Category Archives: Finance

Low Volatility ETFs

The hip new financial product fangirled by every personal finance columnist on the internet is the low volatility ETF.  It is pretty much exactly what it sounds like – an ETF that, while tracking whichever index/industry/etc. it is supposed to, attempts to limit the variability of returns.  You can think of it as a stock with a low beta that moves with the trend of the market but not as severely in either direction during business cycle booms and busts.   Methodologies vary, but techniques are employed to limit the variance of individual holdings as well as the correlation between them.  I analyzed the performance of the PowerShares Low Volatility S&P 500 ETF (SPLV) to see how it stacks up against the market as a whole.

Over the past four years, the S&P500 had both a significantly higher maximum and lower minimum return compared to the PowerShares Low Volatility Index.  The S&P experienced many more extreme returns (+/- 1% daily return), suggesting that returns on SPLV fluctuate less than the market.  The S&P also earned a lower average return with higher variance than SPLV.

Period 5/6/11 to 1/6/15

S&P 500 SPLV
Max Daily Return 4.63% 3.75%
Min Daily Return -6.90% -5.18%
Returns less than -1% 98 62
Returns greater than 1% 110 71
Average Daily Return 0.04% 0.06%
Average Annual Return 0.99% 0.75%
Standard Deviation of Daily Return 10.98% 14.03%
Standard Deviation of Annual Return 15.71% 11.85%

The table below is the same analysis for only the year 2014, during which the US equity market posted more gains.

Year 2014

S&P 500 SPLV
Max Daily Return 2.37% 2.00%
Min Daily Return -2.31% -1.99%
Returns less than -1% 19 14
Returns greater than 1% 19 13
Average Daily Return 0.04% 0.06%
Average Annual Return 0.72% 0.60%
Standard Deviation of Daily Return 10.70% 15.80%
Standard Deviation of Annual Return 11.34% 9.55%

The claim that the PowerShares Low Volatility ETF (SPLV) tracks the S&P with less variability in returns  is corroborated by this simple analysis.  The graph of daily close prices and trading volume below also seems to corroborate this – the S&P500 Index (Yellow) fluctuates around the steady-ish path followed by SPLV (Blue).  The ETF misses out on some gains during the summer months, but outperforms later in the year.

Untitled picture2

Interestingly, the fund achieves its low volatility by being overweight in Healthcare and Financials, not the quintessentially low-risk sectors like Telecom or Utilities.

Sector_Breakdown

 


Mortgage Market Update from Calculated Risk

Calculated Risk is a blog that basically aggregates and analyzes up-to-date financial and economic data as it is released, particularly that which applies to the housing market.  The number of economic and financial metrics that are available on the internet is useful in some contexts but often feels more like a confusing, frustrating glut of information that renders answering a pithy question like “What is the rate of foreclosures like in the current housing market relative to pre-crisis times?” difficult to answer.  Trying to get beyond this issue is where I’ve found Calculated Risk really useful – relevant date for a particular issue is laid out, cited, and analyzed clearly in an effective and timely fashion.

I was curious about the housing market after meeting a seemingly overzealous realtor on the train, and here’s what I found via calculated risk.

Delinquencies 

At the end of Q3 2014, the delinquency rate on 1 to 4 unit residential properties was 5.85% of all loans outstanding, down for the 6th consecutive quarter and the lowest rate since the end of 2007.  The delinquency rate does not include loans in foreclosure, though they as well are at their lowest rate since the 4th quarter of ’07 at just under 2.5%.  Though foreclosures have come down from the stratospheric levels reached during their peak in 2010, they’re still more common than they were before the crisis.  Mortgages that are 30 and 60 days past due, on the other hand, have returned to approximately pre-crisis levels.  

