Creating a Scrappy Trading Business that Focuses on Trading and NOT Engineering
Real trading is not engineering (in most cases).
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“A mediocre trader in an inefficient market often outperforms a brilliant trader competing against the world's best.“
Over the years, I’ve met many great solo traders.
The best of them, all shared similar beliefs:
Never claimed that their success is due to their complex automation models.
Had an extreme awareness of why they were profitable.
Kept their models extremely simple.
Mostly executed them by hand or using simple excel.
Although there’s nothing wrong with automation, many fail to realize that it is not what will make them profitable, by any means.
More often than not, it is what will slow them down from getting at what they want:
Being profitable traders.
The trading world is filled with failed traders that built beautiful systems but never made money or severely underperform the benchmarks.
This, and other reasons, creates an endless loop of people that want to appear smart, rather than showcasing their true professional failures.
Ever heard about that friend or family member that wanted to start their own business, but never got to it, and every time you ask them they say:
It’s not the right time.
The market isn’t good for it right now.
I need to ensure that it is perfect when I launch it.
While at the same time the guy running a small shop, selling cold natural orange juice near a beach, during a hot summer season, is making a killing because he knows fundamentally what his market needs.
Well, traders fall into the same behavior.
The most successful traders I've encountered run strategies simple enough to be "traded by hand" with just a handful of trades per month. They focus obsessively on understanding why their edge exists, not building elaborate infrastructure around it.
Consider what happens when engineering takes over. Months spent optimizing execution algorithms that shave off 0.01% in slippage, while ignoring 100x or 1000x that 0.01%, because the market was in season for their type of trading.
Ask yourself: What am I actually getting paid for?
Successful trading businesses get compensated for:
Taking risks others avoid.
Providing liquidity when it's scarce.
Spotting structural inefficiencies in less competitive markets.
Exploiting price-insensitive flows from institutional traders.
Your engineering should support these functions, not replace them. When evaluating any new initiative, start with "What position should I be holding?" rather than "What tools should I build?".
Selecting the Right Markets for Your Scrappy Operation
Table selection may be the single most important decision you'll make as a trader. Yet too many new traders jump straight into the most liquid, competitive markets like S&P 500 futures or FX, where sophisticated players have been dominating for decades.
Your scrappy operation needs to fish where others aren't casting their nets.
Look for markets with structural inefficiencies that larger players either can't or won't pursue. These include:
- Emerging or frontier markets where institutional participation is limited
- New assets or derivatives that haven't attracted professional attention
- Less liquid securities where big funds can't deploy meaningful capital
The key is finding venues with price-insensitive buyers and sellers—market participants who need to transact regardless of price. Here’s a few examples:
Think liquidated crypto traders.
Mandated institutional rebalancing flows.
Retail investors following rigid investment rules.
Be willing to check your ego at the door. As one trader bluntly puts it: "Oh but I don't wanna be a crypto trader, I style myself a man of finance."
If that's your attitude, you're choosing reputation over profits. The most profitable niches are often in "unsexy" markets that sophisticated professionals avoid.
Your edge should answer the question: "Who do I want to trade against?"
The answer should be: "The least sophisticated counterparties possible."'
Remember this uncomfortable truth: table selection matters more than trading skill. A mediocre trader in an inefficient market often outperforms a brilliant trader competing against the world's best.
Four Viable Business Models for Scrappy Traders
Instead of starting with engineering, start by choosing a business model that aligns with your capabilities and temperament. Here are four viable approaches that require minimal engineering:
1- The Reversion Trader
This model capitalizes on short-term market dislocations caused by unpredictable large flows. When institutions need to move significant capital quickly, they often create temporary price distortions. Your job? Be ready to take the other side.
"Being right on average is enough".
You don't need perfect accuracy - just a consistent process for identifying excessive moves and the discipline to act when opportunities arise. Examples include trading equity index futures spreads when they become dislocated or providing liquidity during liquidity crunches.
2- The Flow Anticipator
Some institutional flows are predictable:
Month-end rebalances.
Option expiries.
Tax-related selling.
By positioning ahead of these known events, you can profit from price-insensitive trading.
This model requires understanding market mechanics and participant constraints rather than complex algorithms.
You're essentially asking, "Who needs to trade soon, and how can I position to benefit from their flows?"
3- The Risk Premium Harvester
Perhaps the simplest and most reliable approach is getting paid to take risks others avoid. Many market participants willingly pay premiums to reduce their exposure to certain risks.
I mostly develop and write about these kinds of strategies for the premium members of this newsletter:
By systematically collecting these premiums with proper risk management, you can build a sustainable business. Examples include:
Yield curve carry trades.
