Tag: Personal finance

Tax loss Harvesting: How to Reap the Most Rewards

Tax loss harvesting is something I tend to think about after a strong year of equity returns. I find myself asking if I should reduce risk in some names or at least re-balance the portfolio. The problem is that this can create significant capital gains.

That said, if you are like me, you probably have some investments that did considerably well this year and some that have done not so well (they generated losses). We can use those poorer performing investments to help offset our capital gains, reduce our taxable income, and even compound our earnings at a better rate, all things being equal.

My goal of this post to provide examples of tax loss harvesting scenarios that will allow investors to not only understand the concept better, but also save money.

The basics are simple – an investor typically sells a stock or fund that has losses to offset another investment she is selling that will result in a gain. Let’s lay down the tax rules first so we’re all on the same page:

  • The long-term capital gain/loss tax rate is typically 15%. However, if you are in the 10-12% tax bracket, your capital gains rate is 0%, but if you are in the 37% bracket, it is taxed at 20%. The analysis herein will assume most people fall in the 15% bracket.
  • The short-term capital gain/loss is taxed at your income tax rate. Short-term capital gains can therefore be quite expensive. If you think it is fine to hold out for a year and a day, it might be worth it to do so. However, never let the tax tail wag the dog – if an investment could plummet, its best to take your winnings an move on.

An important thing to lay out in the beginning before we get into examples: short-term capital losses are worth more because they are taxed at the higher rate. That means they are best to apply to your short-term gains or long-term gains, rather than, for example, applying a long-term loss that is taxed at 15% to a short-term gain that could be taxed at 37%.


Example #1: Using capital losses to offset gains

Simple example. You have a $10,000 gain on ABC stock and also a $10,000 loss on XYZ stock. You sell ABC and XYZ to net each other out. Assuming a 15% tax rate, this saved the investor $1,500 (15% x $10k gain). Further, let’s say you take that saved income and earn 5% per year on it over 5 years (i.e. opportunity cost). That means you would also have an extra $414 after 5 years.

Example #2: Repurchasing the sold shares & avoiding wash sales

If we build on Example #1, we should discuss the “wash-sale rule.” This rule prevents someone from selling a stock for a loss for taxes and then immediately buying it back. The IRS requires you to wait 30 days before you can buy it back. 

Let’s say the price of XYZ stock is still $90 after we wait 31 days, so we buy it back at the same price we sold. Over the next 5 years, our analysis was correct and it appreciates to $150.

Good outcome, right? We have a $50k gain on our investment, less what we owe in taxes ($7.5k), but also have what we saved in taxes from Example 1.

So are we in a better position? What if we didn’t sell XYZ in the first place?

We would have owed $1,500 in taxes in Example 1 and would not have benefited from the $414 time value of money.

As you can see below, it paid off to take the loss, despite having a bigger taxable gain in 5 years from the sale date.

That said, the total amount saved isn’t really that great. Don’t get me wrong, I would take an extra $414 dollars if it fell from the sky, but there must be a way to improve these results.

Avoiding the wash sale rule

One type of loss that is harder to measure is the loss associated with being out of the market as you wait to buy the security back. 

However, you can buy a fund or security that achieves the same goal of that security as long as it is not “substantially identical” to the existing security. For example, you could sell the S&P500 ETF and buy an actively managed large-cap fund and face no issues.

Therefore, you can still be in the market and benefit while you wait. 

Example #3: Think Short Term

While I am sure most people here view themselves as somewhat long-term investors, it is important to think short-term when it comes to tax losses. 

The tax code says that long-term losses first offset long-term gains and short-term losses offset short-term gains. Anything left over will go to offset other gains. 

The LEAST tax efficient thing to do would be to use short-term losses to offset long-term gains. That is because the difference in tax rates can be around 15 percentage points.

In other words, I could have used my short-term losses to offset a short-term gain that I owe tax on at a 35% rate. But instead I am using them to offset something I owe tax on at 15% rate.  

The table below attempts to show this. I sell AAA for $10k gain and BBB for a $10k loss, saving myself from $2k in taxes. However, BBB was worth $3,500 in taxes, so I missed $1,500 dollars in tax savings. 

What asset allocation performed best over time?

“Past performance is not indicative of future results” you say as you read this post. But it can be a tool for analyzing what asset allocation performed the best.

The markets are particularly tough to apply history to, though, because of the wide amount of factors involved. Interest rates, valuations, and broad based sentiment are very hard to control for. Imagine looking at the performance of the market in 1938, but not factoring some how for investor sentiment in a world about to enter WWII.

However, to think we can’t learn anything from studying history is non-sense.

Today, I’ll be taking a look at what performed best over recent cycles in the equity market and walking through some of the take-aways I have. Feel free to share your results as well in the comments! I’ll be using http://www.portfoliovisualizer.com which has some great tools.


My father is currently entering retirement and asked for some advice on how to manage his portfolio. As a retiree, he needs growth, but also needs to weather the downturns a bit better than the normal investor.

As such, I thought I’d take a look and see, “What asset allocation of sectors performed best over the past 2-3 business cycles?

