Understanding Gamma Exposure and How it Moves Markets

In this series of articles, I will address a concept known as gamma exposure.

Gamma Exposure: A very brief overview

Gamma exposure is an estimated measure of the overall option market makers’ (aka option dealers’) exposure to the options Greek known as gamma.

Gamma exposure is an estimate that can help you gauge future volatility and stock price variance.

Gamma exposure informs you how options market makers will likely need to hedge their trades to ensure their options books are balanced.

Much of the discussion on gamma exposure relates to options traded on S&P 500 (SPX) because the options market on this ticker has outsize effect on determining the index price level.

My introduction to Gamma Exposure

I first heard about gamma and its effect on stocks from notes written by Charlie McElligott at Nomura.

I’d see articles from time to time and gamma exposure seemed rational and interesting. I just had to learn more.

I discovered SqueezeMetrics on Twitter which provided me with more information regarding gamma exposure than any other source I’ve seen yet.

Go check out SqueezeMetrics and white paper to learn more. It was one thing I found that actually seemed to explain why the market moved the way it did over very short term (1-3 day) time periods.

Want to Gain a Deeper Understanding of Gamma Exposure?

Frequently Asked Questions

What are the options Greeks?

What is gamma in options trading?

What is an options market maker (options dealer)?

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

Why does gamma exposure suppress or exacerbate stock price movements?

What basic assumptions are made in calculating Gamma Exposure?

How the limit order book became abstracted into options and why gamma exposure matters

Learn more about Gamma Exposure with these great resources

Why you should ask more questions

Asking questions is important.

Why is asking questions important?

Questions force you to think about a topic in terms of what you don’t know. Rather than reading a text or a highlighted passage, and thinking “I got this”, questions force you to search deeper for something else: the unknown.

Why do questions force you to think about what you don’t know?

We are curious people. We like to know the answer to questions. When we ask questions, there’s a natural desire to find and answer to those questions.

When you write questions down about a topic you are learning, you are forcing yourself to read and interpret information from the perspective of finding out what you don’t know.

How can you ask more questions?

Just write down more questions every day. Write down your to do list in the form of questions. Ask yourself, what am I going to get done today? What needs to be worked on first? What are those most important items on my to do list?

Write down questions about a topic you want to learn. Start by writing questions that you want to know the answer to. When you have answers that you are seeking, learning becomes easier.

Writing questions gives your mind something to search for. If you go into a topic with a bunch of questions, personalized to you, you will learn a subject much faster.

I guarantee it.

Risk management is more important than predicting the future

Everyone wants to predict the future. It’s fun to speculate and guess what will happen next in the market. So everyone tries to do it.

This can be a fruitless effort though.

See, the problem with making predictions is your ego. You want to be right so bad. For many beginners and experts too, the position themselves too much based off overconfidence in their predictions.

I was overconfident in October that we would see a market drop. I strongly believed that there were a multitude of factors that would bring the market down.

We had no real China trade deal.

Even so, earnings were going to be down year over year.

Even so, the Fed was going to cut rates, and after they cut multiple times earlier in the year the markets sold off.

Even so, the economic numbers didn’t look good.

Even so, the repo markets were out of control to the point the Federal Reserve felt the need to intervene.

The market just had to go down, right?

Well, I was wrong and lost too much money as a result.

No matter how right you think you are, there is a good chance you can still be wrong. It may not make any sense. None of this rally over the past six weeks made sense to me. But it happened, and I didn’t manage risk properly and I suffered the consequences.

Lots of Gamma Exposure keeps the market afloat

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Source

What is gamma exposure?

Source: TradingVolatility.com

There has been recent research published into the concept of “Gamma Exposure” (“GEX”) on the book of options Market Makers.

In summary:
– Market Makers provide a market for people to buy and sell options.
– Market Makers don’t just take the opposite side of the trade that investors take. They hedge their exposure so that they can profitably manage an options book.
– The hedges must be re-hedged daily so that their position can remain neutral as the underlying stock prices move.
– In scenarios where “Gamma Exposure” gets off balance to the negative side, Market Makers must sell as prices drop and buy as prices rise, accentuating the movement in stocks. Oversold conditions result in a setup for a short squeeze, where both investors are buying oversold conditions AND Market Markets are re-hedging their positions by buying as the stock price rises. The result is a pop higher in the stock.

Source: SqueezeMetrics

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.

I will post more on this topic to come in the future. Please subscribe to be updated when I post this.

You are your own worst enemy

It’s easy to blame others.

It’s hard to blame yourself.

It’s easy to blame things out of your control.

It’s hard to blame those things that are within your control.

Rules can help you make better decisions. Your goal should be to follow your rules. Not making money. Making money should be a product of following your rules.

Don’t think of yourself as a gamblin’ man. Think of yourself as a risk manager.

Make smarter bets through time. Don’t trade too big in any one position or in any one day. When you place your bets is just as important as where you place your bets.

