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FIGuring It Out: Zero Nonsense on 0DTE
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FIGuring It Out: Zero Nonsense on 0DTE

Introduction

In this section, the host introduces Chris Sidio and mentions that they had met before in Las Vegas. They discuss how they will be conducting the interview over Zoom.

Background of Chris Sidio

  • Chris Sidio is a co-CIO of Amber's group.
  • He wrote a paper on zero day to expiry options called "Dispelling False Narratives About Zero DT Options."
  • Prior to joining Amber's, he was a prop trader at two different firms and spent three and a half years at a large Canadian investment bank on the exotic derivatives desk.

Tail Risk Hedging

  • The goal of tail risk hedging is to have a portfolio designed to have a large return during market crashes while being close to flat during normal market environments.
  • Active trading can be used to minimize the negative carry event associated with buying long vol.
  • Trading itself can create enough alpha so that you can offset the cost of carrying that hedge.

Market Maker Approach

In this section, Chris discusses how traditional market makers create derivatives using an approach where they make money during normal environments and have the potential for very big returns when things become dislocated.

Key Points

  • The idea is to trade a lot of flow intraday to offset bleed and be inherently long tail so that when things hit the fan, there is an abnormal return.
  • This model is different from Universal's type of trade structures but similar to what firms like Jane Street employ.

The Business Model of Hedge Fund Managers

In this section, the speaker discusses the challenges of building a business model as a long-focused hedge fund manager and how Ambrose is combining their skills on the long side with experience in identifying inexpensive hedges to play the short side.

Building a Business Model

  • Long-focused hedge fund managers face challenges in building a business model.
  • Investors are skeptical of track records built on small amounts of money and want proof that they can perform with larger sums.
  • There is an element of frustration in building a business model for most long-focused hedge fund managers.

Combining Skills on Long and Short Sides

  • Ambrose combines skills on the long side with experience in identifying inexpensive hedges to play the short side.
  • The portfolio offers positively convex payoffs to downside events.

Identifying Zero Day to Expiry Options

In this section, the speaker talks about zero day to expiry options and how they are used by market participants. They also discuss how their approach differs from what was originally believed about these options.

What Are Zero Day to Expiry Options?

  • Zero day to expiry options are options that expire on the same day they are purchased.
  • Market participants have shown an increased appetite for these types of products.

Divergence from Mainstream Media

  • The price action and quantitative data diverged from mainstream media commentary and research put out by larger banks.
  • As a hedge fund, they had certain coverage which allowed them to see something different than what was being reported.

Directionality Component of Traits

The speakers discuss the surprising lack of discussion around the directionality component of traits in research and how they decided to dive into the data and put out a piece on it. They also mention that other Vault shops understood this as well but nobody was saying anything.

Lack of Discussion Around Directionality Component

  • The speakers find it surprising that there is no discussion around the directionality component of traits in research.
  • Other Vault shops understood this as well, but nobody was saying anything.
  • They were the first group to come out and say that the research was wrong.
  • Four weeks after they put out their paper, some larger banks came out with similar findings.

Wall Street's Standard Practice

The speakers discuss how Wall Street operates when it comes to sharing information between different departments. They also talk about how they plan to use what they learned from their research.

Sharing Information Between Departments

  • It is standard practice on Wall Street for everyone to look at each other's work and lift ideas from one another.
  • There is a Chinese wall between trading and research, which means that they cannot interact in certain ways due to client confidentiality concerns.
  • Some people on the research side do not understand trading tactics because they come from institutional backgrounds.

Using Research Findings

  • The speakers plan to use what they learned from their research in their own work.
  • The trading desk understands that the research was not in line with their knowledge base.

Feet in Both Pies: Research and Portfolio Management

In this section, the speaker discusses the importance of having both research and portfolio management skills to make informed decisions. They also discuss the traditional approach to analyzing trade data and how it can be improved.

Traditional Approach to Analyzing Trade Data

  • The traditional approach involves looking at whether a trade was executed close to the bid or offer price.
  • However, this approach is flawed because many trades are executed right at the minute, which skews the data.
  • Market makers use something called local volatility when trading options, which means that each option has its own volatility based on its tenor and strike.
  • By analyzing changes in local volatility along with other execution tags, such as rate of change, one can get a better understanding of whether market makers are buying or selling.

