Buying a house means buying a job – as a property owner and manager.
Transaction costs are about 9% round trip.
Streeteasy, propertshark, ACRIS and Curbed are really important resources that you should be intimately familiar with pre-transaction. Think of them collectively as your Bloomberg terminal. Also interesting are the Case-Shiller city indexes. Millersamuel.com used to have great data available free – timeseries going back 15-20 years on co-op and condo sales -- and now it’s all behind a paywall.
New York Times has the best buy vs rent calculator. http://www.nytimes.com/interactive/business/buy-rent- calculator.html
Check out its ADVANCED SETTINGS. You’ll see that how long you own the place is really important to the buy-vs-rent calculus. Also important is the rate of return you could be earning on the downpayment if you hadn’t bought a house. That’s also in the ADVANCED SETTINGS.
Adverse selection is alive and well in the real estate market. Places will have problems that are not apparent at first look. Some of this can be mitigated, some of it can’t. For example, if you do plan to fix it up, you could pick the general contractor first, and then have them survey the place before you buy it, and even make a binding bid to fix it up before you buy it.
It is entirely possible to construct a good estimate of construction costs in advance, but it will take some arm-twisting to get this to happen before you’ve bought the place. The seller and the contractor will both fight to prevent this from happening.
Most of the fun things that you might want to do with a bought property could maybe also be done with a rented one? If you shop for a rental with that feature in mind.
Since you brought up schools – the NYC school situation is changing rapidly. Currently in Manhattan, there is a severe supply/demand problem between parents and schools. I see the imbalance being resolved mostly by parents choosing to move out, as we did to Park Slope. Not sure how that affects the Manhattan real estate situation.
Before buying any place, I recommend becoming intimately familiar with its local school dynamics, not because you personally will care, but because the next buyer might. For example, PS 3 and PS 41 have been threatening to change their service boundaries for a few years, which is driving people nuts in the affected areas. Something similar is happening in Park Slope around 5th Avenue.
Two Sigma has been a sponsor of MIT Battlecode for six years now. It's a programming tournament where teams of kids spend a month coding a virtual robot army to battle against other students' virtual robot armies.
Here's what a match looks like:
There's a lot going on in a battle, and it can be confusing. So today my colleague Lee Lin and I coded up some analysis to help us understand what's going on during a match. The x-axis is location on the battlefield -- the left side is one team's home base and the right side is the other team's. The y-axis is the amount of fighting force each team has at that location. We've taken the 2-D battlefield and projected it onto the axis running between the two bases.
The Battlecode code is all java so we started the analysis there. The AffineTransform class came in handy for the projection math. The java code dumped its frame-by-frame data in as valid JavaScript code. The visualization is a Highcharts chart being manipulated by JavaScript code on a simple timer.
The core of the updating code is offensively simple:
function updateData() {
for (i=0; i<2; i++) {
chart.series[i == 0 ? 1 : 0].setData(thedata[roundNum][i]);
}
if (roundNum < thedata.length-1) {
roundNum++;
}
setTimeout(updateData, 15);
}
The chart is in an object called "chart". The data for the entire match is in a two-dimensional array called "thedata". The function "updateData()" gets called every 15 milliseconds -- we'd like a framerate of 60fps if possible. At the end of updateData() we call setTimeout() which asks JavaScript to call updateData() again in 15 millis.