"Leov," as he is known in the Trading Room, hosts the Gamma Optimizer service at EWT, where he provides options education and trade set-ups, as well as access to his proprietary Gamma Optimizer tool. The tool helps traders pick the option strike and expiration that maximize returns for a particular move in the underlying.

Leov has also developed what he calls the Deep Learning Algorithm, which, trained with historical SPX data, seeks to predict 1% upside moves in the SPX within a 5-session period. This algorithm is among the tools Leov provides in guiding members of Gamma Optimizer with options trading strategies and set-ups for minimizing risk and maximizing returns.

With a PhD in physics from Stanford University, Leov is an electrical engineer with more than 20 years of experience in research and development projects. He was a member of the technical staff at Bell Labs Lucent Technologies in the RF and Analog Simulation department, and also a senior member of Consulting Staff at Cadence Design systems for more than 15 years working on analog and digital simulation software projects.

Leo also has developed an **options education video series exclusive to members of his Gamma Optimizer service**, plus a premium set of online Options Courses for all levels of options trading.

Reposting of this article about the GT level for new members (it was posted a long time ago)
Understanding the GT level
Or the not so invisible hand of the market.
You see me posting the GT level from time to time in the main room, and every day in the GammaOptimizer service, and it is also displayed real-time in the full Variance Center app. But what does it mean? And why is it important?
To better answer those questions I need to start by explaining the acronym.

We are seeing very encouraging signs of an end to this crash environment.

Folks, I plan to do a live video for the convolutional nets at 3:15 PM today EST (UTC-5), it will be recorded and that will be the official tutorial going forward. Here is the YouTube link for it:
https://www.youtube.com/watch?v=3NP6YSEXy78
Remember that you can ask live questions on the YouTube chat.
For those not familiar, please test out our Gamma Optimizer tool for selecting the optimal option strike and exp date.

When joining the service new users can feel overwhelmed by the particular lingo that is spoken in all of our posts. Though the terms might sound strange or too advanced most of the time the concepts are very simple to understand. In order to help everyone new to the service here is a list of very common terms used in the room and also YouTube links to where I explain them at length.

Now for the month of February we still have several more sessions to go even though the month ends tomorrow we need to wait more than 1 week to finish evaluating how did it go for it (so we can see if the predictions this week work next week or not).

Because I know it can be confusing it is good from time to time to explain the differences between realized volatility and implied volatility. In essence volatility is a measure of dispersion (how far the returns are spread from a mean) so there should be only one volatility, however in financial markets we have a bunch of them. But for all practical purposes we have the following two:
1. Realized Volatility: Is the actual volatility of the market on any given time frame.

After a healthy correction of 10% from the top the question in everyone’s mind is the following:
At what level will VIX reset ? In other words, after years of low VIX values what would be the new normal level? 12 ? 15? 20 ? Of course it is hard to come up with an estimate right now but looking at certain immediate statistical measurements can provide us with good clues.

For the past several sessions I have been harping consistently about liquidity in the markets. More exactly about the lack of liquidity we are experiencing right now so I want to use this opportunity to dispel some misconceptions about what liquidity really is. The most important takeaway from this post is that liquidity is not volume.

By now you folks must know that I post a detailed view of the term structure of SPX options during the day, also you can get the a realtime curve by using the GammaCentral tool.
However sometimes we don't need anything that fancy to draw some conclusions here. For instance pay attention to VXST and VIX right now. Remember that VXST is implied variance for the next 9 calendar days, while VIX is implied variance for the next 30 days. The current readings are:
VXST = 20.18 and VIX = 18.

Those of you with good eyes have noticed that ES futures trade sometimes at a discount to SPX and other times they seem to trade at a premium. Right now they look discounted (cheaper than SPX) but last week they were a tad higher, why is that ?
The explanation resides in the fact that ES futures trade closely the SPX forward value expected at settlement day.

I can't find any material about this subject even though I'm sure I have posted about this before :) the gist of the long gamma/short gamma threshold that I publish is this:
1. Below the threshold, SPX option dealers are short gamma in the aggregate.
2. Above the threshold SPX option dealers are long gamma in the aggregate.
That is important because:
1. Long gamma hedging always happens against the market.

