Trade Like a Quant Bootcamp is currently closed for enrollment

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Here’s an overview of the course

Trading is hard if you don’t have a plan

Most traders don’t take the problem seriously enough. They jump from idea to idea. They pass over high-probability edges in favor of heroic ideas that are unlikely to pay off.

This course is for the trader, ready to get serious about realistic, high-probability trading approaches.

Getting serious about trading involves two main things:

Market Intuition – understanding the market, its players and the kind of things that make money.

AnalyticsData Analysis and Portfolio Construction Skills – being able to create and test market hypotheses using simple data analysis techniques.

This four-week trading course runs in two parts:

The first, Trade like a Quant, is all about gaining market intuition.

Through explicit examples of real systematic trading strategies, you’ll learn the fundamentals of extracting edge from the market.  

The second, Quant like a Trader, is an introduction to the techniques you need.

The simple data analysis and portfolio construction tools you can use to discover market inefficiencies, test trading ideas and manage trading.

By the end of the course, you’ll have:

A realistic understanding of the market (a highly efficient machine, not a casino)

A business plan for exploiting it profitably, based on selecting the least competitive games

Many examples of specific systematic trading strategies spanning multiple asset classes

A set of tools and techniques to manage your trading and do effective research and strategy development.

In this course, you’ll learn explicit examples of real, effective systematic trading strategies, including:

Risk premia harvesting in equity indexes and government bonds, diversified with alternative assets.

Crypto carry trades, which exploit the supply/demand dynamics of leveraged crypto futures.

Turn-of-the-month “window dressing” effects in treasury bonds

Trading large rebalance flows in stocks and bond indexes

Exploiting lopsided positioning in VIX derivatives

Trading NAV discounts in close-end funds and ETFs in times of severe market stress

Trading structural supply/demand imbalances in crypto futures

Trend and seasonality effects in cryptocurrencies

These are simple uncompetitive strategies that you could trade as a part-time trader.

You’ll learn about the following strategies in less detail (you won’t be able to trade most of these, but they are excellent case studies):

show_chart Created with Sketch. Market Making

show_chart Created with Sketch. ETF Arbitrage

show_chart Created with Sketch. Business-hour seasonality in foreign exchange

show_chart Created with Sketch. Post-earnings announcement drift in stocks

show_chart Created with Sketch. ADR pairs trading and futures spreading in severe market stress

show_chart Created with Sketch. Trading the FTX leveraged token rebalance

show_chart Created with Sketch. Trading brand-new products: example of the FTX MOVE contract

show_chart Created with Sketch. Buying liquidations in crypto futures

show_chart Created with Sketch. Cross-exchange spread trading in crypto

show_chart Created with Sketch. Commodity Carry (in the past)

show_chart Created with Sketch. Equity Pairs Trading and modern statistical arbitrage

You’ll also learn effective, repeatable techniques that you can apply to your trading, including:

How to think about market structure and the price discovery process

How to put together a realistic business strategy for success as a part-time trader

How to align your trading with large sources of drift, so you are likely to “be wrong and still make money”

A process for thinking about and defining market edge – “why will somebody trade at bad prices, and why do you get to trade with them?”

Minimizing costs in your trading and navigating the uncertain return / certain cost trade-off.

How to safely navigate periods of extreme market stress: playing defense, then offense.

Portfolio Construction: How to size positions, manage risk, hedge tails, and construct an effective trading portfolio.


We will teach you how to investigate market edges using simple data analysis tools, including:

How to uncover assumptions and create testable hypotheses

Using data in the most efficient way possible

Minimizing and accepting sources of bias in your data

Pulling data from APIs

Data munging: changing the shape of your data

Factor analysis

Event Studies and markout analysis

Vector- and event-based simulation

Weighing evidence and dealing with uncertainty.

Robot Wealth Bootcamps have been tried and tested by over 1,200 traders.

Bootcamp opens for enrollment April 2024.

What do I get if I sign up for Bootcamp?

Bootcamp is an interactive learning experience, with live support from the RW team and real-time connection with your peers. You can do it at your own pace, and discuss in real-time with us too.

Video lessons, slide-based lectures and written content.

Training material is released week-by-week to keep everyone on the same page. You can go through it whenever you like, and it’ll always be available.

