The Democratic Split

Democrats are optimistic that the Russian and corruptions scandals will propel the party to victory in 2018.  Perhaps they are correct but I fear that they are wrong for two reasons.

First, President Trump continues to give weekly rallies to his enthusiastic base.  There are no figures on the Democratic giving large robust rallies.

Second, aside from Russia and corruption (admittedly two big asides) the entire debate today centers around Trump priorities – basically immigration, trade and low taxes.

The Democrats do much better when the conversation involves health care, student debt, pensions and Social Security.   The common theme linking these issues is that despite the currently strong economy many Americans are financially insecure and are having trouble saving for the future or for education.

Why aren’t Democrats out there rallying their base the way Trump is?

Why aren’t Democrats talking more about financial security — health care, student debt and retirement – issues of concern to working-class households?

The basic answer is that there is a huge split in the Democratic party both on economic priorities and appropriate policies.  This split is paralyzing the party and impeding the delivery of a viable progressive agenda.

 The liberal wing of the Democratic Party offers transformative radical change.  The centrists believe that the liberal wing’s policy proposals are unrealistic and could make many people worse off.

The centrists offer relatively modest policy changes and appear to only reluctantly embrace left-wing proposals when they need votes.   The current message offered by the centrists will not rouse the base.

The liberals correctly believe the current centrist agenda would at best maintain the status quo and at worse could implement compromises with Republicans that will weaken the existing safety net.

This conflict can be illustrated by a discussion of three issues – health care, student debt and retirement savings.   These issues allow for the Democrats to create a theme for 2020.   The theme is how do we make Americans more financial secure and what party do you trust to do this?

This is a good place for me to state my bias.   I am a centrist not a liberal.  However, many of the current policy proposals offered by centrists are insufficient.

Here is an outline of some policy ideas, which could bridge the gap between centrists and liberals.

Policy Priorities

Discussion of Health Care:

It is hard to understand why Democrats aren’t spending more time talking about health care.   The number of uninsured Americans without health insurance rose by 3.2 million people during President Trump’s first year in office.   This issue and other problems with health insurance markets received more coverage in CNBC than by MSNBC.

The liberals want single payer health care.   The fact that single-pay works well in some countries, which have only known single payer, does not mean that the United States could transition from the current system to a single payer system.

The adoption of a single-payer system would make some people more financially secure but would make many people worse off than the current situation.   Many health care providers and doctors would have substantially lower compensations.   This would be a disaster for new doctors with substantial medical school debt.  The single-payer would be more generous than some private plans but might deny or provide insufficient reimbursement for expensive procedures.

Many centrists have endorsed and voted for a Medicare for all plan, even though their more detailed thoughts are more in line with ACA modification proposals.   They argue their vote is a symbolic one in support of universal coverage.   I would argue this vote is a pander.

The centrists want to repair the ACA but their discussions do not fully acknowledge that problems with the ACA existed even before the Trump Administration weakened the program. The ACA was a big step forward but also a disappointment compared to where we want to be.

Despite the enactment of the ACA, insurance premiums and out-of-pocket expenses have continued to rise.  There is some evidence that state exchange insurance has narrower networks and entail higher costs than some employer-based insurance.  Moreover, people who take ACA coverage are required to take employer-based insurance if they obtain a job with an employer that offers coverage.  Rules and tax incentives favoring employer-based insurance over state exchange insurance weaken state market places.

There is no doubt that Trump Administration polices – ending the individual mandate, reducing funds for ACA enrollment, potential new rules allowing alternatives to ACA policies and a freeze on ACA reinsurance payments – have weakened state exchanges and are responsible for the increase in the number of uninsured.

However, centrists need to do more than offer a patch to the ACA.   They need to offer a vision on how we can move to a system that provides more coverage, lower out-of-pocket expenses, and access to all procedures and drugs.

Authors Note: I am currently working on a health care proposal.   It will be published by the end of 2018.

Discussion of student debt:  It is hard to believe that the Democrats aren’t talking a lot more about student debt, especially given recent Trump Administration proposals.   Recent actions or positions taken by the Trump Administration on student debt include:

  1. The proposed elimination of the public service loan program,
  2. The proposed elimination of subsidized student loans,
  3. The end of compensation for student borrowers who are victims of fraud,
  4. The reduced enforcement of rules allowing enrollment in Income Based Replacement loan programs

Why aren’t Democrats talking more about these student debt issues?

The liberal wing wants free college for people attending public universities.   This does work in some countries.  However, free public college is very expensive and the transition would adversely impact private institutions.

The centrists need to come up with innovative pragmatic solutions to the college debt problem and incorporate these proposals in their standard speech.

I have published a working paper, which lists 12 pragmatic ways to reduce the growth of student borrowers with excessive student debt and mitigate debt burdens for overextended borrowers.

One of my proposals involves providing additional financial assistance and reduce student loans to first-year students who do not have an extensive credit history or proven academic record.

A second proposal reduces interest payments after 15 years.   This approach is likely to be more effective than current loan forgiveness programs, which are designed to discharge debt.

