B$ Strategery

Here's an interesting tidbit: For blogs with few incoming and many outgoing links, apparently 5 incoming links or less will put out a nice outgoing value, but 6 or more will drop this back down to 'lesser' levels. 5 links here put out about 12x the blog's actual value, but 6 - 10 links put out only about 4x the blog's total value.

Values rising again... I was able to build a small blogroll up after repeated reindexing, and eventually got values up so that I could reindex other blogs feeding mine to get the values rolling again. Took some time, but it's paying off now again.

Saw a few blogs drop out of the blogroll, can't tell which ones at this point, but it only created a minor hiccup.

Worst problem I'm dealing with now are new links coming in, and balancing outgoing links to match. Had two blogs crash outgoing value because the outgoing count fell too low, had to add more outgoing links and reindex before anything else happened to get those values back up.

Back in January, B$ Operation Potent Wind went into effect, driving share prices up far higher than we'd seen in the game previously, in one of the stated purposes was to increase blog values. By March, top blogs had values of hundreds of thousands of B$, some into the Billion B$ range, including some blogrolled ones, as noted by charts in early entries here. Sadly, the math at that point was not well understood, and values could not be maintained.

We are a ways to go yet before seeing blogs hitting the Billion B$ mark, but the various blogrolls in the game are chugging along nicely, with values in the low hundreds, the Top 100 blogs filled with blogrolled sites. The top 5 blogs have even been encroached upon, and we may be only a week or so away from the #1 blog being replaced.

More sites continue to link together, wheels within wheels. So far the B$ market index graphs have seen little impact from Project Bootstrap, but a small upward spike can now be seen on these graphs. I'm taking this as a promising sign.

Had to open my mouth and post... Had a minor problem two days ago, had some new incoming links and didn't notice, outgoing links fell too low and outgoing value crashed. Managed to recover the next day, but was then hit by a few blogs unlinking from the roll, also some lesser blogs delisted, meaning slow going for a spell while things rebuild.

More blogs linking in today, caught this early and was able to link back before reindexing, but the roll is very unstable now, too many changes happening at once, not enough value being looped back in. The new blogs are going to have to stabilize and start putting out more value before we can keep building.

I can temporarily hold some of this back by keeping my blogs from being indexed with local firewall controls, to keep anything from losing value, but I can't control the other blogs in the roll.

I've noticed this sort of thing before, but hadn't found a great example until now. I've noticed that sometimes a change in incoming value doesn't always correspond to a similar change in outgoing value. You would assume that more in equals more out, all else being equal. Obviously, something is not equal:

Note that in each case, the incoming and outgoing link totals are the same. From the 26th to the 27th, incoming value dropped, and we saw a drop in outgoing value. On the 28th incoming value rose, but outgoing dropped again. On the 30th, incoming dropped, and outgoing dropped even more than before. On the 31st, incoming rose to a similar level as the 28th, but outgoing fell again by a small amount.

Does outgoing depend on a trend of past outgoing values, or is there some other factor at work?

Let's take a look at the data again, this time with the multiplier in the table instead of Market Share (which isn't a terribly useful value anyway). Multiplier calculated as follows: (Outgoing Value * Outgoing Links) / Incoming Value

Now, let's take a look at a different blog, with very different numbers, picking reindex values for those same dates:

Here we can definitely see a pattern, the multiplier vales are identical to several decimal places, and there may be extra precision (more than two decimal places) being tracked by B$ that isn't displayed here which would result in rounding errors, so for our purposes this is close enough to being exact.

Some last values I was able to pull from B$ for several others, with a few more prior dates:

Note that I have two entries for July 23, the very large number of outgoing compared to incoming (12x!) seemed very interesting, but since it fit the multiplier pattern I added the entry for that date mainly as a proof, reindex values for that blog appear later in the chart for June. Going back a month, we can see the values for the multiplier increase, then start falling going back to July 7, bottoming out on June 24.

We have multipliers of 3.8199 on June 23, July 2, and July 31. Since values were lower between June 23 and July 2, the June 23 value was on the downward slope, as is the value on July 31, this puts the cycle of the multiplier at about 38 days. We also see a multiplier of 5.313 on both June 4 and July 21, but I believe that the June 4 value was still on the rise, but may have been close to peaking. We know that the cycle bottomed out between June 23 and July 2, a period of 9 days, so going back to the topmost table, outgoing values will continue to have a lesser multiplier for the next 4-5 days before the cycle hits an upswing again.

So, the big question now is, how to use all of this information. The most pressing thought would be is it safe to reindex a given blog, even if the value is on the rise. I don't have data points to give exact numbers, but early analysis indicates that as the multiplier is about 7 days from reaching its peak, a blog's incoming value can actually drop about 3% in a day, and still see an increase in the outgoing value, after that a blog can lose less value each day to keep the same outgoing (obviously increasing values here would be very helpful), and on the other side of the curve, about 7 days after the multiplier peaks, a blog would have to increase in value almost 4% over the prior day to keep the same outgoing value.

Going back to the 1st table from Part 1, we can determine that the blog only gained 2.14% from the 30th to the 31st. Had the blog instead increased about 2.37% (B$51,258,207.783), it would have been able to keep the same outgoing value.

So, based on this info, if a blog will gain at least 4% in value, it should be safe to reindex, regardless. If the blog will gain less than 4%, it will be important to determine where in the multiplier cycle B$ is to avoid potentially costly mistakes.