This brings up the concept that I call, “Win by not losing“. Let me explain. A lot of people enter the market thinking that they need to buy high growth stocks and want to ride the tidal wave in order to get rich. And quick.

But as we saw from the tech bubble, that can quickly go against you. While you may make a lot of money early on, if your portfolio declines by 50%, you need to go up 100% to be back to breakeven after that.

I don’t believe in timing the markets, but I do believe a good asset allocation can help performance in a variety of markets.


Alright, let’s head over to portfolio visualizer and I am going to go to their portfolio optimization section. Here, we can backtest how different allocations of sectors would have performed over different time periods. The great thing about this tool is we can also select what we want to optimize the asset allocation by.

Screenshot 2019-02-16 at 4.34.09 PM

We need to select funds that capture each sector of the market. Unfortunately, ETFs haven’t actually been mainstream for that long, so funding sector ETFs that go back to 1985 is impossible. I can go back to 1999 though by selecting these funds:

  • XLV – Healthcare
  • XLF – Financials
  • XLE – Energy
  • XLU – Utilities
  • XLB – Materials
  • XLI – Industrials
  • XLY – Consumer Discretionary
  • XLP – Consumer Staples
  • QQQ – Tech
  • FREEZ – Real estate (no ETFs went back this far, so am using a fund)
  • FSTCX – Telecom (No ETFs with enough history. IYZ goes back to June 2000)
  • SGGDX – Gold (again, not ETFs)

This gets us enough history to go back to January 1999. That’s important because we can capture the end of the tech bubble, the early 2000’s recession, the recovery over the mid-2000s, the boom up until 2007, the great financial crisis, and the bull market since then (while also capturing all the wobbles in between including the european debt crisis fears, the interest rate fears, the commodity collapse, and so on). Would I like more history? Of course, but this will make do.

I will first equal weight all 12 of these funds (e.g. 8.33% each) and seek to find the “maximum return with the minimum volatility”. I will set the maximum volatility at 15% also make it so each fund is a minimum of 2.5% and a maximum of 25% (except gold, I will cap at 15% for practical purposes).

Realistically, we need a parameter like this because we can’t know if energy for example is going to tank in 2015/2016 after being super stable from 2011-2014. Housing during the 2000s too is another example. As such, we have to allow for some diversification.

I am not including global ex-US funds, but you can if you’d like. I may do this as a follow up post.


January 1999 – January 2019

Alright, in your mind, how do you think this asset allocation will perform against the S&P 500? For context, here is the current breakdown of sectors:

Screenshot 2019-02-16 at 4.58.25 PM

How does our equal-weight asset allocation stand a chance without the massive secular growth story of tech?

Well, lets take a look:

Screenshot 2019-02-16 at 5.05.38 PM

Wow… the equal weight portfolio crushed the S&P… Investing $10k in the S&P500 would have turned into $30k, but the equal weight was nearly $45k. But the red line crushed both. It ended with $54k in value.

What in the world did it allocate to?? I have to admit, I would not have guessed this:

  • Real Estate – 25%
  • Consumer Discretionary – 25%
  • Tech – 15%
  • Gold – 15%
  • Everything else – 2.5%

When looking at the annual returns for each asset class it starts to make sense. When tech was taking a beating in 2000 and down 36%, real estate was up 30%, so early on this diversifying factor helped. In 2008, people jumped to buy gold in panic, which also helped. I am a bit surprised the healthcare, staples and utilities were not weighted hire for their defensiveness qualities.

Screenshot 2019-02-16 at 5.17.22 PM

Let’s change the time series.


January 2005 – January 2019

 Why this time frame? Because it feels relevant. The fed is raising rates (as it was then) and it is closer to being late in the cycle than being in the early part of the cycle (as it was then, thanks to my hindsight vision).

Again, I just want you to try to guess what would have outperformed against our equal weight portfolio. Spoiler alert: it crushed us.

Screenshot 2019-02-16 at 5.22.32 PM.png

The equal weight performed on par with the S&P, but the weightings of this portfolio really separated from the pack in around 2014 or so.

Screenshot 2019-02-16 at 5.24.33 PM.png

Ah, now it makes sense. Tech comes into the fold and starts crushing the rest of the market. An overweight in this sector definitely added to the out-performance of late (FANG).

I also think this might be impacting consumer discretionary to a certain degree given Amazon’s weighting in that index (it currently sits at ~21% of the XLY index weighting!). Healthcare performed well in 2008 and then experienced strong growth since then.

Here’s an interesting question… How would our top picks from the last backtesting performed in this back testing? Well, when you take out the performance of real estate early on from the year 2000, it puts it on track with the S&P500 (though it did perform well early on in the cycle).

Screenshot 2019-02-16 at 5.35.31 PM.png


Let’s take the gloves off. Allow me now to show the results of an asset allocation that may surprise you, but will hopefully tie things together. I want to allocate my portfolio in a way that I “win by not losing”. Here’s my allocation selection:

  • 25.0% Consumer Staples
  • 22.5% Healthcare
  • 15.0% Utilities
  • 10.0% Tech
  • 10.0% Gold
  • 2.5% Everything Else

This is called “Portfolio 1” in the chart below and “Portfolio 2” is an equal weight of the sectors. I’ve selected re-balancing annually to keep the weights in check.