My student debt proposals are available in my working paper on Amazon.

https://www.amazon.com/Innovative-Solutions-College-Debt-Problem/dp/1982999446

Discussion of retirement security issues:   Retirement security entails Medicare, Social Security and 401(k) plans.

The discussion on this issue should start with a recognition that under current law there will be automatic cuts to Social Security and Medicare benefits unless Congress acts.   Democrats need to ask whether Republicans can be trusted to act given their performance on ACA repeal or replace.

In the 1980s, President Reagan and Democrats in Congress came together to fix Social Security.   The Democrats need to ask whether the current Republican party can be trusted to compromise on this issue.

The other aspect of the retirement security problem is that many workers have insufficient retirement savings. Today few companies provide workers with traditional pension plans.   Many 401(k) plans have high fees and most lack an annuity option during retirement.   Many workers are unable or unwilling to maximize their contribution to 401(k) plans and often the money in these plans is disbursed prior to retirement.

The Democrats then need to provide detailed proposals on how to improve retirement security.   These proposals should recognize two important goals – (1) Social Security needs to be placed on a sound finance system and (2) the entire retirement savings system needs to be improved.

The Democrats need to advance policies that achieve both these goals and must reiterate opposition to Social Security benefit cuts that worsen retirement security.   The proposed solution is likely to include either additional revenue or use of some general tax revenue to maintain current Social Security income.

The Best Dialogue for Democrats

The current political dialogue is being set almost entirely by Trump and the Republicans.   Their focus is on trade and tariffs, immigration, and standing for the national anthem.

My thesis in this essay is that Democrats need to put financial security — health care, student debt, and retirement income at the center of the national discussion.

Centrists must move forward with a pragmatic progressive approach to these issues.  Many key centrists are spending more of their time either pandering to liberals or bashing liberals for being too radical than proposing polices that solve problems.

Some Democrats, both progressives and centrists, are more focused on tax issues and/or inequality.  The centrists are concerned that proposals by liberals will explode the deficit.  They should be more focused on revenue losses from the recently enacted Trump tax cut.

Elizabeth Warren recently pointed out the America was more prosperous when marginal tax rates were over 50 percent.  This defense of high tax rates is a losing argument both substantively and politically.  The decrease in prosperity or the increase in inequality was more likely caused by loss of jobs from factories moving overseas and from technological changes which reduced wages of low-skilled workers.

Tax policy is complicated.   A case can be made for changes in the tax code to obtain more revenue.   However, economists have found that high marginal tax rates change distort behavior.   Most notably, high marginal tax rates can decrease work, especially in two-worker households.

An economic agenda stressing reforms that will improve household financial security will resonate more with voters than an agenda focused on taxes and income inequality.

We live in a world where every one of Trump’s utterances and farts dominates the news cycle. Democrats seem totally incapable of prioritizing the farts.   In my view, Trump’s treasonous approach to Russia and separation of children from parents at the border are more important than Stormy Daniels

Democrats must respond to the moral dilemma created by the Trump Presidency.   However, at the end of the day a person struggling with student debt, worried about health care coverage for her family, and worried about whether she will be able to retire with decent income is more concerned about financial security than the scandal of the day.

Democrats need to get out there and reset the nation’s agenda.  To modify Bill Clinton said it was the economy stupid.   My view is that the economy must be broadly defined to include financial security.

Holdings of Ten Emerging Market Funds

Holdings of Ten Emerging Market Funds

This post started with a list of emerging market funds found at the site below.

http://etfdb.com/etfdb-category/emerging-markets-equities/

I examine and describe the holding and recent returns on the 10 largest of these funds.

I comment on the holdings of these funds, the risk of these funds and the risk of some of the holdings.

List of Funds, Discussion of Geographic Diversifications, and YTD returns:

Some Information on Ten Emerging Market Funds
Symbol Fund Geographic Concentration YTD Returns
VWO Vangarud FTSE Emerging Market 7 of top ten holdings are in China -7.32%
IEMG I Shares Core MSCI Emerging Market 7 of top ten holdings are in China -6.95%
EEM I Shares MSCI Fund 7 of top ten holdings are in China -7.44%
SCHE Schwab Emerging Markets Fund 6 of top ten holdings are in China -7.34%
FNDE Schwab Fundamental Large  Firm Emerging Market Index Largest holding is from Korea and second and third largest holding are Russian.  Top 10 holdings also include companies from China, Brazil and Taiwan -6.71%
DEM Wisdom Tree Emerging Markets Equity Income Fund Top two holdings are Russian.   Most other top ten holdings are form China or Taiwan. -4.54%
RSX Van  Eck Vectors Russia ETF All holdings appear to be in Russia. 4.36%
GEM Goldman Sachs ActiveBeta Emerging Markets Equity ETF 7 of top ten holdings are in China -6.75%
SPEM SPDR Portfolio Emerging Markets ETF 6 of top 10 holdings are in China -6.54%
DGS Wisdom Tree Emerging Markets Small Cap ETF Top 10 holdings are less than 9 percent of all holdings.   Highly diversified, smaller companies. -7.34%

 

Some Observations:

Many of the funds have a very large share of their funds in China.   In fact, some of the emerging market funds could accurately be called China plays.

