ETF Math: Risk/Reward Tactics with Direxion's Ed Egilinsky

Globe and Mail

24-04-2025

(0:30) - Probability Training is the Antidote to Behavioral Bias
(9:45) - Direxion ETFs: You Can Learn A Lot Just By Playing the Game
(13:30) - Leverage: Rewards and Risks That Every Investor Must Study
(22:50) - Single-Stock ETFs Open a Whole New Playing Field
(30:00) - Getting Educated with Direxion on Leveraged And Inverse ETFs
(36:55) - Episode Roundup: [e-mail]
Welcome back to Mind Over Money. I'm Kevin Cook, your field guide and storyteller for the fascinating arena of behavioral economics.
Today my guest on the podcast is Edward Egilinsky, Head of Alternative Investments for the ETF provider Direxion. In over two decades of innovation, they have created a suite of products that active traders find invaluable, like the Direxion Daily Semiconductor Bull 3X Shares SOXL and the Direxion Daily Gold Miners Index Bull 2X Shares NUGT.
Their best innovation to date, in my opinion, are the single-stock leveraged and inverse ETFs like the Direxion Daily TSLA Bull 2X Shares TSLL and the Direxion Daily TSLA Bear 1X Shares TSLS which offers a capital-efficient way to deploy a bearish view on Tesla TSLA.
They also offer single-stock leverage and inverse exposure on other Mag 7 names like Apple, Amazon, and NVIDIA.
But these leveraged and inverse ETF products carry special risks as well as rewards. That's why Ed and his team at Direxion are dedicated to education. Here are a couple of must-engage areas on their website to become more educated yourself before trading these products that can offer a double-edge sword of compounding and decay...
Understanding Leveraged & Inverse ETFs Video Series
And I think education is especially critical for investors because of the one or two-click trading available on most brokerage apps. But now there's a new obstacle to our learning. Allow me to explain.
Mathematical Literacy in the Age of ChatGPT
With the advent of large language models, or LLMs, there's a legitimate concern that people will stop doing their own "deep research."
From high school and college kids fudging on their papers... to traders and investors getting their financial education from social media.
In fact, in the conversations I have on X these days, I would say there is an epidemic of those getting their "minor in macro" from YouTube.
But you don't need a degree in economics to become a good investor or trader.
What you do need is math skills. I've said for decades that probability training is the antidote to behavioral biases that typically make our money disappear.
So imagine me at 29 years old, walking into the trading pits of the Chicago Mercantile Exchange still "allergic to algebra" like I was in high school and college.
But I was captivated by the raucous action on the trading floors where the average Joe and Jane from Chicago could play 3D chess with global markets in Japanese yen, pork bellies, and T-bill futures.
And because I wanted to stick around -- even though I was making only 6 bucks an hour as a clerk -- I hit the books. Specifically, the sacred texts of trading, Jack Schwager's Market Wizards series.
Market Wizards: Gandalf at Your Side
The one strength I brought with me into the pits was my love of reading. So I dove into the Market Wizards, which are all almost entirely based on tape-recorded interviews that Schwager did with successful commodity, futures, and currency traders of the 1970s, 1980's, and 1990s.
The interviews read like fireside war stories.
There's Richard Dennis who started in soybeans and went on to run a fund that did a big chunk of the S&P futures volume. He is probably most famous for training the Turtles.
And Paul Tudor Jones, who started trading cotton for his family on the New York Merc and is still doing global macro and appearing on CNBC.
Then we have the dynamic duo of George Soros and Stanley Druckenmiller who infamously broke the Bank of England in 1992.
There are a dozen more worth mentioning, but I've only got a few minutes here.
My main point is that after reading the first two books, I identified several common themes that I called The 6 Keys to the Kingdom:
>Psychology
>Risk Management
>Systems
>Consistency
>Discipline
>Probability
There was my Achilles heel with the last one: math.
So what did I do? I found more books. Not only was I reading about the complex connections between CME currency and interest rate futures and the global FX and bond markets, I was trying to understand the math of why soybeans, British pounds, or live cattle traded at a premium or a discount in the future.
It wasn't easy for a kid who got "queasy from equations" to grasp concepts like the "cost of carry."
Before Vegas, the Dice Were Loaded With Ignorance
More importantly, I had to learn the most basic math of probability. And I did that by reading the 375-year old story of a Renaissance gambler, the Chevalier de Mere, who knew the polymath Blaise Pascal and brought him a conundrum.
