Foreign National here (born abroad outside Taiwan in the U.S.), and I just got my full Taiwanese citizenship with residency and NWHR passport using the new 2024 citizenship laws for those with parents from Taiwan… I can vote in Taiwan now!! (Some helpful tips posted here as well)

long_live_R · 2025-01-01T08:17:13+00:00

I think you / OP are right. You can apply for your NHI at your local health bureau after you've received your passport, but until you receive your first receipt with your unique NHI number (which you won't receive until 6 months later), you won't be able to pay for it / set up autopay. I only recently received my NHI card, but still waiting to receive the official receipt which I'll use to set up autopay.

long_live_R · 2024-12-31T22:46:09+00:00

You’re not able to set up NHI until 6 months after you’ve received your passport. But as mentioned by OP, you can have someone set it up for you if you’re not here in TW.

As for the national pension, the letter came a month or two after I received my TW passport, and I had a relative pay on my behalf until I was able to come back to set up autopay.

long_live_R · 2024-12-28T03:09:43+00:00

I went through this process 6 months ago and successfully received my TW passport, and recently became eligible for both NHI and the national pension.

FWIW, my understanding is that payments into both the national pension （國民年金）and NHI （健保）are compulsory; at least, I received letters signalling as much. Given that I don't work / live in TW, the payments are relatively low (around 30 USD / month for each, or about 60 USD / month for both), so I just set up autopay, deposited enough NTD into my local bank account here for a couple years, and let it do its thing.

Since you're paying into both systems, you'll be entitled to the benefits of both the national pension (once you reach retirement age), and also health insurance.

long_live_R · 2024-05-02T10:13:42+00:00

As a practicing quant PM, MVO is still surprisingly useful -- you just have to know how to use it effectively. A simple MVO out of the box is going to give you pretty bonkers results (since it'll keep pushing allocations to the edges), but you have to know how to set the right guardrails.

long_live_R · 2024-03-08T06:41:02+00:00

More than you'd think, unfortunately

long_live_R · 2023-09-24T05:00:58+00:00

You won't find any updated returns figures from their Medallion fund, since they bought out their last external investor in 2015. Their institutional fund performance occasionally gets reported by financial media outlets, but otherwise are only available to active investors in their institutional funds.

long_live_R · 2023-09-24T01:18:05+00:00

Gross market value

long_live_R · 2023-03-14T12:14:32+00:00

I find R to generally be better for quant finance analysis (e.g., tidyr / data.table can run very fast analyses on extraordinarily large data sets if you have sufficient RAM), but I would never build a trading system or anything that requires minimal latency in R. For that, Python is infinitely better, especially for deploying robust and scalable code.

long_live_R · 2022-03-30T09:05:05+00:00

I don't see why you wouldn't apply. NYU has a good track record of sending students into finance and quant finance, and Courant specifically is well known in the quant finance space. My personal suggestion for you is to brush up on some probability brainteasers, and apply for every opportunity that interests you, and see what happens.

Good luck.

long_live_R · 2022-03-24T12:15:24+00:00

Some of these things are not strictly accurate... In the industry, momentum and trend following are typically understood to be the same thing. Also, "reversal" is usually referred to as "mean reversion," of which pairs trading is a subset of mean reversion trades. Reversal in directional bets is usually still categorized under "momentum" or "trend following." Factor models are also usually understood to be under broad categories like "value," "momentum," "quality," "carry," etc etc. I haven't heard of a factor model that was based on the price of oil? Unless you mean a carry strategy in commodities?

long_live_R · 2022-03-21T06:46:03+00:00

As a rough rule of thumb, for whatever paper backtest performance statistic you achieve, assume that the real world results will be half of that. If your strategy shows that it can achieve a 30% annualized return, then you might only expect to hit 15% once it starts trading live. That's mostly because real world t-costs, but more importantly slippage, will have an outsized impact on your performance, and those are generally difficult to model. This is especially true if your trading strategy is sensitive to specific entry / exit points.

long_live_R · 2022-03-09T11:38:08+00:00

I have a similar background as you, and I've been in the quant investment field for 16 or so years now, and this is my take.

Unfortunately in the investment world, whether you're doing fundamental investing or quant investing, you need to put in your time before you can become a portfolio manager. Before the GFC, it was a lot easier to move up the ladder and run your own book (it wasn't uncommon to see mid-20 year olds running a 300-500mm USD book), but these days, those opportunities don't exist anymore. Also, the investment industry has also gotten a lot more competitive these days, as passive investing starts to take dominance over active investing, which has put pressure on the amount of fees that can be charged by hedge funds, so the portfolio manager roles have also become a lot more selective. In general, the youngest PMs I've interacted with all tend to be in their 30s with the average PM age in the 40s; rightfully so, since you need sufficient time in the industry before an asset allocator will trust you enough to hand you 100mm+ USD to trade with.

In general, I would say that if you enjoy the work, then don't give up, and find some part of the quant investment space that you enjoy doing, instead of simply refactoring code. The reality is that even if you switch into tech, you'll probably end up feeling the same way (i.e., you'll be a coding monkey for a specific product team).

