LC

1/3 up front, 1/3 upon milestone completions, 1/3 upon finish. Never ever ever ever release full payment unless the job is done, it is your only leverage. GC’ing yourself CAN work if u are flexible or can do work to fill in the blanks. But if you are on a tight timeline, don’t want unfinished work in the house for a week or two, then it may not be worth it. The job of a GC is to make everyone’s life as easy as possible. So u need to know all the tasks, skills, materials, space constraints, involved in all the subcontracting.

I feel like you and I live exactly the same life except I'm at Eastern Market and my park is Kingman Island/Anacostia bike trail/with an occasional Arlington loop sprinkled in. Having visited DC and done lots of tours of multi-family rentals, I have to say that I am incredibly jealous of what a $3,500 budget gets you amenity wise in DC vs NYC. Of course, I live and work from a pre-war apartment for $1,800 in Queens. The value guy in me can't pony up $6,000 for a NYC apartment. Well, not sure what you've got now but a buddy of mine has a decent spot up around your hood, 2600 for 1200sqft. If you're interested PM me I can pass along your info.

Anyone who's ever wandered home depot knows all about simpson strong tie.

Oh thats a good one :D

So much easier to own great businesses - they have a much better chance of "re-rating" higher. I don't mind owning a crappy business, but I want it to be kicking me back cash at every chance it gets. Betting on Mr. Market to re-value your crap business to a "fair" value is a painful experience.

I think that's wrong conclusion to draw. Flu infections don't hit all at the same time as covid infections kinda did. Well, I was comparing the COVID timeframe, which is why I prefaced with "at its peak". Annually you can probably reduce that by a factor of 5-10. In NYC, weeks 12-15 COVID contributed aprox. 12,100 incremental deaths; compared to about 3,300 combined annual deaths from flu,pneumonia,chronic lower resp. diseases, and other respiratory diseases.

Thanks Liberty. The NYT article linked CDC all cause mortality data by week per state which I wasn't previously able to find. Undercounting COVID is not a problem I am concerned with. We can infer COVID deaths incrementally looking back. Here is all-cause deaths in NYC: Week 2020 2019 2018 2017 2016 2015 2014 1 1,062 1,170 1,351 1,190 1,149 1,279 610 2 1,108 1,106 1,331 1,192 1,126 1,180 1,165 3 1,129 1,158 1,171 1,142 1,113 1,254 1,065 4 1,180 1,157 1,277 1,207 1,110 1,207 1,025 5 1,169 1,116 1,171 1,143 1,077 1,226 1,127 6 1,170 1,225 1,218 1,159 1,148 1,195 1,088 7 1,122 1,104 1,197 1,115 1,064 1,218 1,058 8 1,081 1,073 1,084 1,064 1,152 1,191 1,008 9 1,101 1,087 1,122 1,056 1,173 1,158 979 10 1,111 1,102 1,139 1,066 1,151 1,052 1,027 11 1,116 1,091 1,070 1,109 1,118 1,099 1,031 12 1,383 1,036 1,033 1,071 1,086 1,053 1,082 13 2,675 1,097 1,008 986 1,042 1,071 1,070 14 5,570 1,038 1,065 990 1,030 1,104 1,110 15 6,506 1,054 1,093 1,053 1,100 1,024 1,142 16 4,085 955 1,058 1,038 1,060 994 1,077 I truncated weeks 17,18 as those numbers are still most likely being revised. The real question is whether week 16 is up-for-revision. Hopefully it is not, and we are truly seeing deaths starting to sharply decline. Week 15 in NYC sees 80-120 influenza, pneumonia, lower respiratory, and other respiratory deaths (combined). At the peak we are seeing 5,500 incremental weekly deaths for week 15 - indicating that at its peak, COVID is 55x deadlier than the flu.

But quite a bit flabby :)

You're going in circles. Density alone is not a strong predictor as Taiwan has shown. I provided both sources in my previous post. Data collection is surely a problem. Here, I'll make the opposing argument on your behalf: https://www.sciencealert.com/more-than-70-of-americans-hospitalised-with-covid-19-had-at-least-1-underlying-health-condition-the-cdc-says I have no problem acknowledging this because as the (2) point in my earlier post alludes, pre-existing conditions will not model well vs. observed sample of hospitalized cases.

no. covid is particularly dangerous in a population where many people have underlying conditions (obesity being an important one, leading to hypertension and heart disease, that I dare say Taiwan does not have as much of). the poor in US and in the outer boroughs of NYC are particularly at risk because of this, their lack of good nutrition generally, and failure to see a primary care physician on a regular basis. density causes transmission, but underlying conditions (the most prevalent one being poor) causes enhanced risk. Hospitalization i.e. symptom severity is most certainly best explained by age, not underlying conditions: https://www.cdc.gov/mmwr/volumes/69/wr/mm6915e3.htm Underlying health conditions is not a better predictor. Only 12% of observed patients had data showing an underlying condition. But let's play devil's advocate. Let's take obesity. Per CDC analysis, 5.75% of COVID hospitalizations exhibited obesity (12%*.483) Also per CDC (https://www.cdc.gov/obesity/data/adult.html) in 2017-18: The prevalence of obesity was 40.0% among young adults aged 20 to 39 years, 44.8% among middle-aged adults aged 40 to 59 years, and 42.8% among older adults aged 60 and older If obesity were a good predictor of COVID hospitalizations, we would see (1) a much higher rate of COVID patients exhibiting obesity, and (2) more COVID patients in the 40-59 age group vs. other age groups. Yet there is zero evidence of either.

