What Are Quantified Trading Strategies? (Including A Trading Strategy)
Quantified trading strategies are strategies based on finding inefficiencies in financial markets based on numbers, math, data, and statistics. This is done by studying historical data from the past, mostly time series of the price of financial instruments, and the aim is to detect patterns and relationships that are unlikely to occur by chance. We use backtesting to measure profitability.
This website is all about quantified trading strategies, often called algorithmic or quantitative strategies. But what exactly are quantified trading strategies?
What are quantified trading strategies?
Quantified trading strategies are strategies based on finding inefficiencies in financial markets based on numbers, math, data, and statistics. This is done by studying historical data from the past, mostly time series of the price of financial instruments, and the aim is to detect patterns and relationships that are unlikely to occur by chance. We use backtesting to measure profitability.
This article aims to explain the basic concepts of a quantified trading strategy and how you develop a trading system.
Do quantified trading strategies use the scientific method?
Quantified trading strategies use the principles from the scientific method. The rules of a quantified trading strategy are 100% quantified and thus based on the scientific method.
The trading rules are strict and not open to discretionary judgments or anecdotal evidence. When a trading strategy has passed all backtesting and is ready for live trading, the trading signals are mostly passed on to a trading software/platform that executes the trading automatically, also called a trading robot, but you can, of course, enter buy and sell orders manually.
Other labels for quantitative strategies are algorithmic strategies or “quant” strategies. Basically, all labels involve the same elements in their methods. A quant is simply a trader relying on quantified strategies and automatic trading.
We at Quantified Strategies have built quant trading strategies based on our hypothesis for close to twenty years. The strategies are developed on strict mechanical rules that have been successful in past data and which we believe offer profitable opportunities in the future.
The development of quantitative strategies is not new but has risen with steady improvements in computer power. Even Benjamin Graham, the founder of value investing, to some extent, used strict quantitative models to find undervalued securities.
Since then, the advent of computers has made Graham’s methods almost useless because computer power finds those mispricings in seconds. Sooner or later, most strategies get “arbed” into oblivion. Any quantified trading strategy that gets too popular is destined for the graveyard at some point in the future.
You can make your trading strategies complex or simple. We believe in simplicity.
However, it takes significant time to develop the skills to test and trade strategies.
Patience is required. This is a skill like all other skills required for a job, and just like no one expects a recruit to become a carpenter overnight, you can’t become a trader overnight. You can expect years of trial and error to get good at your work.
What are the elements of a quantified trading strategy?
The elements of a quantified trading strategy can be summarized in this list:
- Make sure you have many hypotheses/ideas to test at all times. Brainstorm and write down ideas regularly. Keep your ideas in a trading journal, and for your convenience, we have made a trading journal example.
- Which markets are you going to trade? Why do you want to trade this market?
- Which timeframe should you trade? The time frame in trading is important. Scalping (we believe scalping is a waste of time), day trading, swing trading (1-10 days), or perhaps monthly trading? You decide, but it normally pays off to be an investment agnostic.
- Find variables to test for each idea you want to test. When you formed your hypothesis, most likely you had some variables in mind. Make sure your strategy doesn’t curve fit with many variables. The importance of simplicity can’t be stressed enough.
- Test different ways to enter a trade: enter at close? Enter at open? Enter at the market? Enter with a limit order? Keep in mind that you need to fit your trading into your everyday life.
- Likewise, how and when do you exit a trade? Are you using a stop-loss or profit target? Should you exit at close or on open?
- How many shares/contracts per trade? Quant traders like to call this risk analysis or money management. This is a pretty wide topic in itself. For example, two stocks trading at 50 dollars might have completely different volatility and thus risk. A 1,000-share position in a low-volatility stock might be the same as a 200-share position in a high-volatility stock.
