Crunchbase data unearthed at least eight companies in the robot delivery space with headquarters or operations in North America that have secured seed or early-stage funding in the past couple of years.
Silicon Valley and San Francisco, known for scarce and astronomically expensive housing, are also geographies in which employers struggle to find people to deliver stuff at prevailing wages to the hordes of tech workers toiling at projects like designing robots to replace them.
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Remote robot management is also a thing and will likely see the sharpest growth. Starship, for instance, relies on operators in Estonia to track and manage bots as they make their deliveries in faraway countries.
I have had a number of super helpful comments and suggestions from readers since sending out the Monday note. Since publishing, I have also caught up on this terrific discussion between Meb Faber, Jason Buck and Eric Crittenden on the topic of trend and the rise of ETFs in the space that was flagged to me.
Quick compliance note: while I am hugely appreciative that my pal Niels made himself available to chat, gave me an early sight of his new book and access to the DBP, the? has no association or business relationship with DUNN and all scenario analysis and commentary below is the work of a rodent and not Niels or DUNN.
The ? has spent many happy hours playing with this tool. The DPB defaults (as per screen shot above) to a time period that starts in November 1984 (a time when The Terminator was #1 in the US box office and also the beginning of the DUNN WMA track record) with four illustrative portfolios that range from a 100% allocation to trend (Portfolio 1) to a broadly diversified allocation across equities, fixed income, real estate and gold (Portfolio 4).
The name of the game was to find an optimal asset allocation that solved for solid annualized returns, with contained measures of annualized volatility and maximum drawdown. Over a variety of different timeframes. If you had closed your eyes and allocated 100% to DUNN WMA in 1984 your returns would have annualized at an impressive 13.03% but you would have lived through a maximum drawdown at one stage of over 60%! Fine for those that never open their brokerage statements!
This rodent still feels like a little bit of a traitor to the \u2018narrative\u2019 cause after publishing Monday\u2019s morning embrace of systematic investing. I hope it does not age as well as the annual general meeting of the Turkey Union when they vote in favor of Thanksgiving and Christmas! \uD83E\uDD83
Rest assured, the \uD83D\uDC3F\uFE0F is not out of the storytelling business. As my old friend says, \u201Chumans aren\u2019t done yet\u201D. In fact, this is even the motto for his research business! My \u2018trend-curious\u2019 journey has, however, now evolved to the extent that we are going to be sending a proper allocation of dollars in the direction of the quant robots (i.e. the systematic trend-following models).
This discussion was particularly powerful on the topic of the diversification benefits of trend. I particularly enjoyed Jason\u2019s description of Herschel Walker Syndrome as a mental model for portfolio construction. Be more like the Dallas Cowboys!
One reader (thank you Wes!) kindly pointed me in the direction of an October 2021 paper from AQR (\u2018When Stock-Bond Diversification Fails: Managing inflation risk in investor portfolios\u2019) which contained the following \u2018Frown, Smirk and Smile\u2019 chart which I wish I had included in my original piece on Monday.
Expecting US Treasury holdings to underperform in an upside (inflation) surprise scenario is to be expected (and we know that the reality of 2022 for government bond markets was a great deal worse!). However, the powerful excess returns from trend strategies in all 3 inflation scenarios truly jump off the page (if we are headed towards a period of elevated inflation volatility - the \uD83D\uDC3F\uFE0F\u2019s base case).
As a bonus, if you fill in the quick accreditation form linked in the e-book, Niels can grant you access to DUNN\u2019s web-based portfolio builder (\u2018DBP\u2019). This allows you to back test multi-asset portfolios over any time period since 1984, the actual DUNN WMA Program track record is used as a proxy for your chosen percentage allocation to trend following.
Quick compliance note: while I am hugely appreciative that my pal Niels made himself available to chat, gave me an early sight of his new book and access to the DBP, the\uD83D\uDC3F\uFE0F has no association or business relationship with DUNN and all scenario analysis and commentary below is the work of a rodent and not Niels or DUNN.