Three of the funds have substantial issues in Russia.  Also, most but not all, of the Russian holdings are in the oil and gas sector.  Important to research holding If concerns about corruptions and sanctions would deter you from investing in Russia.   Energy funds that are not in Russia may be preferable to Russian energy plays.

Nine of the Ten funds have negative YTD returns.  The fund that exclusively invests in Russia has a +4.36% return. This fund performed really poorly in prior years.  The YTD return on U.S. large cap stocks is around 6.0%, largely because the market has been up for the past week or so.

Can investments in emerging market ETFs provide insurance against a major downturn in the U.S. market?

 Short answer is probably not:   The downturn in emerging markets in the 2007 to 2009 crisis was larger than the downturn in large-cap U.S. stocks.

Go here for discussion of emerging market funds during the financial crisis

http://financememos.com/2018/07/23/emerging-markets-during-the-financial-crisis/

Thoughts on specific holding of emerging market funds:

Emerging market funds have some well know reputable holding and some firms with dubious reputations, and some firms with little name recognition.

The most successful holdings of the funds in this sector include: (1) Alibaba, (2) Tencent and (3) Baidu Inc.

Investors who want a taste of advanced emerging markets or China may be better off directly investing a small fraction of their wealth in these companies.

Emerging Markets During the Financial Crisis

Emerging Markets During the Financial Crisis

True or False:   During the 2007 financial crisis emerging market funds outperformed U.S. large Cap funds?

Answer:  False:

Evidence:   The chart below compares peak price in 2007 prior to stock market collapse and trough price in 2009 prior to the recovery.   The peak price for VLACX was on October 1, 2007.   The peak price of VWO, the largest emerging market fund, occurred a bit later, on October 22, 2007.   The trough price for both funds was realized on March 2, 2009.

U.S. Large Cap versus Emerging Market During the Financial Crisis
Funds Peak Before Crash in October 2007 Trough at End of Crash in March 2009 % Decline
VLACX U.S. Large Cap 28.1 12.6 55.3%
VWO Emerging Markets 57.5 19.0 67.0%

The collapse in the Vanguard emerging market fund was larger than the collapse in the Vanguard large-cap U.S. equity market.

Perhaps some other emerging market fund did better but I doubt it.

Asset Allocation for Twelve Sector Funds

Asset Allocation for Twelve Sector Funds

Issue:  Under an asset allocation investment strategy, an initial allocation is assigned to all assets in a portfolio and the portfolio is rebalanced from time to time to maintain the original composition of assets.   The rebalancing can be at scheduled dates or whenever the portfolio manager observes large changes in relative asset prices.

The original allocation of assets is maintained by selling assets that do well and buying assets that do poorly.   This approach can backfire.   A hedge fund manager who bought horse and buggy stocks and sold car stocks after the introduction of the car would not have done well.  However, asset allocators who sold internet firms prior to the tech bubble in the late 1990s did quite well.

Question:   Table one below has stock price information on 12 sector ETFs offered by Vanguard for three dates – 7/1/13, 7/1/16, and 6/29/18.

Using this price data, calculate the average annual return between 7/1/13 and 7/116 and the average annual return from 7/1/16 to 6/29/18 for the 12 funds.

What do these annualized return statistics suggest about the likelihood of success of an asset allocation strategy, which starts out with equal shares of the 12 ETFs on 7/1/2013 and rebalances on 7/1/2016.

Adjusted Close Stock Price for 12 Sector Funds
Symbol Fund Description 7/1/13 7/1/16 6/29/18
VDC Consumer Stables 93.55 133.53 134.27
VDE Energy 103.12 88.25 105.08
VFH Financials 38.12 47.48 67.45
VHT Health Care 86.84 133.78 159.14
VIS Industrials 79.06 106.53 135.81
VGT Information Tech 73.07 112.61 181.42
VAW Materials 82.52 104.33 131.56
VNQ Real Estate 56.70 84.58 81.46
VOX Communications Services 68.28 94.02 84.92
VPU Utilities 72.52 106.33 115.96
GLD Gold 127.96 128.98 118.65
SLV Silver 19.14 19.35 15.15

A note on calculations:   The return between two dates is obtained from the formula (APt/ APt-n(1/n)-1

The first period is three years and the second period is two years.   (n is 3 for first period and 2 for second period.)

The table below sorts the funds from least to highest annualized return during the first period.

Annualized Rate of Return for 12 Funds
Symbol Fund Description July 2013 to July 2016 July 2016 to July 2018 Diff.
VDE Energy -5.1% 9.1% 14.2%
GLD Gold 0.3% -4.1% -4.4%
SLV Silver 0.4% -11.5% -11.9%
VFH Financials 7.6% 19.2% 11.6%
VAW Materials 8.1% 12.3% 4.2%
VIS Industrials 10.5% 12.9% 2.5%
VOX Communications Services 11.3% -5.0% -16.2%
VDC Consumer Stables 12.6% 0.3% -12.3%
VPU Utilities 13.6% 4.4% -9.2%
VNQ Real Estate 14.3% -1.9% -16.1%
VHT Health Care 15.5% 9.1% -6.4%
VGT Information Tech 15.5% 26.9% 11.4%

Observations:

Information Technology, the best performing fund in the first period, was also the best performing fund in the second period.  This asset allocation strategy would have reduced holdings of an asset, which continued to out-perform all other assets in the portfolio.