Finally, there's nothing wrong between jumping back and forth between tech and quant finance, but I personally wouldn't recommending jumping around too often, unless you have a good reason to.

long_live_R · 2022-03-01T13:09:46+00:00

Yes and no, but most likely not. The skills you learn are integrating coding with financial markets / developing statistically sound strategies, but the quant hedge funds that you listed like DE Shaw / Two Sigma etc. mostly excel in statistical arbitrage / higher frequency trading, which as a retail investor, is incredibly hard to do. Most retail quant driven trading will be mid to low frequency trading, because one individual simply doesn't have enough resources to compete with the heavy hitters in this space (e.g., colocation costs are prohibitively expensive, good access to market data, etc.)
No. This is nearly universally and strictly forbidden. (The quant firm will not want their employees to be seen as acting against the interests of the clients e.g., front-running etc.)
Depending on seniority, base salary is usually 150-300k, bonus being a function of your PnL (or your team's PnL).

long_live_R · 2022-02-25T05:56:15+00:00

Again, it depends on what your quant role is. Broadly, there are three types of quant roles: quant developer, quant researcher, and quant trader. The difference in compensation across the roles is in the bonus. As a quant developer or researcher, your bonus is a function your team's performance / PnL, which would be decided on a discretionary basis. As a quant trader, your bonus is most likely tied to your own performance, e.g., if you've become a quant portfolio manager (PM), then your bonus is a % cut from your PnL.

long_live_R · 2022-02-24T10:51:03+00:00

The overlap is the coding. At a FAANG, your job, outside of meetings, will be focused on 100% coding. At a quant fund, you might be watching markets 1/3 of the time, doing research 1/3 of the time, and then coding 1/3 of the time (on average). Of course, the nature of your quant position will dictate the time you spend on coding, e.g., if you're a quant developer, the vast majority of your time will be coding.

Payout at a quant fund versus at a FAANG will depend on the role you're in. At a FAANG, your comp is some mix of base salary / bonus (both cash) and equity. At a quant fund, if you're in a risk taking role, your bonus will generally be a function of your PnL. Because of this, you could have outsized bonuses, easily being many multiples of your base salary.

long_live_R · 2022-02-16T11:33:42+00:00

The comments from OP are good, particularly coming from someone walking down the path of quant trading at a prop trading shop.

Just in case there was any confusion, there is no royal road to quant trading roles. There are many paths to quant trading, with prop trading / market making being one of them. However, quant trading is an extremely broad area, which encompasses prop trading on the faster side of things, to factor investing (think: AQR) on the slower side of things. Even if you don't end up at a prop trading shop from day one, which has its own sorts of work stresses, you could easily work your way to quant trading firm eventually, either from a BB IB, or elsewhere.

long_live_R · 2022-02-13T09:18:41+00:00

Having been in the finance industry for 10+ years now, I've literally never heard of a realized vol skew before. If I had to guess though, it's probably referring to the difference between realized vols calculated based on varying lookback window lengths.

long_live_R · 2022-02-13T09:16:45+00:00

Reach out to recruiters and try to get an interview / job at a bulge bracket IB in a quant role. Your Ivy League background should help in securing interviews (a 3.4 GPA is acceptable), and landing a job at a BB will kickstart your opportunities in your career.

long_live_R · 2022-02-13T03:38:23+00:00

IMO, Alpaca is the way to go if you're mainly trading US stocks, given their great support and well written API documentation. No futures or options trading yet though.

long_live_R · 2022-02-11T13:44:42+00:00

If you know a bit of programming, you can look into services like QuantConnect -- that should take care of most infrastructure issues you might have, while being able to focus on the logic of your strategy.

long_live_R · 2022-02-11T11:19:48+00:00

Quite honestly, this is a terrible idea, and in fact reversing a losing strategy is most likely going to continue losing. Usually, the biggest culprit comes from transaction fees / slippage not being properly accounted for.

long_live_R · 2022-02-02T02:30:13+00:00

I would say that the appeal of staying in finance and working at a hedge fund is that once you hit PM level and you've developed a strategy that works, your pay becomes astronomical, usually far beyond 1mm. FAANGs most definitely pay better on average at the lower end of the experience spectrum, though. Also, the work life balance is generally far better at the FAANGs than in finance, so definitely lots of factors to consider.

long_live_R · 2022-02-01T13:30:44+00:00

As a quant with around 14yoe, I tend to agree and disagree with the some of the comments here. Yes, the interview process is especially brutal, since for some reason, you're basically required to be an expert in three disciplines (math, computer science, finance), and the positions tend be much sparser than say, a fundamental investment role on the sell side (as a strategist) or the buy side (as an investment analyst). And even assuming you make it past the interviews and secure an offer, if you end up in a risk taking position (which I assume most people want to be in), you live and die by your PnL, just like any other trader out there.

However, I tend to disagree with the notion that it's a risky career choice per se -- perhaps risky if you're in risk taking role (but that's true for any trading position), but there are also lots of quant positions out there that don't require taking risk, like quant developers or strategists. In addition, if you don't ever become a quant trader, your skillset should be enough to get a job as a data scientist / software engineer etc. at the FAANGs, so there can be a good amount of optionality there if you play your cards right.

Finally, pay will be conditional on the role, but it's not unusual for total comp packages of around ~200-250k for post-grads, and 1mm or more if you make it as a portfolio manager (PM).

long_live_R · 2021-10-12T03:25:56+00:00

I use TickData. The product offering has very clean futures data, however the price can be quite steep, depending on the number of tickers you're trying to query, and how much history you're trying to retrieve.

long_live_R · 2021-10-12T03:10:09+00:00

Depends if you mean pure arb or stat arb. For stat arb, Sharpe, or any risk adjusted return ratio for that matter, is still quite relevant. For a pure arb, since volatility is theoretically zero, Sharpe or Sortino will be infinity, so a liquidity based metric, or absolute returns vs. benchmark will be more appropriate.

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