The Ultimate How Bonds Work Guide

The Ultimate How Bonds Work Guide

Bonds confuse lots of people but actually they are very straight forward. When you buy a bond you loan your money to a company, city, state or country for a fixed term. When you first make the loan, the interest rate is fixed (in most cases) as is the maturity date (the date they have to repay you).

During the period of the loan, you usually receive interest every 6 months. In the vast majority of cases, the interest payment you receive never fluctuates; you always get the same payment regardless of what happens in the stock market and regardless of what happens to interest rates. When the term is up, you (hopefully) get your money back.

What happens if you need to cash in your bonds before they mature?
When you buy a bond, the company or government that borrows the money is only obligated to pay you interest every 6 months and to repay the face amount of the bond when it matures. If you need to cash the bond in before it matures, you must sell it to somebody else.

If you do that you may get more or less than you put in, depending on market interest rates, the general state of affairs in the economy and the specific situation the borrower is in. In other words, the value of your bond goes up and down all the time.

This doesn’t matter if you hold your bond to maturity because at that point, the borrower has to give you back the face amount (assuming they are able to do so).

Bond Terminology
Before we dive too deep into the world of bonds, let’s go through a little terminology. It’s not that complicated and it will really help you get a grasp of what’s going on.

Accrued Interest.

Bonds pay interest every 6 months. This period is fixed. As soon as the bond pays out interest, it starts accumulating interest for the owner the next day. This is known as the accrual period.

Let’s say you buy a bond that normally pays interest to the bond holders on January 1st and July 1st. If you buy that bond on June 1st for example, you’ll get all six month’s interest on July 1st even though you only owned it for 1 month. To make up for that, when you buy a bond in between payout dates, the buyer pays the seller for the number of days the seller held the bond after the last payout. That’s called accrued interest. If you buy a bond in between pay dates, you can confirm the accrued interest the seller is charging you by using any number of online calculators.

In this case, you’d owe the seller of the bond for 5 months of interest and you’d have to pay the seller that accrued interest in addition to the amount you pay for the bonds. That amount would be rolled into the price of the bonds when you buy them.

Call Date

Sometimes, the borrower (or issuer) has the right to repay their loan earlier than the maturity date. This is otherwise known as calling the bonds early. When you buy a bond, it’s always important to ask if the bonds are callable and if so, at what date and price. (Sometimes the call price is different than the face amount of the bond.)

Coupon Payment

This is the amount the bond holder will receive every 6 months. You calculate this by multiplying the interest by the face value of the bond.


The American Bankers Association developed a way to classify municipal, corporate and U.S. government bonds. What they came up with is known as a “CUSIP number” which is a unique nine digit alphanumeric identifier.

Discountbond funds

If you buy a bond at less than face value, the difference is a discount.


The length of years before the bond matures.

Face Amount

This is the par value of the bond. It is the amount that the borrower must pay the bond holder when the bond comes due.

High Yield Bonds

These are bonds that pay higher than market interest rates and they are otherwise known as junk bonds. Usually these bonds pay higher rates because the risk of default is higher. The added interest is meant to compensate the investor for this added risk.

Investment Grade Bond

There are rating agencies that evaluate how secure different bonds are. In other words, the higher the rating, the stronger this rating agency believes the bond issuer is and their ability to pay interest and principal. This in turn means that rating agency believes that the bond is appropriate for investors seeking preservation of capital.


This is the name of the party that borrows the money by issuing the bonds.


This is an estimation of how easy or difficult it will be to sell the bonds on the secondary market. If the bonds are in high demand, it will be easy to sell them if the need arises. If the bonds are not in high demand or there are very few bonds being traded, they are referred to as “non-liquid”. Investors who hold illiquid bonds may have to offer them at a steep discount if they want to sell them prior to maturity.

Maturity Date

This is the date when the issuer must repay all bond holders the face amount of the bonds plus the accumulated interest since the last interest payment date.

Nominal Interest

This is the fixed interest rate that the bond issuer pays to the bond holder.

Payment Date

This is the date that the issuer pays out to registered owners of the bond.


If the market price of a bond is higher than the face value, buyers pay a premium.


This is the face amount of the bond.


This is the return the investor earns based on the actual amount they invest.

Why Bonds Fluctuate In Value Prior To Maturity
The best way to understand this is to look at an example. Let’s assume you buy a $100,000 bond with a 5% interest rate at par value. In this case, you will receive $2500 twice a year for a total of $5000. No matter what happens in the market, as long as the people who issued the bond have the ability to pay, that’s how much you will get. No more. No less.

Now, let’s assume that a couple of years go by and interest rates go up to 10%. If you try to sell your $100,000 bond on the secondary market, you won’t get $100,000 for it. Here’s why.

If I have $100,000 to invest when rates are 10% and I buy bonds, I’ll receive $10,000 a year in interest. So if your bond is only paying $5000 a year, I know I only have to invest $50,000 to earn that $5,000 (because interest rates are now 10%).

That being the case, since your bond is paying a fixed $5000, the most I’ll pay you for your bond when interest rates rise to 10% is $50,000. Make sense? This is why as rates go up, the value of the bonds typically go down.

All investments are ultimately valued by the income they generate; either now or in the future. Remember that. It will help you understand how other investments operate as well.

Of course, the other side of this equation also works. Let’s say rates go down to 2 ½ % rather than go up. Are you going to sell me your bond that pays $5,000 a year for $100,000? No. That’s because, when rates are 2 ½%, someone would have to invest $200,000 in order to replicate the $5000 income your bond is paying you. So if somebody wants to buy your bond when rates drop to 2 ½%, they better be willing to cough up $200,000 or you won’t sell.

Other Factors That Move Bond Prices
Besides market interest rates, there are other economic pressures that impact bond prices. One major influence is the financial security of the issuer. If the company that issued the bonds is on the ropes and nobody expects them to be around when it’s time to pay back the bond holders, the value of those bonds will plummet.

In addition, if the economic conditions of the overall economy change for the better or worse, that could also impact the value of the bonds. That’s because if the open market expects interest rates to shift, bond values will shift along with them.

Another force that impacts bond values is the time to maturity. The longer the maturity, the greater the impact of the changes outlined above – all things being equal.

What happens when a bond matures?
When your bond matures, the borrower (or issuer) stops paying interest and you are supposed to get your money back. In order to understand how you get your principal back, you first have to understand how people actually hold their bond investments.

In the vast majority of cases, people hold their bonds in brokerage accounts. That means they don’t have a physical certificate but merely an electronic notation in their statements reflecting their ownership. This may not sound that secure but in reality, this is by far the safest way to hold bonds.

When a bond comes due in this case, the brokerage company simply removes the bond from the holdings and puts the cash redemption amount into the account. Very easy.

But some investors hold physical certificates instead. In the olden days, this was the only way you could hold bonds; to get a physical piece of paper and store it somewhere safe. And while most people don’t have to bother with this today, some still prefer to do so. For these people, the process of redeeming a bond is more complicated.

If you hold the physical bond certificate and it matures, you send the paper certificate to what’s called the transfer agent when the bond matures. This agent is a fiduciary intermediary that acts as an agent for both you and the bond issuer. When the bond comes due, the transfer agent will get your certificate from you and send it to the issuer. Then, the issuer will send the redemption value to the transfer agent who in turn puts the money in your account.

The idea of holding the certificates may sound appealing to you but there are downsides to this approach. First, if a bond matures and you hold the certificate, the agent or issuer may not reach out to you. It may be up to you to follow up with them. When your bonds are held by the brokerage firm, you don’t have that worry.

Another concern is that bonds held in certificate form can be lost or destroyed. If you happen to misplace your bond, you may have to pay 3% of the face value or more in order to get it replaced.

Bottom line? If you own bonds, chances are you will be far better off by depositing them with a broker.

All bonds are debt instruments because they represent a debt that someone has to the bond holder. There are many different types of debt instruments and each kind has its own benefits and risk profile.

The most prolific debentures are U.S. government notes, bills and bonds. These are all issued by the United States Department of the Treasury. These are all very liquid and are very easy to sell on the secondary market.