Energy, the worst performing fund, in the first period, had a return 3 percentage points over average of the 12 ETF returns in the second period.

Four of the six worst-performing sectors in the first period realized improved returns in the second period.

Five of the six best-performing funds in the first period had worse returns in the second period.  (The only exception is the previously mentioned information technology fund.)

The median annualized return in first period was 10,9 percent.   Only four funds had annualized returns over this level in the second period.

Two sectors – financials and information tech – are positive outliers in the second period.  However, financials have underperformed in last few months.

Concluding Remarks:   Information Tech, the best performer in both time periods, did spectacularly in the second period.  Asset allocators sold the best fund.

Asset allocation strategies tend to work more consistently when the investor holds broader funds, including both the overall stock market and debt funds.  Subsequent research will look at situations where asset allocation provides better results.

Authors Note:  Interested in financial problems caused by student debt.   Take this quiz on student debt trends and proposed policy changes.

http://financememos.blogspot.com/2018/07/a-student-debt-quiz.html

Review of Measuring Portfolio Valuation

My blogging ground to a halt the last few weeks because I was completing a paper “Measuring Portfolio Valuation. “  Will put link to paper here shortly.

My new paper looks at two issues.   The first issue involves correct and incorrect ways to measure the PE ratio of a portfolio of stocks.   The second issue involves the correct way to conduct statistical tests on valuation measures for groups of stocks.

The paper starts with a discussion of the limitations of the PE ratio, the most commonly used valuation measure for common stocks.   The PE ratio is undefined when earnings are negative and unstable when earnings are small. By contrast, the ratio of the difference between market cap and earnings to market cap (denoted (MC-E)/MC) has a clear economic meaning when earnings are negative and is not an outlier when earnings are low.  In addition, there is a one-to-one relationship between this ratio and the PE ratio.

Many investment firms use a weighted average of firm PE ratios to measure the PE ratio of their ETFs or mutual funds.   The firms often discard observations from firms with negative earnings and cap the PE ratio of firms with high PE ratios.   These methods are arbitrary and often tend to understate the valuation of stock prices relative to earnings.

The ratio of the sum of market caps of firms in a portfolio to the sum of earnings of firms in the portfolio is the correct way to measure the PE of a portfolio.   This measure of PE can include all firms even firms with negative earnings.  Moreover, small changes in earnings for firm with high PE ratio do not have a large impact on the overall portfolio PE ratio.

A second way to measure the PE ratio of a portfolio, which relies on the weighted average of the statistic ((MC-E)/MC) is presented and shown to be equivalent to the ratio of the sum of market cap to sum of earnings.   This result is motivated in the following blog post.

Two Ways to Calculate a Portfolio PE Ratio:

https://financememos.com/2017/10/11/two-ways-to-calculate-a-portfolio-pe-ratio/

The paper contains a formal proof demonstrating the two methods of constructing a portfolio PE are identical.

Often analysts conduct hypothesis tests on portfolio financial ratios.   Tests based on PE ratios often provide misleading results because of problems measuring the PE ratio when earnings are negative or small.   Firms with negative earnings are routinely omitted from the sample.  The standard deviation and skew of portfolio PE ratios are often large making it difficult to reject a null hypothesis.

By contrast, statistical tests based on (MC-E)/MC do not require the omission of firms with negative earnings.  Moreover, the distribution of (MC-E)/MC appears normally distributed with few outliers.    As a result, statistical tests using this ratio are more reliable than statistical tests using PE ratios.

Discussing Buy Versus Rent Calculators

  Discussing Buy Versus Rent Calculators

Realtor groups have created a number of on-line calculators that attempt to provide an objective view of the advantages of buying a home versus renting a home.  The link to one such calculator is presented below.

http://www.realtor.com/mortgage/tools/rent-or-buy-calculator/

First, I describe the calculator.   Then I critique it.

Description of Calculator:

The simple version of the buy/rent calculator at www.realtor.com allows one to put in an address and get financial estimates for renting or buying.  The more advanced and interesting version allows a consumer to select assumptions on costs of buying and cost of renting.

The key assumptions on the cost of buying involve home price, down payment mortgage term, buying costs, selling costs, house appreciation, real estate taxes and miscellaneous homeowner fees.

The most important renting costs include the initial rent and the yearly appreciation in rent.

Other key assumptions include the exemption of  $500,000 on capital gains in housing, an investment return, and an inflation rate.

Based on the inputted assumptions the model provides an estimate of the amount of time that it takes for buying a home to be cheaper than renting a home.

