Note: MLP is a German financial advisory firm comparable to companies like Edward Jones in the United States, which operate on a similar commission-based model. However, the business practices of Edward Jones may differ from those described here regarding MLP.
How Financial Advisors Reel Us In
Let’s begin with this: doing something for retirement savings is better than doing nothing. However, whether investing through a financial advisor yields a worthwhile return is a different question. This article is for anyone wondering whether advisors like MLP (or Sparkasse in Germany) are the right choice for managing their financial future.
What do I mean by a financial advisor? I’m referring to professionals from banks or firms like MLP, who earn commissions for selling financial products. Their interest lies in selling products because that’s how they’re paid. Their advice is “free” because their commissions are embedded in the products they recommend. Excluded here are Fee-Only Financial Advisors (more on this later), who don’t receive commissions and instead charge directly for their services.
Funds held on your Lemonway account can be used solely for your transactions on the Estateguru platform. As it is a special purpose account, it should not be used for depositing funds without the intention to invest. As inactive accounts create cost to Estateguru, an “inactive account fee” is charged from users who have deposited funds in their accounts but who have not made any new investments on the Primary or on the Secondary market for the last 12 months. Starting in April 2023, the “inactive account fee” was increased to 10 EUR per month for the first year following the 12 month period of inactivity, and will increase to 50 EUR per month thereafter. The fee will be applied monthly if there is a positive balance on the user’s account. If the user makes an investment, whether on the Primary or Secondary market, the account status will be switched to active again and no further fee applies.
I’m probably not the only one trying to gradually withdraw my money, as the majority of my investment has now defaulted.
To be fair, I should mention that I have already withdrawn half of the money I had previously invested. Apparently, I’ve now reached a year without investment, as €10 has also been deducted from my account. Not great. I had tried to activate an automated investment strategy that kicks in once the account balance reaches €500, so I could at least “rescue” some of my money from time to time, but apparently, that didn’t work. This is certainly one way to force your customers into something.
For me, this means I’ll have to reluctantly make one investment per year and then gradually withdraw my money. It will take a bit longer, but so be it. I can definitely no longer recommend Estateguru.
Today, two topics I find particularly exciting come together: data analysis and visualization, and finance. Choosing the right ETFs is a topic that fills countless web pages and financial magazine articles. However, it’s equally fascinating to explore the overlaps between ETFs. Previously, I compared the Vanguard FTSE All-World High Dividend Yield UCITS ETF USD Distributing (ISIN: IE00B8GKDB10) and the iShares STOXX Global Select Dividend 100 UCITS (ISIN: DE000A0F5UH1). I also analyzed the performance of these two alongside the VanEck Morningstar Developed Markets Dividend Leaders ETF (NL0011683594) and an MSCI World ETF (IE00B4L5Y983).
The holdings included in an ETF can be downloaded from the respective provider’s website; I performed this download on October 5. The data requires significant transformation before it can be compared. My R-based notebook detailing this process can be found [here]. For the visualization, I chose an UpSet diagram, a relatively new type of visualization that I’ve used in a paper and another project. While Venn diagrams are commonly used for visualizing overlaps between datasets, they become unwieldy with more than 3 or 4 datasets. This challenge is clearly illustrated in examples like this:
The size of the circles, for example, does not necessarily reflect the size of the datasets. An UpSet diagram is entirely different:
Yes, it takes a bit of effort, but it shows much more clearly how the datasets relate to one another. On the far left, we see the size of the datasets, with the Vanguard FTSE All-World High Dividend Yield having the most holdings—over 2,000. On the right-hand side, we see the overlaps. The point at the very bottom beneath the tallest vertical bar indicates that the Vanguard FTSE […] has 1,376 stocks that no other ETF includes. Similarly, the iShares Core MSCI World has 757 titles that no other ETF contains. In the third column, we see that these two ETFs share 486 titles that the other two ETFs do not include. I find that quite fascinating. For example, I wouldn’t have thought that the Vanguard contains so many stocks that the MSCI World does not.
The VanEck allegedly has one stock that no other ETF contains, but that’s not accurate; that entry was just cash. Otherwise, 81 of its 100 titles are also included in the MSCI World. All of its titles are included in the Vanguard.