Some of it is pre-recorded from the last times we ran the course. Some of it is created as we go along, based on your questions and challenges and new things we find interesting.

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Weekly interactive live Q&A webinars with James and Kris.

Every Thursday, we hold a Q&A webinar on Zoom to discuss the course content.

We alternate the times of the webinar by 12 hours each week, to ensure everyone can attend sometimes.

All webinars are recorded so that you can catch up on any you miss or re-watch at your own pace.

Exclusive Discord server where you can connect in real-time with your instructors and Bootcamp peers.

This is the main place where we talk and respond to questions.

A supportive community of part-time traders. Connect, collaborate and troubleshoot with your trading peers from across the globe.

Custom learning tools and clean data that’s ready to use, with comprehensive instructions on how to use it.

Lifetime access to all course material so you’ll never fall behind. (Compatible on desktop, mobile and tablet devices.)

You get lifetime access to all Bootcamp training material.

As part of your enrollment you get lifetime access to all the course materials so you can take it entirely at your own pace if our schedule doesn’t quite work for you.

Here’s what you’ll learn:

The Complete Curriculum we’ll be working through, together, over the next 4 weeks.

Week 0

Enrolment & Initiation

You will get immediate access to the Discord community from the time you sign up. So introduce yourself, say hello, and spark up any discussion with us and the team.

You’ll also have access to some bonus background material from previous bootcamps, which you can review whilst you wait for course kickoff on Monday 30th October.

Module 1

Seeing the Market for What It Really Is

Module 1 is available as soon as you sign-up.

In this module, you’ll build up a mental model of the market as it really is (rather than what you’d like it to be!) and start to put together a business plan for making money as a part-time trader.

Buy too cheap / Sell too rich / Don’t get rekt

We start with the simple observation that successful trading requires you to:

  • buy things that are too cheap
  • sell things that are too rich
  • avoid unnecessary risks that lead to you losing lots of money.

We explore how trades would play out if you were the perfect trader, acting with perfect information. And we find that, even in those circumstances, luck or randomness plays a significant role in trading outcomes.

A good trade isn’t one that makes money, it’s one with positive expectation.

Market Structure and Price Discovery

Next, we confront reality.

You’ll learn that the goal of the market mechanism is to find the price that is the balancing point of supply and demand where the most trading happens.

Through many examples, you’ll see how this plays out in:

  • batch auctions, such as the closing auction in stocks
  • the central limit order book
  • automated market makers in crypto swaps

A Realistic Model of the Market

Many traders start off on the wrong foot because they think of the market as a big casino. They think it’s an easily exploitable game driven by fear, greed, and emotions. They see people throwing money around in unsophisticated ways and assume the market must be highly inefficient.

Running through these examples, you’ll begin to understand why the market is highly efficient, despite the presence of lots of gambling maniacs.

And why trading is so hard.

And that’s because we’re trading with many other people. And, although there might be plenty of people willing to trade at bad prices, there’s an extremely competitive race to get to trade with those people.

Just because there’s “dumb money” in the market, doesn’t mean you get to trade with it!

Appreciation of the true nature of the highly competitive game we are playing leads to two important realizations:

First, it’s quite hard to lose money consistently without doing something dumb. We call these dumb things “The Mortal Sins”, and they include:

  • Trading Too Much
  • Trading Too Big
  • Trying To Be a Hero.

These behaviors are sure to lose you money in the long run.

Avoiding these is your first and most important mission as a trader.

Second, as a small part-time trader, you can’t outcompete the best in the business. You need to search out the easiest, least-competitive games to build your business plan around.

And that’s what we start to do in Module 1.

You’ll start to outline a core strategy to exploit market returns, which we visualize as a pyramid. In the pyramid:

  • We need at least one “stonkingly-obvious high-probability edge” to build our trading upon. And it should be as “win-win” and uncompetitive as possible. You want at least one thing you can be very certain about.
  • As long as we avoid the Mortal Sins, the market doesn’t punish us that much for being wrong. This gives us the confidence to go after slightly more competitive active edges.
  • So we look to “Trade More Sh*t” and add simple systematic strategies that exploit market inefficiencies. We look at strategies that exploit large rebalance flows and misaligned trader objectives. These are noisy edges that are less attractive to big players.
  • When we combine noisy edges together, the whole is greater than the sum of the parts. Diversifying in this way is a good idea because it spreads our bets and tends to reduce the variance of our trading portfolio.