Over a long period of time, this crushes the S&P, which we’ll look at. It doesn’t seem to make much difference vs. an equal weight tough.

Screenshot 2019-02-18 at 12.48.23 PM.png

One stark difference though is that portfolio 1’s worst year was much better than the other two. So portfolio 1’s asset allocation protects from the downside. 

Screenshot 2019-02-18 at 12.50.01 PM.png

So let’s look how this performed starting from 2005 instead of 1999.

Here the performance difference is much more stark and you can start to visually see why. Take a look back at the most recent sell off in Q4’2018. Portfolio 1 barely ticked down while the equal weighted and S&P500 suffered greater losses.

Screenshot 2019-02-18 at 12.52.32 PM

Last but not least, lets say again you think we are late in the cycle, but want to stay invested to meet certain fiscal goals. The analogue here is 2005 – late in the cycle and a recession looming a couple years out. Let’s see how stark the performance is up close, from beginning of 2005 to the end of 2012.

Screenshot 2019-02-18 at 1.00.07 PM

This is the most important slide to me. To me, it highlights that someone who played good defense ended up recouping their losses in the crises much faster than the S&P500 (which still did not make it back to its high watermark over this period).


Obviously, some of these sectors such as Utilities and Consumer Staples have benefited from lower interest rates over the past 30 years and its something to consider for asset allocation going forward. However, in a year when rates moved up considerably, these sectors still provided cover in 2018 (outperforming the S&P’s year by 110bps and suffering only a 7% drawdown compared to the 13.5% drawdown from Oct to December 2018 suffered by the S&P.

I’m going to end with a cliche and say sometimes, the tortoise (consumer staples) beats the hare (insert the “it” growth sector here). And maybe asset allocation should be set up that way too.

Are you speculating or investing?

I think when most people begin to invest in stocks, they buy companies that make a product that they really like or that they think will be beneficiaries of major trends. This seems completely reasonable, but is simple speculation until cash flow enters the equation. Before I get into how I approach investing in companies, I’ll first break down the significant differences between the two, as I think it’s an important distinction and provides a valuable backdrop before we put money to work.

Back in the 1990’s, the commercial internet had just dawned. What was clear was that it would change the way we live forever; what was not clear was how. One new service was going to offer grocery delivery ordered online. It would deliver groceries to customers during a 30-minute period of their choosing. This presumably would change the way we shop for groceries forever (sound familiar?). Their plan was simple; they would raise cash from an IPO to fund investments in warehouses and expand to new cities. Clearly, THIS was the future. The company raised $375MM in an IPO to fund expansion and the company at peak was valued at $1.2BN. Moreover, they had an uber experienced and already successful founder, Louis Borders (of Borders bookstore fame), in addition to top-of-the-line VC money and guidance.

The company was growing too. It achieved 750,000 users, had 3,500 employees, and for the 3 months ended Dec-31-2000, the company did $84MM of revenue compared to $9MM in the 3 month period in the prior year (+833%!). However, the company’s losses expanded to $173MM from $49MM (and cash flow was a similar story) as it tried to expand quickly and needed to invest back in the business. In the end, the company was running out of cash, capital dried up (the tech bubble burst, closing the public equity markets), and it declared bankruptcy in 2001. The name of this company was Webvan if you want to study it further.

Ok, so how is that different than investing? Both investing and speculation involve taking risk. As Ben Graham said, investing inevitably has “substantial possibilities of both profit and loss.” However, in speculation the risk vs. reward is often miscalculated. You believe, since the price of something has gone up in the past, you can anticipate these movements and gain profitably from them. And maybe this strategy works for a little while, but see how similar that sounds to a roulette wheel? “It hit black 3 times in a row… it must be red next time.”

Think about today’s market. Infrastructure spending, tax reform, the next tech event… nothing has actually even been laid out yet, which has allowed investors to write their own narrative. This has led to speculation and driving stocks higher.  

When investing, we must take a calculated, fundamental approach to what we are buying, while also being realistic. We are buying an asset that we want to produce cash flows in the future to grow our capital or pay us back. However, we can’t pay any price for it if we want our capital to appreciate at a fast rate – which should be our goal! That philosophy alone also eliminates some “investments” out there, such as art, popular crypto currencies, etc. – to wit, anything that is not a producer of cash.

We must understand the industry, the company’s position, management, and cash flow. Unfortunately, this is harder than speculating, but also can create more significant wealth with much less risk. There is no free lunch, so it does require challenging work, but it can be well worth it and will be the subject of future posts here.

Think about it; is something in your portfolio right now that you’d equate to Webvan? Good concept, excellent product, or immense potential, all they need to do is… make a great leap? Or you’ve seen this stock rise so much in the past, you don’t want to miss the opportunity. This is all speculation and yes, sometimes there is a place for it in our broader portfolios and yes, it can be hard to draw the line between investing and speculating.

In future posts, I will delve further into my investing approach. But for now, I want to leave you with the following; if you have a large speculative position in a company, consider taking some risk off the table in favor of a real investment.

– Diligent Dollar