Local Volatility Model

  • A local volatility model is designed to figure out a price at which an option can be transacted rather than replicated under a Black Shoals framework.
  • This model dispenses with the idea of a normal distribution and instead looks at how all other options are priced in a specific region to determine pricing.
  • Using this model can result in significantly different prices for options compared to using a Black Shoals model.

Conclusion

The speaker emphasizes that having both research and portfolio management skills is crucial for making informed decisions. They also suggest that using a local volatility model can provide more accurate pricing information for options.

Zero DTE Options

In this section, the speaker discusses zero DTE options and their unique characteristics. He explains that they are exclusively indexed with rare exceptions and are almost exclusively very close to the money. The biggest users of these options are market makers and wealth advisors.

Characteristics of Zero DTE Options

  • Zero DTE options are exclusively indexed with rare exceptions.
  • They are almost exclusively very close to the money, making them hyperactively traded contracts.
  • These options behave differently than longer-term out-of-the-money call options on individual stocks because dealers may not find someone in inventory to cross with on a trade.
  • Market makers like Jane Street transact constantly in these contracts.
  • Wealth advisors started participating in these type of yield programs during 2022 when there was nowhere to hide if you were a vanilla wealth advisor.

Trading Zero DTE Options

  • It would be extremely unusual for someone to put in an order for 10,000 zero DTE options as they tend to trade in smaller lot orders which often times gets confused for retail because they're getting broken up.
  • Dollar cost averaging is one way traders can improve frequency when trading zero DTE options over the course of the day.

Differences from Other Options

  • There's a big difference between market makers and end-users like retail investors who tend to trade larger size orders.
  • Selling continuously through the day can result in a higher hit rate than selling all at once due to path dependency.

Understanding Trading Behavior

In this section, the speaker discusses how traders label trades based on the bid or ask price and highlights that this approach captures only a small percentage of trades. The speaker also explains the concept of moneyness in terms of options trading.

Bid-Ask Price Labeling

  • Traders label trades based on the bid or ask price, which captures only 20 to 30 percent of trades.
  • This approach ignores all the trades in between and can lead to inaccurate labeling.

Moneyness in Options Trading

  • Moneyness refers to how far out-of-the-money an option is normalized to percentage terms.
  • At-the-money is considered 100, while one percent out-of-the-money on the call side is considered 101 and one percent out-of-the-money on the downside is considered 99.

Time of Day and Trading Behavior

In this section, the speaker discusses how trading behavior changes throughout the day and highlights that different times of day have different behaviors.

Time of Day

  • Trading behavior changes throughout the day, with different times having different behaviors.
  • Morning time sees people hoarding into selling options while later in the day end-users look to cover positions and take speculative trades in line with market directionality.

Money-Ness and Time of Day

  • Data shows that right at morning time people are hoarding into selling options while later in the day end-users look to cover positions and take speculative trades in line with market directionality.
  • The aggregated view shows that when someone sells a put, they initiate a new position and cause some degree of hedging activity.

Derivative Impact

In this section, the speaker explains how dealers react to derivative impact and how it affects their positions.

Dealer Reaction to Derivative Impact

  • Dealers take the opposite side of an end-user's position in terms of calls or puts.
  • If someone buys a call option, the market maker sells the option and buys stock against it.

Hedging Activity

  • When someone sells a put, they initiate a new position and cause some degree of hedging activity.
  • The dealer has exposure effectively to the market going lower and must Delta hedge that position.

Understanding the Options Market

In this section, the speaker explains how options trading works and how it affects the underlying market.

Selling Puts and Dealer's Hedge

  • Dealers sell puts to investors who are willing to get long in a slightly lower price.
  • The dealer takes on the opposite side of the trade by buying stock.
  • This pushes the market up as more people get long synthetically.
  • The dealer has to close their position at the end of the day when the option expires, which can cause price action.

Price Action and Risk Offset

  • Dealers offset their risk by buying or selling underlying shares.
  • This can cause repeatable price action during certain times of the day.
  • When dealers buy shares to offset risk, it can push prices up even if there is no news driving it.
  • An example is shown where e-mini's intraday goes up overnight but falls off after opening due to overriding zero DT expiry calls.

Call Options and Market Dynamics

In this section, the speakers discuss what happens when an event forces call options to go into the money. They explain how dealers who are short on call options will need to buy stock, which could lead to a continuous increase in the market. They also touch on Opex week and how derivative flow can create sudden price movements.

Call Options Going Into The Money

  • When an event forces call options to go into the money, dealers who are short on call options will need to buy stock.
  • This could lead to a continuous increase in the market as dealers continue to hedge their positions.
  • Opex week is another time when derivative flow can create sudden price movements.

