 34.30 34.78 34.20 34.78 29,179,800 34.29
Aug 7, 2015 34.11 34.26 34.04 34.21 25,627,600 33.73
Aug 6, 2015 34.55 34.59 33.95 34.24 32,734,200 33.76
Aug 5, 2015 34.79 34.83 34.51 34.57 22,837,600 34.08
Aug 4, 2015 34.79 34.80 34.50 34.58 26,249,900 34.09
Aug 3, 2015 34.95 35.02 34.50 34.66 29,677,600 34.17
Jul 31, 2015 34.94 34.99 34.72 34.74 29,880,900 34.25
Jul 30, 2015 34.86 34.89 34.68 34.80 25,958,800 34.31

 

AAPL historical prices

Date Open High Low Close Volume Adj Close*
Oct 30, 2015 120.99 121.22 119.45 119.50 48,812,000 119.50
Oct 29, 2015 118.70 120.69 118.27 120.53 50,240,800 120.53
Oct 28, 2015 116.93 119.30 116.06 119.27 85,023,300 119.27
Oct 27, 2015 115.40 116.54 113.99 114.55 57,953,600 114.55
Oct 26, 2015 118.08 118.13 114.92 115.28 66,019,500 115.28
Oct 23, 2015 116.70 119.23 116.33 119.08 59,139,600 119.08
Oct 22, 2015 114.33 115.50 114.10 115.50 41,272,700 115.50
Oct 21, 2015 114.00 115.58 113.70 113.76 41,795,200 113.76
Oct 20, 2015 111.34 114.17 110.82 113.77 48,778,800 113.77
Oct 19, 2015 110.80 111.75 110.11 111.73 29,606,100 111.73
Oct 16, 2015 111.78 112.00 110.53 111.04 38,236,300 111.04
Oct 15, 2015 110.93 112.10 110.49 111.86 37,341,000 111.86
Oct 14, 2015 111.29 111.52 109.56 110.21 44,325,600 110.21
Oct 13, 2015 110.82 112.45 110.68 111.79 32,424,000 111.79
Oct 12, 2015 112.73 112.75 111.44 111.60 30,114,400 111.60
Oct 9, 2015 110.00 112.28 109.49 112.12 52,533,800 112.12
Oct 8, 2015 110.19 110.19 108.21 109.50 61,698,500 109.50
Oct 7, 2015 111.74 111.77 109.41 110.78 46,602,600 110.78
Oct 6, 2015 110.63 111.74 109.77 111.31 48,196,800 111.31
Oct 5, 2015 109.88 111.37 109.07 110.78 51,723,100 110.78
Oct 2, 2015 108.01 111.01 107.55 110.38 57,560,400 110.38
Oct 1, 2015 109.07 109.62 107.31 109.58 63,748,000 109.58
Sep 30, 2015 110.17 111.54 108.73 110.30 66,105,000 110.30
Sep 29, 2015 112.83 113.51 107.86 109.06 73,135,900 109.06
Sep 28, 2015 113.85 114.57 112.44 112.44 51,723,900 112.44
Sep 25, 2015 116.44 116.69 114.02 114.71 55,842,200 114.71
Sep 24, 2015 113.25 115.50 112.37 115.00 49,810,600 115.00
Sep 23, 2015 113.63 114.72 113.30 114.32 35,645,700 114.32
Sep 22, 2015 113.38 114.18 112.52 113.40 49,809,000 113.40