Evernote Camera Roll 20141116 042456

Mortgage Rates 

30-year fixed rate mortgage (FRM) rates are down 1 basis point (.01) from last week at 4.01%, roughly the same level as 2011 but lower than last year’s 4.46%.  Obviously there isn’t “one” mortgage rate – the rate we’re talking about here is the one that applies to the most creditworthy borrowers in the best scenario possibly to receive a loan from the bank.  Though all other mortgages are based on this rate, it’s not exactly a rate one should expect to be offered by a bank.

Evernote Camera Roll 20141116 043840

The relatively small difference between a mortgage quoted at 4.01% and 4.45% has a surprisingly large financial impact on the 30 year FRM.  A $250,000, 30-yr. FRM at a 4.01% nominal annual rate compounded monthly (as is typically the case) necessitates a monthly payment of $1,194.98, whereas the same mortgage at 4.45% would require a monthly payment of $1,259.30.  With the higher payment, the borrower pays an additional $23,155 in interest over the term of the mortgage.

Another post talks about subdued refinancing activity, which I’d guess is the result of relatively static mortgage rates as it’s generally only financially viable to refinance when rates have changed significantly.  Banks could also be offering fewer refinancing options after the crisis, a reasonable assumption given their cautious resumption of lending post-crisis and the role that refinancing options played in exacerbating the housing bubble.  I’m purely speculating, though, and I’ll look into this more later.

Residential Prices

A widespread slowdown in the rate of housing price increases has been steadily taking hold since February of this year.  Residential prices aren’t decreasing, they’re just rising at a slower and slower rate each month, and now sit 20% below their 2006 peak.  This is not to say we should expect or even wish that housing prices should resume at 2006 levels, as such was clearly unsustainable – furthermore, though slow relative to preceding months, the (annualized) 6%+ experienced last month is still pretty strong and obviously outpaces inflation.

 

Evernote Camera Roll 20141116 050031


Level Payment vs. Sinking Fund Loans

Below is a document explaining how to derive formulas for the most basic level payment and sinking fund loans. This is a simple introduction, as I’m currently working on a more detailed analysis of the benefits/drawbacks to various types of loans (including installment, variable rate, etc.) using empirical data and considering various scenarios, like the option to refinance and varying interest rates.  I used the results from my post on annuity formulas to simplify the derivation, so if you’re confused about how I got from one step to the next, check there!

Level Payment and Sinking Fund Loans


Analysis of the U.S. Output Gap by EconBrowser

I mentioned in my previous post that low inflation means substantial output gaps persist in many advanced economies.  Econbrowser’s post analyzing of the U.S. output gap is worth a read; the downside risks borne from the composition of recent economic growth and unjustified inflation concerns are also addressed.


Recent Developments in the World Economy

The first part of the WEO, which gives a broad overview of what’s happened since the previous WEO released in April, is (very) briefly summarized in layman’s terms below.  A technical note: any mention of rates of growth (positive and negative) refers to the annualized rate of growth of output, or GDP, in an economy (GDP isn’t the only measure of output that exists but it is what’s used here).  You can think of output, or GDP, as a measure of aggregate economic activity.  We care about growth in GDP because it leads to more employment (to meet the needs of the expansion of economic activity), and, generally speaking, a higher standard of living.  You can read a more thorough discussion of GDP growth here.

Global growth in the first half of 2014 was lower than the April WEOs projection by 0.4%.  That was the general trend, but the story varies by country:

Losers

  • Brazil – Negative growth so far this year (two consecutive quarters, which technically qualifies as a recession) due primarily to a lack of investment and confidence
  • France – No growth in output, reflecting fiscal imbalances and declining competitiveness
  • Italy – Contraction of output, albeit small, for Q1 and Q2, high unemployment (youth unemployment is at its historical peak) issues stemming from tight financial conditions (basically no credit available and thus no investment either)
  • Russia – Lack of growth is, not surprisingly, a result of insufficient investment and confidence