The model at www.realtor.com assumes that buying costs are 4.0 percent of the purchase price and selling closing costs are 6.0 percent of the final sales price.   Due to transaction costs associated with home purchases, renting will be less expensive than buying for people who stay in a house for a short period of time.   The output of the model is the number of years it takes for buying to be less

Comments on the calculator at www.realtor.com

 

Comment One:  Often realtors and bankers persuade young homebuyers to use available cash for a down payment rather than immediately retire consumer or student debt.  The model does not have an option to explicitly consider the impact of credit card debt or student debt on the buy versus rent outcome.   The model does require input on the assumption of investment returns.   One way to model the impact of keeping debt is to increase the investment return assumption so that it equals cost of credit cards and student loans.   It would be useful if the model allowed for separate assumptions on investment return and the cost of existing debt.

Comment Two:   I modified one example to consider the breakeven point of a transaction with a 15-year FRM at current interest rates.   I found that buying was preferable to renting after a 6-year period for the 15-year FRM compared to 8 years for the 30-year FRM.   Essay Four provides more information on mortgage choice and lifetime savings.

Comment Three:   The model cannot be easily modified to allow for interest rate uncertainty associated with adjustable rate mortgages.

Comment Four: The model requires an assumption of average annual growth in house appreciation over the entire period and does not consider issues related to the uncertainty of future house appreciation.  House prices do not appreciate in a steady or reliable fashion.   The realtor’s model would have severely overestimated the value of buying a home during the 2004 to 2009 time period and would have underestimate returns from purchasing in 2011 or 2012.  The argument that housing prices would continue to rise was made quite strenuously in 2007 and was used to motivate unrealistic price appreciation assumptions in the breakeven analysis.

The house price appreciation assumption is usually based on what the analyst expects will occur.   An alternative approach would involve basing this parameter on the certainty equivalent.   A certainty equivalent is the guaranteed return that someone would accept rather than take a risk on a higher but uncertain return.

Comment Five. Many people are forced to move because of a new job or divorce.   The rent versus buy calculator does not allow for economic costs associate with moving when house prices fall and house equity turns negative.   Nor does the buy versus rent calculator consider economic costs associated with negative equity that make it difficult for a home buyer to refinance should interest rates fall.

 

The more relevant question not answerable from this calculator is it better for a person to buy now or reduce debt and buy in a couple of years.

Comment Six:  Often realtors will expect home sellers to put additional investments into the property prior to selling the home.  (Most recently in many neighborhoods realtors are pushing home sellers to install granite kitchen tops.)   The model does not include an option to consider likely upgrade costs.  It may be able to correct for this problem by reducing the price appreciation assumption in the model.  However, the need for upgrades appears to differ widely across properties.

Comment Seven:: The buy-sell calculator can also be used to evaluate mortgage properties financed with FHA loans.   The FHA loan program is geared for relatively small mortgages.  The program has a loan limit that varies across counties and can change over time.   The FHA loan program allows for down payments as low as 3.5% FHA loan costs include mandatory mortgage insurance premiums, part of which is paid up front.  Due to the insurance premiums the cost of the FHA loan is often one percent point higher than the cost of conventional loans.  Most often, the number of years it takes for a home buyer to break even on an FHA loan program will be substantially higher than the number of years it takes to break even on a transaction financed with a conventional loan.   Not surprisingly, the use of real estate break- even calculators is usually illustrated with conventional loan examples rather than FHA loan examples.

Comment Eight: The assumption regarding the rate of appreciation of rents has a major impact on the buy versus rent decision.    A larger percent of people are choosing to rent rather than buy consequently more rents are continuing to rise often at a rate that exceeds the increase in the value of the home.   In some markets it may be legitimate to assume a higher increase in rents than home prices.  This alternative assumption might persuade more people to buy rather than rent.

Comment Nine:  Realtors often argue that a house purchase should occur now rather than later because macroeconomic conditions are about to change.   Over the last three or four years realtors have argued that people should buy because the FED is about to raise interest rates.  An increase in interest rates induced by Fed policy would increase the cost of interest on a home but might also lower house prices.

The Fed will eventually raise interest rates but even Nobel Prize winning economists are confused about when this will happen.  Potential homebuyers should not rely upon the interest rate forecasts of realtors when determining whether or not or buy or rent a home.

Concluding thoughts on the Limitations of Buy Versus Debt Calculators:  My comments suggest that for a wide variety of reasons buy versus debt calculators often overstate the case for buying rather than renting a home.    The approach relies on subjective assumptions on a wide variety of economic variables.   Assumptions on the most crucial variable – the future growth of housing prices have been grossly inaccurate in the past.

The one factor that favors buying over renting in the current environment is that stock prices are currently at historic highs and long term interest rates are at historic lows.   I suspect that based on the current market conditions returns on real estate will outpace returns on financial assets in the near future.  Hence an assumption of a low future return on financial assets might be justified at this time.

The buy versus rent calculator does not accurately measure the benefits of delaying a home purchase until consumer debt and student loans are substantially reduced or eliminated.   Nor does the model allow for active consideration of costs, which might be incurred if a young worker with little initial house equity is forced to sell a home in order to take advantage of a new job opportunity.  Usually younger households will be much better off by delaying the home purchase and using all available funds to retire student loans and consumer debt.

