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In this article I show you can invest profitably in the Nasdaq and S&P500 using a relative strength strategy. I show my I have chosen these markets and explain how you can test your own relative strength strategies.### Relative Strength Investing

Most investors want to buy when a market is getting stronger and sell when it is getting weaker. However it can be difficult to judge whether a particular market is strong or weak. The principle of relative strength investing is to buy when a market is getting stronger relative to another market or group of markets. When the market is getting weaker we sell. This principle can be applied to many different markets including stocks, sectors, and indices.### Nasdaq Composite and S&P 500

The chart shows the Nasdaq Composite compared with the S&P 500 since 1990. The Nasdaq is green and red and the S&P 500 is blue and gray. The Nasdaq Composite represents all the stocks traded on the Nasdaq stock market. It is heavily associated with the technology sector. Historically the Nasdaq has tended to move strongly upwards in a risk-off environment and strongly downwards in a risk-on environment. The S&P 500 represents the largest 500 companies listed in the US. The companies in the S&P 500 include many of the largest companies in the world. Historically the S&P has tended to move in the same direction as the Nasdaq but by a smaller amount.### A Relative Strength Investment Strategy

For this strategy I am comparing just two markets: the Nasdaq and S&P 500. I want to capture the Nasdaq’s exuberance when stocks are rising and the S&P 500’s smaller declines when stocks are falling. The way that I have measured relative strength is to firstly calculate the ratio: Nasdaq Close/S&P 500 Close. Then I calculated the 200 period linear regression of this ratio. The linear regression is a statistical tool to identify the best-fit straight line. So if this line is pointing upwards then the Nasdaq is stronger. If the line is pointing downwards the S&P 500 is stronger. One further rule is that I want to wait to enter long Nasdaq when the ratio has closed lower than the previous day and wait to enter long S&P 500 when the price has closed higher. The reason for this rule is to get an improved trade entry price. I tested the strategy using data from 1990 to the middle of 2016.#### Strategy Rules

- Enter Long Nasdaq when the 200 period linear regression has changed direction to point upwards. And the ratio has just closed down compared to the previous close.
- Enter Long S&P 500 when the 200 period linear regression has changed direction to point downwards. And the ratio has just closed up compared to the previous close.

### Strategy Results

This investment strategy was tested using the latest Tradinformed Backtest Model. These models are spreadsheet based using Excel and allow you to test all sorts of investment and trading strategies. They test long and short and can be applied to many different markets and timeframes. Check out the Tradinformed Shop to see what is available. The results of the strategy compared to the two indices are shown below.Strategy | Nasdaq | S&P500 | |
---|---|---|---|

Starting Capital | $100,000 | 196.4 | 321.9 |

Final Capital | $569,648 | 4988.6 | 2137.2 |

Gross Winning Trades | $677,843 | ||

Gross Losing Trades | $-208,195 | ||

Net Profit | $469,648 | 4792.2 | 1815.2 |

Profit Factor | 3.26 | ||

Winning Trades | 22 | ||

Losing Trades | 9 | ||

Percentage Winning Trades | 71% | ||

Average Winning Trade | 30,811 | ||

Average Losing Trade | -23,133 | ||

Largest Winning Trade | $156,162 | ||

Largest Losing Trade | $-74,766 | ||

Max Drawdown | 35.8% | 82.9% | 56.8% |

Years | 25 | 25 | 25 |

Compound Annual Growth Rate | 7.2% | 13.8% | 7.9% |

Results | Strategy with 10% SL |
---|---|

Starting Capital | $100,000 |

Final Capital | $397,454 |

Gross Winning Trades | $389,133 |

Gross Losing Trades | $-91,679 |

Net Profit | $297,454 |

Profit Factor | 4.24 |

Winning Trades | 21 |

Losing Trades | 10 |

Percentage Winning Trades | 68% |

Average Winning Trade | 18,530 |

Average Losing Trade | -9,168 |

Largest Winning Trade | $81,981 |

Largest Losing Trade | $-19,719 |

Max Drawdown | 19.3% |

Years | 25 |

Compound Annual Growth Rate | 5.7% |

Results | Strategy with 10% SL |
---|---|

Starting Capital | $100,000 |

Final Capital | $1,162,418 |

Gross Winning Trades | $1,411,558 |

Gross Losing Trades | $-349,141 |

Net Profit | $1,062,418 |

Profit Factor | 4.04 |

Winning Trades | 21 |

Losing Trades | 10 |

Percentage Winning Trades | 68% |

Average Winning Trade | 67,217 |

Average Losing Trade | -34,914 |

Largest Winning Trade | $318,000 |

Largest Losing Trade | $-88,557 |

Max Drawdown | 34.5% |

Years | 25 |

Compound Annual Growth Rate | 10.3% |

Missing “am” in: “For this strategy I comparing just two markets”.

Hi Waldemar, good comment. I take your point. More trades would have been better. However this is a long term strategy that builds up profits over a long time. Inevitably it will only have relative few trades compared to a mean reversion type system. But still, 26 years and more than 6600 daily closes is quite a lot of data. To get more trades you could extend this test back to 1971 when the Nasdaq index started. However, I would be concerned about how different the Nasdaq is today compared to back in 1971. Overall, this test is only an example of what is possible with relative strength. I am sure there are many ways to improve these results and that is why my focus on this site is to encourage traders and investors to do their own analysis and build their own systems.

Hi. The only problem I have with this strategy is very small data sample. There are on average 30 trades in 25 years. That comes to 1 trade per year (roughly). How about results on a shorter time frame?

Waldemar