Investors have always searched for ways to break through the uncertainty and see clearly when the waters are murky so they can succeed in even the toughest economic times. Over the last few years, the emergence of technological tools and big data has boosted that process in many ways, explains experienced investor Daniel Calugar.
Over the last few years, an increasing number of traders have looked to integrate algorithmic trading into their repertoire. When done correctly, algo trading can help investors remove some of the uncertainty, hesitation, and human error that is very present with traditional manual trading.
Algo trading, which utilizes computers to execute trades automatically based on parameters and instructions that you set, is often associated with executing a large number of trades at one time and buying and selling for profits that may only amount to a few cents per stock.
Because of this, you might think that algo trading might become extra risky during volatile markets. It's hard to blame you for thinking this way, as predicting future market performance based on known data and information can become extremely difficult when markets aren't performing as planned.
However, algo trading can actually help investors manage uncertainty in volatile markets if used in the right way.
Below, Dan Calugar provides some effective algorithmic trading approaches for managing uncertainty in volatile markets and explains why it can prove especially useful in these times.
Benefits of Algo Trading in Volatile Markets
Algo trading provides investors with many benefits, regardless of how the overall markets are performing.
For one, algo trading relies on vast amounts of data and information that you input into the system. As long as you're inputting reliable data and then cleaning and processing it well, your system can make an enormous amount of calculations in fractions of a second. This is something that human brains simply cannot do.
Algo trading can also help you integrate new approaches into your overall trading strategy in ways that you might not have found possible before. You can focus on multiple individual stocks, classes of stocks, and industries and sectors. You can also widen your focus area thanks to the power of computers. You can use arbitrage trading strategies and integrate alternative data into the process, two things that could be very challenging for individual traders.
But perhaps the biggest benefit of algo trading in volatile markets is what it eliminates, not what it adds—human emotion.
One of the main things that algorithmic trading does is make decisions based on hard data and information. It's knowledge-based decision-making at its finest. In fact, it's the most objective way that you can invest.
Daniel Calugar points out that many investors find themselves in trouble during volatile markets simply because they have trouble putting their emotions aside. It's easy to get frustrated, scared, and even angry when markets seem to change on a dime, and all of those emotions can make it difficult to make investment decisions grounded in facts.
This is what algo trading does a great job of. Computers have no emotions, of course, so using algorithms to help make decisions is one of the most disciplined and strict approaches you can take to investing. And in volatile markets, this can prove to be very reliable and successful.
Using Algo Trading to Understand and Define Volatility
The word "volatility" is a rather generic term when it comes to investment markets. The basic definition of the term means "liability to change rapidly and unpredictably, especially for the worse."
It's that last part, "especially for the worse," that most people think about when discussing volatility in investment markets.
But, even during the most volatile markets, not every asset is volatile, and the volatility usually won't be the same for every asset. In addition, there are ways that you can measure volatility and actually work to predict it.
A key insight about volatility is that it is sometimes cyclical. Volatility can either decrease or increase over time and might come every so many years or following a certain piece of news or economic report, for instance.
Savvy traders can actually use the same high-powered computers they use to run algo trading strategies to identify this volatility, which helps them better understand and define it. If you're able to recognize what the cycles are, then you could have the ability to adjust your algo trading strategy accordingly.
Using data and information can also help you define the level of volatility for independent assets, classes of assets, or sectors. While one asset class could experience high volatility, another might be much more stable. Understanding this can help you tailor your algo trading strategy to take advantage of where the least amount of volatility is.
By understanding what might affect and/or cause volatility, you could also be better prepared for major changes ahead. Many times, market volatility follows major decisions by central banks and even geopolitical events such as the outbreak of war. Understanding historical volatility following these types of events can help you make more informed decisions when these events happen again in the future.
Finally, it's important to note that there are ways you can measure volatility. The Chicago Board Options Exchange Volatility Index, for instance, measures what the market could expect in terms of volatility for the month ahead. There are other indicators, such as Bollinger Bands and Average True Range, that perform similar functions.
Understanding Events and Assessing News
One common way that algo trading is used is to analyze news and alternative data points. There are many use cases for this, too—everything from analyzing weather patterns to predicting success in certain sectors to viewing satellite imagery to predict future surges at certain retail stores based on how full store parking lots are.
During volatile times, a great way to utilize algo trading is by understanding events and assessing the news. Market news and even general worldwide events can have enormous impacts on the future performance of assets.