Sep 21, 2015 113.67 115.37 113.66 115.21 46,554,300 115.21
Sep 18, 2015 112.21 114.30 111.87 113.45 73,419,000 113.45
Sep 17, 2015 115.66 116.49 113.72 113.92 63,462,700 113.92
Sep 16, 2015 116.25 116.54 115.44 116.41 36,910,000 116.41
Sep 15, 2015 115.93 116.53 114.42 116.28 43,004,100 116.28
Sep 14, 2015 116.58 116.89 114.86 115.31 58,201,900 115.31
Sep 11, 2015 111.79 114.21 111.76 114.21 49,441,800 114.21
Sep 10, 2015 110.27 113.28 109.90 112.57 62,675,200 112.57
Sep 9, 2015 113.76 114.02 109.77 110.15 84,344,400 110.15
Sep 8, 2015 111.75 112.56 110.32 112.31 54,114,200 112.31
Sep 4, 2015 108.97 110.45 108.51 109.27 49,963,900 109.27
Sep 3, 2015 112.49 112.78 110.04 110.37 52,906,400 110.37
Sep 2, 2015 110.23 112.34 109.13 112.34 61,888,800 112.34
Sep 1, 2015 110.15 111.88 107.36 107.72 76,845,900 107.72
Aug 31, 2015 112.03 114.53 112.00 112.76 56,229,300 112.76
Aug 28, 2015 112.17 113.31 111.54 113.29 53,164,400 113.29
Aug 27, 2015 112.23 113.24 110.02 112.92 84,616,100 112.92
Aug 26, 2015 107.09 109.89 105.05 109.69 96,774,600 109.69
Aug 25, 2015 111.11 111.11 103.50 103.74 103,601,600 103.74
Aug 24, 2015 94.87 108.80 92.00 103.12 162,206,300 103.12
Aug 21, 2015 110.43 111.90 105.65 105.76 128,275,500 105.76
Aug 20, 2015 114.08 114.35 111.63 112.65 68,501,600 112.65
Aug 19, 2015 116.10 116.52 114.68 115.01 47,445,700 115.01
Aug 18, 2015 116.43 117.44 116.01 116.50 34,560,700 116.50
Aug 17, 2015 116.04 117.65 115.50 117.16 40,884,700 117.16
Aug 14, 2015 114.32 116.31 114.01 115.96 42,929,500 115.96
Aug 13, 2015 116.04 116.40 114.54 115.15 48,535,800 115.15
Aug 12, 2015 112.53 115.42 109.63 115.24 101,217,500 115.24
Aug 11, 2015 117.81 118.18 113.33 113.49 97,082,800 113.49
Aug 10, 2015 116.53 119.99 116.53 119.72 54,951,600 119.72
Aug 7, 2015 114.58 116.25 114.50 115.52 38,670,400 115.52
Aug 6, 2015 115.97 116.50 114.12 115.13 52,903,000 115.13
Aug 6, 2015 0.52 Dividend
Aug 5, 2015 112.95 117.44 112.10 115.40 99,312,600 114.88
Aug 4, 2015 117.42 117.70 113.25 114.64 124,138,600 114.12
Aug 3, 2015 121.50 122.57 117.52 118.44 69,976,000 117.91
Jul 31, 2015 122.60 122.64 120.91 121.30 42,885,000 120.75
Jul 30, 2015 122.32 122.57 121.71 122.37 33,628,300 121.82