How to download S&P 500 data from Yahoo Finance using Python

Make sure you have the yfinance package installed first. If you don’t, you can run the following command in your Jupyter notebook:

!pip install yfinance

Input:

import pandas as pd
import numpy as np
import yfinance as yf

Input:

spy_ohlc_df = yf.download('SPY', start='1993-02-01', end='2019-12-01')

Output:

[*********************100%***********************]  1 of 1 downloaded

Input:

spy_ohlc_df.head()

Output:

Conclusion

This is a very brief summary of how you can download stock data information for the S&P 500 from Yahoo Finance, using the Python programming language. If there is something you want to learn about, please let me know in the comments below and I can cover it in a future blog post.

It’s not if, but rather when will a market pullback happen

We’ve had an extremely long run up in the market over the past month and a half.

The S&P 500 is up 8.8% since October 8. The market has barely had much of a pullback since this rally started. It feels like the market won’t pullback at any point soon. But it will happen.

There are a lot of questions to think about though when it comes to timing a pullback in prices:

How much long will markets run higher before the market pulls back?
What will the depth of the pullback be when it does happen?
What is the likely magnitude of the pullback?

These are all impossible to know, but are at least worth considering.

My prediction is that we experience a pullback sometime after December 20, 2019. Why that date? It’s the infamous quad witching date. What’s that?

What Is Quadruple Witching?

Quadruple witching refers to a date on which stock index futures, stock index options, stock options, and single stock futures expire simultaneously. While stock options contracts and index options expire on the third Friday of every month, all four asset classes expire simultaneously on the third Friday of March, June, September, and December.

Source

There is large gamma exposure coming off the books on this date. To the order of $2.7 billion. Source

There are the potential risks that could be a tipping point as well. If any catalysts materialize, a pullback is likely.

Possible risks include:

No trade deal with China, or worse, a more tense U.S.-China relationship.
Issues in the short-term funding market where the Fed can no longer control short-term interest rates
Bad guidance on future earnings
Declining GDP becoming more known

I believe a pullback could see much of gains up to this point being wiped out. $2900 isn’t out of the question of being tested at some point in mid-December to mid-January. That’d be down 7.7% from where we are currently at.

A deeper decline is possible, but would need to be closer before any thoughts about it happening.

I think a pullback could be very quick, 3-4 days like August and May pullbacks. Some even say it could be like February 2018 pullback, but I’m not so sure that the magnitude would reach that level.

With that being said, my predictions are usually wrong. Follow Murphy’s Law: Whatever can go wrong will go wrong. So make sure you hedge your bets and spread them out intelligently over some specified time frame.

BREAKING: Trump signs Hong Kong Bill

bbg hong kong

Donald Trump signed a bill into law that expresses U.S. support for Hong Kong protesters, a move that could strain relations with China and further complicate the president’s effort to come to a phase one trade deal.

Will the market react?

I would guess not. Gamma exposure right now is massive. This has held the markets higher for the past month, along with Fed interventions. If these are actually those items holding the market higher for the time being, we will see the current bull trend continue. This is where my bias is with about 65% probability.

How I document my trades

document

This is the format I’ve been using to track my options trades recently. As you can see, I show the Underlying Ticker, Type, Expiration Date, Strike(s) (multiple for spreads and such), Quantity, Cost per Contract, Cost Basis, Purchase Datetime, Underlying Price at Purchase, Open or Closed, Sale Datetime, Underlying Price at Sale, Sales Price per Contract, Sale Price, Profit/Loss, and Percent Return.

I’ve found with much of my data analysis, this is the ideal format for me with minimizes excess documentation.

One distinction with this is that I use the Open or Closed column to easily identify and match up trades on a First in First out basis (FIFO accounting).

I like having the purchase datetime exactly along with the price of the underlying stock to help review and analyze my entry and exit points within the greater context of the market.

How do you document your trades?

The World Has Gone Mad – Ray Dalio article summary

We are currently “pushing on a string”, a phase which Ray says we have never seen during our lifetimes. This is the situation where investors are flush with cash, and would rather invest it, not spend it.

The prices of financial assets have gone up as interest rates have plummeted. Low expected returns aren’t just driving up the prices bonds, but also equities, private equity, venture capital, etc.

Startups don’t have clear paths to profits, so they rely on selling dreams (Adam Neumann WeWork is a prime example) to get people to invest in their ideas. Investment managers are sitting on large hordes of cash and are looking for any place to park their funds, hence the overblown valuations of companies.

Government deficits are large and continue to grow. As a result, governments must sell more debt that nobody is interested in buying because the interest rates on these debts are so low. Central banks end up buying this debt by printing new money. (But don’t say they are monetizing the debt).

Down the road, as pension and healthcare liability payments come due, those obligated to make these payments will be unable to do so. How does this happen? Those institutions have expected returns of 7%, much greater than expected returns in the market in the coming years.

As these institutions are unable to make payments, unfunded liabilities will balloon as a result of suppressed growth. Teachers and governmental employees are those most exposed to this risk.

In sum, money is basically free (because of low to negative interest rates) for those who have money and creditworthiness. Money is unavailable for those without money or creditworthiness.

This contributes further to the wealth gaps we see today. Technological innovations are creating a way for companies to cut jobs further as well. The effects of low interest rate monetary policies are no longer “trickling down” to workers as a result. Thus explains how to we got where we are today.