Analyzing these events and news can help you gain valuable insights into potential factors that could drive the prices of assets either down or up. That, then, allows you to make more well-informed investment decisions, which could ultimately increase your opportunities to be successful, even in the most volatile markets.
Basic strategies in this realm include analyzing economic indicators such as rates of inflation, unemployment and inflation, and GDP growth. These overarching data points can help paint a clearer picture of the market.
You can then drill down into industry trends to help you identify certain sectors that could be more or less volatile. By integrating basic company financials into the picture, you can obtain insights into individual companies' financial health, which is often a huge indicator of how well they can weather storms—or even take advantage of prime opportunities.
Algo trading strategies that integrate alternative data can be particularly useful during volatile markets. Creating algorithms that pull in social sentiment can help you understand what the general public is thinking through their posts on social media platforms and message boards such as X—formerly known as Twitter—Reddit, and Facebook.
The aforementioned alternative data points of weather and satellite imagery can also prove very valuable. That's because, even in the most volatile of markets, these two factors can help to eliminate some uncertainty.
For instance, even when the market as a whole is hard to predict, spells of cold weather result in people using more natural gas, electricity, and oil to heat their homes. And, regardless of what economic reports are saying, if parking lots are full at certain big box stores, it could be an indication that that specific company will be reporting higher-than-expected earnings for the next quarter.
Dan Calugar says that the point here is that following algo trading strategies can help unveil certainty in uncertain markets.
Algo Trading and Technical Analysis
A tried-and-true way of navigating volatile markets and mitigating losses during them is to conduct technical analyses. This isn't a specific strategy for volatile markets only, as it helps to identify patterns and trends in any market. However, it often proves especially useful during rapidly changing market conditions.
The process of technical analysis involves studying historical volume and price data as a way to predict where future prices may move. The general theory is that all market trends—regardless of whether they move in a positive or negative direction—will continue to move that way until signs of a reversal emerge.
It involves utilizing things such as chart patterns, trend lines, and moving averages to try to identify the trends in the current market. However, not every trader believes in technical analysis, with some arguing it isn't very reliable.
No matter how you feel about technical analysis, though, there's no doubt that breaking down multiple data points during volatile markets can prove valuable. While you may not want to use this information as the sole basis on which you create your algorithms, it could help to inform the strategies you choose.
Specific Algo Trading Strategies for Volatile Markets
All of the information presented to this point describes the benefits of algo trading during volatile markets and ways that the information within the algorithms is invaluable. Below, Daniel Calugar points out specific algo trading strategies that you can use during volatile markets to break through the uncertainty.
1. Arbitrage
Arbitrage is the concept of executing both sides of a trade, sometimes on different markets or different aspects of the same market, to take advantage of price discrepancies. There are a few different ways that you can use arbitrage during volatile markets.
One common approach involves engaging in arbitrage trading by identifying potential company mergers and acquisitions. Success in this strategy requires staying informed about pending or potential deals through news sources. The underlying idea is that the acquiring company's stock price is usually discounted, while the stock price of the target company often rises in anticipation of the deal.
At the same time, the stocks of the two companies combined will often trade at a price that's discounted compared to the price following the merger due to the risk that the merger could ultimately not go through.
The arbitrage strategy here, then, would be to purchase the stock of the company that's being acquired while shorting the stock of the company that is making the acquisition.
Another strategy is relative value arbitrage. Here, you're looking to find the correlation between two securities, specifically "heavyweight stocks" that exist within the same industry and that have a significant trading history.
What you're waiting for here is for the paths of these two securities to diverge. When you identify a 5 percent divergence (or more) for two days in a row, you can execute an arbitrage position on both of them, expecting that they'll eventually converge.
The theory, then, would be to purchase the security that's undervalued and short the one that's overvalued. Once they converge, you'll close your position on both.
2. Market Neutral in Equities
This long-established principle says that gains are often more closely linked to any differences between the worst and best performers than they are to the market's overall performance. This makes them much less susceptible to the general volatility in the market.
What you'll do with this algo trading strategy, according to Dan Calugar, is look for relatively undervalued and relatively overvalued stocks in the same sector. You can do the same thing with peer companies.
Once you identify these companies, you'll buy the undervalued ones and sell the overvalued ones. What you'll be doing is trying to exploit the differences in prices by having equal short and long positions on closely related stocks.
This is a strategy that has been used for a while, even before algo trading burst onto the scene. But where algorithms can really help here is by quickly analyzing and identifying multiple possibilities for this strategy.
