• Karnesh

Quantitative technical analysis of S&P 500 bull market following 2008 crash vs 2020 crash

Updated: Jun 1


This post provides a quantitative technical analysis* of the S&P bull market (uptrend) following the 2008 financial crash recovery (2013-2015). We generated the quantitative metrics on SPY using the ChartAgg tool, and will specifically look at a couple of metrics for this period. We will provide an interpretation of those metrics and how they can be incorporated into your current trading strategy. We then compare the metrics from this period with the quantitative metrics of the current bull market (uptrend) following the 2020 market crash recovery. In both cases, we will analyze the uptrend after the complete recovery of the crash, i.e. - April 2013 to March 2015 (as the 2008 crash completely recovered in April 2013), and Nov 2020 to April 2021 (the month before writing this post). We will see how these two uptrends are showing similar quantitative metrics.


Finally, we will also compare the quantitative metrics of the ending period of the 2013-2015 uptrend following which the bull market went into a hiatus and led to multiple large drawdowns. We will make an argument on how these quantitative metrics can help in signaling a short/long term end to a bull market or beginning of a period of ranging where the returns are very low.




2013-2015 Uptrend Quantitative Technical Analysis:


After the crash in 2008 from the high, SPY completely recovered to 2008 highs in April 2013. Between April 2013 to March 2015 S&P returned ~34%.


While ChartAgg tool generates many different metrics for a selected time period of a stock, to keep it simple, for this case we will compare the 'drawdown' metric and 'time to new high' metric.


Image1 (25%,50%,75% is the shorthand for 25th percentile, 50th percentile, 75th percentile respectively)

First lets take a look at drawdown quantitative metrics for SPY during the uptrend between 2013-2015. As a refresher, drawdown indicates how much a stock went down from its peak during a period. The drawdown here is in percentage. The mean drawdown during this period is 1.76% , i.e. - on an average the price doesn't go below 1.76% from the highest price yet during this period. Let's look at the percentiles**. The 25th percentile is 0.54% , i.e. - in 25% of trading days in the selected period the drawdown doesn't go below 0.54% from the highest price yet. Similarly 50th percentile is 1.2% and 75th percentile is 2.58%. The maximum drawdown is 9.86%. Looking at these metrics suggests that during this uptrend, the probability of SPY suffering a drawdown more than 1.2% is 50% (as indicated by 50th percentile), and in the worst case, the drawdown is 9.86% (as indicated by maximum drawdown). If we were trading halfway through this period, we could make use of this data to manage a position. For example, I would be conformable going long after SPY suffered a 50th percentile drawdown, as the probability of it going down further is only 50%. If we wanted to be more defensive, we could use the 75th percentile number and go long when SPY suffered a 75th percentile drawdown (2.58%), as the probability of it going down further is only 25%. Another scenario where this can be useful is, if SPY suffers a drawdown around ~9% which is in the vicinity of the max drawdown during this uptrend, and other indicators (macro and technical) are still not signaling bear market, then it would be a good risk reward scenario to go leveraged long with a tight stop.


Now lets take a look at the 'time to new high' metric from Image1 above. This metric indicates the time in days it takes for a stock to make a new high, i.e. - time to breach the previous high. The mean 'time to new high' during 2013-2015 uptrend is 12 trading days, i.e. - on an average SPY was making a new high every 12 days. If we look at the 75th percentile - it indicates that in 75% of the days in the uptrend, SPY was making a new high at most within 20 days. In the worst case, SPY made a high in at-most 52 days, indicated by the max number in the metrics. This can again be used to manage trades. If SPY enters a period where it is making a new high in excess of value at 75th percentile days or closer to the max value, it could be an indication that market is loosing steam and the uptrend might be coming to an end for the near future.




2020-2021 Uptrend Quantitative Technical Analysis:


After the crash in March 2020 from the high, SPY completely recovered to 2020 highs in November 2020. Let's take a look at the metrics of the uptrend between November 2020 till April 2021 (the month before writing this post)


Image 2

Comparing the drawdown metrics of 2020-2021 (Image 2) uptrend to those of 2013-2015 (Image 1) uptrend, notice that the mean, 25th percentile, 50th percentile and 75th percentile are very similar in both cases. This could suggest the SPY uptrend generally follows drawdown around these values. To get more conviction, one can analyze more such SPY uptrends using the ChartAgg tool.


Also, all values for 'time to new high' are currently lower than the uptrend in 2013-2015. Since this time period is currently only 6 months, as compared to almost 2 years between 2013-2015, drawdown metrics are showing similar signs, and the return so far in this uptrend has been ~18%, it can be argued this bull market has a lot more time and returns.




Quantitative technical analysis of ending period of 2013-2015 uptrend:


Now let's take a look at the two metrics from September 2014 to August 2015, where SPY was mostly ranging and provided a return of ~6%, with significant drawdowns.



Image 3

If we compare the drawdown for this period with those from Image 1, notice how these metrics have shifted to the higher side. A more clear signal is the comparison of 'time to new high' metric, which is significantly higher in Image 3 than Image 1. The mean is almost 2 times higher towards the end of 2013-2015 bull market and the 50th percentile is 3 times higher than in the overall 2013-2015 uptrend. This can be used as a potential signal to get out of S&P or put hedges in place.




Conclusion:

Quantitative metrics like 'drawdown' and 'time to new high', aggregated over a period of time can provide valuable insights on the future price action in the stock market, thereby potentially leading to better trading returns for your investment. We discussed the interpretation of two such metrics offered by ChartAgg tool. The tool offers many more such aggregated metrics, and we are always on the lookout to add more. You can play around with the tool for free.



Annotations:

* quantitative technical analysis is basically using statistical tools and aggregation on the price, volume, RSI etc. of a stock.

** checkout the metrics guide to understand more on aggregation and percentiles

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