 

SPY historical prices

Date Open High Low Close Volume Adj Close*
Oct 30, 2015 209.06 209.44 207.74 207.87 125,338,300 207.87
Oct 29, 2015 208.35 209.27 208.21 208.89 84,727,800 208.89
Oct 28, 2015 207.00 208.98 206.21 208.94 132,528,000 208.94
Oct 27, 2015 206.20 207.00 205.79 206.57 74,930,600 206.57
Oct 26, 2015 207.30 207.37 206.56 206.99 66,254,500 206.99
Oct 23, 2015 207.25 207.95 206.30 207.52 138,355,700 207.52
Oct 22, 2015 202.98 205.51 201.85 205.21 164,941,500 205.21
Oct 21, 2015 203.61 203.79 201.65 201.87 99,149,500 201.87
Oct 20, 2015 202.85 203.84 202.55 203.09 75,598,000 203.09
Oct 19, 2015 202.50 203.37 202.13 203.32 73,106,800 203.32
Oct 16, 2015 202.83 203.29 201.92 203.27 109,692,900 203.27
Oct 15, 2015 200.08 202.36 199.64 202.29 125,812,600 202.29
Oct 14, 2015 200.18 200.87 198.94 199.30 95,532,400 199.30
Oct 13, 2015 200.65 202.16 200.05 200.18 83,578,000 200.18
Oct 12, 2015 201.42 201.76 200.91 201.59 55,425,200 201.59
Oct 9, 2015 201.38 201.90 200.58 201.40 94,899,000 201.40
Oct 8, 2015 199.41 201.55 198.59 201.20 148,387,100 201.20
Oct 7, 2015 198.90 199.83 197.48 199.43 120,246,700 199.43
Oct 6, 2015 198.31 198.98 197.00 197.81 106,144,200 197.81
Oct 5, 2015 196.46 198.74 196.33 198.48 122,213,200 198.48
Oct 2, 2015 189.77 195.03 189.12 194.99 206,129,500 194.99
Oct 1, 2015 192.08 192.49 189.82 192.16 127,828,700 192.16
Sep 30, 2015 190.37 191.83 189.44 191.59 152,593,200 191.59
Sep 29, 2015 188.27 189.74 186.93 188.08 152,279,900 188.08
Sep 28, 2015 191.78 191.91 187.64 187.91 158,514,500 187.91
Sep 25, 2015 194.64 195.00 191.81 192.87 142,052,900 192.87
Sep 24, 2015 192.15 193.45 190.56 192.93 159,378,800 192.93
Sep 23, 2015 194.11 194.67 192.91 193.60 92,790,600 193.60
Sep 22, 2015 193.88 194.46 192.56 193.90 153,890,900 193.90
Sep 21, 2015 196.44 197.68 195.21 196.44 105,726,200 196.44
Sep 18, 2015 195.71 198.68 194.96 195.36 223,657,500 195.36
Sep 18, 2015 1.033 Dividend
Sep 17, 2015 200.02 202.89 199.28 199.70 276,046,600 198.67
Sep 16, 2015 198.82 200.41 198.41 200.14 99,581,600 199.10
Sep 15, 2015 196.61 198.99 195.96 198.45 113,806,200 197.42
Sep 14, 2015 196.95 197.01 195.43 195.98 79,452,000 194.97
Sep 11, 2015 195.38 196.82 194.53 196.81 119,691,200 195.79
Sep 10, 2015 194.56 197.22 194.25 195.85 158,611,100 194.84
Sep 9, 2015 199.32 199.47 194.35 194.76 149,347,700 193.75
Sep 8, 2015 195.94 197.61 195.17 197.46 116,025,700 196.44
Sep 4, 2015 192.85 193.86 191.61 192.59 207,081,000 191.59
Sep 3, 2015 196.26 198.05 194.96 195.65 152,087,800 194.64
Sep 2, 2015 194.62 195.46 191.77 195.36 160,269,300 194.35
Sep 1, 2015 193.12 194.77 190.73 191.92 256,000,400 190.93
Aug 31, 2015 198.11 199.13 197.01 197.54 163,298,800 196.52
Aug 28, 2015 198.50 199.84 197.92 199.24 160,414,400 198.21
Aug 27, 2015 197.02 199.42 195.21 199.16 274,143,900 198.13
Aug 26, 2015 192.08 194.79 188.37 194.68 339,257,000 193.67
Aug 25, 2015 195.43 195.45 186.92 187.23 369,833,100 186.26
Aug 24, 2015 197.63 197.63 182.40 189.55 507,244,300 188.57
Aug 21, 2015 201.73 203.94 197.52 197.63 346,588,500 196.61
Aug 20, 2015 206.51 208.29 203.90 204.01 194,327,900 202.95
Aug 19, 2015 209.09 210.01 207.35 208.28 167,316,300 207.20
Aug 18, 2015 210.26 210.68 209.70 209.93 71,692,700 208.84
Aug 17, 2015 208.71 210.59 208.16 210.56 79,072,600 209.47
Aug 14, 2015 208.43 209.51 208.26 209.36 72,786,500 208.28
Aug 13, 2015 208.73 209.55 208.01 208.70 89,383,300 207.62
Aug 12, 2015 207.11 209.14 205.36 208.83 168,996,000 207.75
Aug 11, 2015 208.97 209.47 207.76 208.66 126,081,400 207.58
Aug 10, 2015 209.28 210.67 209.28 210.63 80,270,700 209.54
Aug 7, 2015 208.16 208.34 206.87 207.92 117,858,000 206.84
Aug 6, 2015 210.29 210.42 207.65 208.35 116,030,800 207.27
Aug 5, 2015 210.45 211.31 209.73 210.10 85,786,800 209.01
Aug 4, 2015 209.70 210.25 208.80 209.32 81,820,800 208.24
Aug 3, 2015 210.46 210.53 208.65 209.73 113,965,700 208.65
Jul 31, 2015 211.42 211.45 210.16 210.45 103,266,900 209.36
Jul 30, 2015 210.16 211.02 209.42 210.82 91,304,400 209.73

