Algorithmic vs. Quantitative Trading: Which Path Should You TakeI’ve always wondered why anyone would stick to traditional trading methods when algorithms and mathematical models could do all the heavy lifting.
I started questioning everything:
• Why do so many mentors still swear by discretionary trading when algorithms could handle all the heavy lifting?
• Do they really have solid proof of their “own” success, or is it just talk?
• Or are they keeping things complex and discretionary on purpose, to confuse people and keep them as members longer?
• Why deal with the stress of emotions and decisions when an algorithm can take care of it all?
• Imagine how much further ahead you could be if you stopped wasting time on manual trades and instead focused on market research and developing your own models.
When I first got into trading, I thought Algorithmic Trading and Quantitative Trading were basically the same thing. But as I dug deeper, I realized they’re two completely different worlds.
Algorithmic Trading: It’s simple – you set the rules and the algorithm executes the trades. No more sitting in front of the screen “controlling your emotions” and trying to manage every little detail. Instead, you let the algorithm handle it, based on the rules you’ve set. It frees up your time to focus on other things rather than staring at price charts all day.
But here’s the thing – it’s not perfect. You’ll still need to test the rules to make sure the data and results you’re getting aren’t overfitted or just random.
Quantitative Trading: A whole different level. It’s not just about executing trades; it’s about understanding the data and math behind market movements. You analyze historical price, economic, and political data, using math and machine learning to predict the future. But it can be complex – techniques like Deep Learning can turn it into a serious challenge.
The upside? This is the most reliable way to trade, and it’s exactly what over 80% of hedge funds do. They rely on quant models to minimize risk and to outperform the market.
So, which path should you choose?
Quantitative Trading can feel overwhelming at first, I recommend starting with the basics. Begin with Pine Script coding in TradingView—start building a foundation with simple strategies and indicators. As you grow more confident, start coding your own ideas into rules and refining your approach to eventually automated your trading strategy.
TradingView is a great tool for this, and I’d highly suggest grabbing the Premium plan. This will give you access to more data and features to make your learning journey smoother.
Dive into the Pine Script documentation , and begin bringing your ideas to life.
I promise, the more you focus on this, the better and more independent you’ll become in trading.
Every day, aim to get just 1% better.
To Your success,
Moein
Quanttrading
How much should the order amount be in quantitative trading ?First, you need to determine how your strategy calculates the order quantity, which can be based on:
1. Quantity of shares
2. Amount of money
3. Percentage
This article elaborates on the points of using "Fixed Order Amount" .
The amount of margin required for a trade depends on your risk tolerance.
Using "BOT | Trend" as an example,
In the backtested performance, a fixed "initial capital leveraged by 1x" is used as the order amount for each trade,
with a maximum drawdown of 25%, meaning the assets decrease by 25% from the "peak performance point" to the subsequent lowest point (1000 ➡️ 750).
Therefore, there are two key points to note here:
* The amount of margin required should consider “How much risk you can bear? ”
Assuming you currently have 1000 to operate "BOT | Trend," and you can tolerate a maximum loss of 500 (-50%), then the total amount of each trade (margin * leverage) can be set as 2000, and so on.
Example: Now you have 2000, and you can tolerate a maximum loss of 400 (-20%), then the total amount of each trade (margin * leverage) is 1600.
Practice: Now you have 5000, and you can tolerate a maximum loss of 2000 (-40%), then the total amount of each trade (margin * leverage) is ______ (Hint: What is 25% of 2000?).
* Timing to start running quantitative trading.
Running a "trend-following" quantitative trading strategy should not start during a continuous profitable period but rather when the strategy incurs losses (relative low point of equity). This is because for trend strategies, sideways market conditions can cause the strategy to go long at highs and short at lows, resulting in a depletion of funds during this period. Starting during a continuous profitable period is likely to encounter fund depletion right after entering because markets alternate between trending and ranging phases.
Answer: 8000
Are you a victim of your emotions ruining your trading?Emotions... They are the reason why over 90% of traders fail. Emotions always get in the way. Technical analysis helps to measure the psychology of the market but its still very hard to trade using technical analysis without getting the emotions involved and even harder to automate trading using technical analysis.
This is the biggest reasons why quants are popular and becoming even more popular. Quants take emotions out of trading. Unfortunately, quants are mostly used by Wall Street right now.
The Wall Street Journal has a multi-story piece about quants with catchy titles like "Meet the New Kings of Wall Street" and "The Quants Run Wall Street Now."
We think this needs to change and that quants should be available to the masses. This is why we started Quant Engine, our goal is to provide everyone access to quants.
We think trading should be automated using scientifically proven trading models.
With that said, we want to introduce you to our first strategy model that we are providing to the public. This is only the beginning and it shows the possibilities.
This models is for BTCUSD 1 Day resolution.
To get access follow the link provided.
More strategies are coming soon so make sure to like and follow us.