It would now be interesting to see how the weightings align. However, that’s an additional dimension that would likely be difficult to represent in an UpSet diagram. Still, it’s necessary to take a closer look at this because the overlaps might result in unintended overweighting of certain stocks. That would be a topic for the next blog post.
Disclaimer: This is not financial advice or a recommendation!
The article “When Chasing More Dividends Leaves You With Less“ from the Wall Street Journal by Jason Zweig (who, by the way, wrote the commentary for The Intelligent Investor) sheds light on the appeal and associated risks of dividend strategies. Investors who focus on high dividend yields often hope for a steady income stream, especially in times of low interest rates. However, as the article points out, chasing high dividends can ultimately reduce long-term returns. The problem arises when investors blindly flock to funds that offer exceptionally high dividend yields.
Depot student Dominik has already provided a good overview of how to export data from the ING depot via the ExtraETF workaround. However, not every tool can handle the CSV export properly. For example, DivvyDiary immediately recognized the relevant columns, but the balances didn’t match. The reason for this is that CSV files can vary significantly, as can the data within them. Sometimes, columns aren’t separated by a comma but by a semicolon. And while the difference between 1,000.00 and 1.000,00 might seem minor to us, for DivvyDiary, a 1000 turned into a 1 because the thousands separator was treated as a decimal point.
The solution: As much as I dislike working with Excel, if you open the CSV file in Excel and then save it again as a CSV, even DivvyDiary (and many other tools) can handle it.
Disclaimer: This is not financial advice! No warranty.
When selecting ETFs, various factors come into play, including tax considerations. In the last article, we discussed what partial exemption means. However, the tax differences between ETFs with different domiciles and their holdings in US stocks are also interesting. This article focuses on two specific and popular ETFs, and even though both contain US stocks, that doesn’t necessarily mean that the ETF domiciled in Ireland will deliver higher returns.
Disclaimer: This is not financial advice, all information is provided without warranty!
Introduction
Investments in ETFs (Exchange Traded Funds) are highly popular among investors due to their diversification, low costs, and ease of use. There are two main types of ETFs: distributing ETFs, which pay income directly to investors, and accumulating ETFs, which automatically reinvest income. However, the taxation of these earnings can be complex, particularly due to the partial exemption and the pre-tax lump sum. This article explains how partial exemption works and how accumulating ETFs are taxed in Germany.
Some tools online offer the ability to see how many dividends are likely to come your way. For example, extraETF provides a tool where you can see what the dividends might look like based on an assumed growth rate (CAGR), a certain number of years, and asset gains.
What I haven’t seen so far is a tool that, starting from a portfolio, calculates the dividend growth based on an assumed CAGR and dividend yield, while also factoring in taxes. That’s exactly the kind of tool I’ve created.
The problem with the code above lies in the use of the pipe operator (|>), right before ggplot. ggplot2 is not natively supported with the R-specific pipe (|>), as used here. However, ggplot2 works seamlessly with the Magrittr pipe (%>%) from the dplyr package. Here is the correct usage:
library(ggplot2) library(dplyr)
mtcars %>% ggplot(aes(x = mpg, y = hp)) + geom_point()
Alternatively, the data must be explicitly passed to ggplot, as shown here:
I’m a big fan of sub-accounts to keep budgets for different categories well separated. To do this, I’ve tried a few different banks. bunq didn’t work reliably and had very unfriendly support. I used to really like N26, but what I didn’t find very funny was that when downgrading from a more expensive to a cheaper plan, you can’t keep the IBANs for the sub-accounts. Then I found vivid. I hated the app’s color scheme from the start, but the features were okay, especially since I could link different virtual credit cards to different accounts. Unfortunately, the support wasn’t particularly good here either. And now, existing accounts are being closed because vivid is parting ways with Solaris Bank. New IBANs again. So, I’m moving on, or rather, going back to ING. They don’t have sub-accounts quite the way I need them, but I’ll figure out a different way to manage my budgets.
The fact is that with every neobank, you have to pay for the really interesting features, and in return, you don’t always get great support. The ING account might not be as sleek as those of the neobanks, but it’s free, and the support is usually good. I’ll keep my vivid account after upgrading it, but I won’t pay for it. Sometimes, the boring and old-fashioned offerings turn out to be not such a bad idea in the medium to long term.