Taiwan was from January onwards recommending masks, washing/sanitizing hands and social distancing. NY, started in March for social distancing. Masks from two weeks back. Right - So we can conclude that population density (or its weak proxy: poverty) is not a great predictor Next, in terms of social policy response: Are you aware of other refuting cases, i.e where we have two areas with similar policy suggestions and timeframes, but very different viral infection patterns? Or does every city with a similar density to NYC, and similar March timeframe for masks/distancing, show the same viral pattern? I don't know the specifics for each city globally, but this is the analysis needed to show a causal relationship. The point I am driving at is that contagious respiratory illness is difficult to manage and there is a danger of setting unrealistic expectations by attributing viral spread solely to the factors which we are able to easily measure, while ignoring other factors mainly because they are too difficult to measure.

I sold short dated OOM calls in Feb with strikes around the market highs of Jan/Feb; most of these I closed out for pennies. In March I moved long stock positions into 2 year LEAPs to free up cash as a hedge (potentially costly, as you mention) but maintain long exposure. Otherwise trying to strategically shift to more "antifragile" businesses to use a pop-art word.

the strongest link between poverty and known factors of respiratory disease transmission is population density. and critics of that link will point to Taiwan which has one of the highest population densities in the world but a very low infection rate. how would you resolve this? perhaps you can argue there is a link between poverty and ability to get tested/go to a doctor if you present severe symptoms. however again critics would argue this has a low impact overall as (1) most cases are not severe and would not require a hospital visit; and (2) of these severe cases which would require a doctor, age is a much, much better predictor of outcome.

Frankly there are lots of unknowns to explain such divergent results. NYC has a tremendous casualty percentage, was this because they refused to wear masks while other areas (e.g. California) wore masks from the start? The evidence does not support that. Educated guesses would point to differences in population density. But even using pop.density is difficult. Look at Taiwan, for example. Extremely dense, very low casualties. There is most likely not one major factor. Rather a variety of factors (travel, density, masks, quarantine/social distancing, viral evolution, weather, demographics, etc.) that formed in deadly combinations in some areas rather than others. Knowing this is probably impossible. What is possible is to control what we are able to control - wearing facemasks, quarantine procedures, and such. We can debate how large the effect these factors play, but they are easier to control compared to the weather.

Let's not forget to add all the relevant data, particularly when the context is a comparison vs. the USA: From Worldometer Deaths/Million Taiwan: 0.3 Japan: 3 S. Korea: 5 Germany: 74 USA: 179

Oh the irony, this clip from back in 2001: https://youtu.be/rtnF5gIfhYQ?t=91

Loooooong indeed. Are you using them as a hedge against dropping rates i.e. duration trade?

It's just unfair to compare Germany, which is led by a former quantum chemist, to the USA which is led by a reality TV persona.

Agreed on Greg’s last point. We will see if depressed earnings are priced in. UPS gave some indication this morning...

If the docs can beam sunshine into your lungs and fry COVID with UV light or inject Lysol gel into your windpipe and wipe out coronavirus in one minute, Trump was right! If not, well...”he was just asking a question!” The problem is Trump is 100% double talk. Zero responsibility as it were. Those who engage in and enable this behavior are spineless.

I wouldn't characterize that as being smart. For example, the exact opposite can also be true: Buffett knows "so little" about tech and see a consistently high P/E of Microsoft as a signal - but really it is just noise as the company continues to outperform for decades. In both cases the problem is myopia. Of course, people have been incredibly successful despite a highly narrow vision, so maybe I am just playing devil's advocate.

https://www.statnews.com/2017/05/23/donald-trump-speaking-style-interviews/ He used to sound (speak) a lot smarter (read attached article for proof). It's either: an intentional change (appeal to lowest common denominator with plain speech) or he has dementia or he has a brain-eating parasite. Or perhaps a combo of all three. He's unfit. I gotta say, it’s pretty impressive how many ways he’s suggested that people kill themselves.

Financial assistance terms. In short, review the two most recent 8k's before investing.

Carcinoma to COVID: "You must be new here, kid, but I run this block"

It doesn't - what happens is most commodity derivative pricing models assume a lognormal distribution; when your spot price is negative it blows up this assumption. The short term fix is a parallel shift to a slightly-above-zero amount but this may violate the lognormality assumption. Just to put it bluntly, a lognormal distribution is: e^(distribution). These values can only be positive, that is, e^(positive value) = positive value, and e^(negative value) = positive value