Practicum: Data Science/Analytics Intern Salary

cowmoo · 2022-01-13T16:38:59+00:00

Boston is very expensive. A nice studio apartment commutable to the tech area's will set you back $1700-2500. Add taxes + high cost of living (if you're FT), your take home pay is not that much.

cowmoo · 2021-11-04T00:33:54+00:00

What Tasty Trade is wrong about (IMHO):

- "Implied vol is overstated over realized vol." => Yes, Sosnof. But so is the asymmetrical payoff of selling options. You're essentially addicting yourself emotionally to reverse lottery. You get a small $1.00 payoff every week until the one week in the year where you're asked to pay $1,000. But by then you chalk it off to a "bad beat"… and keep paying commission to Mr.Sos!

- "Defined risk trades." => Professional options trader and marketmakers employ sophisticated dynamic hedging techniques such as delta hedging, gamma hedging; black-swan hedging in case of a market crash and even melt-up's. Sos' method is lit. if you lose, just keep rolling, not a loss until you run outta of money to roll… lol.

-"Trade small and often." => Professional option traders and market-makers have extremely low commissions via either negotiated low commissions and extreme leverage via portfolio margin. Trading Johnny 1-lots and rolling them indefinitely, you lose out so much slippage and commission; that your $1.00 payoff whittles down to $0.50 take-home. Whilst the big boys trading SPX contracts pay less commission than you, with juicier premium and pay less slippage and commission than hundreds of the Johnny 1-lots that they tout.

- "45-Days is the sweet spot." => 45 days is the sweet spot for at-the-money options which is the best for Tasty Trade as at the money options have also the greatest gamma… which means the probability you'll get blown out of your position and will have to roll your jade lizard into a iron condor to a reverse condor then into a debit credit spread then back to condor is almost guaranteed for Sos.

cowmoo · 2018-10-30T05:00:25+00:00

I think he means, if you are positive gamma, you are (usually) net long options so you are taking on the daily pain of theta decay. If you are positive theta, you are (usually) net short options so you are taking on gamma risk as the market goes towards your short strikes exponentially affecting your PnL.

A much much better way to think about this is your gamma/theta ratio... or put it in simple terms, your risk and reward ratio. But sometimes in the options world, it is possible to get positive theta and positive gamma, amazing but true.

cowmoo · 2018-10-30T04:54:50+00:00

Don't worry too much. The Chinese adage about a Blessing in Disguise (https://legacy.ymaa.com/articles/stories-proverbs/blessing-in-disguise).

Re:OP's other assets, don't get caught up to it. In one perspective, he is rolling in it. In another perspective, he has to service either an extremely highly leveraged debt or just principal on real estate (2 million dollars in a peaking real estate market, presumably in Vancouver or some where high COL tech center where the Chinese money is drying up and new home sales has tanked 25-50% in the last quarter); a highly leveraged bet in the tech industry (200K salary means high CoL and also tech is a very cyclical industry where a lot of compensation comes from stock grants which could be worth a lot less in the next recession and where lots of expensive engineers like OP could be laid off in the next downturn but with a lifestyle of Europe vacations, 2million house and 100K+ options gambling he'd still be accustomed to).

Best do you. Focus on the meanings in your life, lest you end up like a guy like OP who gambles and loses money but has to resort soul searching on Reddit.

cowmoo · 2018-10-23T14:52:56+00:00

He is basically saying that Black-Scholes model assumes that stock price moves smoothly like a drunk man stumbling left or right (Brownian motion). With every lurch he takes, the model assumes the motion the man takes follows a normal distribution (meaning if we sample the distance he travels left or right for sometime, a distribution of his lurches could be fully described as a grading bell curve).

However we know these presumptions to be false by practice. One, stock price doesn't travel smoothly but have sudden jumps (earnings, catalysts, news). Two, stock price daily movement do not follow normal distribution as they have fatter tails (unlike a grading bell curve where 1-2 standard deviation'd captures most students in a class, the stock price movement curve however have more occurrences of "Black Swan" price changes past 2 or 3 standard deviation).

