Related Articles
Start Backtesting

Backtest Study: So You Want to Short the S&P 500?

December 31, 2021
Robson Chow
Tradewell logo

This study uses the tools of backtesting and data visualization to examine the challenge posed by short selling the SPDR S&P 500 ETF Trust.

The last few weeks in the S&P 500 have been a bit of a roller-coaster ride, with the SPY declining just over 5% in an 8-day period and subsequently making a new all time high over the following 15 days (on a closing basis). The recent volatility may have caused you to question holding long exposure to the S&P 500, and even tempted you to go short.

Recent all time highs in the S&P 500 index have coincided with market turbulence

This study presents an analysis, gathered from historical data, that may be relevant to anyone considering testing the short side on SPY.  

Backtest Analysis

So let’s take a look at the data. As the summary table below indicates, the historical probability of SPY closing higher ten days following any market open is 62%. So, within this timeframe, the S&P 500 has a natural upside drift.

Trading Days After t[0]

Probability SPY Closes Higher

1 day

54.48%

5 days

58.71%

10 days

62.06%

15 days

64.00%

21 days

66.01%

42 days

69.32%

60 days

71.63%

But, curiously, at the time of this study, the probability that SPY closes higher at least one of the days between day 0 and day ten is 88.82%. Let’s dig deeper.

The forward return chart below shows every single 10-day return period for the S&P 500 ETF, the SPY, since its inception.  

The blue lines show every single 10-day return period where the SPY closed higher at least once.  The red lines show every single 10-day return period where the SPY failed to close higher at least once, ie. T[0] was the highest price the SPY traded over the following 10 days.  

If it’s not already obvious, the density of the blue lines is a lot higher than the density of the red lines, simply because there are a lot more blue lines than there are red lines.  

The figure below highlights the occurrence of red line price paths by date and shows the 10-day returns of each date on the y-axis.

Medium-Term Timeframes

The same probabilities not only persist but intensify when we observe in 15-day and 20-day timeframes:

  • In each 15-day period the SPY historical probability of closing higher on day 15 is 64% and the probability that it closes higher from time 0 in at least one of those days is 91.53%.  This historical tendency played out yet again in the most recent correction, which started on November 18th but saw SPY close higher on day 15. You can see that in the first chart – the candlestick chart at the start of the post.
  • In each 20-day period, the historical probability that SPY closes higher on day 20 is 65%, and the probability that it closes higher from time 0 in at least one of those days is 93%.

Longer Timeframes

And do these tendencies persist over a 60-day period? Incredibly, when we look at the historical data, SPY has closed higher at least once over the next 60 trading days 97% of the time.

Takeaways

So, what are the takeaways from this?

  1. The S&P 500 exhibits a natural upside drift. Historically, SPY has closed higher than its t[0] value well over 50% of the time, over virtually all n-Day forward timeframes.
  1. More importantly, the price path the SPY takes to its final destination often registers many new highs from its starting point. In each of the 10, 15, 20 and 60 day timeframes the SPY has exhibited a historical tendency of closing higher at least once 89%, 92%, 93%, and 97% of the time respectively. This underscores how averaging down can actually prove itself a worthy strategy for index traders with long time horizons.

I hope you find this research helpful in your investment and trading process. Thank you for reading.

Read This Next
Robson Chow
Backtest Study: So You Want to Short the S&P 500?
This study uses the tools of backtesting and data visualization to examine the challenge posed by selling the SPDR S&P 500 ETF Trust.
Read Article
Humza Sarwar
What is a Backtest?
Backtesting is a method used in trading and investment research to assess the quality of strategy by simulating its performance against historical data. Learn more about the basics of backtesting by reading this article.
Read Article
Albert Huang
How to Backtest Your Trading Strategy: A Comprehensive Guide
Backtesting plays a key role in developing a successful trading system. Read this article to discover the steps a trader must take to backtest a strategy.
Read Article
Albert Huang
VIX Trading Strategies to Backtest
This article will explain what the VIX Index is, what instruments a retail trader can trade to profit from changes in equity market volatility, and also reveals three VIX-related signals worth monitoring. 
Read Article
Humza Sarwar
What is Trading Analytics and How Can Traders Benefit?
This article will help you understand the basics of trading analytics and how they can improve your trading performance.We'll also walk you through some of the most popular analytics options today so that you can find a solution that meets your needs.
Read Article
Get started with Tradewell for free

Start with the free version and upgrade when you need a larger metric library and longer lookback periods.

METRICS SOURCED FROM TRUSTED PROVIDERS OF MARKET AND ECONOMIC DATA
TradeBlock logo
FRED logo
CBOE logo
IEX logo
EIA logo
CME Group logo
Tradewell logo
Tradewell
β
© 2021 Tradewell, Inc. All rights reserved.
Start Backtesting