By the end of module 1, you’ll start seeing the market realistically, rather than hopefully. And you’ll start building a realistic strategy for exploiting it.

Module 2

Stonkingly Obvious High-Probability Edges

Module 2 is available from the 30th of October.

If you start a business venture, it’s clear you need an obvious, reliable way to make money. You wouldn’t try to blag it.

“I’m smart and hard-working” is not a business case.

You need a stonkingly obvious way to get paid.

Drawing lines on a chart and hoping you can figure out when to buy and sell is NOT a stonkingly obvious way to get paid. It depends on your discretion and skill. It’s a lousy business case. I wouldn’t lend you money to do that.

Throwing features into a machine learning algorithm is a lousy business case too. There’s no reason to think you’d get paid for that. I wouldn’t lend you money to do that either.

In this module, you’ll learn about the following systematic strategies which have historically been very effective:

  • market-making
  • ETF arbitrage
  • commodity carry and trend-following
  • equity pairs trading
  • risk premia harvesting
  • crypto basis effects
  • VIX futures basis effects.

You’ll discover they have a few features in common.

And the big one is that the reason these trades “worked” is that you were being paid for:

  • doing something useful (though this may not be immediately obvious)
  • taking on risk or “unattractive” work (otherwise everyone would do it)
  • doing it well

If module 1 was about putting together a high-level business strategy, this is about making sure the business case stacks up.

Every business needs a business case that makes sense.

So we look to build your portfolio around at least one specific “stonkingly obvious edge”.

We pick a “stonkingly obvious edge” and we’ll go in-depth, helping you to specify fully systematic trading rules and processes to trade it.

  • Risk Premia Harvesting in stock indexes and government bonds – diversified with alternative assets. We look to exploit the long-run positive drift of risk assets in a diversified, risk-managed way.

And we’ll close out the week with a discussion on how not to screw up the best edges by overcomplicating them.

Module 3

Inefficiencies and Where to Find Them

Module 3 is available from the 6th of November.

In module 3, you’re going to learn about Finding and Exploiting Inefficiencies.

Now we’ve looked at “stonkingly obvious high-probability” edges, we can start looking at slightly more competitive games which exploit market inefficiencies.

Strategies like risk premia harvesting are “win-win”. Nobody needs to “lose out” for you to harness excess returns there. That’s why we can easily believe in it persisting.

Exploiting market inefficiencies is “win-lose”, at least if you think about expected returns. Your excess returns come from “buying from someone too cheap”. Or “selling to someone too expensive”. Someone loses out.

So how do we find these opportunities?

First, we find other traders who are prepared to sell to us too cheap or buy from us too rich.

We’ll return to our model of market structure and price discovery and show how tradeable inefficiencies can arise due to:

  • market microstructure (stale orders or AMM prices)
  • conditional risk premia, or a desire for certain “fashionable” exposures
  • lumpy trading flow – due to random large trades or forced trading
  • under-reaction (trend)
  • over-reaction (reversion)

But maybe even more importantly, we need inefficiencies that aren’t being completely “gobbled up” by the bigger aggressive players.

And how do we make sure we are the ones that get the opportunity to trade these inefficiencies, given there are more sophisticated, faster players trying to do the same thing?

These are the questions we’ll explore together in this module.

You’ll discover that you need two things to be true:

First, you need to find a time when a large group is willing or forced to trade at inopportune prices. You’ll need to understand the constraints and incentives of the big “end users” in the market.

Second, you need inefficiencies that aren’t completely “gobbled up” by the bigger “aggressive” players.

There is a reason trading firms buy order flow from Robinhood. They can eat all the edge there. But not everything is so neatly contained.

Inefficiencies can “leak out” because:

  • the inefficiency is too big to be fully absorbed by the market
  • the flows that generate it are too noisy or unpredictable to be fully absorbed by the market
  • the opportunity is too small, too noisy, too capital intensive, or too awkward to be worth bigger players getting out of bed for.

Understanding this leads to us being able to identify inefficiencies that you can exploit.

To help you through this process, you’ll learn how to make simple testable “elevator pitches” for the inefficiencies we’ll look at.

These “elevator pitches” are simple statements of:

  • why you think the inefficiency exists
  • why you think you can exploit it.

