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Joined July 2019
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Hey guys! I’ve just released a refined, compact edition of one of my newsletter series on the foundations of quantitative trading. It is a theoretical introduction designed for aspiring quants who are beginning to explore the field. The focus is on first principles, method, and the conceptual framework behind quantitative trading.
Link in the comments. I hope you enjoy it.
It wouldn’t be the first time... you’re conducting a review with your team, and even though everyone has read the same paper, it’s as if you’re all talking about different trading systems.
View regained Nasdaq minimum-bid compliance as a delisting de-risking event. In this case, the setup has edge when compliance follows an extended deficiency period and aligns with stabilizing fundamentals like cash runway, margins, top-line trends, or financing terms. Gauge how much listing-risk discount remains baked into the price, and confirm the stock can sustain the threshold through market demand.
Measure amendment frequency, severity, recurrence of the same accounting topic, and whether corrections affect revenue, earnings, cash flow, share count, or internal controls. The warning becomes stronger when amendments cluster in time and coincide with restatements, delayed filings, or control weaknesses. Use it primarily as a long-avoidance filter, then short only when market behavior begins confirming reporting-risk deterioration.
The Standard and Long-horizon tasks arent matched versions of the same problem. They can differ in parameters, conditions, and required outputs. There is also a distinction between two meanings of horizon:
-Solving a chain of dependent calculations when the scenario is given upfront.
-Maintaining accurate state as new information arrives over separate interaction.
Measure amendment frequency, severity, recurrence of the same accounting topic, and whether corrections affect revenue, earnings, cash flow, share count, or internal controls. The warning becomes stronger when amendments cluster in time and coincide with restatements, delayed filings, or control weaknesses. Use it primarily as a long-avoidance filter, then short only when market behavior begins confirming reporting-risk deterioration.
I’m researching subscription businesses where deferred revenue expands because customers are renewing and prepaying. Check organic deferred-revenue growth with stable churn, improving retention, and healthy cash conversion. The setup happens when deferred revenue accelerates before recognized revenue. Go long only when the implied future-revenue gap is large and price begins confirming the improvement.
The paper’s differentiation criteria discourage a flat tariff structure, so this is more nuanced than observing that a constant model would be stable
Long time without seeing this conditions probability formula. I think I should re-edit all the proba series
I’m researching subscription businesses where deferred revenue expands because customers are renewing and prepaying. Check organic deferred-revenue growth with stable churn, improving retention, and healthy cash conversion. The setup happens when deferred revenue accelerates before recognized revenue. Go long only when the implied future-revenue gap is large and price begins confirming the improvement.
It's pretty common for some SaaS companies to expand their RPO before revenue accelerates. For example, RPO captures contracted future revenue, so persistent RPO growth combined with stable conversion can reveal demand strength that hasn’t yet appeared in the income statement. The setup occurs when current RPO growth, total RPO growth, and deferred revenue all improve while cancellations remain low. Go long only when the implied forward-revenue gap is large and price begins confirming the expected re-rating.
The study separates wallet scoring, model fitting, and evaluation chronologically. However, the authors disclose that the top-decile focus, volatility scaling, and evaluation-window choice were selected after results were available.
It's pretty common for some SaaS companies to expand their RPO before revenue accelerates. For example, RPO captures contracted future revenue, so persistent RPO growth combined with stable conversion can reveal demand strength that hasn’t yet appeared in the income statement. The setup occurs when current RPO growth, total RPO growth, and deferred revenue all improve while cancellations remain low. Go long only when the implied forward-revenue gap is large and price begins confirming the expected re-rating.
Identify industrial or software companies where bookings growth turns higher before reported revenue responds. Then, measure the gap between new bookings, and current revenue growth to estimate how much future sales acceleration is already embedded in contracted demand. The long setup happens when bookings quality is high, cancellations remain low, and the bookings-to-revenue ratio expands while reported growth is still muted.
PBO is 0.85, this indicates that the in-sample winning configuration is very likely to rank poorly out of sample under the study's cross-validation procedure.