Humans may only be able to identify one or two possibilities for this strategy when trading manually. It's even possible that their analysis is incorrect or that the two companies they zeroed in on don't provide the best opportunities for this strategy in the market.
By using algo trading, you can quickly identify all existing opportunities and capitalize on the ones with the best indicators for success.
3. Non-Directional Investing
The most common way of trading is called directional investing. It involves gaining a position that requires the market to continue moving in one particular direction to make gains. For long positions, for instance, the market must continue improving, while short positions require the market to go down.
Volatile markets can result in a lot of uncertainty, with the "direction" moving up then down, or vice versa, quite frequently and quickly. This makes directional investing tricky, at best.
Non-directional investing, by contrast, seeks to manage volatility and risk when investors believe the market—or individual stocks within the market—are going to either remain flat or not indicate a strong bias in one direction or the other.
This type of investing will look to make profits through the premiums gained from options selling. It can involve individual options sales or multi-legged trades.
There are many different examples of this, including:
Short Straddle: Investors will sell a put and call option at the exact same expiration date and strike price. When the asset remains flat, the strategy will result in profits.
Butterfly Spread: With this, you'll sell and buy put and call options at three separate strike prices. In doing so, you'll create a shape that resembles a butterfly on the chain. You'll realize a profit with this strategy when the asset sticks close to its middle strike price.
Iron Condor: For this strategy, you'll sell a put option and call at two different strike prices. At the same time, you'll buy a put option and call at further strike prices. This will create the shape of a condor on the chain. You'll profit from this strategy when the asset remains in the specified range of prices.
It's fairly straightforward to see how algo trading can be useful in non-directional investing. Daniel Calugar points out that computers can quickly identify the best assets to use with these strategies and then execute the options at the best prices.
You'll be able to set all the specific parameters that will result in the best returns with whatever non-directional investment strategy you choose to use and then allow the algorithms to perform their magic.
This is one of the best examples of how algo trading can help you manage uncertainty in volatile markets.
The discussion above provides a high-level review of the topic of algorithmic trading, including types of approaches that might be executed algorithmically; however, Dan Calugar points out that in his opinion, more than 99% of investors would be much better off simply buying and holding index-related investment such as QQQ (Invesco QQQ Trust Series ETF) or SPY (SPDR S&P 500 ETF Trust). If you invested $100 in QQQ on November 17, 2003, your QQQ investment would be worth $1,324 on November 18, 2023. That is a twenty-year 13.2% compounded annual growth rate. According to data provider Hedge Fund Research (HFR), over the 10-year period from 2009 to 2018, hedge funds (many of which specialize in running algorithmic strategies) produced an average return of 6.09%. During the same period, an investment in QQQ produced an average annual return of 18.52%. That means that $100 invested for ten years with a professional hedge fund manager in 2009 would have, on average, grown to $180, while $100 passively invested in the QQQ ETF would have grown to $547. If you feel your instincts are substantially better than most professional hedge fund managers, Dan Calugar suggests you take the following precautions before launching into an algorithmic trading strategy:
Don't assume that a strategy that backtests brilliantly will come close to duplicating those results going forward. The stock market certainly does exhibit patterns that backtesting can exploit when viewed through the rear-view mirror, but those patterns rarely play out the same way going forward.
Read Nassim Taleb's book "Fooled by Randomness."
Don't believe that an algorithmic strategy sold on the Internet for $5,000 is going to work. In the investment world, there is a lot of truth to George Bernard Shaw's quote, "Those who can do, and those who can't teach." Investors who have perfected niche ways to extract alpha with algorithmic approaches spend their time making money by investing internally, not by selling their trade secrets to other investors.
Before investing real money in an algorithmic approach, paper trade the strategy for at least six months.
Stay clear of day trading strategies. Unless you are a sophisticated flash trader, the costs associated with ultra-short-term trading almost always outweigh the benefits.
Don't trade an algorithmic strategy unless you can identify a specific repeatable "edge" that the algorithm gives you that is not present with a buy-and-hold investment.
When you do start trading with cash, remember that you must pay ordinary income tax rates on most short-term investment returns. Compare your after-tax returns to what you would have made by investing in a combination of QQQ and SPY, and cut your losses if your after-tax return doesn't keep up with buy and hold.
About Daniel Calugar
Daniel Calugar is a versatile and experienced investor with a background in computer science, business, and law. He developed a passion for investing while working as a pension lawyer and leveraged his technical capabilities to write computer programs that helped him identify more profitable investment strategies. When Dan Calugar is not working, he enjoys working out, being with friends and family, and volunteering with Angel Flight.
