I was hoping someone might be able to help me out with the following question:

I have built a spreadsheet that generates data on a monthly basis for 100 distinct "blocks" (January through December, vertically oriented, 100 times; the example below features only 2 months for 1 of those 100 12-month "blocks"), with each month containing several identical categories (two of which are "

**Exp. X**" and "

**Exp. Losses**").

Column B features all of the listed categories and Columns C through V represent unique situations based on years, as such:

1 | A | B | C | D | E | F | G |

2 | JAN. | Category 1 | 1999 Data | 2000 Data | 2001 Data | 2002 Data | 2003 Data |

3 | JAN. | Category 2 | "" | "" | "" | "" | "" |

4 | JAN. | Exp. X | $500 | $100 | $300 | $200 | $400 |

5 | JAN. | Exp. Losses | ($50) | $0 | ($100) | $0 | ($200) |

6 | JAN. | Category 5 | "" | "" | "" | "" | "" |

7 | JAN. | Category 6 | "" | "" | "" | "" | "" |

8 | JAN. | Category 7 | "" | "" | "" | "" | "" |

9 | FEB. | Category 1 | "" | "" | "" | "" | "" |

10 | FEB. | Category 2 | "" | "" | "" | "" | "" |

11 | FEB. | Exp. X | $200 | $300 | $100 | $200 | $500 |

12 | FEB. | Exp. Losses | $0 | $0 | ($25) | $0 | $0 |

13 | FEB. | Category 5 | "" | "" | "" | "" | "" |

14 | FEB. | Category 6 | "" | "" | "" | "" | "" |

15 | FEB. | Category 7 | "" | "" | "' | "" | "" |

<tbody>

</tbody>

Would it be possible to SUM all of the

**Exp. X**numbers in Column C (which would encompass both the January and February results of course), but

__?__

*only those that also feature a loss in***Exp. Losses**Meaning, something along the lines of SUMIFS(B1:B15,"*Exp. X*",C1:C15) but then only if AND(B1:B15,"*Exp. Losses*",C1:C15,"<0"). I am trying to pair the SUM of the

**Exp. X**with only the cells that also feature a negative number in the

**Exp. Losses**cell.

The actual results for Column C would equal $500, because the $200

**Exp. X**in the month of February does not feature a loss in the

**Exp. Loss**category.

Any help with crafting the formula would be greatly appreciated!

Many thanks,

HGL