Old Antoine Gombaud (aka the Chevalier) offered wagers to daring souls with dice. And he couldn't figure out why one bet -- rolling at least ONE SIX in 4 throws of a single die -- was less likely than the second bet -- rolling at least one DOUBLE SIX in 24 throws of a pair of dice. By his calculations, they were equal.
Pascal threw himself into the challenge by engaging his mathematician friend Pierre de Fermat. And in a series of letters they exchanged in the 1650s, they solved the mystery and created the foundations of Monte Carlo and Wall Street.
This effort of mine, this work to know how probability worked, inspired me to learn basic statistics. And these were foundational for an understanding of the Black-Scholes options pricing model and volatility dynamics.
From Math Flunky to Science Junkie
And that is how I built a career for myself in the late 1990s and early 2000s. It was hard and confusing, with many accidental twists and fortuitous turns, but if I could go back, I wouldn't change a thing. It also ignited my passion for science like evolution, astrophysics, and neuroscience.
I'd always read books about these favorite topics, but now I could begin to understand the data measurements and statistics that were crucial tools for the scientists doing the work and trying to explain their findings to us.
I should add that part of my good fortune wasn't just found in books. I was also in the right place and time for two other reasons:
First, I was a clerk in a commodity options pit where I got to watch math geeks with pricing sheets work their magic making two-sided markets to paper (the incoming orders). They were primarily doing delta-neutral volatility arbitrage and I was fascinated to watch and learn in the pit and then try to simulate it on my own later.
Second, since Chicago was THE birthplace of options trading for stocks, commodities, and financial futures, we had the best teachers around. One in particular was Sheldon Natenberg, a math lover turned options trader who wrote the quintessential handbook Options Volatility & Pricing. He also taught classes at the Merc and I was lucky enough to take several.
For me it was total immersion with stories, experiences, and simulation -- just like when my Dad taught me to fly an airplane at 15 years old. In fact, I give him credit for teaching me how to think in terms of planning and contingency long before I applied those skills to markets.
AI is a Message from the Future: Step Away from the Xbox
And that's why my personal mission for the rest of my days is to inspire as many kids as possible to find their passion for science and math. The world is changing very fast, and we can't be sure what jobs will still be here a decade from now or what new industries will be created.
But having basic agility with science and math concepts will always be crucial to navigate these shifting landscapes. Since the US still graduates 75% of high schoolers below proficiency in math, I know there are lots of kids out there like I was.
Many just need a different way to learn the material. Imagine all the kids who might actually love science and math if only their internal spark of curiosity were ignited with alternatives to text books full of equations -- like VR and AR driven by AI. I actually pitched this idea to the National Science Foundation (NSF) in 2017. Some have said I was channeling ChatGPT before any of us knew what an LLM was.
In a sense, we are all like the Turtles of Richard Dennis when we first start out -- able to learn anything with the right instruction.
I ask almost every parent and teen I meet if they play video games. Then I ask them to consider how much smarter they would become if they put down the video controller for 1 or 2 hours a week and learn how an NVIDIA GPU actually works to create those cool graphics.
Here is one of my introductory articles about making science and math come alive for teens...
Curiosity Solves Everything: How the Wright Brothers Changed History
And you can find my 2017 proposal to the NSF for a youth STEM Learning Design Engine using AI, VR, and AR at the pinned post on my X feed @KevinBCook.
Okay enough of my sermon on math, and learning, and trading. My guest today is someone who probably knows more than I do about all three. And he's definitely met more real-life Market Wizards than I have.
Go listen to Ed explain the ins and outs of trading leveraged and inverse ETFs.
Two More for the Road
And here are two more good education resources for learning about Direxion tools and tactics for managing your risk/reward...
Leveraged and Inverse ETF Education Center
Trading the Ups and Downs of NVDA
Kevin Cook is a Senior Stock Strategist for Zacks Investment Research where he runs the TAZR Trader portfolio and makes studying NVIDIA AI a full-time job.
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