A 5-year-old should be able to understand why your edge makes money.

You’ll go through examples with the team. They’ll look like this:

  • What: Mechanical wealth management equity/bond rebalance flows are very large.
  • Why: Due to their size they might not be fully dispersed when performance differences between the asset classes (and, therefore, rebalance trades) are very large.
  • How: We might get paid for buying what they’re selling around month-end.
Click the twitter image to read the rest of the thread

If doing this sounds intimidating, it’s probably because it is, a little. You probably aren’t used to thinking like this. And maybe you don’t have the experience to trust your instincts yet. But, through lots of discussion, examples, and investigation, we will work with you to make sure you “get it”.

You’ll learn about 13 different inefficiencies across many different asset classes, and how they might be exploited with simple systematic trading rules:

  • Turn-of-the-month “window dressing” effects in treasury bonds
  • Business day seasonality effects in foreign exchange
  • Supplying liquidity to large rebalance flows
  • Post-earnings announcement drift in stocks
  • Taking advantage of lopsided positioning in VIX derivatives
  • Buying close-end funds or ETFs trading at discounts in market stress
  • ADR pairs trading or futures spreading in market stress
  • Trading leveraged token rebalances
  • Trading brand-new products: example of the FTX MOVE contract
  • Shorting crypto perpetual swaps with structural supply/demand imbalances
  • Trend and seasonality effects in crypto
  • Buying liquidations in crypto futures
  • Cross-exchange spread trading in crypto

Module 4

Working with Financial Data

Modules 4 and 5 are available from the 20th of November.

So far in the course, we’ve concentrated on growing your market intuition and trading smarts. In Module 5, you’ll learn the basics of doing effective quant research.

This isn’t going to be super-complicated nerd stuff.

This is simple data analysis you can do in Excel or a statistical programming language like R or Python.

These are the simple basics you need to test out ideas effectively and model market phenomena.

You’ll start by learning how to uncover assumptions you make about the markets and form them into testable hypotheses.

For example, you might say that you use a stop loss on your trades to “control risk”.

Well, what is that risk? What is it not? What risk do you care about? What needs to be true about the markets for that rule to actually do what you want?

Much of this is a process of “calling bullshit” on yourself. Then transforming the assumptions you have made into something you can test out: something you can look for evidence of in market data.

Typically, this requires getting hold of some data. So you’ll learn how to do that, and how to validate, clean, and reshape your data if you need to.

Finally, we’ll give examples of working with price and return data, including various gotchas.

By the end of module 4, you should be confident with the basic nuts and bolts of working with financial data.

Module 5

YogaResearch Mindset and Data Analysis Techniques

Module 5 is available with module 4 from the 20th of November.

Now we can think about data analysis and research.

First, we talk about the mindset required to do effective research, and the importance of moving fast, not being prissy, and iterating on the simplest reasonable thing to disprove your ideas.

I want to give you the confidence to get out there, make a mess, and learn some lessons.

You can always loop back.

And this must start with a discussion on bias. Everything we look at is going to be biased in some way. You have to accept this, but it’s important to understand how you can best control for it in your analysis.

Next we look at the basics of return prediction – which, after all, is what most of trading is about.

How do we look for factors that help us predict asset returns, or future returns relative to other assets?

We’ll cover the essentials of the following techniques:

  • Data munging: changing the shape of your data
  • Plotting histograms: visualizing the distribution of your data
  • Plotting time-series charts
  • Dealing with non-stationarity: normalizing data
  • Scatterplots: does x explain y?
  • Factor analysis
  • Event studies and markout analysis

Next, we’ll look at how simulation can help us answer questions, even if we’re really bad at maths.

You might not always be able to work all problems in closed form, as I often can’t, but we’ll show you how you can use simulation to answer questions.

Questions like:

  • what is the probability an effect I observe is due to random chance?
  • under what conditions might a stop loss or time stop rule be helpful?

Next, we’ll look at how we can design a set of processes to exploit the effects we observe in the market.

Here, we allow everything to be driven by the effect we think exists. The effect comes first, then the rules and processes to exploit it.

We’ll also look at backtesting trading strategies, which is something we like to do if I can do it easily, though we’ll happily trade things without a backtest if we’re confident enough in the idea.