- Is your strategy correlated to your other strategies? You want to have a low correlation in trading. Do its trading signals overlap with your other strategies? Does it add significant value to your profits? Usually, it’s a good idea to trade several markets to get diversification and potentially smooth your overall returns. The idea is that gains in another quantified strategy offset losses in one strategy. You aim for little correlation between your quantified strategies and it’s absolutely crucial to investigate how a strategy performs alongside your other strategies. The lack of correlation among the trading strategies is very underappreciated! It’s more likely that you’ll perform better the more systems/stocks you trade. Many “suboptimal” strategies are much better than one “best” strategy. The reason is diversification and because many strategies go through periods of mediocre profits, even losses, and most strategies simply stop working after some time.
- Last but not least: when you develop a quantified strategy, test out-of-sample“. Out of sample simply means you test your strategy on future unknown data. You must commit to this procedure because of the risk of curve-fitting your strategy to the past data. The best way to do this is to trade with “paper money” in a virtual account for several months before you go live.
What is an example of a quantitative trading strategy?
To let you better grasp what a quantitative strategy is, we can use our strategy that used RSI(2) on QQQ (published several years ago). This is a simple trading strategy, but simplicity is the way to go. The quantified strategy has four rules and is meant to be traded on Nasdaq futures or the ETF with ticker code QQQ, but it works on many other stock indices as well:
Trading Rules
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Despite its simplicity, the strategy has performed remarkably well for over two decades in both bull and bear markets:
The strategy returned almost 14% annually, compared to only 7.9% for “buy and hold”.
What are the advantages of quantified trading strategies?
The advantages of quantified trading strategies are mechanical and thus less liable to trading biases, you reduce emotions in trading, and you can find out what works and don’t work.
One of the main obstacles to generating acceptable returns is yourself. Anyone who has traded can agree that we easily fall prey to behavioral mistakes, for example, selling in a panic and buying when markets are euphoric.
Quantified strategies are, per definition, mechanical and not open to judgment from you, and thus, they don’t let you form any opinions on where the market is heading. You can focus on just executing the strategy. The temptation to twist your strategies lurks on every corner, but hopefully, a quantified strategy can help you limit this risk.
When a new trading day starts, you initiate your programs and let them run. It enables you to overcome greed, fear, and frustration. You take most of the emotions out of the trade.
Of course, this requires a good deal of faith in the system. But it should be relatively easy to implement if you are confident it makes money in the long run. Consistency is important to have faith in your systems. Our experience indicates that the traders succeeding, in the long run, have quantified rules when trading.
Another advantage of quantified rules is that you can regularly analyze them to determine what works and what doesn’t. It’s also a lot easier to trade many more strategies simultaneously. Done correctly, this smooths your equity curve. You take advantage of the law of big numbers and simultaneously develop a mindset of thinking in terms of probabilities. This is the same logic that helped Jim Simons and the Medallion fund to generate 66% a year for 30 years.
When thinking in probabilities, you better understand the law of big numbers. Over a large sample of trades, where one trade is very uncertain, the variability of the result can be drastically reduced if you have many trades and strategies.
You free up time to explore and research other strategies by quantifying and automating your strategies. By enabling a trading platform (see below) you can practically trade as many strategies as you like, which is impossible if you enter trades manually.
You can even have a full-time job and let your strategies run in the background or only at certain intervals, for example, at the opening or the close. By programming, you can pretty easily automate all these procedures. Time is money!
What are some of the trading software used to quantify trading strategies?
Some of the trading software used to quantify trading strategies are, for example, Amibroker, Tradestation, Multicharts, TradingView, Ninjatrader, etc. We in Quantified Strategies use Amibroker and Tradestation:
All trading platforms let you connect to a broker to allow for live trading.
However, don’t underrate the classical spreadsheet. Most traders have at least some basic knowledge of using a spreadsheet, which is a great way to start.
You can, for example, code a simple script in Visual Basic to generate orders from different cells in a spreadsheet. But to trade multiple strategies, it’s recommended that you get some basic understanding of a trading platform.