Treasury bills are debts that mature in one year or less. The interest is included in the price you pay for the bill. That means you pay less than the face amount of the bond when you purchase them. And when it matures, you will receive the full face amount. The difference is the interest and this is an example of buying bonds at a discount.

Treasury notes are issued for 2 to 10 years. These bonds pay interest semi-annually.
Treasury bonds are the longest maturity U.S. government debt you can buy. They are issued for 20 to 30 years.

The government also sells inflation protected bonds called “TIPS”. This is an acronym for “Treasury Inflation-Protected Securities”. You may recall that with typical bonds, the maturity value and interest payments are fixed while the value of the bond fluctuates prior to maturity.

With TIPS, the rate stays the same but the maturity value is adjusted by the Treasury department to compensate the bond holder for risk. If rates rise (CPI) the maturity value of the bonds rises as well. This way, if inflation gets out of control, TIPS investors have a built-in safety net.

Currently, TIPS investors receive interest every 6 months and can buy bonds that mature over 5,10 or 30 years.

While these bonds may sound attractive for those worried about inflation, you might want to hold on to your check book for a while. I say this because nobody knows which way rates are going and how long it will take them to get there. If rates are low and stay down for years, it might take a long time before your TIPS prove themselves as worthwhile investments.

The government bonds discussed above all provide interest that is taxable at the Federal level, but State tax free.

Municipal Bonds
Besides U.S. government bonds, you can also loan your money out to cities, and states. These are referred to as municipal bonds and when you buy these bonds, the interest you receive is Federal tax-free. And in many cases, the interest you earn is also State tax free. The reason the interest is tax free is to make these investments more appealing to investors while making the borrowing costs lower for the cities and state.

The value of the bonds fluctuate and are subject to the same risks as discussed above.

Other Types Of Bonds
You can loan your money out to different countries or private companies as well. The same risks apply to these investments without the tax benefits described above. When you loan money to another country, the backing is only as secure as the country itself.

The history books are full of cases where sovereign nations defaulted on their bonds and left bond holders high and dry. Because of these risks, some foreign nations have to pay higher rates in order to attract investors. Of course, this depends on the financial stability of the borrower at the time they seek out funds.

You can also lend money to corporations here and overseas. Again, these bonds work the same way I’ve described above. And like foreign national bonds, the interest earned and the investment safety are very much a function of the particular party you are considering lending money to.

What happens if the borrower doesn’t repay you?
If the company, city, state or country that borrowed money from you does not have the wherewithal to pay you the interest or the principal they owe, you probably won’t be a very happy camper.

When this happens it’s known as default and it’s usually ugly. When the issuer is a company, they usually file for bankruptcy before they default. If they don’t, the bond holders usually force bankruptcy on the company.

If the company goes into a Chapter 7 bankruptcy, the court takes over the business and its assets are sold off. If your bonds are secured by assets, you’ll be among the first to see some money. If your bonds are unsecured, you won’t see a dime until the secured creditors are taken care of.

Chapter 11 bankruptcy puts the court in charge of the company but assets are not sold off. The hope here is that debt holders will get more if the company continues to operate rather than be sold off.

In either case, bond holders usually lose money when the issuer goes into bankruptcy and the value of their bonds will likely whither.

Municipalities can go bankrupt too but that doesn’t happen often. That’s because it’s very difficult for a municipal government to do so. In fact, there have been fewer than 500 municipal bankruptcies over the last 60 years compared to tens of thousands of business bankruptcies filed each year.

In the rare case where a city does file bankruptcy and defaults on its debt, the recovery rates were about 62% according to Moody’s Investor Services. To give you something to compare this too, corporate bond holders of defaulted securities usually recovered only 49% on average between that same period 1970 to 2012.

What about bond funds?
There are many ways you can invest in bonds. You can buy individual bonds of course as I described above. But you can also use mutual funds and/or ETFs to buy bonds. There are pros and cons to each. Let’s take a closer look at bond mutual funds, ETFs and index funds).

When you invest in a bond fund, the fund managers buy……ahhhhh……bonds. No surprise there.
But there are big differences between buying a bond outright and buying them through funds or ETFs. When you own a fund for example, you incur fund expenses. Some bond funds are expensive and others are very inexpensive. (We’ll look at fund expenses later on in the guide.)

On top of that, funds don’t have maturity dates – individual bonds do. The fund is a pool of potentially hundreds of different bonds and each one comes due at a different time. When one bond matures, the fund managers will in most cases immediately turn around and reinvest the proceeds into a different bond. Because there is no maturity date with a bond fund, you never have a fixed date when anyone is forced to repay your money.

Also, with an individual bond, you know what interest you are going to receive and when. With a bond fund, it’s not that simple. Remember, there are hundreds (sometimes thousands) of bonds that make up the fund. They all have different rates and different pay dates. While the income won’t change that much in any one month, it will change over time as old bonds mature and new bonds (at different rates) are purchased.

(Bond funds themselves come in a variety of different stripes. You can buy muni bond funds, international corporate or sovereign bond funds, and corporate bond funds. The holdings of each fund is determined by the fund prospectus. This is the document that details what the fund managers can and can’t do. Typically, the prospectus spells out what kind of bonds the fund will purchase, what quality the bonds will be and what the duration of the bonds would be as well.)

So these are two downsides to owning bond funds. But there are also some strong positives.

First and foremost, a bond fund spreads your risk. If you put all your money into one bond, you could lose it all if the bond defaults. With a bond fund, no one bond default can hurt you that much. Also, with a bond fund you have expert managers at the helm. All they do is read prospectuses and check out the financial strength of potential bond issuers all day long. These people have more expertise and time than you have and they are better equipped to keep your money away from shaky deals. This is not to say that they are always successful. But they do have better tools and resources than you do.

Also, you can put any amount you want into a bond fund. That’s not the case with individual bonds. Typically individual bonds are sold in increments of $100,000. That’s a lot of scratch for most people. If you buy individual bonds you need to invest several million dollars in order to have a diversified portfolio. With bond funds, you have access to wider diversification with only a $100 investment.

Last, with bond funds, you usually don’t have to worry about liquidity. If you own an individual bond and want to sell it before it matures you have to sell it on the open market and hope for the best. That involves commissions of course but it also involves risk. And if the bond you want to sell is a small issue and illiquid, it may take time to sell. To make matters worse, illiquid bonds are often sold at steep discounts as I mentioned before. If that’s the case, you could take a major haircut on your principal if you need to bail out of an individual bond prior to maturity.

This isn’t a problem for bond fund investors because the fund has more liquidity. Keep in mind that on any given day investors are buying and selling shares of the fund. Often, a fund manager can use the cash inflow to pay off those people who want to cash out. Often they can do this without even selling off any bonds.

Also, as the market shifts, bond holders can easily shift with it. For example, if you decide you want to sell your corporate bond fund and buy a municipal bond fund (or any other fund) instead, it’s very easy and inexpensive to do. The same can’t be said for investors who own individual bonds as this process is much more costly for them.

How to buy bonds and bond funds
Most people who buy individual bonds do so through their broker. The one tricky thing about this is that sometimes you don’t know how much commission they are charging. For some reason, it’s actually legal for a bond broker to “bury” the commission into the cost of the bond so the customers don’t know what they are paying.

For example, lets’ say you want to buy a bond. You call up your broker and tell her what you are looking for and she comes back to you with an offer of XYZ bond paying 4% maturing in 2030.

Let’s say you like the sound of that so you give your broker the green light and she buys the bond at par value – $100. This could be OK – but you don’t know for sure. It could very well be that the broker only paid $97 for the bond and is charging you over 3% to make the transaction. This is referred to as “mark up”. It’s a cost that is often difficult to ascertain because it’s buried into the price of the bond. This might be OK in someone’s world but it’s not OK in mine.

There are calls in the industry for brokers to fully disclose markups but so far this requirement has not been put in place. The best thing to do is ask your broker what the mark up is and hope they are being honest. Once you get that information, check with another broker to determine what price they would charge for the same bond – and tell your existing broker you are going to do so. Very few people do this but it’s the only way you can audit your broker under current rules and is very much worth the time.

