You're conflating micro and macro price movements. Sure, you can't predict black swan events with technical analysis, but it wouldn't be out of the question to predict short term fluctuations based on a mixture of market psychology and herd thinking.
I don't employ any technical analysis in trading, nor am I a strong advocate, but technical analysis is more about reactionary psychology than about predicting the future. In the most micro sense, the market is dictated by single individuals buying and selling stock, and in the broadest sense, it's a statistical result of millions, or billions of unknowns. Those are two totally different games.
To add, it provides a general measure of sentiment. It's a measure of actions taken rather than words. It's not a crystal ball, but does give a slight edge if you figure out which indicators to use.
I've used it for years and had very good success when I was actively trading (traded longer timeframes. Usually made weekly/monthly trades) to the point I was able to live off of it. The last couple of years I've taken off from trading to focus on developing my business, but will likely jump back once that launches and is in a good enough place, as it's both a time and emotional drain.
Thanks for the note! I'll change the wording in my article WRT bills/notes. :)
With regards to safety, I noted that I think there are two types of safety to note here:
1. Default risk.
2. Asset price volatility.
Ultimately if someone is willing and able to hold to expiry, they aren't subject to #2, but this clearly wasn't the case with SVB and may also be the case with other institutions. I think it lacks nuance to not consider the middle states between the purchase of a bond and the full return of the bond upon expiry.
I haven’t heard much from Bordeaux on crémants, but i can vouch for burgundy and loire for crémants that perform as well as many champagnes, for under $25.
@tdarb's pblog (https://pblog.xyz) is pretty simple. It's just a shell script that builds a site and RSS feed with pandoc. The build system's a makefile.
This is totally my personal bias, but I'm unsure that speculation has a positive value in the housing market, and I think governments should largely try to ensure that as many people as possible can afford homes, rather than ensuring that people can profit off the sales of their homes.
In the United States, people have long seen real estate as a path to wealth (unlike Japan, for example), so it's difficult to reason that people's primary homes shouldn't be their escape hatch into retirement (e.g. the dream of someone buying a house in 1980s Palo Alto and selling it in 2022).
I'm not sure that's how it works—at least in the case of NYC. The ~4% tax only applies to those with residence within the city's limits. If you live in Westchester however and work in Manhattan, you escape the 4% income tax (but instead pay higher property taxes).
They label property taxes as an absolute value paid, rather than as a percentage. Illinois per the Tax Foundation had the second highest rate*. In fact, it speaks to Illinois' and Chicago's affordability** that with such a high marginal rate, their property taxes as a dollar amount are on-par with many other states.
I'm not sure what you're saying, yes Illinois property taxes are high but that's mainly because of the collar counties around cook (https://www.civicfed.org/civic-federation/blog/2017-effectiv...). It's hilarious that you think that high taxes has done anything good for Illinois. the state is bankrupt and in absolute shambles financially. The taxes are high on everything to try to dig out of the hole (which will never happen), effective sales tax in the Chicago area is now over 10%!! All of this nets reduced buying power so yeah, housing will probably be slightly cheaper on average but at the cost of standard of living all around. Your argument is absolutely clueless to the reality on the ground. High property taxes just look good on a spreadsheet.
+1, lest we forget the original premise behind VC returns was that seed checks had huge returns because most people weren't willing to take on the risk, timeline or probability distribution of funding startups. Now everyone is willing to, so that arb is gone.
At least in India, most of the venture capital startups are copies of existing products but with discounts and rewards attached through VC investments.
The timeframe for return on investments is too low for any risky bets. You aren't going to end up cashing out deep tech in few years.
Related, maybe tangentially; I'm seeing lots and lots of startups whose basis seems to be "we build X <tool/SDK/API> technology as a service." Data management or transformation stuff. Packages for doing X in the cloud. Analytical libraries. Not products, but infrastructure.
On one level I'm very pleased to see this stuff funded, because it wasn't really 10-15 years ago.
On the other hand, what worries me here is that this stuff is entirely secondary and subservient to other services, its potential revenue completely depends on the success of businesses further up the food chain. And if things start to really slow down, I worry these will be the first to suffer and a lot of these startups (which seem to be hiring for a lot of the interesting work) will shutdown.
Personally, I feel like there are too many dollars and startups in this space now.
I feel like the risk profile is such that I'd never buy most of the products being built. I don't want core business infrastructure sitting in the cloud of a startup which might not exist tomorrow due to missing a VC round or an agile pivot. I also don't want an integration of 50 different cloud services.
I'm glad to use established open-source technologies. I'll also use AWS or similar big players if open source doesn't exist. However, most of the niche proprietary startups just don't make much sense here to me. I'd invest a lot of money and take on a lot of risk.
I do feel like there is big money in value-adds: hosting open-source solutions, consulting, etc. A lot of non-tech companies are struggling with data, ML, and visualizations.
There's a feedback loop here. Once these startups start shutting down, the above problem will be recognized, cascading their collapse.
Yeah I think there's wisdom to what you're saying.
I do think there was a deficit before that this wave of stuff is working to remedy. In the mid-2000s, companies like Google and Amazon had a competitive advantage because they had the inhouse talent and $$ to build e.g. Bigtable, MapReduce, Dremel, Borg, etc. before anybody else had those tools. Then there was an awkward few years (early - mid 2010s) where everyone and their dog was trying to clone those in the open source space. And now we're in a situation where there's startups whose whole business model is structured around providing "big data" or "data transformation" etc. tools etc. They look like compelling places to work, on account of the interesting work they do, but I worry about their viability.
I wouldn't quite go so far, but I don't think piecewise enterprise SaaS makes sense. The whole model of having dozens of interacting SaaS pieces, any of which make change APIs, have a bug, or go under any day has peaked.
I'm okay relying on AWS.
I'm not okay having one company handle email, another columnar database, another tabular database, another map-reduce, another streaming / logging, and so on. I understand why each of those might be better than their AWS counterpart, but for business continuity or for security, it's a train wreck.
I'm usually okay relying on hosted versions of open source platforms, since if something goes very bad, I can move over to hosting them myself. Even there, I hesitate with things really central to continuing operations. But for the 95% of other stuff, I find something like hosted postgresql or redis to be most robust.
A company specializing in redis will beat my IT staff. On the other hand, it's low-risk. A lot of companies disappear in a few weeks, but it's rare that they disappear overnight.
I don't employ any technical analysis in trading, nor am I a strong advocate, but technical analysis is more about reactionary psychology than about predicting the future. In the most micro sense, the market is dictated by single individuals buying and selling stock, and in the broadest sense, it's a statistical result of millions, or billions of unknowns. Those are two totally different games.