By the end of Module 5, you should be confident in your skills to do exploratory data analysis and design simple systematic strategies.

Module 6

Simulation, Portfolio Construction, and the Fine Art of Sitting on your Hands

Module 6 is available from the 27th of November.

In the final module, you’ll learn how you can use simulation to help in portfolio decision-making, sizing, and risk management.

You’ll learn a simple quantitative approach to portfolio management.

You’ll learn how to put simple trading strategies together to create a high-performing portfolio.

You can create extraordinary results at the portfolio level from many noisy strategies using “ensemble” methods.

Or, as we like to say, “Trading More S**t”.

By the end of module 6 you’ll understand:

  • a system for thinking about portfolio construction, both practically and emotionally
  • how to set portfolio management objectives
  • how to identify risk factors
  • how to size and rebalance positions and strategy exposures
  • how to attribute pnl to return drivers in your portfolio
  • what to do when things get weird
  • how to chill out and “Trade More S**t”

You won’t be left with your hands waving in the air.

We’ll help you think about how to structure things to meet your unique objectives and risk tolerance. And you will know what you should do with the next addition to your systematic trading portfolio.

We finish the course with a discussion of what’s next, and the reassurance that “There Will Always Be More Trades“.

The trader needs to balance confidence and humility. You must never pretend that trading is not hard. You must never think you’ve got it all figured out. A certain amount of anxiety that you are losing your edge is appropriate.

But you must be confident in your ability to find new trades.

You are smart. You have good tools. You have solid strategies. You have a solid approach to the markets. You have examples of good, quick, pragmatic research. You have tried-and-tested strategy frameworks. You have realistic expectations about the market mayhem. You have a team of people who will help you and share ideas. There will always be new trades and new ideas.

You just need to stay relaxed, think clearly, don’t get greedy, stay true to the fundamentals, and generously give your time to others.

Click the tweet image to read the full thread

Bonus Module

Options, Volatility, Tail Hedging, and Market Chaos

We’ve taken this module out of the main course, but I think some of you will still find it interesting, so it’s presented as an optional bonus module.

In this module we look at options and how you can use them to protect a portfolio against extreme, unpredictable events. We also discuss the dynamics of equity volatility and present a systematic strategy for trading VIX derivatives. We finish the module with a discussion of the unique opportunities that present themselves in times of extreme market stress.

One of the challenges of active trading is that:

  • the best opportunities tend to occur in the eye of the storm, when normal market relationships are stretched
  • but that’s usually after a significant drawdown in most effective strategies.

So, if you’re not careful, you can end up in a situation where you have the least buying power just when you want it the most.

Options have useful properties to help us try to navigate this. We might choose to “pay up” for protection against a market crash, to cushion drawdowns, and ensure that we have the capital we need to take advantage of opportunities in the chaos.

We’ll look at very simple tail hedging techniques.

Next, we look at a time-varying volatility risk premium harvesting strategy in VIX derivatives.

In module 2 you learned about Risk Premia Harvesting. You learned that you tended to make excess returns over the long haul for taking on certain risks.

We didn’t try to “time” our exposure to the “risk premia’ in module 2 because:

  • these premia appear to be very large
  • every time we are not exposed to them we “miss out” on the premia
  • there’s a lot of evidence that timing our allocation to risk assets is hard
  • we didn’t want to screw up a “stonkingly obvious high-probability edge” by overcomplicating it.

However, there is some evidence that some risks are not rewarded all the time. In fact, there’s evidence that taking on some risks can sometimes appear to be quite a bad idea. A good example of this is what we call the Volatility Risk Premium.

On average, equity index options look to be slightly too expensive. It is easy to understand why. You learned earlier that an effective way to “insure” a portfolio of risk assets is to buy options that pay off large in bad times.

“Selling volatility” (using equity index options or VIX products) tends to receive a risk premium because it tends to incur large losses in market crashes.

But there’s evidence that it’s a bad bet to take on that risk all the time. In fact, due to very lopsided customer positioning, going long volatility tactically can be an excellent trade at times.

We’ll walk through this dynamic and describe a simple trading strategy to exploit these effects using VIX ETPs or VIX futures.

