Every now and then the mainstream media will do an article covering the hatchet job that the Fed has done on the savers of this country. Today they printed one such article, entitled At Tiny Rates, Saving Money Costs Investors.There's really nothing in the article that we haven't said a million times before: the Fed is reinflating the economy at the expense of savers, the very investors who were least responsible for the economic collapse. The elderly who lived off a fixed income are being especially hard-hit as saving and CD rates tumble from 5-6% to under 2%.

Perhaps the most interesting part of the article was the following quote:

"Experts say risk-averse investors are effectively financing a second bailout of financial institutions, many of which have also raised fees and interest rates on credit cards.

“What the average citizen doesn’t explicitly understand is that a significant part of the government’s plan to repair the financial system and the economy is to pay savers nothing and allow damaged financial institutions to earn a nice, guaranteed spread,” said William H. Gross, co-chief investment officer of the Pacific Investment Management Company, or Pimco. “It’s capitalism, I guess, but it’s not to be applauded.”

I've written about this before also and it's appalling. What the banks do is borrow money from me and you, or even the Fed for 1% and under and then lend it out at 5-6%. They can't lose money. Banks are reporting profits because they are in a no-lose interest rate environment and also because they changed the accounting rules to make their bad assets disappear. You'd think they'd be sharing the wealth, but instead, credit is tight, and the banks are raising credit card rates and lending standards.

We help them recapitalize and strengthen and they stick us with the bill. Oh, and they pay themselves nice fat bonuses. Give me a break. A high schooler could recapitalize a bank in today's interest rate environment.

Is there anything you can do? Yes, if you plan to deposit money, make sure you deposit it into a high yield savings or cd account. You might as well get the best savings rate or best cd rates you can. Reward the banks that are willing to pay a bit more for your hard-earned cash.

It was a relatively quiet week as markets and consumers ready themselves for the Holiday season. The biggest news had to do with the increase in the yield between the 2 year Treasury Note and the 30 year bond. The yield curve earlier in the week was the steepest it's been since 1992. What's behind this? The Fed is keeping short term rates low. Long-term rates are rising though as investors look ahead to increased Treasury security offerings and investors become more and more concerned about nflation. Still, for all the worry about inflation, there is remarkably little on the horizon. As this Wall Street Journal article indicates:

"Based on prices of U.S. Treasury Inflation-Protected Securities, where principal and interest payments are adjusted for changes in the CPI, inflation is expected to be less than 1% in 2010, says Michael Pond, Treasurys and inflation market strategist at Barclays Capital.

Looking a little bit further out, TIPS prices suggest inflation is expected to be 1.5% per year over the next five years and roughly 2.1% over the next 10 years, according to Barclays. "

Some investors feel that TIPS are just cheep and haven't yet priced in future inflation. Maybe so. But there is still tremendous slack in the economy and it is far more likely we'll see an asset bubble before we see a jump in CPI inflation.

The impact in the steep yield curve can be seen in the dichotomy between deposit and lending products.

CD and Savings Rates

Short term and medium term rates remain low and dropping.

All savings and CD rates dropped last week. Savings rates dropped last week by 4 basis points from 1.61% APY to a new low of 1.57% APY. One year CD rates also dropped by 4 basis points to 1.95% APY while 3 year CD rates dropped by 8 basis points to 2.72% APY. Five year rates dropped by 9 basis points from 3.35% APY to 3.26% APY. It's uncharacteristic for 5-year rates to drop by so much and after rallying a bit from summer lows of 3.22% APY are closing in again on that level.

Looking at the yield ratio we have developed for deposit accounts, the spread the spread between savings rates and 36-month CDs came down slightly due to the drop in 3-year CD rates. This drop in longer-term CD rates reverses the slightly upward movement that we saw since the summer. It's possible we'll see 5-year CD rates below 3% APY in the next couple of months if the current trend continues.

My guess is that the downward blip in 3 and 5 year CD rates was a temporary phenomena. Treasury notes and bonds saw their yields rise last week and as the Fed begins to remove stimulus it's easier to see rates going up in the future than going down. It's still hard to recommend putting money into anything longer-term than a 12-month CD, especially with rising equity markets and signs that the economy may be coming back to life. For those worried about interest rate risk, cd laddering may be a good way to smooth out the return you receive from your CD portfolio.

Mortgage Rates

Longer term mortgage rates for the first time in several weeks.

According to the BestCashCow rate tables, the average 30-year fixed rate mortgage rose from 4.957% the previous week to 4.971%. The fifteen-year fixed-rate mortgage average went from 4.4% to 4.43%. While mortgage rates rose on most products, they are still close to historic lows. This is a good time to refinance and these rates won't last once the Fed ends its mortgage and Treasury Bond buybacks. Many analysts expect rates will increase into the 6% range once this happens.

You can compare the best mortgage rates in our new mortgage section.

Now before you run away from a seemingly boring and incredibly technical topic, I want to at least relay the importance of it. Complex financial modeling is at the heart of risk management and dictates how much capital banks, insurance companies, pension funds, corporations, and individuals need to hold in order to meet all of their financial liabilities. This topic is important to understand because it played an integral part in the massive financial destruction that was 2008. I would not be able to write a comprehensive article on financial modeling without approaching the size of a book, but what I will try to do is explain the principal components (no pun intended) of complex financial modeling and why it has to be so complicated.