If you want to buy Treasuries, you can sidestep this entire problem and buy them directly from the Federal government.
All you have to do is go to their website (Treasury Direct) and have at it. If you do, you won’t have to worry about commissions and mark ups as there are none. There are some costs to this but they are relatively minor and nothing to worry about.

On your first visit, you’ll have to open an account – but that only takes about 10 minutes. Once you do that, you can buy Treasury Bills, Notes, bonds or TIPS.

The easiest way to buy mutual funds or ETFs is to do so through a broker. Don’t buy funds at a mutual fund company however. If you go that route, you can only buy funds offered by that particular fund family. If you buy your funds through a brokerage firm like TD Ameritrade, Fidelity or E*TRADE, you can buy almost any fund you like. I’ll discuss this in further detail later on.

Bottom line on Bonds
Bonds are very popular – but that doesn’t mean they are the right investment for you. It depends on your investment objectives. Please refer back to the Ultimate Investment Guide for a deeper discussion on this point. Bonds may have a place in your portfolio. And if they do, this guide has explained most of what you need to know in order to make smart decisions about bonds. As always, speak to your investment professional before making investment decisions.

How to Improve Your Finances with Personal Financial Statements

How to Improve Your Finances with Personal Financial Statements

How often do you sit down to review your finances? Not just taking a glance at your latest statement looking for fraud, but really sitting down and analyzing your income, spending, savings, investments, and whether or not you are on track to meet your financial goals? If you are like most people, the answer is not very often. In fact, some people never take the time to understand their finances. They just complain and react without taking time to set goals and make a plan to achieve them.

As a Senior Financial Analyst at a Fortune 500 company, I spent my days doing this for $1 billion+ product lines to ensure we were on track to reach our goals for product profitability. If you want to reach personal profitability, you should look at your finances like a business. Read on to learn about three common financial statements and how you can use them in the pursuit of personal finance success.

Income Statement

For personal finances, one of the most important tools you have is a budget. Your budget isn’t a restriction on what you spend, it is a tool to plan for your income and spending to ensure you reach your financial goals.

Businesses use their income statement to understand and report income and losses for a specific period of time. Also known as a profit and loss statement or P&L, this is the most important tool you can use for your own financial planning.

Remember that an income statement includes both revenue and expenses. You can budget until you’re blue in the face, but you will never get rich if you don’t increase your income. My side hustle brought in $40,000 in 2014 in addition to my full-time job. It is easier to earn more on the side than you may realize, and having diverse income sources helps protect you from unexpected income losses in the future.

There are a handful of free budgeting websites and apps that you can use to connect your bank, credit, and loan accounts to automatically create a personal income statement every month.  Also, if you want to make it simple, there are a fewingenious ways to track your spending that cost you nothing and take almost no time to do.

Balance Sheet

Big businesses use a balance sheet to understand assets, liabilities, and shareholder’s equity in a business at a snapshot in time. Public companies are required to report this information quarterly, but I look at my own personal balance sheet once a month, and have done so since July, 2008.

What most businesses call a balance sheet, individuals call net worth. Calculating your net worth doesn’t have to be difficult. I use the free site NetworthShare to update my net worth every month.

Looking at my personal balance sheet, I can get a quick view into my assets, debts (travel rewards credit cards I pay off in full every month), and financial health with less than five minutes of work every month.

Cash Flow Statement

A cash flow statement appears to be less related to personal finances than the others on the surface, but it also has an important role in your personal finance statements.  This statement tells you where your money comes from and goes to within three major categories: operating, investing, and financing.

For our purposes, operating activities are any source of work or self-employment income and expenses. Investing is activities related to stock market and other investments, or investing in your own education and skills. Financing is debt related activity like buying a car or home with a loan.

Looking at your finances through this lens shows you how each part of your finances is working independently of the others. Maybe your investments are doing really well, but debt is keeping you from success. Maybe your job is supporting your investments and debt – that is very common.

There is no right or wrong here as long as you bring in more than you spend. However, looking at your cash flow into investing or financing, for example, can show how much you are doing to prepare for retirement or how much of your income is being eaten up by debt payments.

A Small Investment Can Pay Big Dividends

Putting together financial statements and taking the time to better understand your finances doesn’t cost you a cent! It only costs you a little bit of time. But don’t look at that time as an expense, look at it as an investment. By spending the time to understand your finances today, you know where to focus and work in the future. That can pay back huge dividends.

For me, it led to earning about one hundred thousand dollars in real estate. It led me to earning over six figures between a day job and a side hustle. It allowed me to quit my job to focus on my side hustle full-time and move to the beach in sunny Southern California. I now make more than double what I was paid at my old day job, but it wouldn’t have happened had I not started by understanding my finances.

Of course, everyone can’t expect to quit their job just because they understand their finances, but if you can get your finances under control and start working towards your goals, anything is possible.

So are you going to take action and understand your finances, or just let your finances happen like most people who drone forward in their day-to-day life wishing for something better? Stop wishing. Take control of your finances. It starts today with your personal financial statements. Who knows what tomorrow has in store?

Should You Drive For Uber? These Real Numbers Help You Decide

Should You Drive For Uber? These Real Numbers Help You Decide

If you are interested in earning extra cash, you might consider driving for Uber. A lot of people are doing just that. In fact, according to a recent study by Princeton, 40,000 new drivers are signing on every month. They are attracted by the flexible hours, the opportunity to be their own boss and the potential to make big money. What’s not to love?

driving for Uber

I have to admit, on the face of it, it sounds appealing. And because so many people turn to me and ask for good ways to earn a few pesos on the side, I took a deep dive into the Uber opportunity to see if it’s really all it’s cracked up to be.

Super Important Note: Being an Uber driving partner (that’s what they call it) is a very unique experience. I scoured the net for everything I could find on this opportunity and a few very important points became very clear very quickly:

a. As you’ll see, whether or not this job is suitable for you depends on YOUR unique circumstances.

b. The profitability of this work is also highly dependent on your unique situation, the market you drive in and how you work the market. (More on this later).

For that reason, I did a ton of research – so you can make an informed decision. Reading or listening to one individual driver’s experience might be interesting, but it won’t give you any idea about what you need to consider in deciding whether or not to drive for Uber. That’s what this post is going to solve for you.

Specifically, here is what you’ll learn by the time you finish reading:

A. How much you can make as a driver.
B. How the Uber business model works and why that’s important for you.
C. 3 ways to earn more as a driver.
D. How to calculate your real costs to drive for Uber.
E. How to apply for the job.
F. How to run your Uber business
G. Who this job is good for.

Before we go too deep, I want to point out that Uber offers two services. Their first and trademark service is ridesharing. That’s what the following discussion is about. But they also offer UberEATS – which is a food delivery service. It’s not hard to get a job with Uber and it’s even easier to drive for UberEATS.

You only need to be 19 years old and have one year of driving experience to deliver for UberEATS. Also, just about any car is acceptable so it’s much easier to land that job. You can even work if you only have a motorcycle, scooter or bicycle. The pay structure is different but the cost structure is the same. That’s why even if you are interested in signing up for UberEATS you should still read this post in its entirety. Here is moreinformation about UberEATS.

How Much Can You Make as An Uber Driver?

To make a good decision about working for Uber, you have to calculate your net profit for each hour you work. It doesn’t matter how much you make. It matters what you keep. And in order to understand how much you make, you first have to take a look at Uber’s business model.

The Uber Model

Customers use the Uber app to request a ride for which they are charged a fare. This fare is based on a base rate, the distance traveled and how much time it takes to complete the ride. On top of that, customers pay $1 to $2 to book the ride. Other than the booking fee, all the revenue is split 80% to the driver and 20% to Uber.

Let’s look at an example.

Let’s say you are an Uber driver working in LA and you take a customer on a 9 mile trip that takes 35 minutes. (It’s important to specify the city you are driving in because the tariffs differ by local. This will be very important later on as you’ll see.) In this case, the customer would pay about $15 of which you’d be paid 80% or $12. Simple.

Can You Earn More?

Yes – and this is key. Uber charges riders “surge” pricing when there are fewer drivers and greater demand. This happens often during bad weather, special events, or rush hour. It can happen anytime during the day (or night) whenever lots of people need Uber and there just aren’t enough drivers. Surge pricing can be 1.3x to 2.1x times the normal rate. In the example above, if that LA ride was made during a surge period, you’d be taking down 80% of (maybe) $30 rather than $15. Sweet.