 

That was a lot of numbers ….

You should be looking over the numbers for ranges that have happened in the prior year in one month and one week buckets.  Of course, past performance does not guarantee future performance, but it often gives you a good clue.

What is my conclusion?  Apple seems to swing around a lot more than the options premium would justify. I don’t think just out of the money puts make sense, you would have to go to much more out of the money options to balance the risk of the stock movements.  The stock trades high volume and the options and pretty liquid as well. If you are a big Apple fan and follow them closely, it might work.

AT&T moves in a much tighter range in weekly and monthly buckets. Premiums are small but volatility is small as well.  This is the stock that I use to trade my strategy. Because the weekly profits are small, it is harder to recover if there is a week where the trade swings against you. The main advantage for me is that it pays a good dividend so if I cannot close a trade and get put I do not mind owning the stock.

SPY is also good. Much more of a swing than AT&T as the general market had some large up and down days in the period being reviewed. This is instructive as it reminds you that you can have a quick and bad day at any time. Stops help some but do not help much when there is a flash crash. That is why it is important to pick a stock that I you are put you do not mind owning.

So three stocks and any of the three could work, it depends on your personality and emotional ability to handle price changes.  You cannot make money every week or month, you need to accept and cut losses and roll over to the next period. Over time, with the right focus, you should be able to make a profit more often than you make losses (which tend to be fewer but larger).

  • Pick the period

The longer the period you pick, the more time value you receive and the more time for a temporary change in trading to revert back to the expected pattern.  However, it also is more time for the entire market to change direction or some external event to change a stock price (of course, longer dated options do give more time to recover).

I have traded one month, two month and one week options with this strategy. All worked.  For AT&T I prefer 1 week options, but 1 month work well too. When I tried Apple, I tried 2 month options as the stock was up and down more but the overall trend was flat to up so the longer term options gave more time for the strategy to work.  I found the price swings too much and there was too much non-company news that moved the stock and too many “event” days so I stopped trying to use this trade with Apple.

The other very important strategy is to avoid “story” weeks. When a stock goes ex-dividend the stock often reacts more than just the dividend. Earnings releases should also be avoided with this strategy. There is extra volatility those weeks which are good for options pricing, but they are also weeks that do not follow the pattern and the trading that you are attempting. They can be traded, but not via the strategy I am explaining here. Avoid them.

  • Pick the option

You want options that are out of the money so if the stock is flat through your period the trade works. That allows for upwards or flat movement to be a winner. You need to look at typical stock moves for the stock you picked and make sure the average down move will not cause such a large loss that it wipes out the gains you had made before.

For AT&T I have been trading weekly options and the option closest to the actual share price that is in the money. For monthly options I pick options that are deeper in the money but still give me more return than the weekly options.  For AT&T I switched to weekly options mainly because the premiums for deeper in the money longer term options did not give me the return I wanted considering the extra time used for each trade.

My results

I trade 30 AT&T options a week for about $400 – $500 a week of option premium. That is about $24K to $26K of potential income.  I have averaged $20K a year for the last several years doing it. If you get put you need about $100K to buy the shares (margin). I can trade a lot more options but my schedule often means I cannot monitor the price all day (especially when I am in China) so I am often “naked” on the close day and just need to accept being put because the stock is too close to close the trade.

Most people that do not trade on margin have enough margin available for this strategy and you can make much more than the smaller number I said above.

Options as a Strategic Investment

 

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