We’ll investigate the time-series properties of VIX. And you’ll note that it’s easy to predict:

  • It tends to cluster (stay the same in the short term)
  • It tends to revert to its mean over the longer term
  • It is positively skewed
  • It tends to have a floor under which it won’t go lower
  • It tends to increase when the equity index declines
  • It tends to show conditional trend effects.

It is not surprising that VIX is predictable, because you can’t trade VIX. So there is no competitive mechanism to drive out inefficiency.

So we’ll look at VX futures and observe significant basis effects in the futures prices. If VIX is very low, the futures will tend to trade higher than the index. If VIX is very high, the futures will tend to trade lower than the index.

Why?

Because everyone knows volatility is likely to revert from extreme values.

So you won’t find anyone prepared to sell you VIX futures at 9% when VIX is at 9%. The sellers will demand a premium and the buyers will be happy to pay – because everyone knows VIX is more likely to go up.

The futures contracts tend to “price in” the obvious, predictable changes in volatility. You’ll see that trading VIX products is not as simple as “predicting VIX”.

You’ll model the “basis” as made up of two elements:

  • Predictable future expected changes in volatility.
  • The left-over stuff that’s not explained by that – which we call a “time-varying risk premium”.

This leads to a simple systematic strategy to attempt to exploit the time-varying volatility risk premium. This is the most untamed of the strategies we’re looking at. So we’ll have a robust discussion about skew, risk, and sizing.

Finally, we’ll look at strategies for taking advantage of market stress. Some of the very best opportunities present themselves in times of severe market stress, because:

  • leveraged traders are trading when they have to, not when they want to
  • arbitrage trading is more constrained than usual.

This means that some of the normal “arbitrage relationships” between instruments can become stretched. Sometimes you can buy $100 worth of assets for $90.

We look at simple trades you can use to take advantage of market stress in Close-End Funds, ETFs, ADRs, equity futures, and crypto futures.

Ready to start?

We are open for enrollments April 2024. Join the waitlist for udpates.

Here’s what some of our past students have to say about their Robot Wealth Bootcamp experience…

30-Day Money-Back Guarantee

If you start the course and decide it’s not quite what you need at this point in your trading journey, we genuinely don’t want your money.

All Robot Wealth Bootcamps come with a 30-day money-back guarantee.

This means you have 30 days to dive in and experience the course — to watch the training videos, have a go at implementing the strategies, join the live webinar sessions, get support and make some genuine connections in the private Discord server. If the Bootcamp experience still isn’t hitting the mark for you, we will refund your full enrollment fee, no questions asked.

Enrollment info

$499 USD

One payment

Enrollment opens April 2024.

Your enrollment includes:

4 weeks of interactive training including video lessons, written content and custom tools

4 weekly LIVE Q&A Webinars

Private Discord server for real-time discussion with your instructors and peers

A quantitative approach to portfolio construction and management

Lifetime access to all training material

BONUS Embrace the Mayhem video course

BONUS Options, Volatility, Tail Hedging and Navigating Market Chaos Module

BONUS Previous Course Webinar Recordings

BONUS Market Basics

BONUS Doing Financial Data Analysis in R

BONUS Simple Cryptocurrency Research in R

30-Day Money-Back Guarantee

All Robot Wealth Bootcamps come with a 30-day money-back guarantee.

If you want a refund within 30 days for any reason, just let us know and we’ll send your money back, no questions asked.

Enrollment closes at midnight (UTC) next Monday and we won’t open again until Q2 2024. We close because we want to dedicate our attention fully to our members.

​If you have any pre-purchase questions about Bootcamp, we are happy to help. Email us at [email protected]

Meet your instructors

James Hodges

Your Teacher

“I left a career in institutional finance and tech to trade STIR futures spreads and equity volatility. Ten years later, I’m now running high-frequency trading bots in the cryptocurrency markets. I love teaching, strive to explain things as simply and accessibly as possible, and get enormous satisfaction from seeing students “get it” for the first time.”
You can find me on twitter as @therobotjames

Kris Longmore

Founder of Robot Wealth

“After a 10-year engineering career, I became a hedge fund quant and later consulted with Asia-Pacific’s biggest fund managers on AI and ML before settling in to quant prop trading. Working with the RW community brings me an immense amount of satisfaction.”

FAQ’s

I’m a trading beginner – is this course for me?