Winners

  • China – Relatively strong growth in Q1 despite issues in credit and housing markets that Chinese officials successfully subdued (via lowering required reserves and credit easing aimed at small and mid-size firms) for higher growth in the subsequent quarter
  • India – Stronger growth is resuming after a protracted downturn thanks primarily to much-needed investment
  • United Kingdom – Relatively strong growth (‘strong’ in comparison to what was expected in recent years, but considerably less than growth in China in India in raw number), and a strengthening labor market due to increased business investment

Investment is, unsurprisingly, prevalent in healthy economies and positively related to confidence.  If you’re surprised investors are wary of putting money into Russian markets then you must have been under a rock while Russia invaded Ukraine, and if you’re surprised about Brazil, maybe you didn’t know that it’s run by a feckless imbecile who just (barely) survived reelection.  Just as lack of investment and confidence hampers growth, India proves that  investor-friendly reforms spur investment, and the U.K. has recovered almost completely from the crisis thanks to business investment.

Those were the extremes – the rest of the world falls somewhere in the middle.  The United States economy is strengthening, but expected growth has necessarily been revised downward to adjust for the surprising contraction in the first quarter, largely a reflection of temporary factors (harsh weather, inventory accumulation in Q4 ’13, decline in exports), that won’t affect the future much.  In Japan growth continues along weak yet stable path, as the country’s enormous level of public debt inhibits its ability to grow too much despite good signs elsewhere in the economy.  Output nearly stalled in the Euro area as (mostly periphery) countries struggle to emerge from the recession, while some are achieving modest growth (Spain and Germany mainly).

Inflation is below targets in advanced economies which means they’re operating below their potential; meanwhile, inflation in emerging markets hasn’t changed.  Monetary policy is easy/accomodative in advanced economies and will continue to be as the ECB is slated to implement new policies, including targeted credit easing, and the Fed has made clear that it will aim to keep rates low for some time despite having wrapped up its asset purchase program last month.  In response to the Fed’s plans, financial conditions have eased and long term interest rates have decreased a bit, compared to data in the April WEO.  Risk premiums are low and volatility is low in advanced economies, which has some worried that risk is underpriced – but more on risk and its implications in a separate post.

So the global rate of growth or inflation or any other metric doesn’t convey much useful information because conditions are anything but  uniform across countries.  The story of the recovery is and will remain fragmented, with different problems and strengths contributing to a given market’s recovery.  That being said, all economies can expect to adjust to a level of growth that pales in comparison to the growth of the early 2000s.  Potential output, which has been revised downwards for the past 3 years, is too low for the growth rates of old to materialize.  This is due to the legacy of the recession in advanced economies, but growth-limiting structural issues also plays a role in developing economies.  For more on that, directly from the IMF, watch the short video linked below.

http://bcove.me/tcz9ghm8


Deriving the Present Value and Future Value of an Annuity Immediate

Below is the derivation of the present and future value of a unit annuity immediate, or a series of $1 cash flows that occur at equal intervals of time at the end of each period.  I originally wrote this document as a review for myself in preparation for actuary exam FM/2.  The majority of questions on the exam, despite the wide array of topics covered, come down to solving for the value of some annuity.  Granted, it likely won’t be a case as simple as the one below, but many problems about loans, bonds, yield rates, and even financial derivatives biol down to an annuity problem.

Annuity_Derivation


Takeaways from the BLS jobs report

Ben Casselman at FiveThirtyEight provides a detailed breakdown of the BLS jobs report.  248,000 jobs were added in September, and figures for July and August were revised upward by almost 70,000.  These data are the talking points you’ll hear on the news, but they’re deficient measures of labor market health on their own.  Casselman delves into the BLS report to corroborate his stance that the report was, in fact, good news – something raw numbers of jobs added can’t do.  (Side note, why is the font on BLS reports so awful?  The color sucks too – it’s like a “my printer is almost out of ink” light grey.)  Anyway, the good:

1) The number of people who gave up on looking for work because they didn’t think any was available is down considerably – less than 700,000 in September, compared to over a million back in 2010.