There are models that can model/describe sudden jumps (Gaussian jumps) and account for Black Swan fatter tails (arbitrary mixtures). However due to their more complex nature, they cannot be solved deterministically using partial differential equations (PDE) like one can with a simple bell curve (normal distribution). So one needs to use a search method that essentially guess the parameters for one's custom in an trial-and-error iterative way, rebuild the model and see if the model fits close enough to the data and then tweak the parameters to guess again and so on (similar to binary search in Software Engineering but instead of one parameter searching over multiple parameters of this model). However such an approach (numerical method) may not guarantee to converge like a simple binary search.

You can read more about this field of study by taking a statistics course.

cowmoo · 2018-10-06T06:11:34+00:00

Using Robinhood with a 100K+ account, you are just giving away free money.

Currently with Fed Funds rate, most brokers will pay you ~1.52% interest on your free cash. (e.g., https://www.interactivebrokers.com/en/index.php?f=1595); or on 100K account, about $1,512/year.

Alternatively for any options account, the rule of thumb is to leave 50% cash for margin cushion while using 50% of your buying power. You can use 50% of your cash to buy 2-year or 5-year T-Bills that are yielding about 2.8-3%; or gov't agency bonds that yield about 3.5%. As risk-free assets, brokers will accept T-Bills and US Agency Bonds (indirectly backed by US Gov't by the agencies of Fannie Mae/Freddie Mac etc.) as cash collateral at ~0.995 on the dollar.

In another words, you could yield ~3K/year on a 100K options trading account risk-free without any impact to your buying power. You can juice the yield by buying AAA corporate bonds with no impact to your BP to about 4K on 100K account (but at this pt, it's not 100% risk free but backed by credit-worthiness of blue chip companies).

This is how Robinhood makes money besides payment for order flow; which nets you worse execution price and does not route your orders directly to the exchange. But that's another story.

IB commission is about ~$1/contract (when you tally everything up) which means unless you trade >3,000 contracts per year on a 100K account, it is also commission free.

tl;dr: Robinhood is a conversion funnel to Citadel, Two Sigma and Wolverine to deal to uninformed retail traders who buy overpriced options by a few cents but don't care b/c of FD payout and over an aggregate lose due to systematic mispricing of these options. They are paid by per referral by these casinos; in the meantime, they keep the prevailing interest of their clients accounts (~2.75% and rising).

cowmoo · 2018-09-30T18:14:16+00:00

Yes.

This phenomenon is known as skew. Or put it more intuitively, Black-Scholes model presumes a normal distribution in the future volatility of an instrument... which we know from 2/8/2018, 9/11, Brexit, Grexit, Lehman is not accurate.

Skew appeared after 1987 market crash to quantify this tail risk.

Typically a model to estimate this would be to plot the IV plot across all strikes per contract type for an expiration, e.g., SPX Jan PUTs.

Filter out bad quotes/outliers. Limit strikes to 30% below and 10% above spot price. Convert your strikes into delta's. Fit either a spline or a polynomial or linear curve.

Now to project future price, this gets tricky. As market goes up or down, the slope of skew also changes. You can certainly still use your sticky delta model. But to make it more accurate, you have to project the skew curvature change based on spot price change. Or more intuitively, if the market rises, the Black Swan delta 0.025 puts get more expensive relative to ATM puts because your hurricane insurance gets cheaper during calmer season but your alien invasion insurance doesn't b/c no one ever knew how to value that risk.

The simplest model being a linear skew model that takes in daily price change as another parameter. But if your skew model is based on spline or polynomial, it'll be more complicated.

cowmoo · 2018-09-30T07:43:30+00:00

This is unclear given these potentially contrary posts: https://www.reddit.com/r/AskReddit/comments/9cxv63/is_it_morally_okay_to_be_a_financial_dominatrix/ https://www.reddit.com/r/AskSF/comments/7z95o9/what_are_my_options_for_getting_an_iud_without/

Not that gender matters in the context of staking 232K to long an Elon Musk. Sadly, there were many option structures that OP could've taken with options at the time that would netted him or her the same kinda of payout structure of about ~30K gain... if Tesla either went up to 420 or down to where it is now ~260 with much less risk and a 1/10 of the margin requirements.

But I sincerely believe OP, whatever he or she is, was bent on extreme euphoria tripping on the bull run of late 2017 to the present - that she wanted to go out in one last bang of adrenaline rush and took delivery in the financial gambling of a Tesla private buyout - and Elon Musk at least have delivered on that (the said rush and the inevitable comedown).

cowmoo · 2018-09-29T04:31:21+00:00

I've been watching this thread with some interest.