We assume some fundamentals about financial markets and products, but don’t assume that you have any past experience trading. Fundamental concepts are explained from first principles throughout and you are welcome to ask any questions you have on Discord or on Zoom.

I’m not a skilled coder, can I still participate? 

Yes! You won’t need to write code. We assume you can use Microsoft Excel or Google Sheets. Some of our examples are in the R statistical programming language, but we don’t assume you can use it in the course, we’re just illustrating techniques.

I’m a discretionary trader, is this for me?

Yes, I think the course will be very valuable to you.

There is significant discretion to all trading, including the design of quant trading systems.

This course will help you quantify and test your discretionary judgement.

I don’t have much free time, can I still join Bootcamp?

There are a couple of ways to tackle Bootcamp.

To immerse yourself in the interactive experience of tackling Bootcamp as part of a community, we recommend 3-4 hours per week to keep on top of the course material, and assignments and to be involved in the community – but you can get more involved if you wish.

If you’re really pressed for time, you can keep up by attending the weekly webinar, or watching the replay.

If you prefer to learn at your own pace, you have lifetime access to the course content and can review the material at your convenience.

Will I get all the training at once or is it drip fed?

Training material is released weekly over the 4 weeks of Bootcamp.

Content Modules will be released every Monday. This includes videos, written material, and assignments. Content review webinars are held every week for the duration of Bootcamp with a Q&A session at the end of each webinar. All webinars are recorded so that if you are unable to attend you can catch up in your own time.

How is the course taught?

The course will be taught through a combination of video lessons, weekly live webinars, presentation slides, written materials, and our Bootcamp Discord server. 

We find this combination works well for those on a very tight schedule who struggle for free time, so they can stay on top of things more easily.

All live webinars are recorded and the worldwide breadth of our membership means that you’ll find someone online in the Discord workspace 24/7.

What kind of support will I get? 

Our Bootcamp Discord community is very active during the course. You’ll not only get help and insights from your instructors, James and Kris, along the entire journey but from your fellow teammates throughout Bootcamp.

Being an international community, you will always have other community members around to talk to. Questions are also addressed at the weekly live webinars and these sessions are recorded and posted online for you to review if you’re unable to make the live session.

You guys are based down under. I’m in Europe or the US. Will I be able to participate?

Yes – definitely! 

Our Bootcamps comprise people from all across the globe. We’ve had hundreds of Bootcamp participants from the northern hemisphere who have successfully completed Bootcamp.

We run the live webinar sessions at alternate times each week to try to accommodate everyone at least some of the time. 

All the webinars are recorded and made available for viewing soon after for you to watch at your convenience.

If you can’t make the webinar, you can submit questions you’d like answered ahead of time on Discord and we’ll address them during the session.

James and Kris are usually around on Discord enough that we cross paths with all timezones between us, and – due to the diversity and global depth of our member base – you can almost always find someone online in the Discord workspace at any time of the day or week.

I’m a non-native English speaker and am unsure if I can participate effectively.

The hardest thing for non-native English speakers who join us for Bootcamp is making sense of Kris’ Australian accent! But thankfully, James does most of the talking, and he speaks a lovely, clear version of British English.

In addition to webinars and video content, we also provide written content, which you can consume at your own pace. Your interaction with us will mostly be via the written word on Discord and submitting questions in webinars via the chat feature.

Also, if you did find that the language barriers were insurmountable, we will of course provide a full refund. Rest assured that if you wanted to, you can try out Bootcamp risk-free.

Do I need a lot of starting capital to join?

No. To quote our RW mantra: “Trade broad, trade small, trade humble”.

Of course, you need money to make money, but we recommend starting with an amount of capital that you are financially and emotionally able to lose without dire consequences, in a worst case scenario.

​That being said, our goal is to make your money grow, and as long as you have realistic expectations about what can be achieved with a small retail-level account, you’re in great company.

But I don’t have an expensive trading setup?

That’s fine! It would mostly be redundant, because you simply don’t need expensive setups to do well.

You just need a broker to be able to trade ETFs or access to a cryptocurrency exchange.

Everything else will be provided to you.

Where will I get the data I need for research?

We supply everything you need as part of Bootcamp.

How is this Bootcamp different to those we’ve run previously?

Trade like a Quant Bootcamp includes no automation, no coding, and the trading strategies we discuss are those that can be executed manually.