For those of you curious about the 1997 thing, back in Jan30 I posted this: https://www.elliottwavetrader.net/members/atchat/?threadId=4548643 explaining that 2788 "could" be the bottom for this move if 2018 were in fact following that year (based on another earlier post about 97% correlation for the January action).

Ubah has done a very interesting analysis for the NDLA that he shared on this thread: https://www.elliottwavetrader.net/members/atchat/?threadId=4548681 in case some of you are interested on looking at the numbers.

This has been requested so I'm putting it here for those of you that want to play with the performance of the new DLA algo with data since 2017 until Jan 24 2018. Here is the link for the .csv file: https://storage.googleapis.com/gamma-trader-positions/amb/infer_ndla_2017.csv
You can run your own statistical analysis with it. The high level take away from that data is this:
Precision: 71.19% (This is the amount of signals >=0.

During the early days of 2018 we have seen a consistent and huge move upwards in price in the SPX index, it has been a relentless move that is pushing the index to all time highs on a daily basis for almost all of the sessions in January so far.

I know some folks here are interesting on coding their own Ambiguity and Probability of Negative returns heuristics (which is an step towards coding their own DLA's :). As you can imagine my implementation of those concepts is secret sauce and won't see the light of the day anytime ever (trade secrets). However the ideas behind them are public and available to any of you that want to pursue them.

This post is for Pegasus, he has requested information about how to compute weights based on assumptions of a normally distributed factor.
The process is very simple, first take the factor that you want to use and analyze the distribution for example this one:
1,4,4.5,5,5.5,5.5,4.5,5,10
That distribution is mostly centered around 5 with a couple a big outliers so the weights should reflect that.
1. Compute the mean and standard deviation:
mean = 5, sd = 2.318405
2.

Remember folks you can access some webapps that can be useful to you.
Positions app: https://gamma-trader.shinyapps.io/positions/
Momentum center: https://gamma-trader.shinyapps.io/center/
Gamma Central: https://gamma-trader.shinyapps.io/gamma/?token=6e66d3982189c6b3dcbc55bd20342959 (the link changes frequently so better to use the official link from the Gamma Optimizer tool).

Implied volatility in SPX is finally coming down a lot and option prices are starting to become decent again. However the next time we are in a similar situation of high IV and expensive options and we want to play upside we can use a binary risk reversal. Remember that a normal risk reversal is:
RR = short put + long call
The idea is to finance the expensive call with an even more expensive put that we are selling.

Making use of the holiday this is a good time to re-post my thoughts about option "strategies" in particular those that seek to generate "income" in a regular basic, like weekly time frames. This is what I wrote in the past about this subject: https://www.elliottwavetrader.net/members/atchat/?threadId=4542766
Those strategies don't exist, they are just bogus claims from dishonest or inexperienced (or both) traders.

Folks Tom has kindly provided me with the link to my latest Gamma webinar (the one on Wednesday) so for those of you that were not able to attend here is the link: https://www.elliottwavetrader.net/videos/Optimizing-Your-Options-Trades-201805104816.html

With the close today the DLA is batting 3 trade jackpots in a row (max gain trades) with gain per trade north of 700%. With those numbers is easy to get lost in the hype and the adrenaline and forget that even though the DLA has been very accurate over the whole of 2017 and start of 2018 (64% precision), the true edge of those trades doesn't come from the DLA signals themselves. Instead the edge comes from an structural mispricing of binary calls in SPX.
The mispricing is very simple to figure out.

For those of you new to the site we have a mini-Web app that tracks our current open positions: https://gamma-trader.shinyapps.io/positions/
Right now we only have two positions on. The list is updated real time every 10 seconds and also as I add and close new positions.

I don't have a single source of information for the DLA as it is just a deep neural net that I trained last year and I have been sharing periodically with you folks. So here is a collection of links to whatever I have written about it:
https://www.elliottwavetrader.net/members/atchat/?threadId=4545945
https://www.elliottwavetrader.net/members/atchat/?threadId=4546964
And this is the origin of the Naive strategy that gave birth to the DLA: https://www.elliottwavetrader.