The biggest restraint is not computational power but more likely limits on the programming abilities of the trader or how to generate ideas to test. As a quant trader, you are dependent on having ideas to test and trade.
To generate ideas to test, we recommend you start live trading. When you trade real money, you force yourself to think, forcing you to pay attention. As always, trade small and within your comfort zone. Testing strategies are called backtesting:
How do you backtest quantified trading strategies?
You backtest quantified trading strategies by using software or a trading platform. You can perform backtesting in either Excel or a trading platform, like, for example, Amibroker, as already mentioned.
Backtesting involves testing the hypothesis on historical data, but out-of-sample testing is the most important aspect.
Out-of-sample testing is when you test the strategy on data not included in the backtest. You can do this by splitting your dataset into two parts, one for creating the strategy and one part where you test the strategy out-of-sample. Even better is to test the strategy on live data for several months daily.
What is successful quantified trading?
Successful quantified trading is to generate alpha. Alpha is the return you get when beating “the market” or a relevant benchmark.
As an individual trader, you must compare your relevant investment opportunities. The opportunity cost should be your benchmark. An option is, for example, to invest in mutual funds, which historically have risen about 6-7% annually in real terms. Thus, your aim as a trader could, for example, be 10% annually before taxes.
However, you have to factor in costs. Trading involves time and stress. Long-term investing (in most cases) defer taxes until you realize the gains, while trading involves annual taxes. In the long run, taxes are a headwind to consider. You need to find out what suits you best: Trading or investing – what is best?
There is no denying that alpha is difficult to generate. Market participants compete with each other – it’s a battleground. The market is a zero-sum game in relation to an index, and only a small group of participants can generate an excess return (alpha) above the index. The traders or funds who beat the index typically vary over longer periods. Very few manage to beat the market over long periods.
Does a quantified trading strategy last forever?
A quantified trading strategy doesn’t last forever. No strategy lasts forever, and ultimately, all trading strategies stop working. Something that gets too popular will eventually get “arbed” away. Any strategy that looks good on paper and in backtesting might turn out to be a trap in the real world.
Why is that? That is because traders often curve fit their data to fit the past, and that is, of course, unlikely to replicate in the future.
Both the world and markets change and evolve. How can you factor in that terrorists hijack planes and fly them into skyscrapers? How about the Covid-19?
The fact is that markets are quite random, and the focus changes from year to year. Any aspiring trader is recommended to read the books by Nassim Nicholas Taleb to understand this better.
Yet another issue is the natural market cycles of the markets. Any super-performing strategy in the past could happen just as well because of the ebb and flow of the markets. Any profitable algorithmic trading system could produce profits during a bull market, while it’s unlikely to perform well in a bear market.
The anatomy of bull and bear markets are usually significantly different from each other.
What are quantified trading strategies? Conclusion
Quantified trading strategies are trading signals that are 100% mechanical and without judgment from your side. We believe this can help many aspiring traders because most fail due to a lack of a plan.
It’s based on mechanical rules based on past data that help you eliminate behavioral mistakes, let you trade multiple strategies to reduce correlation, and force you to think in terms of probabilities. These are important aspects of successful trading and help you find market niches.
FAQ:
– How do quantified trading strategies work?
Quantified trading strategies use the scientific method, with rules that are 100% quantified and not subject to discretionary judgments. These rules are developed by studying historical data and are often executed automatically by trading software or platforms, also known as trading robots.
– What is the significance of simplicity in quantified trading strategies?
Simplicity is emphasized in quantified trading strategies to avoid curve-fitting and enhance strategy robustness. Despite the option to make strategies complex, the belief in simplicity helps in better understanding, testing, and trading.
– How does risk analysis or money management play a role in quantified trading?
Risk analysis or money management is crucial in quantified trading to determine the number of shares/contracts per trade. It involves understanding the volatility of different stocks and adjusting position sizes accordingly.
Related Reading: Quantitative Trading vs Algorithmic Trading
Related Reading: Time Series Analysis Strategy