Selling volatility in calm markets.
Providing liquidity in less popular assets.
This approach requires emotional discipline rather than technical sophistication.
4- The Opportunistic Specialist
New or structurally inefficient markets often present opportunities for traders willing to develop specialized knowledge. By focusing on niche areas where sophisticated competition hasn't arrived, you can exploit basic inefficiencies.
This might involve arbitrage between similar assets trading on different venues or developing simple models for pricing new financial products relative to established ones.
Here’s a practical example of one of these strategies that I ran quite recently in my own portfolio:
The key is becoming a specialist in areas that larger players overlook due to their size or mandate constraints.
When selecting your model, be honest about your strengths and limitations.
Are you emotionally equipped for the stress of reversion trading?
Do you have the time to monitor flow patterns?
Can you handle the volatility of risk premium harvesting?
Your trading style should fit your personality and resources, not just chase the highest theoretical returns.
Practical Portfolio Construction for Small Operations
Another powerful concept in trading isn't a secret indicator or algorithm - it's running multiple uncorrelated strategies simultaneously.
When your crypto trend following strategy struggles during choppy markets, your fixed income carry trade might be thriving. This portfolio approach smooths your equity curve dramatically, allowing you to endure the inevitable drawdowns that would otherwise knock you out of the game.
Position sizing deserves religious attention. Remember this trading axiom:
Your worst day is not in your backtest, it's in your future.
Size each strategy conservatively enough that a major adverse move won't threaten your overall capital. Here’s an article I wrote on sizing:
When in doubt, trade smaller until you've proven a strategy's reliability in live markets.
Implement volatility targeting to standardize risk across different positions. This means scaling position sizes inversely to volatility - taking smaller positions in highly volatile markets and larger ones in calmer markets. This simple technique ensures no single position dominates your risk profile.
Starting small is a strategic advantage, not a limitation.
Begin with modest allocations to each strategy and let compounding work its magic. As strategies demonstrate consistent performance, gradually increase allocations. This patient approach builds confidence while preserving capital.
Finally, focus ruthlessly on portfolio-level results rather than obsessing over individual trades or strategies.
Some components will always underperform - that's the nature of diversification. What matters is the overall portfolio trajectory, not the performance of any single piece.
Implementation: From Idea to Execution
Turning your trading ideas into reality doesn't require an engineering department and it’s a fundamental step to understand if you’re right about your edge.
The most successful scrappy trading operations follow a pragmatic path that prioritizes market validation over technical perfection.
Start with the simplest possible implementation to test your edge.
This might mean manually executing trades in a spreadsheet for a few weeks.
Remember, if your edge isn't viable with simple implementations, it probably won't hold up in complex implementations either.
Focus relentlessly on the velocity of experimental validation. Can you quickly determine whether an idea has merit? Rather than spending months building infrastructure for an unproven strategy, develop lightweight frameworks that let you rapidly test hypotheses. As one trader put it: "I'd rather test ten simple ideas than a perfect complex one."
Before diving into sophisticated strategies, ensure you have sufficient operational infrastructure. This means:
Reliable data feeds.
Basic position tracking.
Simple risk management.
These fundamentals must be rock-solid before adding complexity.
When that foundation is in place, you can automate the boring parts—routine data cleaning, standard calculations, and basic reporting—to focus your precious time on finding edges.
A practical workflow might look like:
Research phase: Develop a hypothesis about market inefficiency
Basic model: Create the simplest version that can test your idea
Manual trading: Execute by hand to verify real-world performance
Gradual automation: Add technology only where it clearly saves time or reduces errors
Remember that your goal is to stay focused on identifying and exploiting market inefficiencies—not building beautiful systems that don't make money.
When in doubt, ask yourself: "Is this engineering work helping me hold better positions, or am I just avoiding the hard work of truly understanding markets?
I hope you’ve enjoyed today’s article!
Ps… Looking to Work With Me?
After testing 100’s of trading strategies and spending 1,000’s of hours studying trading and building my own models, I had a few clients reach out to work with me and the outcomes have been quite good so far!
I’ve helped multiple clients now:
Develop their first systematic model
Help reviewing their current trading processes
Build solid frameworks on trading system development
Stop wasting money and time on bad ideas
Develop better risk management models
And much more…
If you want my custom help on your trading business, or would like to work with me, book a free 15-minute consultation call:
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Disclaimer: The content and information provided by the Trading Research Hub, including all other materials, are for educational and informational purposes only and should not be considered financial advice or a recommendation to buy or sell any type of security or investment. Always conduct your own research and consult with a licensed financial professional before making any investment decisions. Trading and investing can involve significant risk of loss, and you should understand these risks before making any financial decisions.