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On the Agenda – December 22, 2019 Update

As you can see, I’ve posted many more articles on gamma exposure and repo operations. My goal is to continue to build out these topics and address more questions that you have on these subjects. (Let me know questions you have along the way and I will address them in future articles.)

I also plan to write more about Python for finance, and how I use it day-to-day to help facilitate my trading.

Stay tuned.


How to write trading rules

Do something.

Realize, oh shit I shouldn’t have done that.

Write down what you shouldn’t do.

Result: new trading rule.

Tip: Study those things that have ruined those who have come before you. Better to understand someone else’s big blunder to avoid one happening to yourself.

Who and What are primary dealers?

Primary dealers are trading counterparties of the New York Fed in the implementation of monetary policy. The make markets for the NY Fed as needed, and bid on a pro-rate basis in all Treasury auctions at reasonably competitive prices.

There are 24 banks designated as primary dealers. Well known banks that are primary dealers include JP Morgan, Wells Fargo, Bank of America, Citi Group, Deutsche Bank, just to name a few.

Why do we have primary dealers?

Primary dealers are counterparties who buy government securities and resell them to the overall market. These are banks that have an inside track to buy US Treasuries.

Primary dealers purchase the vast majority of the U.S. Treasury securities (T-bills, T-notes, and T-bonds) sold at auction. They will then resell those securities to the public. Their activities extend well beyond the Treasury market.

Arguably, this group’s members are the most influential and powerful non-governmental institutions in global financial markets.

Where are primary dealers located?

Many dealers are in the US. There are also dealers across the globe, including Japan and Europe that distribute US Treasuries to those geographical areas of the world.

What are the requirements for primary dealers?

Firms must meet specific capital requirements before it can become a primary dealer.

The capital requirements for broker-dealers that are not affiliated with a bank is $50 million. Banks acting as primary dealers need to have $1 billion of Tier 1 capital (equity capital and disclosed reserves).

Prospective primary dealers need to show they made markets consistently in Treasuries for at least a year before their application.

Great Resources for Economics, Investing, and Programming

This post is a work-in-progress and will be updated frequently, so please bookmark this page so that you can refer to it often.


Youtube – How the Economic Machine Works by Ray Dalio

One of the best resources, along with Dalio’s book Principals for Navigating Big Debt Crisis, to help you understand how the economy functions on a larger scale. This video and book are better than any economics course I took in High School and College because they focus on what actually happens in the markets from a transactional perspective, and not from a theoretical, supply/demand curve perspective.

Economics 101 — “How the Economic Machine Works.”

Created by Ray Dalio this simple but not simplistic and easy to follow 30 minute, animated video answers the question, “How does the economy really work?” Based on Dalio’s practical template for understanding the economy, which he developed over the course of his career, the video breaks down economic concepts like credit, deficits and interest rates, allowing viewers to learn the basic driving forces behind the economy, how economic policies work and why economic cycles occur.

Book – Principals for Navigating Big Debt Crisis by Ray Dalio

big debt

Crucial for anyone looking to understand macroeconomics and to understand how the market works as one piece.

The template comes in three parts provided in three books: 1) The Archetypal Big Debt Cycle (which explains the template), 2) 3 Detailed Cases (which examines in depth the 2008 financial crisis, the 1930’s Great Depression, and the 1920’s inflationary depression of Germany’s Weimar Republic), and 3) Compendium of 48 Cases (which is a compendium of charts and brief descriptions of the worst debt crises of the last 100 years). Whether you’re an investor, a policy maker, or are simply interested, the unconventional perspective of one of the few people who navigated the crises successfully, Principles for Navigating Big Debt Crises will help you understand the economy and markets in revealing new ways.


The Black Swan by Nassim Nicholas Taleb


This book showed me how important it is to manage risk when investing and trading options. Nassim Taleb provides a unique insight into investing based off his years as an option trader in the pit.

The Black Swan is a standalone book in Nassim Nicholas Taleb’s landmark Incerto series, an investigation of opacity, luck, uncertainty, probability, human error, risk, and decision-making in a world we don’t understand. The other books in the series are Fooled by Randomness, Antifragile, Skin in the Game, and The Bed of Procrustes.

A black swan is a highly improbable event with three principal characteristics: It is unpredictable; it carries a massive impact; and, after the fact, we concoct an explanation that makes it appear less random, and more predictable, than it was. The astonishing success of Google was a black swan; so was 9/11. For Nassim Nicholas Taleb, black swans underlie almost everything about our world, from the rise of religions to events in our own personal lives.


Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems by Aurélien Géron


This book was one of the most useful books to me when I was learning more advanced programming concepts such as machine learning and deep learning. I used the first version of this book, and I know the second version is just as good with minor updates.

It is an absolute must that you use the resources made available by Géron on GitHub to learn this material. One of the most effective ways to learn programming for me was to input the code, tear it apart, understand why it was there, then try to recreate it myself.

Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.

By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started.

What are the options Greeks?

This article is part of a more broad series of research questions I address regarding Gamma Exposure. Check out this post for more.

Greeks refer to dimension of risk that an options position entails. The Greeks are used by options traders and portfolio managers to hedge different risks to their positions.

Is simple terms, the Greeks are derived based off a pricing model, like Black-Scholes, using inputs: option price, underlying stock price, days to expiration, and risk free interest rate.

The most commonly used Greeks used are Delta, Gamma, Theta, Vega.


Delta is the amount an option price is expected to move based on a $1 change in the underlying stock.

Calls always have positive delta, between 0 and 1. If the underlying stock price goes up and no other variables change, the price for the call will go up.

If a call has a delta of 0.50 and the stock goes up $1, the price of the call will go up about $.50. If the stock goes down $1, the price of the call will go down about $.50.

Puts always have a negative delta, between 0 and -1.


Gamma is the rate of change in delta for every $1 change in the stock price. If delta is the “speed” at which option prices change, you can think of gamma as the “acceleration.”

Options with the highest gamma are the most responsive to changes in the price of the underlying stock.

Gamma is highest for options with strike prices near the current underlying stock price. It is also highest for those options at the money that are closer to expiring vs. those options which are due to expire further out in the future.


Theta, aka time decay an option buyer’s biggest enemy, and option seller’s best friend. Theta is the amount the price of calls and puts will decrease theoretically for a one-day change in the time to expiration.

In the options market, the passage of time will erode an options value. Time value melts away and does so at an accelerated rate as expiration approaches.


Vega is the amount call and put prices will change, in theory, for a corresponding one-point change in implied volatility.

Vega does not have any effect on the intrinsic value of options, it only affects the “time value” of an option’s price.

Typically, as implied volatility increases, the value of options will increase. That’s because an increase in implied volatility suggests an increased range of potential movement for the stock.


If you’re trading options, you absolutely must understand those Greeks above and how they impact your trading strategies.

What is delta hedging? How does this influence option market makers’ gamma exposure?

This article is part of a more broad series of research questions I address regarding Gamma Exposure. Check out this post for more.

Market makers are exposed to risks in the market and continuously protect themselves against these risks. One way they they manage risk is by remaining delta neutral on their portfolio. This is called delta hedging.


Say you wish to buy one call option on SPY which has a delta value of 0.45. The market makers, who took your order, will have the opposite position of a -0.45 delta.

When the market maker sells you that call option, they can immediately hedge against their -0.45 delta by buying one call option on SPY with a 0.45 delta OR by buying 45 stocks, (which always have a delta of 1).

For the purposes of gamma exposure, we make the assumption that the market makers are hedging their trades by buying stocks in the underlying instrument.

What is gamma in risk management? How do you hedge gamma?

Gamma is a risk to the market maker when the markets are moving drastically in one direction. Gamma hedging is done to protect the dealer from larger than expected moves in the underlying options contract.

Gamma is the convexity of an options position, and is never get hedged away immediately. By continuously hedging delta risks, dealers hope to limit their exposure to large moves in the stock.


To go along with the example above, let’s assume the dealer gamma has a value of -0.05.

Say your call position moves up $1, and now on the market makers book, they have a delta of -0.50, down from -0.45. The dealer would look to sell 5 more shares of the stock. The gamma was at -0.05 and the underlying price moved up by $1, and this caused the delta on their books became more negative by this -0.05 amount.

If the call position moves down $1, from a delta of -0.45 down to -0.40 on the dealers books, then the dealer would look to buy 5 shares of the stock.

It is this simple (theoretical) illustration that shows the activity of market makers (dealers) that can help you understand the activities of those and how those active rehedging programs can have such a sizable impact on the options and stock market.

Why does gamma exposure suppress or exacerbate stock price movements?

This article is part of a more broad series of research questions I address regarding Gamma Exposure. Check out this post for more.

When gamma exposure is positive, it implies that market makers will hedge their positions in a manner that stifles volatility. It means market makers are selling into  highs and buying into lows. They are essentially buying the dip and selling the rip, and keeping volatility low in the process.

When gamma exposure is negative, it implies market makers will hedge their trades in a manner that magnifies the movement of the market. Market makers are now selling into the lows or buying into the highs.