As I said, surges can happen anytime and there is no guarantee that if you work a particular time, you’ll enjoy the higher fares. But as a driver, you can make yourself available during times (and in areas) which are most likely to have surges as described above and increase your odds of earning more money.

Earning Even More Money With Uber

The basic service is called UberX. People who order up this program get a normal car to take them where they want to go. But many riders want to be carted around in luxury vehicles and Uber is only too happy to oblige. And if you own a swanky ride, you can earn more. The higher-end options include:

    • UberXL


    • UberBlack


    • UberSelect


    • UberPlus


    • UberSUV



Each level up demands that you provide a cooler sled but also commands heftier fees. Again. that means you’ll earn more for every hour you drive. I doubt it’s worth trading in your Pinto for a Lamborghini just for those higher fees. But if you happen to own a nice car, this option could really pay off for you.

Bottom Line On Gross Income

Near the conclusion, I’ll provide a few of the hacks the successful Uber drivers use to make this gig pay. But as I said at the outset, your gross earnings will vary by when, how and where you work. But you need some figure to work from. That being the case, it’s probably best to use $20 an hour. That’s the national earning average as calculated by Uber.


The pay sounds pretty cool but don’t forget about your costs. When you drive for Uber, you use your own car and pay all the associated expenses. Many Uber drivers fail to understand the true costs of this arrangement and as a result overestimate their earnings. Let’s take a walk through the cost side of the Uber equation. I want to make sure you really get this.


If you are thinking about driving for Uber, you probably already own a car and that means you probably already have car insurance. The thing is, your existing policy may not be adequate. That’s because once you start earning money with your car, you become a commercial driver and that usually calls for different car insurance.

Call up your insurance company and tell them that you will be driving for Uber. Ask them if the policy you have is enough. There is a slim chance that your existing policy will be sufficient but probably not. Here’s why.

When you become a paid driver you are a higher risk. That’s because you are on the road more hours and that means you are more likely to be involved in an accident.

Your insurance company might be able to sell you a hybrid policy that covers both personal and commercial use and if so, your premiums will go up. If your company doesn’t offer a policy, Uber can sell you this added coverage but the Uber policy isn’t enough. You’ll still need your own personal policy. So make sure to find out what your additional insurance costs are going to be.


Of course if you make money driving for Uber you’ll pay tax on that income. Keep in mind that you are an independent contractor and while Uber will send you a 1099, you’re still responsible to file.
Also, remember you’ll be an independent contractor and as such your tax preparation may be more complex and therefore may cost you more money to have prepared.

But there is also some good news when it comes to taxes. Because you will be in business for yourself, you might be able to write-off more of your work related expenses and that could end up saving up a nice chunk of change. Rejoice.


In order to make this business work, you must have a smart phone and a data plan. You can install the Uber app on the iPhone 4s,5,5C,5S,6 and 6 Plus running iOS 7 or later. You can also use an Android 4.0 or later. If you already have both a smart phone and a good data plan, this isn’t really an added cost.

Gas, Maintenance, Wear and Tear

Each driver has different car costs associated with working with Uber. Your costs will depend on your gas mileage, how well you keep your automobile, the kind of driving you’ll be doing and your car’s current condition.

I did a lot of sniffing around and found that the typical Uber driver figures it costs them about $.30 per mile to drive for Uber all in. If I was thinking about driving for Uber however, I’d assume it cost me $.40 per mile just to be on the safe side. The cool thing is, the IRS allows you to deduct $.53.5 (2017) per mile or actual costs – whichever is greater. So you might be able to write off more than it actually costs you and save some tax dollars. Cool.

Adding It All Up

There is a lot of controversy about Uber driver-partner expenses. And it is a murky subject. Your expenses will vary depending on how you work. I read everything I could on this topic (including scouring the Uber driver forums). Bottom line? Expect to set aside about 30% of your gross to pay your expenses.

Who Is Allowed To Drive for Uber?

In order to get on the Uber gravy-train, you have to meet certain requirements:

  1. Be 21 years old or older.
  2. Minimum 3 years driving experience.
  3. Have an automobile insurance policy in your own name and in the same state you want to drive in.
  4. Have a Social Security number.
  5. Submit to a background check.
  6. Have a clean driving record.

This may seem onerous but don’t worry. Nobody expects you to be perfect. As long as your driving history is good and you don’t have a criminal record, you’ll probably be accepted.

Also, a basic license will probably be enough in order to drive at UberX level. If you want to drive at a higher level you may need a higher license classification. The company will let you know.

You need a model year 2000 or newer sedan that seats a total of 4 people minimum (including you). Your car must have license plates issued in the state where you’ll be driving and the car can’t be salvaged.  If you don’t have the appropriate car, reconsider signing up for UberEATS.

How Do You Start The Process Of Becoming An Uber Driver?

If you meet the requirements described above, you shouldn’t have any difficulty getting started.
All you have to do is fill out this application and have your car inspected. Then, you’ll turn in the paperwork to get your background check done. This won’t take long and once you’ve cleared these low hurdles, you will get started by setting your schedule and earning money. In most cases, you should be able to start driving within a week or two (max) of completing your online application.

How to Start Earning Money with Uber

The actual work process is very straight forward. You just open the Uber driver app. Once that’s done, you’ll be connected with the next rider you are closest to.

If you accept the trip, the navigation in the app will direct you to the passenger pick-up location. Then, the app will navigate you to the destination and your work is complete. You don’t need to collect any money as the rider is charged automatically and you’ll get paid via direct deposit every week.

One very cool benefit of this job is that you don’t have to submit a schedule. If you are ready to work, you turn the app on. If you don’t want to work, you shut it off. Simple.

Is Driving For Uber A Good Job?

Driving for Uber can be a great part-time, seasonal or temporary job for some people. This is especially so if you need a flexible work schedule. It’s also a cool way to supplement your income by putting in some extra hours behind the wheel after work or in between class instead of vegetating in front of the TV or computer.

More than 80% of Uber drivers work less than 35 hours a week in their 20 biggest markets and more than half drive between one and 15 hours a week. (Just keep in mind that in order to stay active you have to accept at least 1 trip every 30 days. If not, you’ll have to go through the application all over again.)

If we figure you can make $20 gross on average and it will cost you 30% of that in expenses, your hourly rate should come in around $14 an hour. Having said that, we don’t know yet what your gross will be and we don’t know what your expenses are going to cost you. That said, I’d say, give Uber a try if you are willing to earn $10 to $12 an hour. If not, find something better.

Who Uber Is Great For

If any of the following describes you, Uber is a gig worth trying:

  • You need a flexible schedule.
  • You want to try being self-employed.
  • You want to earn more money.
  • You are retired and while you dig having a few extra shekels in your pocket, you are really interested in meeting new people and staying useful.
  • You are looking for ways to pay off credit cards or other high cost debt.
  • You want to earn money to fund a very specific financial goal.

Of course, as I’ve pointed out, the money issue is tricky. After reading everything I could find on this topic I’ve come to the conclusion that the only way to really know what you’ll earn driving is to give it a try. Having said that, you’ll increase the odds of being successful if you:

  1. Make yourself available during surge periods.
  2. Work in a less-competitive market.
  3. Keep meticulous income and expense records.

Beyond these three tactics, the most profitable Uber hack is to use your time wisely. If you can utilize your downtime for things like studying or doing other work, this will be killer. That’s because you erase downtime from the equation and as a result, your hourly rate goes through the roof.

I started this post by explaining that 40,000 new drivers sign up to become an Uber driver-partner every month. There is a lot of turnover in this business but more than 50% of the drivers who sign on, are still driving a year later.

That tells me that a lot of people think this gig is profitable. Just don’t expect to hit cruising speed right off the bat. If you decide to give this a try, give yourself a few months to learn the ropes.

Once you do, you can make a good income, name your schedule, meet cool people, and have your own business. The thing is, you’ll never have any of this unless you give it a try.

Taxes Are Worse Than You Thought

Taxes Are Worse Than You Thought

“It is a paradoxical truth that tax rates are too high today and tax revenues are too low, and the soundest way to raise the revenues in the long run is to cut the tax rates.” 