2) Layoffs are at a 10 year low.

3) The (slight) majority of the unemployed either voluntarily quit their job or (re)started the job search

(1) and (3) show some confidence in the labor market. Fewer people think that a desirable job is totally unattainable given current labor market conditions, and more people are willing to voluntarily quit their jobs because they think better opportunities are out there.  These are good signs.  There are bad signs, too:

1) Many of the jobs added were in Retail, which tends to be low-paying.  More desirable sectors added relatively few jobs

2) There is still no wage growth

3) Lots of people are working part time only because they can’t find full-time employment

(1) is maybe expected, and stems from an issue that has been brewing in the U.S. economy for a while – structural unemployment.  The U.S. economy needs more people with the right skills in the right geographical areas before it can add a decent number of jobs in higher-paying sectors. (Many economists have echoed this train of thought, suggesting that structural unemployment is the driving force behind persistently high unemployment post-recession. One way to investigate this is to analyze the Beveridge Curve.)

(3) shows us that while employment has accelerated, many of those working are underemployed. (Part time workers generally don’t receive benefits – recent legislation, which you can read about here, is starting to change this, however.)  As the linked article explains, part of the increase in part-time employment could reflect better incentives for part-time work, not underemployment.  Nevertheless, while incentives could have driven the work decision of a portion of part-time workers, many indicated that the only reason they are working part-time is because full-time employment is unavailable – corroborating the underemployment suggestion.

(2) is an issue I wrote about in a previous post, and, I’d argue, the most important of the three.  There will not be sustainable growth until wages grow, and the <2% of the past year simply won’t cut it.  Furthermore, the lack of wage growth implies that there’s still plenty of slack in the labor market.

As a technical aside, below is what I mean by real wage growth, i.e. the wage growth that needs to occur before consumption can rebound and support a robust economy.  When we say real anything in economics, we mean inflation adjusted.  The real rate of wage growth is thus the inflation adjusted rate of growth of wages.  The raw, or nominal, rate of wage growth simply tells us by how much wages increased, ignoring the price level.  This is not all that useful, because wages affect consumption via the purchasing power of consumers – and if we don’t know what the inflation situation is like, we don’t know if consumers’ purchasing power increased, stayed the same, or decreased.

You could easily look up real wage growth (i.e. inflation adjusted wage growth), but for the sake of completeness here is how you can calculate the real growth in wages given the nominal rate of wage growth and a measure of inflation:

Screen Shot 2014-10-08 at 1.29.47 AM

For the nominal rate of wage growth, you could use the % change of Average Hourly Earnings (reported by the fed), and for inflation you could use the CPI % change over the same period.  These aren’t, however, the only metrics that will work – there are plenty of ways to quantify wages and inflation, each suited to a slightly different scenario.


A Post on Measuring Historical Volatility

I’ve reblogged a concise yet thorough explanation of the calculation of market volatility. The post makes very clear how input parameters (weighting, time frame, etc.) affect its validity as an estimate of future market movements (link).  The phrase “Fat Tails” is often thrown around like a meaningless buzzword in financial media (Squawk Box, for example), but the concept is explained intuitively here. In a separate post, market data from the S&P500 is used to demonstrate the decay factor’s effect on log returns (link).

 

mathbabe

Say we are trying to estimate risk on a stock or a portfolio of stocks. For the purpose of this discussion, let’s say we’d like to know how far up or down we might expect to see a price move in one day.

First we need to decide how to measure the upness or downness of the prices as they vary from day to day. In other words we need to define a return. For most people this would naturally be defined as a percentage return, which is given by the formula:

$latex (p_t – p_{t-1})/p_{t-1},$

where $latex p_t$ refers to the price on day $latex t$. However, there are good reasons to define a return slightly differently, namely as a log return:

$latex mbox{log}(p_t/p_{t-1})$

If you know your power series expansions, you will quickly realize there is not much difference between these two definitions for small returns- it’s only…

View original post 807 more words


Is the Stock Market a Viable Barometer of Economic Health?

