Dear Statalist,

I would like to know how to interpret the results of a regression that I'm running. I'm regressing the monthly returns of a portfolio given in decimal form on the monthly change in the TED spread (which is also given in decimal form). These 2 variables are both in percentages originally.
I'm getting the following results from the regression
Code:
 reg portfolio1 changeted
portfolio1 Coefficient Std. Err. t
changeted 1.722623 0.6577956 2.62
_cons 0.0046564 0.0012223 3.81
Now what is the correct way to interpret these results?

1. A 1 percentage point increase in the monthly change of the TED spread increases the returns of the portfolio by 172 percentage points

2. A 1% increase in the monthly change in the TED spread increases the returns of the portfolio by 172%

Here's a subset of my data below so you can see how the relevant variables are depicted:

Code:
* Example generated by -dataex-. To install: ssc install dataex
clear
input float mdate double portfolio1 float changeted
358   .00849232634736   -.0028476184
359    .0196473443785    .0002295738
360   .00908474893664   -.0018010028
361  -.00789620730366   -.0008674185
362    .0195815621909   -.0003057416
363     .027590637801    .0020110048
364  .000916804789517   -.0005902257
365    .0158492072062   -.0011095237
366    .0228994165542   -.0002857144
367    .0160825575945    .0005199136
368    .0436228907427     .001891866
369    .0429131154968     .001658134
370  -.00697735981956    .0010681814
371    .0216892669748    .0005894741
372   -.0095828701076   -.0005085217
373   -.0324055587067    -.003454636
374   -.0063345531009   -.0010813158
375  .000701541869713   -.0008307146
376  -.00404627954966    .0001476193
377    .0240512142543   .00038309535
378  .000794257469344   -.0007313639
379 -.000107101605566   -.0011945884
380   -.0114348075008   -.0004490479
381  -.00761210352102    .0008163638
382     .033791962529    .0004188996
383    .0174744570914 -.000015263446
384    -.042712548086   -.0014185715
385   -.0115241663969   -.0004714285
386    .0120620200275   .00022727274
387    .0114044506298    .0006477272
388   .00235680516069   -.0008907893
389    .0115165324735    .0000976075
390    .0113243855309   -.0003318181
391    .0333249198916        .000215
392   .00759933642572    .0005016667
393    .0144097172053    .0019904762
394   -.0133345697828    .0008902256
395  -.00943171681865    -.002456892
396   -.0373814303009   -.0007220551
397   -.0157087963392    -.000368421
398   -.0125583788066  -.00021304353
399   -.0254557869421    .0006980435
400  -.00886132794598   -.0007586842
401   -.0211462904909  -.00016722502
402   -.0127728666938  -.00007813843
403   -.0047867762325  -.00015714276
404  -.00181247685364   .00023333333
405  -.00387143948895    .0010778571
406    .0147179584594   .00010499987
407   .00182382931063   -.0006299999
408   -.0242212731622  -.00020473683
409    .0272000913751   -.0000526316
410    .0155942011949    .0008038902
411   .00510120234059    .0006879228
412  -.00116494962791   .00049555534
413    .0144875169313   .00004636357
414  -.00659186811291   .00025863666
415    .0186325126031   -.0008086367
416    .0160257094466    .0006493507
417    .0309753274867     .001664286
418    .0274654193376   -.0008300003
419   .00460671756132        .001935
420   .00574407730955        -.00152
421  -.00290292902279   -.0014139474
422    .0126022717027    .0004702518
423 -.000910747414227    .0004198067
424  -.00232210454743   -.0012634918
425  -.00376991614283    .0007887445
426  -.00587224952977   -.0006363639
427   -.0215626957343    .0003181817
428   .00919582327103    .0008318182
429    .0431705338809    .0007642857
430  -.00230383648953    -.001385714
431  -.00833769362855    .0008293232
432   -.0160017915454    -.000600752
433   .00873168041384   -.0009671426
434  -.00758796582581  -.00017095264
435   .00613113205471    .0011609523
436   .00637332670668   -.0006799996
437    .0182696639881   -.0000400003
438    .0235125729808    .0001718183
end
format %tm mdate