The first and most important principal in financial valuations is that everything in the financial world is viewed as a stream of cash flows. The only thing that distinguishes between securities is how those cash flows are derived. The simplest type of securities from a valuation perspective are fixed income bonds. A coupon bond has a series of payments each year related to the coupon and one final payment of principal on the final maturity date:

Coupon Bond Cash flows (Assume 10% interest paid semi-annually)

The coupon bond is easy to value because all you have to do is discount the fixed cash flows at current interest rates to come up with the current value. Instruments become difficult to value when their cash flows are unknown and/or variable.

Equity prices can be considered the discounted value of both variable and unknown cash flows. A stock’s value is nothing more than the discounted value of all free cash flows that the company produces from now until infinity (assuming the company survives). Equity analysts spend incredible amounts of time forecasting cash flows and growth rates for individual companies going forward, just so that they can come up with what they believe is a discounted free cash flow “fair value”.

It might have seemed like I went off on a bit of a tangent with simple bonds and equities, but it is important to understand those concepts before we leap into the more complicated. The more complicated items include equity options, mortgage backed securities, collateralized debt obligations, etc. There are many hundreds of ways I can dice up the categories, but nearly every one of them has a common a element – Optionality.

Options, in this definition, make the value of the security depend upon some future observation of a market. I probably lost just about everyone with that statement, but give me a chance to explain. What if I said you needed to value a variable annuity in which the contract provides the policy holder a fixed stream of cash flows 20 years in the future and the size of those cash flows depends upon the level of the S&P 500 in 20 years? This might seem complicated, but in reality this is on the simpler side of options. What if the cash flows did not depend upon the return of the S&P 500 from now until year 20, but instead it was a series of resetting options for 20 years in which every year the gain was locked in and the option was reset? Even better, what if the options depended upon the average performance of multiple indices such as the S&P 500, Eurostoxx 50, and FTSE 100?

The bottom line is that there is no simple way of valuing complex options. It is not as if there is a simple equation defined for each exotic contract, therefore modern mathematical finance has used “stochastic” processes. A stochastic process is a set of random variables over time. In our case we consider the different markets that we trade in random processes with certain characteristics. By defining these markets as random processes, we can randomly draw an infinite number of paths for each market which allows us to value these “path-dependent options” across all possible market outcomes. As a result, we have a set of valuations across all possible market paths and if we discount all of those valuations to today and average the discounted cash flows we come up with the expected value of this complex option. This simulation process is called a Monte Carlo method.

The above rhetoric might be too much to grasp, but the bottom line is that complex options are valued by looking at the payout over a large number of theoretical market outcomes and then taking the average of those payouts.

A naive monte carlo simulation showing possible stock price paths

I consider the above monte carlo simulation naive because it simply draws its returns from a normal distribution with mean 8% and standard deviation 20%. With a normal distribution I would never see a return as largely negative as 2008 at about -40%. Therefore there are many refinements that are done to the process to try to account for fat tails. Some have “regime switching” methods in which the model will flip from say an 8% return with 20% standard deviation world to a -10% return 30% standard deviation world. Other models will draw from actual historical observations to account for the actual tail returns.

Simple two regime switching equity model

It is not important to get into the details, but very important to point out some of the flaws. No model is perfect in producing returns that are real world equity returns. Likewise, it is even more difficult to produce random interest rate yield curves that are perfect Now let us take it one step further, how do you create random economic environments that are realistic?

This brings us to the real heart of what we are trying to achieve, and that is a measure of economic capital. How much capital does a firm need in the real world to cover losses under extreme economic environments? This question can only be answered by valuing both assets and liabilities through some sort of monte carlo simulation so that you know what the tail distribution looks for worst case asset/liability ratios. In order to do this, a firm must develop an economic scenario generator. Now we are getting complicated.

An economic scenario generator is just a complex multi-dimensional monte carlo simulation. I explained how important it was to have the correct assumptions and chosen model so that the simulation accounts for fat tails in equity returns, now we not only need fat tailed equity returns, but realistic assumptions for inflation, credit spread movement, interest rate curves and the correlations and interactions amongst all of these factors. Now you can see that the sort of difficult problem just became extremely difficult. This is an area of finance that is under heavy development but still in its infancy.

This complexity should segue into the bank failures during this last credit crisis. How could their models not have told them that the risks on their balance sheets were too much for the capital that they held? The answer is multi-faceted with reasons stemming from compensation plans to stockholder interests, but on the financial risk modeling side it was simple: they did not model it completely and if they thought they were modeling it well they either did not believe it or did a shoddy job of modeling. The underlying instruments such as the highly leveraged CDO’s were complicated enough to value by themselves, but when you put the whole mess together it was even more hopeless.

The positive spin is that 2008 has provided real world extreme market conditions that show just how terrible things can get. Previous to 2008, all financial companies relied upon rather muted historic data to “stress test” their balance sheets. In retrospect, we all know that using historic data did not show them the extreme stress test that these financial institutions would endure during 2008. Going forward, the banks will be sure to run their “2008 Scenario” first and foremost to test the strength of their balance sheets.