– John F. Kennedy (Yes, a Democratic president back in the Camelot days of the early ’60s wanted to slash taxes.)

This week’s post will make half of my readers indignant and the other half feel righteously vindicated in their thinking. I have no idea which half you are in. What is so controversial? Who pays taxes and why they should.

Research indicates that the top 1%/5%/10% are already paying the bulk of the income tax. Research also points out that the progressivity of tax rates, which climb relentlessly upward with income, surprisingly fails at incomes of over $10 million. This is an assumption because at that point capital gains tax and other tax-incentivized income comes into play that is typically not available to those of us with merely mortal incomes.

The next time we have a crisis and Democrats are in control of the White House and Congress (and after almost 50 years of observing political to-ing and fro-ing, I consider that a near certainty), the only alternative will be for the Democrats to introduce and pass some form of a value-added tax, which will not be accompanied by income tax cuts. Income tax cuts for the upper end of the income spectrum is just not on their agenda. They don’t understand the philosophical or economic reasons why that is something that should be done. I’m not asking them to here – that’s a debate for another day. I’m just saying that if Republicans don’t come to the realization of the situation, and introduce a VAT in a manner that they can live with, they’re going to have it shoved down their throats in a far more devastating and complicated manner.

If we don’t change things around then everyone better prepare for a slow recovery, followed closely by the Mother of All Recessions. I’m quite serious about that and will be writing about it over the next few weeks. Meaningless “tax reform,” which only messes around at the edges, will not keep us out of the next recession, which will likely be triggered from Europe.



Why Conferences Don’t Need More CE, They Need Better (Practice Management) Content

Why Conferences Don’t Need More CE, They Need Better (Practice Management) Content

In fact, the irony is that the most common reason financial advisors ask for CFP CE credit from conference sessions is not because it’s hard to get CFP CE credit, or that we need to go to a conference to get it. It’s because a lot of conferences have mediocre sessions… which means if we as advisors are going to attend, at the least we want some CE credit as a consolation prize for the time and dollars spent! And with so many conferences unwilling to invest into paid speakers, and still relying on sponsors to fill their speaking slots – despite the fact that most sponsors have a long history of delivering sales pitches in lieu of real education – it is no surprise that CE is a common demand. If you expect the content to be mediocre, the CE is the only remaining reason to bother showing up!

But when it comes to good content, the value of the content can more than pay for itself, regardless of CE credit. And good content can come in the form of a technical session or practice management. In fact, financially, good practice management content – that provides real takeaways that can be implemented to make meaningful changes in the business – can actually provide a much higher ROI than technical content. And in point of fact, it really is the conferences that spend the most time and effort (and in some cases, hard dollars) on content that are seeing the most growth and financial success!

The caveat when it comes to practice management content, though, is that even the best session isn’t likely going to be useful for all advisors, or even most of them. After all, a great session on selling a firm won’t be valuable to the majority of advisors who currently aren’t looking to sell their firm anytime soon. A great session on technology won’t be valuable the large number of advisors whose platform makes the technology decisions for them. And a great session on marketing won’t be valuable for the large number of paraplanners or associate planners who don’t have business development responsibilities. Which means even the best practice management speaker will rarely draw a large crowd for a practice management session. But that doesn’t mean conferences should avoid this content altogether! Rather, they should be careful about how it is scheduled – put practice management content in breakout time slots, paired with different content for those who won’t find the session relevant, and be cognizant only to put practice management speakers into general sessions if their content is truly relevant to the whole audience!

Ultimately, as CFP and other types of CE becomes more and more commoditized and accessible from many sources at a low cost, the value in attending a conference is not the CE. Advisors may leave audience feedback requesting CE, but that’s not a sign they truly need CE – it’s a sign that the conference needs better content, so the audience isn’t demanding CE as a consolation prize!

Dynamic Programming As A Methodology For Financial Planning Retirement Projections

Dynamic Programming As A Methodology For Financial Planning Retirement Projections

Executive Summary

While most financial planners are familiar with the leading practitioner-based research in retirement planning – for instance, Bill Bengen’s 4% safe withdrawal rate studies – the reality is that economists have actually developed their own research approach to evaluating financial planning trade-offs, including optimal strategies for retirement spending and asset allocation. Notably, though, the two tracks of retirement planning research employ substantively different approaches – where practitioners most commonly “test” a particular retirement plan or strategy to see if it’s sustainable (or not), while economics researchers try to create models that can be optimized. However, the gap between these distinct lines of research and practice are beginning to blur, as practitioner-oriented research becomes more sophisticated, economic research becomes more practical, and computing technology makes it easier than ever to conduct complex analyses.

In this guest post, Derek Tharp – our Research Associate at, and a Ph.D. candidate in the financial planning program at Kansas State University  takes a deeper look at dynamic programming, a economics-based methodology for conducting financial planning retirement projections, that introduces new opportunities beyond traditional financial planning software in optimizing retirement spending and asset allocation, and may be outright superior in projecting and modeling how retirement spending and asset allocation might change over time, based on whatever future market returns turn out to be.

The core of the dynamic programming (also known as dynamic optimization) approach is really just a methodology of solving larger problems by breaking them down into smaller problems. In the context of financial planning and retirement projections, it’s about taking a long term retirement plan, and breaking it down into a series of sequential retirement years, each of which can then be optimized based on what happened (or didn’t happen) in the preceding years. What’s powerful about dynamic programming, though, is its capabilities to model a greater number of retirements that might all vary at the same time; for instance, dynamic programming could allow spending (consumption), asset allocation, investment returns, and longevity to all vary at the same time, and then truly optimize the financial plan across all of those variables at once – rather than the more manual process of testing “a plan” and then repeatedly tweaking it with “What If” scenarios until a client is satisfied with it, as is more common amongst practitioners today.

A key advantage of dynamic optimization is that a single dynamic programming analysis also has the potential to provide guidance about what to do now and in the future in a way that a one-time Monte Carlo projection cannot. Dynamic programming can do this by effectively providing a three-dimensional road map of how over time a retiree might adjust spending, and adapt the allocation of their portfolio, based on the actual investment returns that are experienced in the future. And, by being more responsive to an individual’s consumption preferences and investment returns that are experienced, dynamic programming not only helps guide retirement spending decisions that are better suited to an individual’s unique goals and desires, but it may increase a retiree’s consumption in retirement, as prior research from Gordon Irlam & Joseph Tomlinson has found that dynamic programming can provide significant enhancements in retirement income over traditional rules of thumb utilized by advisors. Financial planners who want to explore dynamic programming further can explore products such as Gordon Irlam’s AACalc or Laurence Kotlikoff’s ESPlanner.

Ultimately, it’s still not clear that there’s one “right” way to do retirement planning. Whether it is Monte Carlo versus historical… goals based versus cash flow based… or dynamic programming versus non-optimizing approaches… all can provide different insights, which in turn can help guide decision for clients given the risks and sheer uncertainty they face in planning for retirement. But in the end, if the whole point of doing financial planning is at least in part to come up with an actual plan for how to handle an uncertain future, dynamic programming provides a unique tool set that isn’t available in today’s traditional financial planning software solutions… at least, not yet!

The Two Tracks Of Retirement Planning Research

Retirement planning research has historically developed along two distinct tracks, which in turn has shaped the kinds of retirement planning strategies and tools that we use today.

Practitioner-Oriented Research On Financial Planning Strategies

Financial planners will likely be most familiar with practitioner-oriented research, particularly given the widely-read Journal of Financial Planning, which is focused on this type of research.

Perhaps the most famous example of this type of practitioner-oriented research is William Bengen’s 4% withdrawal rate study (published in the Journal of Financial Planning in 1994), but practitioner-oriented research would also include the wide range of studies from scholars since Bengen who have examined questions related to how people ought to best plan and save for retirement. Notably, practitioner-oriented research doesn’t actually have to be created by a practitioner (as was the case with Bengen); a key aspect of such research is that generally it is aimed at providing advice regarding how people ought to behave in order to succeed financially. This is what researchers would call a “normative” approach to research, and it is different than a “descriptive” (or “positive”) approach to research, which simply aims to describe reality as it exists today.

