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S&P 500 Annualized Returns Fun Facts

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S&P 500 Annualized Returns Fun Facts

I just grabbed the S&P 500 annualized returns, including dividends but not inflation, from 1871 to 2017. Some fun facts: -The longest run of positive returns is 9 years. -9 year positive return runs happened 3 times, 1894-1902, 1991-1999, and 2009-2017. -That means if 2018 is a positive return year, this would be the first 10 year positive return run ever in the 146 history of the S&P 500. -The average and median length of positive return runs is 3.6 years and 2 years, respectively. -The longest run of negative returns is 4 years, this happened once from 1929-1932. -The average and median length of negative return runs is 1.3 years and 1 year, respectively. -The best ever annual return is 56.8% in 1933. -The worst every annual return is -44.2% in 1931. 2008 was second worse at -37.2%. But from 2000-2002 there was a 3 year run of negative returns totaling -43.4% (-9.1%, -12.0%, -22.3%). -The average positive and negative annual returns are 19.1% and -12.3%, respectively. -The average and median annual return for the entire 146 history of the S&P 500 is 10.8% and 11%, respectively. These numbers really gave me a sense of appreciation for the power of and confidence in the free market capitalist system and index investing. This growth represents wealth generation in the economy driven by competition and the desire to improve our lives. 10.8% return per year, 3.6 year positive return runs and only 1.3 year negative return runs, passively, I’ll take that deal all day long. All I have to do is buy the S&P 500 and sit back and reap the benefits. If only we could figure out a sustainable way to operate it.

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Indie HackersFits the IH revenue-focused audience · Strong signals: including · Missing: supports, reddit linkedin, podcasting
90%90% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsStrong engagement from HN community · Strong signals: ide, 000, io · Missing: https docs, excited, just released
62%62% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
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48%48% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
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43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
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34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.
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29%29% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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