Two Ways to Calculate a Portfolio PE Ratio

Two Ways to Calculate a Portfolio PE Ratio 

Question:  The table below contains data on the market cap and the earnings for four high-tech firms.

Market Cap and Earnings for Four Tech Firms
Market Cap

($ B)

Earnings

($ B)

AAPL 892.16 46.65
MSFT 585.37 21.2
AMZN 475.37 1.92
TWTR 13.11 -0.44797

 

In this post, I am asking you to use two methods to calculate the PE ratio of this four-stock portfolio and to confirm that both methods provide the same answer.

Method One:

Calculate the PE ratio of this portfolio by taking the sum of the market cap numbers for the four stocks and dividing by the sum of the earnings of the four stocks.

Method Two:

Calculate the ratio of (market cap minus earnings) divided by market cap for the four stocks.

Calculate a weighted average of the values (MC-E)/MC for the four stocks with the ratio weighted by MC.  Give the name to this weighted average the letter f.

Calculate 1/(1-f).

Show that the PE ratio from method one is identical to 1/(1-f).

Analysis:

The straight forward way to calculate the PE ratio by taking the ratio of the sum of the market caps to the sum of the earnings is presented below.

Portfolio PE Ratio – Method One
Market Cap

($ B)

Earnings

($ B)

AAPL 892.16 46.65
MSFT 585.37 21.2
AMZN 475.37 1.92
TWTR 13.11 -0.44797
Total 1966.0 69.3 28.4

 

This four-firm portfolio has a PE ratio of 28.4.

The PE ration calculation for method two  is presented below.

 

Portfolio PE Ratio — Method Two
Market Cap Earnings (MC-E)/MC Weight
AAPL 892.16 46.65 0.9477 0.4538
MSFT 585.37 21.2 0.9638 0.2977
AMZN 475.37 1.92 0.9960 0.2418
TWTR 13.11 -0.44797 1.0342 0.0067
1966.01 1.0000
f 0.9647
1/(1-f) 28.4

 

The second method for calculating a PE ratio gives the same result as a the first – 28.4.

Implications:   The PE ratio of a portfolio can be expressed as function of the weighted average of the ratio of the difference between market cap and earnings of the firm to market cap of the firm.    This is a very useful result.

PE ratios of firms are frequently not useful.

First, the PE ratio can become very large when earnings are very small. This means it is misleading to look at a weighted average of PE ratios because one firm can have a a very large impact. In our current example, the PE ratio of Amazon is 248 and the weighted average PE ratio for the four stocks is  77.

Second, PE ratios have no economic meaning when earnings are negative.

The PE ratio of a firm with negative earnings would reduce the weighted average of PE ratios in a portfolio.  By contrast, (MC-E)/MC will be larger than 1 if E is less than 0.

A firm with slightly negative earnings would have a negative PE ratio with a larger absolute value than a firm with very large losses.  This ranking of firms is incorrect because larger losses should be associated with lower relative valuations.   By contrast, (MC-E)/MC will always rise when E falls.

By contrast, the ratio of the difference between market cap and earnings over market cap is inversely related to the valuation of a firm.   When earnings are negative this ratio is greater than one.   When earnings are zero the ratio equals one.   When earnings are very small the ratio approaches one and is not an outlier.  The ratio of the difference between the market cap and earnings to market cap is intuitively defined for all earnings and not impacted by outliers.

 

A House Equity and Mortgage Payoff Spreadsheet

A House Equity and Mortgage Payoff Spreadsheet:

Question:   A person buys a house and plans to either sell and move or pay off the mortgage in twelve years.

The person is considering taking out a 15-year or a 30-year fixed rate mortgage.

The assumptions on the home purchase, house equity growth, the cost of selling and moving, and the cost of funds for the payoff of the mortgage are presented in the table below.

Table One: Assumptions for 30-year vs 15-year FRM Comparison:

Label 30-year FRM 15-year FRM
Purchase Price of House $500,000 $500,000
Down payment percentage 0.9 0.9
Initial Loan Balance $450,000 $450,000
Mortgage Term 30 15
House appreciation rate 3.0% 3.0%
Mortgage Interest Rate 4.0% 3.3%
Years person owns house 12.00 12.00
Cost of selling and moving to a new home as % of house value 9.0% 9.0%
Tax Rate on Disbursements from 401(K) Plan 30.0% 30.0%

 

Create a spreadsheet that provides estimates of house equity after the sale and move or mortgage payoff amounts after twelve years when the house buyer uses a 30-year FRM and when the house buyer uses a 15-year FRM

Base your mortgage payoff calculation on the assumption that the source of funds for the mortgage payoff are fully taxed funds from a 401(k) plan.

Spreadsheet:

http://wp.me/a2WYXD-4i

 

 

Results:

The results for the comparison of the 15-year and 30-year FRM for the assumptions presented in table one are presented in Table 2.

