Back to list of Stocks See Also: Fourier Analysis of SSBNX, Genetic Algorithms Stock Portfolio Generator,
and Best Months to Buy/Sell Stocks

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Seasonal Analysis of SSBNX (STATE STREET TARGET RETIREMENT 2020 FUND CLASS I)

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Seasonal Analysis

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Notes: "Adjusted Close" means closing price was adjusted for splits
and dividends; Weekly (not daily) Adjusted close price was used for calculations;

Using data from 10/1/2014 to 7/26/2021 for SSBNX (STATE STREET TARGET RETIREMENT 2020 FUND CLASS I), this program was able to calculate the following historical seasonal cycles for this stock:

Historically, the best month to buy SSBNX is January

Historically, the best month to sell SSBNX is December

In January, SSBNX is historically down by -4.66%

In February, SSBNX is historically down by -3.60%

In March, SSBNX is historically down by -2.99%

In April, SSBNX is historically down by -1.44%

In May, SSBNX is historically down by -0.58%

In June, SSBNX is historically up by 0.07%

In July, SSBNX is historically up by 1.29%

In August, SSBNX is historically up by 1.16%

In September, SSBNX is historically up by 2.02%

In October, SSBNX is historically up by 2.70%

In November, SSBNX is historically up by 2.20%

In December, SSBNX is historically up by 3.83%

Right click on the graph above to see the menu of operations (download, full screen, etc.)

See Also: Fourier Analysis of SSBNXGeneral Statistics | |

Number of Data Points | 357 |

Start Date of Data | 10/1/2014 |

End Date of Data | 7/26/2021 |

Minimum Value of Adjusted Close | 7.59 |

Maximum Value of Adjusted Close | 13.10 |

Average Value of Adjusted Close | 9.67 |

Median Value of Adjusted Close | 9.59 |

Standard Deviation of Adjusted Close | 1.40 |

Coefficient of Variation for Adjusted Close | 14.48% |

The average ("mean") and median are measures of central tendency.

For the given time period, the price of SSBNX tends towards a value in the vicinity of 9.67 (the mean) and 9.59 (the median).

Standard Deviation and Coefficient Of Variation are measures of dispersion. These can be used to measure the volatility (risk) of a security, and also to estimate the expected ranges of the price.

Assuming a normal distribution, we expect to see 68% of values within one Standard Deviation of the mean (average), 95% of the values within two standard deviations of the mean, and 99% of the values within three standard deviations of the mean.

If the price of SSBNX goes above 11.07 (mean + 1 standard deviation) or below 8.27 (mean - 1 standard deviation), then the reader is urged to investigate further for a possible buying or selling opportunity.

If the price of SSBNX goes above 12.47 (mean + 2 standard deviations) or below 6.87 (mean - 2 standard deviations), then the reader is urged to investigate further as this would be an unusual event.

For the given time period, the price of SSBNX tends towards a value in the vicinity of 9.67 (the mean) and 9.59 (the median).

Standard Deviation and Coefficient Of Variation are measures of dispersion. These can be used to measure the volatility (risk) of a security, and also to estimate the expected ranges of the price.

Assuming a normal distribution, we expect to see 68% of values within one Standard Deviation of the mean (average), 95% of the values within two standard deviations of the mean, and 99% of the values within three standard deviations of the mean.

If the price of SSBNX goes above 11.07 (mean + 1 standard deviation) or below 8.27 (mean - 1 standard deviation), then the reader is urged to investigate further for a possible buying or selling opportunity.

If the price of SSBNX goes above 12.47 (mean + 2 standard deviations) or below 6.87 (mean - 2 standard deviations), then the reader is urged to investigate further as this would be an unusual event.

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