Market Dynamics and Narratives

  • Mechanical features of the market take on a life of their own in the absence of news or fundamental changes.
  • Constructing narratives around these mechanical features creates predictability and forces us to make sense of what's happening.
  • Experts in the derivative space have observed data that supports this narrative, making it hard to refute.
  • During 2020, larger institutions started implementing option trading in their portfolios, leading to a Renaissance Era of option trading during 2021.

The Rise of Option Trading

In this section, the speakers discuss how 2021 marked a Renaissance Era for option trading. They explain how data shows that it's hard to refute how many options are being traded and by whom.

The Renaissance Era of Option Trading

  • During March 2020, larger institutions started implementing option trading in their portfolios.
  • During 2021, all mandates were approved and went into process for using options in portfolio management.
  • Data shows that it's hard to refute how many options are being traded and by whom.
  • Experts who trade options every day have observed this trend and attribute it to reflexivity in the derivatives market.

Impact of Derivatives Market on Stock Prices

In this section, the speaker discusses how the derivatives market impacts stock prices and how quickly the market moves after a large print.

Derivatives Market Impact

  • The speaker explains that after a large print in the derivatives market, such as a call option or some sort of color, the stock market moves in response.
  • This is not a coincidence and shows how impactful the derivatives market has become in a short period of time.

Conclusion and Recommendations

In this section, the speaker concludes by recommending people to check out Ambrose Group's website and follow Chris on Twitter for more insights.

Summary and Recommendations

  • The speaker thanks Chris for his contribution to the system and encourages people to check out his work on Ambrose Group's website.
  • He recommends reading Chris's paper and following him on Twitter at k-s-i-d-i-i-i. He warns people to beware of fake accounts.
  • The speaker emphasizes seeking out people who back up their work when looking for information.
Video description

Michael Green discusses the 0DTE option market with Kris Sidial of Ambrus Group For more information, visit simplify.us. Simplify Asset Management Inc. is a Registered Investment Adviser. Advisory services are only offered to clients or prospective clients where Simplify Asset Management Inc. and its representatives are properly licensed or exempt from licensure. SEC registration does not constitute an endorsement of the firm by the Commission, nor does it indicate that the advisor has attained a particular level of skill or ability. Be sure to first consult with a qualified financial adviser and/or tax professional before implementing any strategy. This website and information are not intended to provide investment, tax, or legal advice. This content is solely for informational purposes and does not intend to make an offer or solicitation for the sale or purchase of any specific securities, investments, or investment strategies. These materials are made available on an “as is” basis, without representation or warranty. The information contained in these materials has been obtained from sources that Simplify Asset Management Inc. believes to be reliable, but accuracy and completeness are not guaranteed. This information is only current as of the date indicated, and may be superseded by subsequent market events or for other reasons. Neither the author nor Simplify Asset Management Inc. undertakes to advise you of any changes in the views expressed herein. PAST PERFORMANCE IS NO GUARANTEE OF FUTURE RETURNS. INVESTING INVOLVES RISK AND POSSIBLE LOSS OF PRINCIPAL CAPITAL. UNLESS OTHERWISE NOTED, ANY PERFORMANCE RETURNS PRESENTED IN THESE MATERIALS REFLECT HYPOTHETICAL PERFORMANCE. HYPOTHETICAL STRATEGIES AND INDICES PRESENTED ARE UNMANAGED, DO NOT REFLECT ANY FEES, EXPENSES, TRANSACTION COSTS, COMMISSIONS OR TAXES, AND ONE CANNOT INVEST DIRECTLY IN ANY OF THESE. THE RESULTS PRESENTED SHOULD NOT BE VIEWED AS INDICATIVE OF THE ADVISER’ SKILL AND DO NOT REFLECT THE PERFORMANCE RESULTS THAT WERE ACHIEVED BY ANY PARTICULAR CLIENT. DURING THIS PERIOD, THE ADVISER WAS NOT PROVIDING ADVICE USING THIS MODEL AND CLIENTS’ RESULTS MAY HAVE BEEN MATERIALLY DIFFERENT. Hypothetical model results have many inherent limitations, some of which, but not all, are described herein. One of the limitations of hypothetical performance results is that they are generally prepared with the benefit of hindsight. In addition, hypothetical trading does not involve financial risk, and no hypothetical trading record can completely account for the impact of financial risk in actual trading.