Table Two: Results for the 30-year vs 15-year FRM Comparison:

 

30-year FRM 15-year FRM
House Equity after Selling and Moving Costs $318,303 $540,109
Forecasted Mortgage Payoff Amount -$472,025 -$155,160

 

Observations on the 30-year vs 15-year FRM comparison:

The person taking out the 15-year FRM mortgage has around $222,000 more in house equity at the end of the 12-year holding period.

The mortgage payoff calculation when funds are disbursed from a 401(k) plan includes tax on the disbursements.   Inclusive of the tax bill, the mortgage payoff amount is $317,000 higher for the buyer who uses the 30-year FRM than for the buyer who uses the 15-year FRM.

Other Applications for the House Equity or Mortgage Payoff Spreadsheet:

 Modify the mortgage payoff calculation to allow for a situation where funds for the mortgage payoff are obtained from three sources – (1) a savings account, (2) sales of common stock, and (3) disbursements from a 401(k) plan.   Treat tax rates as an endogenous variable in the new model.

Compare results for both mortgage types under the 90% LTV assumption to results under an 80% LTV assumption.

Run the model on 15-year and 30-year FRMs for holding periods ranging from 1 to 15 years.   How does the advantage of the 15-year FRM vary with holding period?

Authors Note:   This problem was discussed further in the post below.

Essay Nine: Retire Mortgage Debt or Accumulate in Your 401(k) Plan:

https://financememos.com/2015/10/09/essay-nine-retire-mortgage-debt-or-accumulate-in-your-401k-plan/

Essay nine points out that many financial advisors stress accumulation of wealth in 401(k) plans rather than mortgage balance reductions even when their clients are nearing retirement.  The major banks employing the same financial advisors issue mortgages and sponsor 401(k) plans.   As a result, the interests of the financial advisors and the interests of their clients are not automatically aligned.

This approach can backfire when stock markets underperform nearing retirement.

During working years. the tax code favors people with large mortgages and people who are contributing to their 401(k) plan.  However, after retirement the person who must disburse funds from a 401(k) plan often has a hefty tax bill.

 

 

How to correctly calculate portfolio PE ratios?

 

How to correctly calculate portfolio PE ratios?

Question:   Two analysts are given the task of calculating the PE ratio of the DOW using the data below.   (Note:  Data on one firm is missing because of a recent merger.)

The first analyst uses method one and takes the ratio of the weighted average of market caps for the 29 companies to the ratio of earnings for the 29 companies.

The second analyst uses method two and takes the weighted average of the PE ratios of the 29 stocks.

What is the correct way to calculate the PE ratio for this portfolio?

What are the ramifications of using the wrong method to calculate the PE ratio for this portfolio?

The Data:

Financial Information on Stocks In The Dow
Share of Dow Market Cap ($B) Trailing Earnings ($B) Trailing PE
MMM 0.0645 124.9 5.2 23.87
AXP 0.0278 79.8 4.3 18.5
AAPL 0.0474 793.6 45.5 17.44
BA 0.0781 149.7 6.7 22.18
CAT 0.0383 73.7 0.1 696.65
CVX 0.0361 222.6 5.8 38.1
CSCO 0.0103 166.5 9.4 17.7
KO 0.0138 192.0 4.0 47.5
DIS 0.0303 152.1 8.7 17.48
XOM 0.0252 347.4 11.7 29.6
GE 0.0074 209.4 7.1 29.45
GS 0.0729 92.1 7.4 12.44
HD 0.0503 192.8 8.2 23.5
IBM 0.0446 135.2 11.3 12
INTC 0.0117 178.9 12.3 14.5
JNJ 0.0400 348.9 15.9 22
JPM 0.0294 336.1 23.8 14.1
MCD 0.0482 126.9 4.9 25.7
MRK 0.0197 174.6 5.0 34.7
MSFT 0.0229 573.7 20.9 27.5
NKE 0.0159 85.1 4.1 20.7
PFE 0.0110 212.3 8.1 26.1
PG 0.0280 232.0 14.2 16.3
TRV 0.0377 33.8 2.8 12.2
UTX 0.0357 92.7 5.2 17.7
UNH 0.0602 189.4 8.1 23.5
VZ 0.0152 201.9 15.9 12.7
V 0.0323 240.7 6.2 39.1
WMT 0.0240 233.4 12.4 18.8

Methodological Note:  Assume the columns of your spreadsheet are – (1) Share of DOW in A, (2) Market Cap in B, Trailing Earnings in C, and Trailing PE in D.

Also assume there are 29 rows, 1 to 29 for each variable.

The formula for method one is =SUMPRODUCT(a1:a29,b1:b29)/SUMPRODUCT(a1:a29,c1:c29)

The formula for method two is

=SUMPRODUCT(a1:a29,d1:d29)

Analysis:   The DOW PE ratio for method one is 20.5, a pretty high number compared to the historic norm of PE ratios for this index.

The DOW PE ratio for method two is 46.7, a number that is implausible for the portfolio of DOW stocks

Market Cap Weighted Total 203.4
Earings Weighted Total 9.9
Dow PE Ratio Method One 20.5
DOW PE Ratio Method Two 46.7

The PE ratio of one company in the DOW, CAT is 696, an extreme outlier.  This outlier drives up the weighted average of the PE ratios by a lot.

