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By Erik Skyba, CMT
Senior Quantitative Analyst, TradeStation Labs
What if you heard that the S&P 500 Index gained 1 percent today? What meaning would that number have to you? Most likely, responses will vary. But most of us would probably be more concerned with the size of the number than how the price action developed; that is, we often care more about the size of the price movement than the part of the day it came from. The question we consider here is, what value, if any, is there to be gained from examining the intraday session?
Our goal through this analysis is to shed light on internal market return dynamics and relationships, while exploring and identifying where trading biases should lie in the intraday session.
Please note that the intraday price analysis in this paper is measured and referenced as "returns." This is a standard method of modeling and comparison. This approach takes the objective stance of a long-side trader; that is, rising prices generate "positive returns," while falling prices generate "negative returns." Traders should understand that, using this reference terminology, a short-side trader may profit during a period of "negative market returns." This is pointed out again later as part of this analysis.
If we were to analyze the scoring data of any given basketball game, we would probably observe how leads expanded or contracted throughout the game, and perhaps changed hands between teams. The intraday returns of the market behave in a similar fashion, except that unlike in a basketball game, there are falling prices (negative returns) that cause market values to decrease. In both bull and bear market cycles, the bulk of the market's price changes, up and down (returns), are made in particular periods during the intraday session. Coincidently, cyclical outperformance among these periods within the intraday session is not only indicative of when a trader should be more inclined to trade, but also implies the continuation of positive or negative day-to-day returns. This paper will discuss the character of intraday returns as they relate to bull and bear market cycles in what we refer to throughout as Intraday Return Structural Analysis (IRSA).
Our study focuses on the S&P 500 Large Cap Index ($INX in the TradeStation platform), which trades during regular market hours (9:30 a.m. to 4 p.m. ET). We analyze intraday market returns by breaking down the regular session (390 minutes) into thirds. Each third consists of 130 minutes (9:30 to 11:40, 11:40 to 1:50, and 1:50 to 4:00); each period serves as the foundation for the three return series in our study. Our analysis not only compares each third of the day's price action to each of the others, but also to the S&P 500 Index's daily returns. In comparing the performance of each third of the trading session, we simulate how a $100,000 investment would have done, over time, if continuously invested in one of the three periods, as Figure 1 illustrates. (It should also be noted that the returns we use are continuously compounded returns and not simple returns.)
Figure 1 – $100,000 dollars invested (1/01/2005 – 1/01/2006) in each third of the trading day (Red = 9:30 – 11:40, Green = 11:40 – 1:50, Blue = 1:50 – 4:00). The fourth line represents the day-to-day returns.
IRSA is the study of the intraday return structure of a security. This analysis focuses on the composition of daily returns, which in turn leads us to the dynamic of trading biases within the intraday session. The main goal of IRSA is to create a mapping process for determining where daily returns are generated within the intraday and overnight sessions. This paper will focus on the intraday session.
The intraday return structure of a security is always evolving. As mentioned earlier, different thirds of the day exhibit return relationships that sometimes last for months to years at a time. In terms of their contribution to the daily return of the S&P 500 Index, each third of the trading day has varying degrees of influence. These influences on the daily return are what traders must be aware of. After understanding this concept, we can introduce the idea of trading biases, which is relatively simple as it relates to IRSA. Since these intraday influences are typically easy to identify (as you will see in the examples below), we add a new type of bias into our day trading by following the trend of the three intraday periods. Let's examine some examples of this behavior. In Figure 2, we see that the first third of the trading session (9:30 to 11:40) has more of an impact on the daily return of the S&P 500 Index (black line), while the second third (11:40 to 1:50) exhibits a period where it's moving in the direction opposite both the first and last thirds of the session.
Figure 2 – $100,000 dollars invested (8/31/2010 – 2/11/2011) in each third of the trading day (Red = 9:30 – 11:40, Green = 11:40 – 1:50, Blue = 1:50 – 4:00). The fourth line represents the day-to-day returns.
In Figure 3, we note an interesting example of divergence between intraday periods. As the S&P 500 Index (black line) heads lower, the first third of the trading session (9:30 to 11:40) is doing worse than the daily return of the index and is the driving force behind its negative returns. However, the last third of the trading session diverges and actually establishes a positive return for this period of time, while the second third (11:40 to 1:50) moves sideways.
Figure 3 – $100,000 dollars invested (11/21/2008 – 3/20/2009) in each third of the trading day (Red = 9:30 – 11:40, Green = 11:40 – 1:50, Blue = 1:50 – 4:00). The fourth line represents the day-to-day returns.
In Figure 4, we see an example of how the intraday return leadership can change roles. In the highlighted area of this illustration, the first third of the trading session (9:30 to 11:40) moves lower, while the last third (1:50 to 4:00) moves higher.
