Friday, April 16, 2010

On Tax

Saw a post here: http://www.wisebread.com/bar-stool-economics-0

The complaint is about that over half of the population pays no income tax. Ten percent of the population pay 70% of all income tax.

For those who complained about "unfair share" of tax on the rich, let me also provide this statistics from government study of wealth distribution:
- top 1% of the poupulation owns 34% of total assets in this nation
- top 20% of the poupulation owns 85% of total assets
- the bottom 80% claims only 15% of the assets

As you know assets generate capital gain, interest, and rent. These income are almost effortless. (say compare to coal miners.) Those who wrote articles like in the above link never cite these statistics side by side with tax burden. I think we need to consider the whole picture. Tax is an unpleasant fact of life. But US tax burden on the rich is less than most, if not all, OECD countries. It is a necessary evil. And I think the rich should be a bit more compassionate toward society.

A recent report from WSJ: Wall Street Banks are lobbying against centralized clearing house for derivatives trading because $20 billion of revenue is at risk.

But without centralized clearing house, it means future government bailout is inevitable because society can not afford the melt down of the entire financial system.

From this example you can see anyone's wealth has to do with how the law is written. That centralized wealth I quoted above has a lot to do with US law and lobbying.

I think when considering tax policy we need to factor in these facts. The bottom 80% who owns only 15% of all assets obviously don't have the resources to do much lobbying.

Thursday, April 08, 2010

Can you really measure and model risk?

I am not saying statistical inference is useless. As I said in my first post, for life insurance and the risk of a claim due to death is predictable. In fact if you have a large enough risk pool, the projection can be accurate to an impressive degree. On the other hand, the risk of mortgage default is a very different animal. With the benefit of hindsight I understand today that it has to do with trillions of easy credit flowing into this country, with China and Japan together lending us more than 1.6 trillion. The potent power of low interest rate created the asset bubble and the bust that follows. As you can see this is an external variable that keeps accumulating (by just look at the trade deficit). But AIG keeps selling Credit Default Swap (CDS) as if it is a life insurance to insure mortgage default, to the degree that without 80 billion of government bailout, it means chain bankruptcy of financial institutions all over the world and the Great Depression 2.0. I don't want to elaborate on the relationship between Great Depression 1.0 and World War 2 as I am not an expert, but you understand the scare. So let me conclude by answering to the question "Can you really measure and model risk?". My thought is that it depends on what kind of risk you are talking about. You need to use a common sense judgement before you apply the state-of-the-art software. And you need to have a sufficient understanding of the boom and bust nature of economic history. And when someone pretend to be able to model things that can't be on a sound scientific footing, you should be able to call their bluff and air your skepticism. It is healthy for quants to air their skepticism. You are helping the society by demystifying the quants.

Monday, April 05, 2010

Quantitative Modeling

Wrong forecast gives a false sense of security. You can safely argue that none of the Lehman, AIG, and Bear Stern modelers forecasted the coming tsunami in 2007. Not even the Fed foresees the damage a nationally depreciating housing price can do to the world economy. The fact that world governments resort to fire fighting by printing money - 1.4 trillion in the US alone - speaks volumes to the failure of forecasting. That is why Mr King is advocating improving robustness of the infrastructure, and funding the fire fighting capacity. The true lesson from this financial crisis is that financial modelers are very ignorant about economic history, and determined to stay that way, while layman put too much trust in these "quants". Don't be fooled by people claiming to have an equation that can forecast a society's behavior. Issac Newton said he can not, and so you should be skeptical. Your skepticism will make the financial market healthier - you become part of the robust system.

Thursday, April 01, 2010

Can risk be modeled?

If you are talking about Life Insurance and the risk of death, more than one hundred years of experience has proven that, short of a war or pandemic, mortality is predictable. Law of large number will reduce the variability and you can model to a degree of confidence. If you are talking about probability of default on debt, then you are talking about modeling people's behavior that will be driven by incentives and the performance of the entire economy, which as many under currents. Everyone probably still have the credit crisis and financial panic of 2008 in mind. One of the source of the panic is that financial engineers assume mortgage default rate will behave about the same as the past 10 years, and priced the CDO/ CDS accordingly. When law of large number does not stabilize the default rate and it becomes clear that trillions of derivative assets are priced on wrong assumptions, the run starts. The disaster was a magnificent view. You put your trust on the model you don't fully understand at your own peril. And some short sellers are wise enough to profit handsomely on it. The lesson I learned is that I should examine the assumptions modelers use carefully, before embracing "financial weapon of mass destruction" (Buffett) as a panacea to reduce funding cost.