Market makers are buying or selling their stock positions in the same direction with the current market. This is one reason why selloffs can become so deep, and why the swing back after a market selloff is so dramatic.

Much of this has to do with the effect of gamma and how it affects the delta of an options position. The gamma is a measure of the effect a $1 move on the underlying stock will have on delta.

If a market maker has a large gamma exposure value in their option book, then a $1 move in the underlying has a large effect on the delta exposure of a dealers book. This means when gamma is high, you can anticipate large changes in the delta, which the dealer will ultimately hedge against.

What basic assumptions are made in calculating gamma exposure?

This article is part of a more broad series of research questions I address regarding Gamma Exposure. Check out this post for more.

Note below adapted from SqueezeMetrics White Paper

There are a few assumptions we make when we calculate gamma exposure. These are the following assumptions:

All options traded are facilitated by delta-hedgers. We assume that all orders run through a market maker who owns a book of options.

Call options are sold by investors and bought by market makers. Based off skew, open interest at a strike, and effects of GEX, call overwriting drives the options market for calls. We assume call options are written as covered calls for portfolios.

Put options are sold by investors and bought by market makers. Puts are bought by parties looking to protection their portfolios against a drop in market prices.

Based off skew, the implied volatility of put options is generally higher than the implied volatility for call options.

Market makers hedged deltas continuously. This may not be the case, but the assumption is held for the purposes of gamma exposure.

Possible issues for those assumptions above:

If traders and investors are buying more call options than they are selling to market makers, this would drastically change the calculation of gamma exposure. This would also be true if traders and investors are selling more put options than they are buying from market makers.

Like any signal in the market, the gamma exposure signal could go away as it becomes more known. For that reason, gamma exposure should only be used as one component of your decision making process.

Great Resources on Gamma Exposure

This article is part of a more broad series of research questions I address regarding Gamma Exposure. Check out this post for more.

We believe that the greater granularity of the GEX distributions suggests that there is some element of market volatility that is simply not able to be captured by the VIX model, or indeed any other variance metric based on quoted option prices. Rather than prices, GEX concerns itself with the quantity and characteristics of all existing option contracts at all strikes, and at all expirations―and the market participants who trade them.


If investors continue to look toward the option market for alpha signals and risk assessments, they would do well to consider Gamma Exposure as a smarter alternative to price-derived volatility and variance estimates.

The key deficiency in using option prices to gauge future volatility is that no two market-makers’ books are the same, and a tight spread from any one market-maker completely obscures the risk appetite of every other.

This problem is readily ameliorated by computing the GEX of options known to be in circulation and deriving projected return distributions from the historical market impact of those contracts.

And so, when―in light of the evidence―investors eventually acknowledge that the option market does have a truly pervasive, day-to-day impact on the paths and volatilities of stock prices, we think that it is a natural next step to consider GEX an essential addition to the equity investment process.

SqueezeMetrics – Documentation

Gamma exposure (GEX); refers to the sensitivity of existing option contracts to changes in the underlying price. Like with DPI, substantial imbalances can occur between market-makers’ call- and put-option exposures, and when those imbalances occur, the effect of their hedges can either accelerate price swings (like a squeeze) or stifle movement entirely.

We have developed a novel way to quantify this exposure and the direction of hedging that occurs in the event of n% price moves. The effect of this insight on our forecasting has been profound.

SqueezeMetrics – Monitor

This monitor by SqueezeMetrics will provide you with Dark Pool buying as well as Gamma Exposure for all of the components of the S&P 500. (Please note, this is NOT Gamma Exposure on the S&P 500 index (SPX) itself. Rather it is a calculation of all of the component stocks on the S&P 500. For SPX GEX, you can subscribe to SqueezeMetrics or find that information at TradingVolatility below.)


Trading Volatility – GEX Charts

Gamma Exposure Charts

A view of the cumulative Gamma Exposure (in $) across each strike for a given stock, calculated using all options with less than 94 days to expiration.

gex chart

Spot Gamma – Updated Tables on Gamma by Strike and by Expiration Date

These options data tables based on open interest produce gamma readings which can be used to define important levels in the S&P500 (SPX) market. This data is recalculated each night based on a proprietary model. Some traders and investors believe that large open interest at a specific options strike produces actionable trading intelligence. These tables are all grouped by strike, not expiration date.

Bookmark this post if you wish. I will be updating it frequently. Consider all my posts to be a work in progress.

If you have other resources with regards to Gamma Exposure, please share them in the comments below!