Figure 4 – $100,000 dollars invested (11/01/2007 – 4/01/2008) in each third of the trading day (Red = 9:30 – 11:40, Green = 11:40 – 1:50, Blue = 1:50 – 4:00). The fourth line represents the day-to-day returns.
Notice on the right chart in Figure 5 that this relationship holds and that the second third (11:40 to 1:50) of the session outperforms the first third (9:30 to 11:40) from roughly June to November 2008. The chart on the left shows that from around November 2008 to March 2009, the last third of the trading session's (1:50 to 4:00) outperformance was substantial. This was one the most extreme examples in all the 130-minute data we explored.
Figure 5 – (Left) $100,000 dollars invested (10/21/2008 – 3/9/2009)
Figure 5 – (Right) $100,000 dollars invested (6/01/2008 – 10/21/2008)
In Figure 5, a $100,000 investment in the last third of the trading session (1:50 to 4:00) resulted in an ending value of $124,544, while an investment in the first third (9:30 to 11:40) had a value of $79,759. This is a remarkable difference in performance. For someone trading the S&P 500 Index's ETF (SPY) or the E-Mini S&P 500 futures contract, this might have been valuable information.
This kind of information would have assisted traders in the form of a trading bias, and Figure 6 is a great example of this. Here we can clearly see where the long and short biases are in Verizon's stock. For whatever reasons, the first third of the trading session from May 2009 to July 2010 was consistently negative. It would have been prudent for traders to have a short bias in their trading in the first third of the trading session (9:30 to 11:40). Meanwhile, a long bias could have been considered in the last third of the trading session (1:50 to 4:00).
Figure 6 – $100,000 dollars invested in Verizon (4/20/2009 – 2/15/2011) in each third of the trading day (Red = 9:30 – 11:40, Green = 11:40 – 1:50, Blue = 1:50 – 4:00). The fourth line represents the day-to-day returns.
Depending on how one categorizes them, the markets can experience cyclical periods of bull and bear runs for various lengths of time. A more traditional approach is to classify these events in percentage terms. Therefore, the rule applied here states that if the market advances or declines by more than 20 percent, this will constitute a bull or bear move. Price movement of this magnitude is recognized by many financial market professionals as a change in market cycle.
Figure 7 represents the compounded total return of the S&P 500 Index for the first, second, and third periods (9:30 to 11:40, 11:40 to 1:50, and 1:50 to 4:00) of the trading session within each successive bull and bear market from 9/1/1983 to the present time. In analyzing the data, the information is evident. First, the 9/1/1983 to 8/21/1987 and 12/4/1987 to 3/24/2000 bull markets, which occurred in the first two decades of the data, had most of their returns formulated from the last third of the trading session (1:50 to 4:00). At the same time, the 10/4/2002 to 10/12/2007 bull market, along with the current one, have had greater returns occur in the first third of the day's session (9:30 to 11:40).
Figure 7 – The compounded return for bull and bear market cycles in each third of the trading day (Red = 9:30 – 11:40, Green = 11:40 – 1:50, Blue = 1:50 – 4:00) since 1983.
In Figure 8, we can see that in bull markets, the positive returns that the market experiences on average come from all three periods of the intraday session. However, the returns are highest in the first (24.33 percent) and third (74.52 percent) periods, with the second period still being positive at 14.44 percent. We should point out the return impact of the 268.84 percent in the third period of the 12/4/1987 to 3/24/2000 bull market. Even if we cut this number down by some factor, the returns are still significant for this period.
As we look at the sequence of returns in bear markets, they are also very interesting. They typically start with painful selling in the first third of trading, as Figure 9 illustrates. The average bear market return shows that from the 9:30 to 11:40 period, the return was -29.69 percent. In bear market cycles, however, the market selling becomes less pronounced as the day progresses. The second period of trading returned -9.60 percent on average, while the third period returned -1.07 percent on average. So in bear market cycles, there seems to be some good opportunity to either short early in the first third of the trading session or buy on weakness somewhere in the last third of the session. These observations are made to stimulate thinking and analysis, but require greater examination to determine statistical significance, if any.
Figure 8 – (left)The average return for all bull market cycles from 9/1/1983 to present.
Figure 9 – (right)The average return for all bear market cycles from 9/1/1983 to present.
In this paper, we defined and addressed the benefits of IRSA. We gave you a few examples of how intraday returns can change leadership roles, as certain periods become the driving force behind daily returns or even diverge from daily returns altogether. Through an intraday resolution (130-minute bars), we are better able to understand the true driving force of these returns and this paper was a glimpse into what is possible.
There are two issues we have not discussed in this paper. First, our study focused on 130-minute bar intervals by breaking the trading day up into thirds. Would higher resolutions of data generate more precise information – say, by looking at 65- or 30-minute bar intervals? Finally, we spoke briefly about using the trend of each third period in adopting a trading bias, but what does this really mean? Join us next time, as we establish and quantify logical rules as they relate to IRSA in determining the utility of the intraday return structure to the active trader.
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