Have you ever thought about what can happen during 1 minute? One can tell a joke, drink a glass of water, and a couple new messages can appear on the timeline. But how about financial markets? How much do they move during 1 minute? Or during 1 day, or even overnight? Most of the time not so much, but sometimes a lot. This happens when an outlier occurs.
What is an outlier?
An outlier is a data point that is significantly different from the other data points in a dataset. In statistical analysis, an outlier is a point that lies outside the range of the majority of the data, and is considered to be an unusually high or low value. Outliers can be caused by a variety of factors, including errors in data collection or measurement, extreme values in the data, or the presence of exceptional or unusual cases in the dataset. In general, outliers can have a significant impact on the results of statistical analysis, and should be carefully examined and treated appropriately to ensure the accuracy and reliability of the analysis.
Financial markets live and die by the outliers
In the context of financial time series, outliers refer to unusually high or low returns that are observed during a specific period. It’s good to remember, that these returns don’t have to only be day to day change, but can also be discussed for intraday changes or daily gaps. A gap occurs when opening price for a specific trading day is significantly different than the previous day closing price. Outlier returns can occur for a variety of reasons, such as market high volatility, shifts in investor sentiment, or the release of important economic data. They can potentially have a significant impact on the overall performance of an analyzed security, and require taking careful approach and strategic planning to deal with effectively.
A lot happens at night
Using daily data of S&P 500 index from TradeStation platform, let’s take a year 2020 as an example. In 2020 there were 50 trading days (out of approximately 250) that started either 1% above or 1% below previous day closing price. In 2021 there were none. So, no matter what software you use, technical indicators that are applied to the daily chart will be significantly affected. TradeStation indicators are not an exception, but knowing that such a thing can occur can be helpful.
Technical indicators are statistical tools that are used to analyze the behavior of a security or market, and are based on past data. When outlier returns occur, they will affect the data that is used to calculate these indicators, which in turn can impact the signals that the indicators generate. For example, if an outlier return causes a sudden shift in the price of the S&P 500 index, this will affect the data used to calculate a moving average or other trend-following indicator. As a result, the indicator will move much more than it usually does and could generate a false signal, such as a buy or sell signal, that doesn’t reflect the underlying trend in the market. This could lead to incorrect investment decisions, and could potentially result in losses for the investor. In general, outliers can cause technical indicators to behave in unpredictable ways, and can make it difficult to rely on these indicators to make investment decisions.
There’s also a bright side of outliers. Guys from Advantage Trading argue, that in periods of elevated volatility, some trading strategies can perform better than in periods of calm markets. The reason for it is simple – some trading strategies are built to squeeze the most out of a dynamic move. If there are no strong moves, they will underperform. But once the volatility rises, they will take advantage of it.
A lot can happen during 1 minute
Another way of looking at the problem of outliers is a close examination of intraday changes. Investors usually think, that during 1 minute, not much can happen. And usually they are right. Data for last 20 years shows, that little over 97% of 1-minute returns of S&P 000 index are within -0.1% to 0.1% range. But what happens outside this range, is very important. There are minutes that witness moves that are stronger than 1%, both up and down. Two strongest moves occurred (obviously) in 2008 and 2020.
Last trading minute of a session on September 29th 2008 caused the market to drop 2.18%, and on March 16th 2020 between 9:45 and 9:46 S&P 500 dropped 2.10%. On the opposite side we have March 3rd 2020. Between 10:00 and 10:01 S&P 500 went up by 2.14%. Anther fun fact about these strong moves is that they cluster. If we take 1-minute up moves that are stronger than 0.2% or down move stronger than -0.2% we can say that 2008 was the most volatile year on record. 5.24% od 1-minute returns were outside -0.2% to 0.2% bracket. On the other hand, in 2017 only 0.01% of intraday changes were strong enough to fall outside this range.
It’s not easy, but an investor can try to analyze the frequency of outlier returns in real time, and look for any patterns or trends in the data. For example, it may be the case that outlier returns are more common during certain times of the year, or during specific market conditions. By identifying these patterns, investors can gain a better understanding of when outlier returns are likely to occur, and can take this information into account when making investment decisions.
How to deal with it?
Finally, there are a number of potential approaches that investors can take to mitigate the impact of outlier returns on their investment portfolios, or even to take advantage of these returns to generate profits.
One possible strategy for dealing with outlier returns is portfolio diversification. By holding a variety of different stocks or other assets, investors can reduce their exposure to the risks associated with outlier returns in a specific stock or sector. This can help to protect the overall value of the portfolio, and can reduce the impact of any negative outlier returns on the portfolio’s performance.
Another potential strategy is to use stop-loss orders or other risk management tools. These tools can help investors to limit their losses if an outlier return causes a stock or the overall market to decline. By setting a stop-loss order, investors can automatically sell their stocks if they reach a certain price, which can help to minimize the potential losses from an outlier return.
Finally, investors can also try to take advantage of outlier returns to preserve capital or even generate profits. For example, if an outlier return causes a stock or the overall market to fall, investors can use this opportunity to buy more stocks or other assets at a lower price. This can help to capitalize on the outlier return, and can potentially generate profits for the investor. This is a double-edged sword though, because the first occurrence of outlier return might be the sign, that the market goes into bear market. Most positive and negative outliers occur during periods of market decline, so sometimes, buying the dip will not work out.
Overall, there are a number of different strategies that investors can use to deal with outlier returns in financial time series. The best approach will depend on the individual investor’s goals and risk tolerance, and may require careful analysis and strategic planning to implement effectively.