August 25, 2009
New pricing data come out on the housing market today and on a month over month (May to June) basis it was positive. This was true for the previous period (April to May) as well. The increase was not overwhelming but reasonably strong, but it is hard to get to excited when the latent supply (additional foreclosures, under water homes,.).

What I found interesting was the breadth of the rise. Nearly all the sub components rose as well even place where the foreclosure situation is a mess. (What does this tell you about that factor as a driver?….)

A friend asked a question related to the degree to which I though this was driven by the first time buyer tax credit and what would happen to demand when that went away. Without doing too much investigation my response was if it is all first time home buyers (which I can’t find the data but I’m told that they are heavy participants) then the ‘homeowner’ pool is getting bigger. This is because people who were not in the owner category shifted to it and the seller will likely look for another house (stay in the owner category). Although I expect this ‘owner’ group stickiness to be less true than is normal because of the compositions of sales (ala foreclosures).
That said the home price index is incredible correlated with mortgage credit and where that goes I expect housing prices to go; so did the tax credit matter, sure for someone somewhere; did it fix the housing market? no, the credit markets really broke the housing market and are now trying to put it back together, we will all see if they succeed.
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Posted by pwswartz
August 13, 2009
In my view one of the most important component of alpha generation (financial gambling) is weighting. How large to make your bets. Interestingly this is not often discussed in the class room or the board room. Valuation, timing, and strategy are discussed but when was the last time someone asked you what the geo-metric mean maximizing weight of your strategy was (if ever)? [An interesting side discussion is, 'is the reasons it is one of the most important components of alpha generation because it is discussed so little']. Also the formal designs of weighting are much less developed (or maybe it better to say much more complicated; even when it is a single strategy weight and not a strategy in the context of a portfolio) than valuation. But for the under use and difficulties that the sizing of bets entails it makes financial gambling much much easier than ‘life gambling’.
Consider that for a financial gamble you can scale it to your confidence, without (for most of us) having any impact on the market. In short the way you scale the bet doesn’t impact the way the bet turns out. On the other hand in life you can’t just scale the bets to confidence because how you scale the bets (which in this case I mean the effort/commitment that you put into an activity) changes the outcome significantly. Consider the realm of foreign policy if you think a foreign excursion (pays off 10:1) is worthwhile even given it only 20% chance of success. A PM (portfolio manager) would put on a weighted bet based on the payout but the statesman would have to calculate the weight that he was willing to commit (and at the same time) consider what they would be doing to the chances for success. A more challenging problem.
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Soft Topics & Uncertainty, Uncategorized |
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Posted by pwswartz
August 10, 2009
One purpose of floating exchange rates is to help global imbalances resolve themselves (at a basic level if you are running a trade surplus then your currencies should rally (purchasing power becomes greater, other regions become more competitive, and hopefully at some point the surplus (savers) country will spend their funds…so that they debtor country doesn’t explode)). But currencies have a large number of other influences on them (the most significant of which is capital flows), so does it work just this way. We’ll here’s a chart that tries to tell when currencies are doing the job of resolving global imbalances (when the blue line is positive it is ‘working’).

The charts shows the 12 mth moving average of the slope of an OLS (regression…read ‘a line drawn through points’) on the real exchange rate against the current account balance. If you are running a surplus then your currency ’should’ go up (this would mean that a positive slope suggest that the currency markets are working’). The blue line is the sum of countries current accounts as a % of local GDP…this is supposed to get a the size of global imbalances. So what you’d like to see it the red line (the imbalances line) close(r) to zero but to the extent that it is not one would hope that the blue line would become go higher.
Admittedly this is way too complicated for what it is trying to do and it has problems in that it is dealing with a change (in the currency) and a level, sort of, in the current account balance. The results are some what sensitive to the period that is chosen for the currency change. (if you are interested I’ve chosen 24 month changes). All that said I still think it is an interesting picture….why?
Because it shows that global imbalances blew up after 97/98 when the currencies stopped ‘working’, getting more in balance as currencies ‘worked’ between 00-03, and then expanding again when currencies stopped working again. (Although given that the world has significant non-floating currencies, its not fair to blame it all on ‘non-economic’ markets)…
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Currencies | Tagged: imbalances |
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Posted by pwswartz
August 9, 2009
The CBO put out its Long Term Budget projection a while back but the cover it worth pondering. Both scenarios it has evaluated are non workable. At lease they are being honest…let hope we can tackle our fiscal problems before they tackle us.
Another interest note is that the recent spike in debt % of GDP matches (or reasonably closely) up with (with respect to change and velocity of change) WWI, the GD, and (only the first year) of WWII.

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Policy | Tagged: fiscal |
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Posted by pwswartz
August 7, 2009
A nearly daily complaint I have about financial media is that they don’t get into the detail about the data. They simply report the headline. For example about a month ago Bloomberg lead with the following…..
“June 26 (Bloomberg) — Consumer spending rose for the first time in three months in May as incomes jumped by the most in a year, a sign that government efforts to revive the economy may be starting to pay off.”
It was all due to a one of tax credit.
“Personal current transfer receipts increased $162.6 billion in May, compared with an increase of $59.1 billion in April. The American Recovery and Reinvestment Act of 2009 provides for one-time payments of $250 to eligible individuals receiving social security, supplemental security income, veterans benefits, and railroad retirement benefits. These benefits boosted the level of personal current transfer receipts by $157.6 billions at an annual rate in May. “
http://www.bea.gov/newsreleases/national/pi/pinewsrelease.htm
but once in a while they get something close….
like with the Reuters storythat job hunters take summer off…although they needed an explanation of why 247,000 people lost their jobs and the unemployment rate went down from 9.5% to 9.4%. At least they didn’t simply report a drop in unemployment. That said, saying that this is driven by the unemployed taking a vacationing is some what deceiving. The labor force dropped by 422k which could be true (and likely is to a degree) that the unemployed are discourage but it is more likely a statistical fluke and that the labor force will jump up next month….which they will then attribute to coming off summer break.
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Stats & Modeling |
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Posted by pwswartz