The control chart from the momentum center: https://gamma-trader.shinyapps.io/center/ displays a lot of useful statistical information. Things like Skew, Kurtosis, Mean, Standard Deviation, Realized Volatility. I pay attention to all of them and each provides useful information, but the one that I'm always looking at other than realized volatility is Kurtosis.

Given that the DLA seems to be the hot item "du jour" I'm getting many questions about the correct ways to interpret the probabilities displayed on the table. So to clarify misconceptions once and for all I want to post a basic premier about probabilities in general first and then more specifics about the DLA itself.
Let's start with a quick review of the following question: Is the market going to move 1% up in 5 trading sessions ? (That is the basic question that the DLA wants to answer).

I got a very good question over the weekend about the Ambiguity indicator and the Deep Learning Algorithm (henceforth known as DLA) and I think it deserves to be answered in a wider space as it could be helpful to a lot of you folks to understand the differences between the two of them and how I use them.

The power of long gamma expressed with binary options :) Remember that a tight vertical spread is basically a binary option, and also remember that a binary option is basically a pure gamma bet (not delta). So in this case our SPX uber-lotto: https://www.elliottwavetrader.net/members/atchat/?threadId=4544946 which I paid 0.8 for it initially and then added at 0.7, I also took some off at 2.6 ;) last week, is a perfect example of this.

Here is the link for the Hedging video in YouTube: https://youtu.be/WKxNHaKGVbI, we can use this thread for Q&A

I just completed the material for the Hedging Class and it certainly looks like it will be a very long video, so I wonder if you folks want me to just go ahead and record it or if you want a live class format where you can also asks questions (as usual the recording will be in YouTube after that).
Please let me know. If you like the class format we can shoot for this afternoon.

Simple Practices for Maximizing Gains in Vertical Spreads - Jan 29, 2020

Leo covers why the Gamma Optimizer service makes extensive use of spreads instead of single options.
He shares the most common mistakes that options traders make when trading spreads and how to eliminate them
and maximize gains through a set of simple best practices.

Optimizing Your Options Trades - May 10, 2018

Playing Market Volatility
With SPX Options - Sep 15, 2020

Leo discusses the best way to use SPX index options to take advantage of the expected seasonal volatility
and added dynamic of the presidential election.

Leo has developed an options education video series in his Gamma Optimizer service. The 6-part series, ranging from an introduction to options to advanced options trading strategies, is currently only available to GO members, and archived in the service's video section. The series covers:

1) Introduction to Options: Basic concepts and tips.

2) Options Pricing: Pricing options in a risk-neutral world, plus Binomial model introduction.

3) Talking Greek: Advanced options pricing, Black Scholes Merton Model, volatility and greeks.

4) The Power of Gamma: Time decay, Gamma and Vega in detail.

5) Put-Call Parity and Synthetics: Trading implications and applications related to synthetic positions.

Class 6 to follow.

Leo has also developed a premium set of online courses for all levels of options trading. Whether you're just getting started in the options world or wish to master sophisticated strategies, these courses will make a savvy and skilled options trader. Learn more and get discount code to save more than 50%.

When joining the service new users can feel overwhelmed by the particular lingo that is spoken in all of our posts. Though the terms might sound strange or too advanced, most of the time the concepts are very simple to understand. In order to help everyone new to the service, here is a list of very common terms used in the room and also links to YouTube videos and site posts labeled "Education," to where I explain them at length.

**Ambiguity:** I post a chart about a statistical quantity called Ambiguity, which is a close
cousin of VIX (it was created by one of the co-inventors of VIX). It measures the Knightian uncertainty
in the market. The concept is pretty advanced, but the way I use the chart is simple: We look for low
ambiguity to start a leg up, and for very high ambiguity when expecting downside action.