The \uD83D\uDC3F\uFE0F has spent many happy hours playing with this tool. The DPB defaults (as per screen shot above) to a time period that starts in November 1984 (a time when The Terminator was #1 in the US box office and also the beginning of the DUNN WMA track record) with four illustrative portfolios that range from a 100% allocation to trend (Portfolio 1) to a broadly diversified allocation across equities, fixed income, real estate and gold (Portfolio 4).
I wanted to use the DPB to help me think about how to optimize my allocation to a trend following strategy. There is a danger with selecting arbitrary time periods and I do wish that the DUNN WMA track record extended back far enough so to that we could do more of a deep dive into the asset class\u2019s relative performance during the last bout of inflation volatility during the 1970s.
However, trend\u2019s non-correlated return streams start to work \u2018magic\u2019 in combination with other risk assets. I started by (over) simplifying the back test exercise, by just looking at a standard 60/40 US stock/ global bond portfolio (over, 40, 30, 20 and 10-year overlapping periods) adjusted for an incremental sliding scale allocation to trend following.
In section 2 of the note, we summarize the findings from this exercise and construct a \u2018no touch\u2019 portfolio of readily accessible listed products with which the \uD83D\uDC3F\uFE0F is building his allocation to the robots.
In a note related to systematic investing, I thought it would be fitting to tip the hat to the greatest that this game ever saw and who sadly passed away, aged 86, at the end of last week. I was touched by this tribute below. RIP Jim Simons (April 25, 1938 \u2013 May 10, 2024).
The robots can deliver to any location on the Oregon State University campus, not just residence halls. Use the map in the app to search for the campus building or location and place the map pin where you would like your delivery to arrive. Starship Robots can deliver to the door of your building, but cannot go inside.
Browse menus from campus restaurants and select from a variety of meals, snacks and beverages. There is a $1.99 delivery fee and a 10 percent service fee. When your order is placed, the restaurant will confirm your order and you will receive an estimated delivery time.
You will receive notifications in the Starship app when your food delivery is on its way and when your robot has arrived at the destination you selected. You will receive a unique code for your order -- enter it to open the robot and take out your delivery.
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For many years, I was an off-ice official for a local minor league hockey team. This league was the equivalent of A-League if one compared it to the baseball farm system. Over my years, I would see players come and go. Some would move up quickly or within a few seasons, but the majority of them would eventually realize that they were not going to make a living playing the sport they loved and quit. Most of my time in the league, I kept the stats sheet. I would log a player's goals, assists, penalties, and other key bits of data for the position they played on the team. In this role, I knew exactly which players were going to be leaving us soon for nicer ice rinks at the next level and which players were hitting the road to go back home. The stats painted a picture of which players were ready to move on to bigger things and which ones needed to give it up.
It is odd now that I find myself in a similar role when it comes to startups, especially those in the robotics space. For the past couple years, I've come across hundreds of startups in the robotics industry. Similar to those minor league hockey players, I have started to recognize which firms are going to move up the proverbial ladder to the bigger things, which ones that may need more time in the minors to develop their tech, and which ones are going to be going home to try other things.
So what are the things on a robotic startup's "stat sheet" that tells me where they are heading and if they are definitely on a path to joining the big leagues and are ready to work with a Fortune 500 company like FedEx? It all comes down to checking boxes A, B, C, and D:
Too many times I have been approached by a startup who think they have created something that has never been seen before in the industry. In all honesty, the number of startups that have shown me something I haven't already seen in a similar iteration somewhere else - I can count on one hand. Most of the time I can pull up a news article in The Robot Report or another trade publication and show them a company doing the same thing. So the first thing every startup needs to do is assess the market and see if they are doing something similar to others in the space. If they are, then they need to ask themselves what makes them special/unique/better than the twenty companies doing the same thing? If they can't answer that, it is already time to reassess their technology and business proposition. 152ee80cbc
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