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Most investors evaluating algorithmic trading have no framework for what to actually look at.
Jim Simons is the name everyone knows. The Medallion Fund is the reference point. But the gap between knowing that algorithmic trading exists and knowing how to evaluate a trading system is enormous, and most of the people deploying capital into algos right now are working without a checklist.
I've been working with trading algorithms since 2018, and more actively since 2023. Five things matter. In order.
1. Instruments traded.
The instrument determines everything downstream: scalability, risk layers, position sizing, your realistic expectations.
Highly liquid markets like futures, equities, forex, BTC and ETH each behave differently and reward different rule sets.
The mistake is treating them as interchangeable. A system that works on gold does not automatically work on the S&P, and a forex strategy ported to crypto is a different product entirely.
Pick one instrument, build the rules independently for that instrument, and stop borrowing logic across markets.
2. Approach.
Your directional thesis dictates the architecture. A long-only system needs downside risk mitigation as its primary design parameter: that is the whole game.
A long/short system is a different animal: you are stacking conditional approvals to confirm trend, override prior signals, and avoid whipsaw. Most retail algos blur these. Institutional ones do not. Decide what you are before you write a single rule.
3. Strategy.
Strategy is the intersection of position sizing, timeframe, and indicators.
The non-obvious truth is that you can be directionally correct on one timeframe and completely wrong on another, and both can be true simultaneously. Funds, trade desks, and family offices solve this with an Investment Policy Statement, a document that defines what the capital is for, what risk it can take, and what timeframe it operates on.
Anyone deploying capital into an algorithmic strategy should be able to articulate where that strategy fits in their own IPS. If they cannot, they are not investing.
They are gambling with extra steps.
4. Risk management.
Once a strategy aligns with an IPS, the next question is whether the software itself enforces the discipline.
Drawdown protections, override rules, position limits, kill switches. If those are not built in, you are looking at a black box: or worse, a self-built system iterated inside an AI feedback loop, which feels like progress and usually is not.
The harder problem, which I have run into over the years, is that developers do not want to ship.
Quants and engineers treat their systems like living organisms they want to keep improving, which is exactly the wrong instinct once real capital is deployed. A frozen parameter set with documented performance beats a constantly evolving one. Before you deploy, you need to understand the parameter set you are deploying, and then you need to let it run long enough for the market to give you real feedback.
You will not always be right. There will be winning months and losing months. A losing month does not mean the technology is broken. It could be the thesis was wrong, the calibration was wrong, or the thesis itself was wrong.
5. Take profits.
This is the one that determines how you actually feel about algorithmic trading over time. When algos hit, they hit hard, meaningful monthly returns are possible.
Nothing goes up and to the right forever so when a strategy delivers an outsized month, you take some off the table.
The inputs determine the outputs.
Algorithms should not be the entire portfolio, but they can be a strong sleeve within one if the five points above are answered before the capital moves.
Algorithmic trading is not just a product category. They are amplified market discipline products.
Treat it like one.
@GrantCardone S&P Earnings yields running hot, the lower the yield the more expensive you're buying companies.
The lower the 10 year return ends up being for your buy and holds on the s&p
The right people make you better
The wrong people create doubt
The cost of the wrong people in your life is not linear... it's a spiral.
The reward of the right people isn't linear progress... it's quantum leaps forward & exponential growth
Yesterday @coinbase announced bitcoin backed mortgages. Higher interest but no margin call.
Great for retail, competition for traditional banks with mortgage products, but what about DATs.
As I understand it currently, operating companies are not subject to the institutional single family investment block.
So I see an opportunity for @Strategy and @saylor to take the same over collateralized approach for their digital credit, to now do so and create a product.
Digital Real Estate Credit.
This would disrupt traditional Real Estate hedge funds, REITs, and other products that are trying to integrate bitcoin along side their portfolio.
This could unlock mandated money that needs to be backed by physical assets and could be a product conservative money would understand and trust.
The counter argument to this product as to why they wouldn't do it in my opinion would be due to...
- not enough product to acquire fast enough since the traditional system is slow
- Trying to package up 5B-10B of real estate would take time and would require consistency discipline and could be a side quest compared to the other markets
- Slightly changes the marketing Saylor would have to tweak some messaging but he's got enough credibility to do so if he really bites on it.
If strategy doesn't do it we could see DATs adopt the strategy to differentiate and gain more market attention.
The person you are becoming cannot grow in the shell you're currently in
Every seed must crack before it grows into a tree
Every identity must crack before it expands
5 Truths Most People Learn Too Late:
1. Nobody’s coming to save you. If your life’s off, your money’s off, your body’s off, your mindset’s off, that’s on you.
2. Being busy doesn’t mean you’re winning. A lot of people are just spinning their wheels and calling it work.
3. The people around you will either raise your price or keep you broke. Bad rooms cost more than most people realize.
4. Opportunity doesn’t wait until you feel ready. The longer you hesitate, the more someone else cashes in on what should’ve been yours.
5. Respect isn’t given to talkers. It goes to people who execute, stay solid, and prove themselves over time.
Sooner or later, everybody meets the truth. Winners just meet it sooner.
You can tell the sophistication of an investor based on their abilities to have long term bets amidst short term volatility or unrealized temporary losses.
Conviction without allowing it to playout is the curse most shot term investors fall victim to.