Volatility and Changing Trends

Volatility

This most recent market correction (10% decline) was one of the fastest in S&P 500 history at just twenty days. The Covid “correction” was eight days and the ‘growth scare’ in 2018 was thirteen days. Rapid market declines like these are most often related to panic selling or forced selling. Panics can’t last forever by definition. Of course this is in reaction to Trump’s daily on and off policy changes which have reintroduced volatility to the market. The impact of algorithmically optimized social media doesn’t help, whether it’s clips of Trump or reaction videos interpreting the knock on effects of his actions.

The last 15 years have been fairly low volatility compared to historical standards. There were periods in 2011, 2015, 2018 and of course 2020 when markets spooked dramatically for very good reasons. The last major selloff was August of last year when the Japanese Carry Trade unwind hit markets – too much borrowing in Yen at ultra low rates to invest elsewhere. We can now add Trump’s Tariffs of ‘25 to the volatility record books. It’s not over and it has re-introduced a real risk premium to equity markets. One can view this recent sell off as a fast resetting of valuations from high to medium.

All of the above refers to the short term. The long term is a much more complex debate that can easily branch off into many far reaching narratives. The biggest question in my view is how the global monetary system changes in the coming years. I’ve mentioned this recently in previous articles. An example of a previous change is the dollar leaving the gold standard in 1970. Another example is globalization exporting manufacturing to China which gave them a surplus that they reinvested into US treasuries (among other assets), which helped push down US rates. These changes are like shifting tectonic plates. We just ended a 40 year bull run in rates, from 1980 to 2020 where the 10 year fell from 15% to 0.50%. On the horizon is a new set of monetary rules that could shape the next 40 years.

The Mar-A-Lago Accords are one possible next step. The basic early premise is that the US will provide military support to the G7 if they agree to participate in helping rebuild US manufacturing. This includes creating a sovereign wealth fund in the US that would accept/buy EUR, YEN, RMB and other currencies to help push down the value of the dollar. While this may be the target policy, the US is so far behind Chinese manufacturing and production it’s not even funny. 90% of the world’s battery storage components are produced in China along with 65% of EVs, 80-95% solar and roughly 50% of basic commodities like ammonia, iron and steel. These are slow moving trends by nature so we should see them take shape in real time, over time.

For what it’s worth, I see two paths for this cost competitive manufacturing revolution in the US. We either use 100% automation or we crash our housing market by dramatically increasing supply so that these factory workers can afford housing on minimum wage. The latter is not going to happen, so I’d bet on 100% manufacturing automation. Figure.AI is the current headline player in this space (they get the hype for now). AI will play a big role in training and developing robotic manufacturing. Even though Amazon is way ahead in robotic warehouse automation, we’re still in the early stages of the manufacturing automation trend.

OpenRouter

I’ve mentioned this website in the past. OpenRouter uses APIs to connect all available LLM models into a single application. There are 349 LLMs currently from OpenAI, Google, DeepSeek and newer less headline grabbing models like Qwen produced by Alibaba. This is a great site to test breakthrough models as they are released or compare the quality and limitations of the LLMs from the big brand names.

Maps

Regular readers know I like different data maps. Here is a heatmap of Strava runners. Look at how much land there is to build more housing and how many places are basically completely empty. People like to cluster around cities. The Northeast is fairly packed. Tokyo’s population density is impressive.