It’s easy to understand why practitioners are drawn to normative research, as the job of a planner is to help clients make decisions. In this context, how people do behave matters much less than how people ought to behave. While the former might help give planners foresight of problems their clients may encounter, it’s the latter that planners spend their time advising clients on. In other words, given that the purpose of financial planning is to help people make good financial decisions, it makes sense that practitioners gravitate towards research which can help facilitate that purpose.

Another notable feature of practitioner-oriented research is that it tends to be practical. Bengen’s 4% rule is useful because it provides answers that can be directly applied to client questions. Practitioner-oriented research tends to lead to either rules of thumb of what people should try to do or achieve, and/or straightforward frameworks for making decisions based on individual goals, circumstances, and trade-offs. As a result, it also tends to be more of a “satisficing” than “optimizing” approach to making decisions.

For instance, whether based on straight-line projections or Monte Carlo analysis, most planners simply help clients evaluate different alternatives until they reach a solution that satisfies their needs. Planners typically don’t run thousands of different scenarios adjusting a large number of variables until they find the one single scenario that provides the “best” outcome available, as might be done under a truly “optimizing” approach (though, it’s reasonable to question how effectively optimization can generally be done in the first place, and to what extent greater precision would actually change the outcome).

Economic Research On Financial Planning Strategies

The second broad branch of financial planning and retirement research comes from economists, who view it as a study of consumption across the life cycle. In contrast to practitioner-oriented research, which primarily focuses on how people ought to behave, economists have historically focused both on how people ought to behave and how they actually do behave.

Some notable developments in the history of economic thought related to retirement planning in particular include Keynes’ (1936) marginal propensity to consume, Duesenberry’s relative income hypothesis (1949), Modigiliani & Brumberg’s (early 1950s) life cycle hypothesis, Freidman’s (1957) permanent income hypothesis, and Shefrin & Thaler’s (1988) behavioral life-cycle hypothesis.

One key component of these theories, at least since Modigiliani & Brumberg, is the idea that people seek to engage in consumption smoothing—i.e., borrowing, saving, and “dissaving” (i.e., spending) across the life cycle in an effort to stabilize their level of consumption throughout their lifetimes.

This approach relies on the economic concept of utility (i.e., satisfaction received from consumption) and individuals are said to have some type of “utility function” which defines their consumption preferences. Models can vary significantly in their complexity and design, but armed with a mathematical representation of how individuals are assumed to rank consumption preferences (quantifying the benefit of spending more versus less, now versus later, etc.), economists can then seek to find conditions which maximize utility and derive conclusions about how consumption behaviors should change as a result.

Dynamic Programming: Where Two Paths Meet?

While both economic and practitioner-oriented retirement research have developed mostly independent of one another, one promising characteristic of dynamic programming is that it provides an avenue to begin to potentially merge these distinct fields of study. Dynamic programming is practical enough that it can be used by practitioners to help clients solve real-world problems, but it is also robust enough to incorporate insights and methods more commonly used by economists – particularly the optimization of consumption and asset allocation decisions across the life cycle.

What Is Dynamic Programming?

To understand what dynamic programming is, it may be helpful to first explore what dynamic programming is not.

Consider straight line projections and Monte Carlo analysis, which are two of the retirement planning methodologies most familiar to financial planners currently. Under straight line projections, every input in a plan is assigned a specific value. For instance, a retiree may be assumed to live 30 years in retirement, hold a 60/40 portfolio, earn 6% per year, spend $50,000 per year, and increase their spending annually with inflation at a rate of 3%. Of course, straight-line projections can be more complex, but the key is that there is no variability within the assumptions. Planners may choose to look at several different scenarios—perhaps comparing the results of a less risky portfolio earning a lower return or prolonging retirement for 35 years instead of 30—but in order to do so, a new straight line projection must be run.

Monte Carlo analyses are mostly the same but introduce the potential for variability. Most commonly, this variability will exist among investment returns. For instance, instead of a 60/40 portfolio earning a constant 6% per year, returns may be assumed to have a mean of 6% and a standard deviation of 10%. Allowing variation in investment returns provides a more realistic range of investment outcomes that a retiree may experience, but the rest of the assumptions are still static. A planner or retiree may again adjust the plan to analyze additional scenarios, but the usual process is more one of satisficing rather than optimizing—i.e., adjustments are made until the retiree is satisfied with the results, rather than truly optimizing across a range of variables.

Understanding Dynamic Programming

Dynamic programming (also known as dynamic optimization) has many applications and is really just a method of solving larger problems by breaking them down into smaller problems. In a 2014 article in The Journal of Retirement, Gordon Irlam and Joesph Tomlinson provide an overview of how dynamic programming can be applied to retirement income research.

From a financial planning perspective, dynamic programming introduces variability to a greater number of planning assumptions, while still allowing (mathematically) for quickly finding optimal solutions based on that given set of assumptions.

For instance, dynamic programming could allow spending (consumption), asset allocation, investment returns, and longevity all to vary at the same time. Adjustments to each could be tested in various combinations, effectively providing a “map” of optimal paths of spending and asset allocation, given the actual investment performance and longevity a retiree experiences, rather than simply testing a particular spending and asset allocation strategy against certain investment and longevity assumptions to “see if the plan works” (and manually change the assumptions if it doesn’t).

Consumption Risk Aversion (Vs Portfolio Risk Tolerance)

Risk aversion is an important concept for understanding the role utility functions play within dynamic programming analysis. While personal and consumer finance researchers often consider financial risk tolerance (i.e., the willingness to tolerate uncertainty) as the theoretical opposite of financial risk aversion (i.e., the unwillingness to tolerate uncertainty) (Grable, 2008), Irlam & Tomlinson’s (2014) overview of dynamic programming views these concepts differently. Specifically, risk aversion refers to the willingness to tolerate fluctuations in consumption whereas risk tolerance refers to the willingness to tolerate downside portfolio loss potential.

For instance, suppose an individual has won a unique lottery where they have a 50/50 chance of receiving either $10,000 or $20,000 annually for the rest of their life. We can assess their consumption risk aversion based on what amount of guaranteed income the individual would accept in lieu of this uncertain proposition.

From a purely expected value perspective, this proposition is worth $15,000 per year (as 50% of the time you get $10,000 and 50% you get $20,000), and an individual who would accept $15,000 in lieu of the risky alternative would be said to be risk neutral. However, most people are assumed to be risk averse, which means we will pay a premium for certainty (i.e., most people will accept some guaranteed number less than $15,000). An individual who is risk averse might accept just $13,000/year if it was guaranteed, rather than having the possibility of receiving $20,000/year but facing the risk of getting only $10,000; by contrast, a less-risk-averse person might still prefer the gamble unless the guaranteed income was at least $14,000/year.

Notably, this is not the same trade-off as portfolio risk tolerance. An individual may have both a high ability to tolerate portfolio risk (high portfolio risk tolerance) and a strong preference for consumption certainty (high consumption risk aversion). Or, viewed another way, just because an investor can maintain their composure and mental state in the face of a high risk of portfolio loss, doesn’t mean that person actually enjoys or prefers consumption uncertainty (and thus, might still choose a guaranteed consumption amount even though they’re willing to tolerate portfolio uncertainty).

While searching for optimal solutions, dynamic programming is primarily concerned with consumption risk aversion, though restrictions could be added to a model to account for portfolio risk tolerance as well (e.g., even if a 100% equity allocation would optimize an individual’s consumption utility function, possible solutions could be bounded to only include those up to 70% in equities).

A Simple Dynamic Programming Example

(Note: The following example is overly simplified and based on Irlam & Tomlinson’s methodology laid out in Retirement Income Research: What Can We Learn From Economics? Irlam’s AACalc software is available for free online and can handle more complex and realistic scenarios.)

As a simplified example to illustrate dynamic programming, suppose John is 70 and knows he will live exactly 5 more years. He’ll be in great health this entire time, but he will not live longer. John receives $15,000 in Social Security income and has a $250,000 Roth IRA with no other assets or liabilities. John is trying to decide how his portfolio should be invested over time.