**Binary Options:** In the room I talk frequently about binary options, in particular the 1%
upside binary call. A binary option always pays 100 if it finishes in the money, or 0 otherwise. Because
of this it is a very simple way to play certain scenarios because it allows to compute in advance both
expected profit and losses. For a more detailed discussion please check this video

**Complex Trades - Butterflies, Calendars, Risk Reversals, Vertical Spreads:** These are a
set of trades that can be done with options and are called in general Complex Trades. The reason is that
the trade requires the simultaneous execution of multiple “legs” where we are buying and selling options
with different strikes and or/expirations at the same time. See video for more information:

**Convolutional Nets:** These are neural networks trained with SPX historical data that seek
to predict moves in a 5-trading session period. One of the networks, called **Ultra-4**,
looks for 1% up-moves in the market. A second, called **Zero-I**, provides the most basic
prediction (market up, or market down). The third, called **Neg-I**, predicts -0.5% market
declines. Unlike Leo's original NDLA algorithm, Convolutional Nets can be used to play both positive and
negative signals.
See
video.

**DLA and NDLA:** This is a deep learning algorithm trained with SPX historical data that
seeks to predict 1% upside moves in SPX within a 5 trading session period. The DLA was the original implementation
and in 2018 we replaced it with the “New” DLA or NDLA.

**Gamma:** This is probably one of the most frequent words you’ll see in the room, it will
be accompanied by a qualifier most of the time: long gamma or short gamma. Gamma is a mathematical parameter
that describes the amount of non-linearity of an option. For a more in-depth presentation on this please check
my YouTube video

**The Gamma Central tool** provides a nice snapshot of the current realized and implied volatility
status for any underlying. The tool provides functionality through tabs, and what follows is a brief description
of what each tab does. For more in-depth information about the tool, please check the following YouTube video

**Gamma Optimizer or GO:** This is a reference to our Long Gamma Optimizer tool, which is a
tool we use to compute the best options to play a particular thesis. For a tutorial of the tool please check this video.

**GT / Gamma Threshold Level:** The level at which most options dealers are neutral in the
aggregate (i.e., they don't need to hedge). Above that level, dealers are long gamma, with their hedging
activity tending to slow down big market moves, producing lower volatility. Conversely, when below the
GT level dealers are short gamma and their hedging activity amplifies or accelerates moves, creating more
market volatility.

**Kurtosis:** In the momentum chart we have the control chart that displays a value called
Kurtosis. This is a basic statistical number that tells us a lot about the nature of the distribution of
intraday log returns. When kurtosis is 3.0 the distribution is normal (also called Gaussian) and means that
most of the action is perfectly random fluctuations of price.

**Log Returns:** In finance returns are usually measured as log returns. This is a simple concept and
it is defined as: Log Return = log (close/ prev close) where log() is the natural logarithm function.

**SPX Term Structure:** This is a chart that I publish frequently in the room and represents
the Implied Volatility of options across different expiration dates. It gives you an idea of how expensive
options are based on how close to expire they are. The X axis of the chart is time in days, and the Y axis
is implied volatility in percentage. For a more detailed explanation of this concept please check the
Gamma Central tutorial.

**Standard Deviation:** This is a statistical term that is very important to options. It is
defined as the square root of the variance (so if you know variance you know standard deviation). This is
explained in more detail in the volatility videos (see "Volatility").

**Variance:** This is another statistical term, and it it corresponds to the classic variance
of population distributions. It is a very important concept for options and it is explained in more detail
in the Volatility videos (see Volatility).

**VIX:** Another term that you will see a lot in the room is VIX. This is an index created by
the CBOE that measures the 30-day implied variance in the market using only SPX option prices. It is a very
useful measure, and although it can be traded directly there are lots of products connected to it, like VIX
futures, or volatility ETP’s like VXX and SVWY. For more information about VIX check the CBOE website and
also this video.

**Volatility:** This is a very frequent word in the GO room and it is a key concept for option
trading, in finance volatility is basically the standard deviation of log returns, scaled to an annual value
and also printed as a percentage (10%, 20% etc). It comes in several flavors most notably Realized Volatility
and Implied Volatility. See video here.

**Volatility or Momentum Center:** This is a helper application with multiple charts updating
real time, most of them designed to track momentum in any underlying.
See video.

**VRP:** Another term that appears very frequently is VRP or Variance Risk Premium. In its most
basic form the VRP is an added premium between "implied volatility" and realized volatility. In general,
implied volatility trades above realized volatility (it trades at a premium called the VRP). For more
information please see video.

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