It is inappropriate to take the average of PE ratios because often a PE ratio for a particular company is an outlier or is below zero.

PE ratios below zero are economically meaningless.    For a discussion of how to calculate the PE ratio of a portfolio when some stocks in the portfolio have negative earnings go to the following site.

PE Ratios When Some Firms Have Negative Earnings

http://www.dailymathproblem.com/2017/05/price-earning-ratios-for-portfolios.html

Many analysts deal with the issues of negative or outlier PE ratios by dropping firms from their analysis.     There is no need to drop firms when you calculate a portfolio PE ratio if you are using an appropriate method.

Evaluating Fund Performance

Evaluating Fund Performance

Investment funds, both ETFs and mutual funds, are usually compared on the basis of returns of arbitrarily selected holding periods.   Typically, the fund manager reports year-to-date returns and return for one, three, five, and ten years.  The discussion of fund risk is usually based on a subjective assessment of the risk of the assets in the fund.

The conventional approach to presenting statistics on fund performance is inadequate.   Funds can be purchased at any time, not just a few arbitrarily selected dates.   This post measures the mean and standard deviation of return for two popular funds when there are multiple possible purchase and sale dates for each fund.

Statistical tests are used to evaluate whether the observed difference in return and risk outcomes for two funds are statistically significant.

Question:   This post considers two of Vanguards most successful funds.  VFIAX is a fund that mimics the S&P 500 and VWELX a fund that is around 70% equity and 30% fixed income.

The 48 potential purchase dates for both of the two funds are the first day of each month starting in January 2002 and ending in December of 2005.

The 48 potential sale dates for the two funds are the first day of each month starting in January 2012 and ending in December of 2015.

  • Assume that each combination of purchase and sale dates is equally likely.
  • What are the expected return and the standard deviation of return for both funds?
  • What are the minimum and maximum returns for each fund?
  • Can we reject the hypothesis of identical variances for the two funds?
  • Can we reject the hypothesis the mean returns are identical?

Analysis:

There are 2304 (48 x 48) possible (purchase-sale) outcomes.  For each of these outcomes I calculate ln(AP2/AP1) where AP2 is the adjusted price in the 2012 to 2015 time period and AP1 is adjusted price in the 2002 to 2005 time period.

The mean standard deviation, minimum, and maximum for the two funds are presented below.

Returns from Two Funds
Fund Description Mean Standard Deviation Minimum Maximum
VWELX Stocks and bonds 0.763 0.177 0.341 1.14
VFIAX Stocks 0.692 0.226 0.178 1.21

Sample size 2304 based on 48 possible purchase dates between 2002 and 2005 and 48 possible sale dates 2012 and 2015.

Observations:

  • The mean return of the bond/stock fund is higher than the mean return of the stock-only fund by around 10 percent.
  • The standard deviation of returns for the bond/stock fund is lower than the standard deviation of returns for the stock-only fund by around 21 percent.
  • The maximum return is higher for the stock-only fund by around 92 percent.
  • The minimum return is lower for the stock-only fund by around 6 percent.

Comments:

Comment One:  The finding that the combined stock/bond fund has a larger mean return compared to the stock-only fund is extremely unusual because over long periods stocks tend to have higher returns than bonds.    However, the stock portfolios of the two funds differ.  The stock portfolio in VWELX is broadly diversified but does not track a specific index.   The stock portfolio in VFIAX tracks the S&P 500.  VWELX was able to get higher returns than VFIAX because its stock portfolio outperformed the S&P 500 while the bond portfolio lowered risk.   It also did not hurt that interest rates fell and bond prices rose in this time period.

Comment Two:  The stock-only portfolio was much more risky than the combined bond-stock portfolio.   This is evidenced both by the lower standard deviation and the higher minimum return.  The minimum return statistic measures the worst-outcome return.  The worst-outcome return for the combined stock-bond portfolio is around 92 percent higher than the worst-outcome return for the stock-only portfolio.

Tests of equal variances for returns:

A test of the hypothesis that the variances of return for the two portfolios are equal was conducted.   The F-statistic comparing the ratio of the two standard deviations was 1.63, which is significantly different from 1.0.    The hypothesis that the two variances are identical is rejected.

Tests of equal mean returns:

A test of the hypothesis that the mean returns for the two portfolios are equal was conducted.  The t-statistic for this hypothesis test was 12.9.   The hypothesis of identical means is rejected.

Technical Note:  I used STATA to make the calculations in this note.  Period one and period two data were placed in separate data sets.   The N to N merge provides the 2304 outcomes.

Concluding Thought:  The practice of presenting return numbers on investment funds for a few arbitrarily chosen holding periods is, in my view, not very useful.    The holding periods are arbitrary and subject to manipulation.   There is no measure of risk.

The technique presented here relies on many possible outcomes defined by different purchase and sale dates.   The multiple outcome approach allows for the presentation of risk measures.

The note shows that the performance of the VWELX fund was exceptional in this period.