Further, suppose that John has a moderate level of consumption risk aversion. As a result, dynamic programming might generate an asset allocation map that looks like this:

Sample Dynamic Programming Asset Allocation Map In Retirement

These results show that John’s optimal asset allocation may actually change over time, depending on how his portfolio is performing along the way. The higher his portfolio grows, the smaller the percentage of stocks that he would need to support his retirement goal. Conversely, the lower his portfolio declines—making his total consumption more dependent on Social Security—the more attractive it becomes to place all of his portfolio in stocks with the hopes of catching a bull market. The key point: with dynamic programming it’s not simply a matter of projecting a range of returns around an initial portfolio allocation and selecting the allocation which works “best”. Instead, dynamic programming assumes that the portfolio can and would be altered each year — adapting to what has actually happened in the plan up to that point.

Technically, though, the way this map is determined by a dynamic programming analysis is actually to start in the last year of John’s life and then work backward. Given John’s utility function, the program evaluates all possible combinations of consumption and asset allocation at a particular asset level, and then determines the optimal allocation which is indicated in each coordinate of the chart (e.g., 40% equity with a $500,000 portfolio at age 74). After optimizing across all asset levels at age 74, the program continues to solve backward by optimizing values at age 73.

At this point, you can probably see why dynamic programming requires so much computing power – particularly when evaluating longer time horizons and accounting for more granular differences in asset levels, consumption, and asset allocation. With multiple variables over multiple years (or decades), the number of different combinations to test grows exponentially. In practice, different mathematical algorithms can be used to generate results quicker than literally running every single combination of scenarios, but there is still a lot of computation required to generate results.

Further, the asset allocation map generated above is only part of the results generated by a dynamic programming analysis. In addition to optimal asset allocations, dynamic programming generates optimal consumption paths as well. Assuming that an individual has no bequest motives (i.e., they derive no utility from leaving assets to heirs), a greater proportion of remaining wealth would typically be consumed each year until ultimately consuming 100% of remaining wealth in the final year of life (at least if you assume this final year is known).

Of course, rarely do we have reasonable estimates of how much longer we will live (and if we do, it’s usually over a short time horizon), but the use of stochastic (i.e., random) dynamic programming methods do provide the possibility of varying time horizons as well. In other words, one assumption might be to simply assume that in any particular year, the plan is to spend over the individual’s remaining life expectancy, recognizing that the life expectancy time horizon itself will change with each additional year of survival. Furthermore, rather than simply smoothing consumption to be level across time, more realistic modifications—such as the assumption of “impatience” (i.e., that future utility is discounted more than present utility… possibly resulting in declining spending throughout retirement) or the addition of known cash flows to particular years (e.g., planned trips or other goals)—can be utilized to more accurately model utility maximizing consumption paths throughout retirement.

Returning to our example of John’s retirement, we can consider some hypothetical consumption paths based on his particular utility function (i.e., how John would get the most satisfaction from varying levels of consumption in retirement).

Hypotehtical Consumption Paths In A Dynamic Programming Retirement Projection

Under each scenario, John starts out consuming $70,000, which includes $15,000 of Social Security income adjusted annually for 3% inflation. Recall that John has a $250,000 Roth IRA, which, based on the asset allocation map shown earlier, suggests he should utilize a 60% equity portfolio at age 70. (Note: To simplify this illustration even further, only portfolio consumption [starting at $55,000 per year] is considered in the charts above and below.)

It’s important to note that there’s more going on here than can be captured in either the asset allocation map or by the consumption spending paths independently. Because dynamic programming can adjust both consumption and asset allocation based on the conditions actually experienced, you can envision each point on the map as having both an asset allocation and a consumption amount associated with it. It is generally easier to think of these in isolation from one another, but the reality is that they are intertwined, in what would look more like a 3-dimensional roadmap.

For purposes of simplification, assume all straight-line returns, with a low returns scenario providing 1% annual returns over this five-year period, an average returns scenario providing a 6% annual return, and a high returns scenario providing 10% annual returns. If this were the case, then John would experience the following:

Dynamic Programming Asset Allocations & Consumption Levels With Varying Return Results

Under the 6% return scenario, at age 71, John would have a Roth IRA worth just shy of $207,000. Based on the asset allocation map (shown earlier), this suggests John would maintain a 60% equity portfolio. By age 72, John’s Roth IRA would have roughly $159,000, indicating he would still maintain a 60% equity portfolio. But consider what would have happened if John actually experienced the low returns scenario (1% annual returns). Under this scenario, not only would have John decreased his consumption by roughly $1,000 at age 71, but at age 72, his portfolio would also only be worth roughly $144,000. Based on the asset allocation map (see example referenced earlier), this would suggest that John actually increases his equity allocation to 70%. While these numbers are purely hypothetical and for illustration purposes only, the point is that the dynamic programming approach is providing a roadmap to how both spending and asset allocation might change, based on what future returns turn out to be. In this hypothetical scenario, given John’s utility function, his guaranteed Social Security income is giving him room to make his portfolio more aggressive in the bad return scenario with the hopes that it rebounds (and knowing that if it doesn’t, Social Security is still making up the majority of his income anyways). Other retirees might have different utility functions that would weigh these trade-offs differently, but the key point is that dynamic programming is providing different courses of action based on the conditions ultimately experienced.

We could then continue this process all the way through John’s life, utilizing his experienced investment returns and consumption to identify the potential paths for his ideal consumption and asset allocation in any subsequent year. This “mapping” process that can be provided by dynamic programming is one of the core benefits of the approach.

Notably, even with a dynamic programming analysis that is designed to account for adjustments over time, some updates may still be appealing. In some cases, that may be because the original projection used simplifying assumptions (e.g., used a fixed retirement time horizon rather than dynamically projecting mortality), such that the plan must be periodically updated for new assumptions. Or, alternatively, the key inputs could vary over time, beyond the scope of what was dynamically programmed. For example, a retiree may receive a cancer diagnosis that materially shifts their mortality curve more than just the assumed changes for getting older. Or it may be the case that the retiree exhibits “time-varying risk aversion” (i.e., their portfolio risk tolerance changes materially over time) as has been investigated by Blanchett, Finke, and Guillemette (2016). As a result, Irlam & Tomlinson (2014) do note the importance of ideally updating dynamic programming projections just as would be done with a traditional financial plan.

Nonetheless, the key point remains that traditional Monte Carlo analysis happens at a single point in time and typically assumes the retiree charges forward blindly with their original spending and asset allocation, regardless of the scenario experienced, while dynamic programming not only assumes adjustments will be made along the way, but it tells us (based on optimization) what those adjustments would need to be as well!

Why Dynamic Programming Matters

As we’ve seen above, one of the main benefits of dynamic programming is that it is truly an optimizing approach rather than a mere satisficing approach as most planning is today. A single dynamic programming analysis also has the potential to provide guidance about what to do now and in the future in a way that a one-time Monte Carlo plan cannot. Assuming no material changes in a retiree’s life expectancy or utility curve, the retiree could identify the path they’ve encountered and make the appropriate adjustments to their consumption and asset allocation, all from the original plan projection.

Dynamic programming also leads to some advice that is significantly different than traditional rules of thumb and ongoing advisor guidance. For instance, while strategies like taking an inflation-adjusted 4% distribution do serve as a means to smoothing consumption (something generally assumed to be desirable under economic models), it’s possible they smooth consumption too much. This is particularly true in light of two important observations: (1) consumption may be more valuable earlier in retirement rather than later, and (2) many retirees just want to spend their money (not too quickly, but enough that they don’t leave over a giant bequest that has no value/utility to them).

The first observation—that consumption utility is not equal across all points in time—implicitly acknowledges considerations such as the fact that while people are young and healthy (i.e., in their “go-go” years of retirement) consumption may be able to buy more satisfaction than it does when they are aging and frail in the “no-go” years of retirement.

