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Random Investing in High Tech Stocks

The question considered in this article: How would the average fund have performed since 2010 if it just picked 10 stocks from NASDAQ-100 at random that were up in prior 120-day period? The answer may, or may not after all, surprise you.

The setup

  • Buy at random ten stocks from NASDAQ-100 with 120-day rate of change greater than 0.
  • Position size is available equity/10.
  • Sell a stock if the 120-day rate of change falls below zero, or if it is not in the index any longer.
  • Always keep a maximum of 10 stocks in the portfolio.
  • Backtest period is from 01/04/2010 to 02/02/2021
  • Repeat backtest 500 times and determine the distribution of annualized return (CAGR)

For the backtests in this article we used Norgate data for NASDAQ-100 index that include current and past constituents to remove survivorship bias. This is essential for generating realistic results. We highly recommend this data service (we do not have a referral arrangement with the company.)

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CAGR frequency distribution for 500 backtests

Below is a table of basic statistics:

Parameter Value
Average CAGR 16.2%
Standard deviation  17.%
Skew 0.205
Kurtosis 2.8
Minimum CAGR 11.1%
Maximum CAGR 21.7%
Average max DD -26%

Note that in the test period, buy and hold CAGR for NASDAQ-100 is 19.3% and maximum drawdown is 28%.

Few observations

  • Worst annualized return was about 11% with the random investing.
  • A few random investors outperformed buy and hold.
  • The “average random investor” made about 16% annualized return.

Next the questions

  • How many macro and quantitative funds did worse than random investors?
  • Or, better, are macro and quantitative funds worse-than-random investors?

Answers to the above questions are left as an exercise to the reader.


Charting and backtesting program: Amibroker

Data provider: Norgate Data

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