One
of the most important parts of trading the market is finding an edge in
the market which is sort of reliable to trade constantly. That usually
involves when market participants like the market makers are being forced to buy or sell a certain asset.
Today
we will discuss how we could use gamma exposure to come up with a
somewhat consistent trading strategy. First of all, what is gamma
exposure?
Gamma exposure is the second order price sensitivity of a certain derivative to changes in the price of its underlying security.
A
big factor in market movements is the market makers buying and selling
options from and to the traders. In order to do that they are forced to
also hedge that risk they are taking by buying or selling that option’s
underlying security. This process is often referred to as Delta Hedging.
However, when hedging, the options value changes differently (the
Delta) based off how far the underlying security’s price is from the
option’s strike price. Not only the delta but also its rate of
sensitivity changes as well. This rate of sensitivity is called the
Gamma.
This
makes the process of hedging way more complex, therefore as the price
of underlying security changes the dealers would need to adjust their
hedge for every point change by buying or selling additional shares in
order to make sure their positions remain neutral to their side. The
reason this is important to understand is because this could often cause
bigger movements of volatility in the market like the recent massive
movement in GameStop ($GME) share prices.
Essentially,
gamma hedging could be described as the process of adjusting a delta
hedge relative to the underlying security’s price. As an example, let’s
say you purchased a call option with a delta of 0.50 you could hedge
your long position by shorting 50 shares of the underlying security. If
the option’s gamma is .10, after a 1 point increase in the security’s
price the delta would become 0.6 and after the 2 point increase the
gamma becomes 0.20 this would make the delta 0.80. In order to adjust to
the change in Delta you would have to short 10 more shares for a 1
point increase and 20 more shares for the next. On a larger scale like
the market makers and institutions, millions of shares being shorted
(sold) after each point increase in the price would also affect the
price of that security.
The constant force of buying or selling counter to the markets direction caused by gamma hedging is often a cause of a volatility decrease.
There
are two sides to gamma hedging: long gamma or short gamma. The example I
gave earlier is an example of long gamma, counter to that, short gamma
is just the exact opposite. As gamma hedging causes a reverse effect on
the security, for every point decrease in the price of the security the
dealers would have to buy shares. By doing that, there would also be a
point where the dealers would change from being overall long gamma to
being short gamma or vice versa. You call this point the Zero Gamma level.
When
dealers switch from being long gamma to short gamma, at the zero gamma
level, that would usually cause a level of support for the securities
price and therefore we see a lot of upside at that level. That is
obviously due to the change from mass selling to mass buying from the
dealers.
People
could take advantage of this by calculating this securities zero gamma
level and entering positions based off the condition from there. I will
demonstrate how to calculate this using Python.
Calculating GEX and Zero Gamma Level
First of all we will be downloading data from the official Cboe website. In this example we will be using SPY but you could do it for any stock. You could find the overall code for this at the bottom.
In
order to find the zero gamma exposure level we need to also find the
total amount of gamma exposure for both the calls and the puts. First we
will organize the data into a python data frame and store the spot
price of the stock in a different variable.
We calculate the Total Gamma Exposure(GEX) for each strike by multiplying each option’s gamma, for all the calls and puts, by their respective Open Interest.
After that we multiply them by 100 as the each option represents 100
shares. For the puts we multiply each by -1 as their gamma is negative.
When we have them all calculated we add all the gamma with similar
strikes together which would be the Total Gamma Exposure(GEX) for each strike. If you plot it it should look something like this.
Trading the ‘Zero Gamma Level’
After finding this value on SPY, we could use it to predict bounces in the reverse direction and use that for a quick scalp trade. Another thing we could expect at the zero gamma level for SPY is a spike in VIX futures as it presents a change in risk in the market. If you are not familiar with the VIX,
it is the Cboe Volatility Index which represents a real-time index of
the market’s expectations for the relative strength of near-term price
changes of the S&P 500 index.