Asset Allocation, Ruin and Geometric Return

In "A Practical Framework For Portfolio Choice" Michaud 2003, with a footnote reference to Block 1969, he gives this example of asset allocation and geometric return.

6.3 Asset allocation strategies that lead to ruin.
Suppose an investor invests 50% of assets in risky securities in each time period. Either the return matches the investment or it is lost. Both events are equally likely. This is a fair investment game similar to an asset mix investment policy of equal allocation to risky stocks and riskless bonds with rebalancing. In this case, investment policy leads to ruin with probability one. This is because the likely outcome of every two periods results in 75% of original assets. However, the investment is always fair in the sense that the expected value of your wealth at the end of each period is always what you began with. For two periods the expected geometric mean return is negative and declines to the almost sure long-term limit of −13.4%, which is found using (2). This example vividly demonstrates the difference between the expected and median terminal wealth of an investment strategy. It shows that the expected geometric mean return implications of an investment decision are often of significant interest.

I wasn't quite following this so I thought I'd try to figure it out.  I had two main questions:

1. What does he mean when he says " the likely outcome of every two periods results in 75% of original assets?" when the outcome of every single period is "fair," and

2. How did he get -13.4% in the sentence "For two periods the expected geometric mean return is negative and declines to the almost sure long-term limit of −13.4%, which is found using (2)."  Where "(2)", about which he says "the (almost sure) limit of the geometric mean is the point distribution," is:

This wasn't too bad. For question 1 I blew out an expected value tree over three periods and matched his assumptions to see what it looks like.  It looks like this:

Which shows that yes, in fact, the "likely outcome of every two periods results in 75% of original assets" using cumulative probability between any two-interval periods.  And the expected value is in fact still fair, with wealth constant in single intervals.

For question 2, I originally struggled for no clear reason until I just took equation (2) at face value after which it was straight-forward.  There is a 50% chance of an r = .5 (150k/100k-1) and a 50% chance of an r = -.5 (50k/100k-1). That means ln(1+.5) = .405.  ln(1+ (-.5)) = -.693 so the expected value with 50/50 weights (average) is .144.  That makes e^EV -1 = -13.4 which is what he said in the first place.  Interpreting that is another thing but his point that a fair single period return can be negative in geometric multi-period terms and "of significant interest" is made.