The S&P’s record close of 1992.37 on Thursday begs the following question: what, if anything, does a soaring stock market index, up almost 8% just this year, say about the health of the real economy?  As I’ve mentioned previously, there are quite a few issues in the current U.S. economy that may have to be rectified before the real economy can sustain robust growth – a weak labor force and stagnant wage growth, for example.  If we are to interpret the appreciation in the price of a stock market index as a sign of economic health, as many pundits on TV seem to do, then Thursday’s record close seems to contradict what the assertion that wage growth and a robust labor force are vital to the U.S. economy’s health.  This subject is briefly addressed on page 101 of  Freefall by economist Joseph Stiglitz, an account of the financial crisis, its causes, and aftermath.  He says:

“Unfortunately, an increase in stock market prices may not necessarily indicate that all is well.  Stock market prices may rise because the Fed is flooding the world with liquidity, and interest rates are low, so stocks look much better than bonds.  The flood of liquidity coming from the Fed will find some outlet, hopefully leading to more lending to businesses, but it could also result in a mini-asset price or stock market bubble.  Or rising stock market prices may reflect the success of firms in cutting costs – firing workers and lowering wages.  If so, it’s a harbinger of problems for the overall economy.  If workers’ incomes remain weak, so will consumption, which accounts for 70 percent of GDP.” 

I quoted the preceding passage because it cogently argues that stock market gains are not necessarily emblematic of health in the economy, as the media – particularly on business-oriented news shows – often suggest.  The two scenarios Stiglitz mentions (expansionary monetary policy and firms cutting costs) result in higher stock prices but not a healthier economy.  It is erroneous to conclude that the price of the S&P 500 is a sufficient and reliable barometer of economic health.


Econ Week in Review: 6/9 – 6/15

Emerging markets have lost momentum throughout the past year, as investors adjust to the changing macroeconomic climate. According to news outlets (MarketWatchBloombergLibertyStreet) global risk aversion is to blame.  Though emerging economies are still poised for more GDP growth than their developed counterparts in 2014 – 2.2% versus 4.9% – they aren’t expected to increase that growth rate by much in ’15 and beyond.

Growth prospects that are relatively weak in comparison to previous estimates (though still strong in comparison to other economies) is one reason why investors are pulling out of emerging market economies, as evidenced by capital outflows in those markets (IMF).  Another is the outlook for developed economies, particularly the United States, which looks much better than it did a year ago.  Now that investors expect the U.S. economy to recover and interest rates move away from the zero lower bound, they expect new financial opportunities to emerge in developed economies as well.  Now that investors think they’ll be able to make a decent return in an advanced economy, there’s less of an incentive to take on the risk associated with emerging markets.  There is evidence of this if you look at capital outflows immediately following Ben Bernanke’s speech in May 2013; it seems that the cautiously positive economic outlook Bernanke conveyed in his speech led to a sell off in emerging markets that has continued for the past year.  Some economists have justified this phenomenon using the VIX as an indicator of risk aversion

Capital outflows put emerging market economies in a tight credit position, constraining their growth potential.  Previously they had enjoyed abundant credit because investors in advanced economies had to go abroad for financial returns.  Furthermore, it has been shown that Quantitative Easing and related policies in the U.S. put downward pressure on interest rates in emerging markets, facilitating even easier borrowing.  This shouldn’t come as a surprise since financial markets are becoming increasingly integrated, but it could pose some problems by limiting the effectiveness of domestic monetary policy (full discussion on if/how us policy affects global market here).  Integrated financial markets are generally a good thing, though , and the fragmentation that currently plagues most of Europe is a pertinent example of that.

I’m going to write a follow-up on QE and the role of expectations in the next week or so (after I finish reading the IMFs global economic outlook), and hopefully delve deeper into the current situation in emerging market economies.


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