The Three Phases Of Retirement Spending Behaviors

There are other rational reasons for retiree “impatience” as well, particularly given the fact that our lives can always come to an end sooner than we wish. Even if we assume an individual maintains consistent health throughout retirement and an adequate asset base to hedge against the opposite concern (i.e., that we live longer than we expect), it may still make sense to maintain a downward sloping consumption path (in real dollars) throughout retirement. Barring scenarios that involve cryogenically freezing a body or other attempts to attain life after death, it is simply a mathematical fact that the probability we are alive one year from now is greater than the probability that we are alive two years from now. Thus, there’s a rational case for being present biased even when adequately accounting for longevity risk. Of course, we could just incorporate decreasing spending into a Monte Carlo analysis, but this may provide a consumption path that is too rigid relative to the reality experienced, whereas dynamic programming (presuming the assumptions remain accurate) provides guidance on how consumption should change based on the investment returns experienced.

Another strength of dynamic programming is that it can more adequately address bequest utility (i.e., our desire or willingness to leave over unused principal to the next generation). Given the conservativeness that is inherently built into retirement distribution strategies such as the 4% safe withdrawal rate strategy, retirees blindly adhering to this rule may wind up with significantly more bequest than they desire. One potential limitation of traditional safe withdrawal rate methodologies like this is that they test against historically worst case scenarios. This may be the appropriate benchmark to test against given a retiree’s risk profile (or perhaps not even conservative enough), but this approach potentially ignores valuable insight as a retiree progresses through retirement.

As an example, suppose a retiree has made it ten years into retirement, avoided catastrophic scenarios, and market valuations provide no reason to be particularly concerned. If this individual sticks with a consistent inflation-adjusted 4% distribution from their time of retirement, they are very likely going to leave a substantial estate. Once they survived the period of greatest sequence of return risk, they are likely on a path that could have supported a greater than 4% withdrawal rate. If this individual has high bequest utility (i.e., they want to leave a big inheritance behind for heirs), perhaps no adjustment is needed, and they can simply feel more confident they will leave a larger estate than they might have anticipated entering retirement. However, if this individual has low (or no) bequest utility and simply wants to spend their money to the extent possible in retirement, then a method that doesn’t adjust spending in light of their low bequest utility and experienced investment returns could unnecessarily leave a substantial (and suboptimal) amount of assets unspent. Dynamic programming better illustrates how these adjustments could be made, both upfront and on an ongoing basis.

To illustrate the potential differences between industry rules of thumb for determining withdrawal and asset allocation strategies and dynamic programming recommendations, Irlam & Tomlinson (2014) found that when comparing stochastic dynamic programming (SDP) versus common industry practices, SDP provided a 38% enhancement in initial retirement portfolio income relative to a 60/40 fixed allocation throughout retirement utilizing a 4% withdrawal rate strategy. Interestingly, utilizing SDP to determine both withdrawal rate and asset allocation only provided about 3% higher initial retirement portfolio income when compared to a 90/10 fixed allocation with a 1/life withdrawal rate strategy. However, because spending paths are not consistent between variable spending strategies, initial withdrawal rates don’t necessarily tell the full story. Additionally, many advisors might be wary of investing clients as aggressively as the optimal strategy recommended by SDP, but advisors could constrain the model to lower equity exposures, if necessary to accommodate client portfolio risk tolerance.

Initial Retirement Spending Levels Dynamic Programming Vs Other Retirement Strategies

Irlam & Tomlinson (2014) note that one of the reasons for their findings of SDP outperforming rules of thumb, is that many rules of thumb continue to recommend declining equity allocations throughout retirement, even though Samuelson and Merton both found that stable allocations provide higher lifetime utility than declining allocations as far back as 1969. While this highlights another example of the disconnect between the two separate tracks of retirement planning research, interestingly, these same findings have been found in practitioner-oriented research as well. Bengen noted this in his 1996 research and Pfau & Kitces (2014) found similar deficiencies in declining equity glidepaths — yet there hasn’t been much notable change in industry practices. However, Blanchett (2015) did find that a decreasing glidepath resulted in more utility-adjusted overall potential wealth compared to a constant glidepath, so perhaps there is some wisdom embedded within industry practices that hasn’t been fully borne out in prior research, but Blanchett’s study also acknowledged that randomization over a wider number of variables and greater consideration of a specific client’s circumstances and preferences can be beneficial – and dynamic programming provides improvements in both of these areas.

Another strength of SDP models is the potential to take variable distributions during times of poor market conditions. This allows for sustaining higher equity allocations in retirement than may be possible if distributions remain consistent regardless of market conditions. In other words, if retirees are willing and able to adjust their spending to volatile market conditions as a way to manage sequence of return risk, it may be feasible to maintain more volatility in the portfolio itself (which in turn enhances long-term returns and allows for improved retirement spending in the long run as well).

Limitations Of Dynamic Programming

While dynamic programming’s biggest strength is the ability to utilize some elegant models and complex math in order to optimize both asset allocation and distributions, arguably, this could also be one of dynamic programming’s biggest weakness. The insights of dynamic programming are only valuable so long as they reflect reality. If a utility function doesn’t actually capture a retiree’s utility or distributions aren’t actually as flexible as assumed, then the optimization under dynamic programming may not actually be optimizing utility and might even be suggesting actions that would decrease satisfaction in retirement.

And, unfortunately, unlike the inputs into traditional financial plans that tend to be fairly straightforward and easy to comprehend, utility functions and risk aversion coefficients are far more nebulous concepts to most people. It’s hard enough for us to measure abstract concepts like risk tolerance, much less the even-more-complex trade-offs inherent in defining a utility function. Notably, this isn’t an inherent limitation of dynamic programming itself, but it is a limitation of the ability to effectively utilize dynamic programming. In theory, underlying utility functions are only limited by our ability to conceive and develop them, but such an exercise may be a difficult task for most people without a graduate education in economics or mathematics. However, it is also possible that the continued design of new “assessment” tools will allow advisors to better understand how clients feel about various spending and uncertainty trade-offs.

Fortunately, this is one way in which further merging of the currently distinct tracks of practitioner-oriented and economic research can help advisors and researchers collaborate to come up with better solutions. Practitioners can help give insight into what is practical information to act on when working with retirees, while academics can continue to develop better measures of risk tolerance, assessment tools to determine utility, and economic models that more accurately align with retiree archetypes.

Advisors who are interested in utilizing or learning more about dynamic programming can check out Gordon Irlam’s AACalc (free) or Laurence Kotlikoff’s ESPlanner ($950 first year subscription and $750 annual renewal thereafter), which are two retirement planning projection tools that utilize dynamic programming. Both provide some basic utility assumptions that can be used to estimate a retiree’s willingness to engage in trade-offs, with some ability to adjust for their overall aversion to risk and uncertainty.

Like any other planning methodology, dynamic programming has its advantages and disadvantages, though the advantages or significant enough that it will likely play an increasingly large role as planners become more familiar and comfortable with the approach. In particular, the appeal of dynamic programming is the ability to optimize and to illustrate to the client, up front, the benefits of making dynamic adjustments to spending and asset allocation, rather than simply taking a wait-and-see monitoring approach. As a result, dynamic programming can provide a richer and more holistic perspective on how an uncertain future at least might unfold, just as the range of potential outcomes in a Monte Carlo projection provides a richer perspective than just a straight-line projection (and thus why it came into common use).

Ultimately, there’s no one “right” way to do retirement planning. Whether it is Monte Carlo versus historical analysis… goals based versus cash flow based planning… or dynamic programming versus non-optimizing approaches… all will give us different insights which can help guide decision making under risk and uncertainty. But, in the end, if our goal in doing financial planning is at least in part to come up with an actual plan for how to handle an uncertain future, dynamic programming provides some unique functionality that isn’t currently available in today’s non-optimizing financial planning software solutions.

2 New Alternative ETFs Seek Absolute Returns In Any Market

2 New Alternative ETFs Seek Absolute Returns In Any Market

The premise of positive returns in any market is an alluring proposition for risk adverse investors.  These types of alternative strategies were once the realm of sophisticated hedge funds and institutional portfolios.  However, they are now starting to make their way into the accounts of mainstream investors via exchange-traded funds (ETFs).

Alternative strategies are generally given more flexibility than a traditional passive index tracking a basket of stocks or bonds.  They may have the capability to own futures contracts, short positions, currency pairs, or even volatility-linked products. Put simply, these “go anywhere, do anything” investment styles have the freedom to select virtually asset classes they feel are most appropriate for the current market environment.