Automation and coding are great ways to scale a trading operation – but without the fundamentals in the place, they aren’t worth anything in the markets. The intent of Bootcamp is to help you become brilliant at the basics – the things that will set you up for a lifetime of sustainable, sensible trading. The strategies can be traded by hand with a very small time commitment. They also lend themselves to automation, but we won’t cover that in Bootcamp.

What other bootcamps/courses are available and when will they be open?

We offer Bootcamps twice a year, roughly every 6 months. We plan to run Trade Like a Quant bootcamp again around March/April 2024.

What are the next steps for my trading after Bootcamp?

First and foremost, you’ll have gained an appreciation for the most important aspects of running a serious systematic trading operation:

  • How to think about the market, its participants, and their constraints and incentives
  • How to find opportunities to get paid in the market and how to think about “edge”
  • How to put together simple trading rules to harness such opportunities
  • How to manage a portfolio of edges so that the whole is greater than the sum of the parts
  • How to avoid the mistakes that guarantee failure

Once you’ve got that stuff nailed, you’re on your way and are very well placed to develop your trading operation further. The most obvious next step would be finding more things to trade. Perhaps, depending on your goals and ability to commit time, you might think about automation.

If you’d like to continue with us after Bootcamp, we can help develop your trading operation further. You’ll get the opportunity to join our membership community.

I’m already an experienced trader, can I join the community directly?

We only accept people who’ve completed Bootcamp because:

  • There is a minimum level of knowledge that is required in order to get the most out of membership which we’ll make sure you get via Bootcamp
  • We like to keep things focused and moving forward (once, we tried letting people in directly without doing a Bootcamp, and essentially wound up having to run a mini-Bootcamp to get them up to speed…. was frustrating for members, newcomers, and us – we’ve learned our lesson!)
  • We share our life’s work inside Pro and like to get to know people beforehand
  • It isn’t for everyone, and doing a Bootcamp is the best way to get to know us and our approach before making the commitment.

Community membership is offered to all Bootcampers in the final week of Bootcamp so if you join Trade like a Quant today, you can be a RW Pro member within 4 weeks.

Do you use backtesting to find trading opportunities?

We use quant analysis and market knowledge to find opportunities (as well as less glamorous approaches such as talking to other traders!).

Backtesting is literally the final step in the process and really only serves to confirm that the thing that we researched could indeed be harnessed with simple trading rules under modeled cost constraints. We do a lot less backtesting than you probably think we do.

Can you give some statistics around the performance of the Bootcamp strategies?

Many strategies are discussed in bootcamp. Historically, their sharpe ratios have ranged from around 0.8 to 3.

But don’t read too much into that. The truth is that a backtest is only so useful for setting performance expectations. Real life performance is highly dependent on the actual specification and execution of the trading rules. And the only guarantee about market inefficiencies is that eventually they will disappear. We plan against this by trading a few of them – and adapting to the markets. Trading isn’t set and forget. It’s a grind.

Things that are quite useful in forming a view on whether a particular edge is worth pursuing in the future include:

  • Is there a compelling reason for the trade to exist and to persist? (ie why would I get paid for taking on this risk?)
  • Related, does the trade make sense given my model of the market, its actors, and their constraints?
  • Is the positive expected value of the edge supported by the data? (using simple quant analysis, we look for evidence of persistence and stability of the edge in the data across time and assets)

There’s more detail about these questions and how we’ll answer them in Bootcamp in the outline of the course curriculum.

What instruments do you trade in your own trading operations?

Right now, we’re trading global macro assets and cryptocurrencies. We trade some of the strategies we discuss in the bootcamp.

Will we be using Zorro in this course? Can you help me learn Zorro?

We won’t be using Zorro or any coding or automation during Bootcamp.

Trade like a Quant Bootcamp is focused on the fundamental lessons of running a systematic trading operation. We wanted to exclude anything that might distract from or obscure those important lessons – so there’s no coding, no automation, and no heavy quant stuff. The strategies are specifically designed such that a time-poor, part-time trader could manage them by hand with a small monthly time commitment. They do lend themselves to automation, which you may want to consider at some point after Bootcamp.

We have some training material around Zorro in our RW Pro membership group, which Bootcampers are invited to join at the conclusion of the course.

Join the waitlist to get email updates.

More testimonials from past Bootcampers…