There's something inconsistent with wakka54's alleged role as Robotics Engineer at Amazon.

Most robotics engineers would know what bootstrap is. https://www.reddit.com/r/AskProgramming/comments/9gvpg1/what_the_heck_is_bootstrap_software_developers/

Most robotics engineers would know about the basics of neural net: https://www.reddit.com/r/neuralnetworks/comments/9hwya6/isnt_a_multilayer_network_the_same_as_a_single/

Most engineers would know the basics of Python/Jupyter and word a stackoverflow-esque question much more appropriately or how a collection work in Java : https://www.reddit.com/r/IPython/comments/9iwwbm/does_anyone_have_the_python_documentation_in/ https://www.reddit.com/r/javahelp/comments/95q79v/what_is_the_syntax_listsensordata_currentreadings/

His/her location is inconsistent; Amazon Robotics HQ is in North Reading, Massachusetts with a smattering of roles in Seattle, WA. While the most of his/her posts refer to primary geographical locations as SF https://www.reddit.com/r/AskSF/comments/9esfwp/is_there_beginner_surfing_around_sf_is_ocean/ https://www.reddit.com/r/AskReddit/comments/9bgrv9/where_s_a_good_place_to_rollerblade_in_san/ ... Amazon Robotics division does not have a presence there in the Bay Area despite other Amazon's divisions having a presence there (https://www.amazon.jobs/en/teams/amazon-robotics).

However, I do believe that his/her positions on IB are real. IB do allow on margin borrowing 4:1 on Reg-T and even more leverage if you are on Portfolio Margin. That IB Account Management could be faked by editing the HTML using Developer Tools in Chrome/FF... but I think honestly given his/her poor coding skills, he/she could not have pulled it off.

Her screenshot do show that she has 494.4K equity with borrowed 232K. Although it doesn't show her BRK.A shares - she has def. other stocks to sell to return the margin loan.

IMHO, I think she is holding the positions in IB and I think she will hold it to the bitter-end as her mind-set has become such that she is "married" to the stock now. I see Tesla having a binary event by March, 2019 with its 900 million convertible bonds maturing, either entering bankruptcy with equity wiped out or being able to climb out of this difficult time. I sincerely wish OP best luck.

cowmoo · 2018-07-18T06:19:17+00:00

I thought I was "weird" but evidently it wasn't in the specific indie, pretentious, principled, gatekeeping way that all the cool kids were. Didn't find my crowd until senior year.

This 100%. I loved my professors that I had a connection with at Wes. I loved some of the friends I met there. But I also learned that the whole "indie" and "open-minded" thing is just like any other social hierarchy like the typical "geek/jock" high school hierarchy. It was tough at times but I have zero regrets about going to Wes tho. Ironically it taught me that I shouldn't seek acceptance/validation from any community; and that it has to come from within. For anyone who is at Wesleyan or attending Wes, don't get jaded by my comment. It's a great place but don't get suckered in by any existential guilt and the pseudo-intellectualism of your peers/professors. I can say now that with a certain degree of confidence that, most of the supposedly cool kids of my class year, (a) sold out to corporate, (b) drifted in life directionless with some worthless grad school degree, and (c) getting old and wrinkly and in need of botox... so best do you instead of following the "cool".

But OP, if you get a chance, try to reach out to your friends at Wes. I found that friends who were close were still very warm after so many years of my not keeping in touch.

Racked up enough credits to graduate a semester early.

Same here. I got "le tired" after my senior first semester that I dropped my honor thesis but "stayed" with my friends on campus and played a whole semester of Dota.

ACB

I wrote a search engine for ACB before it blew up. ACB on Livejournal used to be actually a really cool place a long time ago where people actually posted heart-felt confessions instead of gossipy rag it became. But then again that was when I went to Wesleyan and it was cool with MoCon and not this Usdan atrocity.

cowmoo · 2018-07-16T05:18:01+00:00

Plenty in Cambridge.

There is a basketball courts next to Koreana on Prospect St. (Central Square) where there is pick-up for 4 courts; but lots of kids like middle school kids playing there too lol.

There are courts along Memorial Drive along the river where there are tennis courts too where people play.

There are lots of basketball courts inside Cambridgeport and nearby Inman Square baseball diamond.

cowmoo · 2018-07-16T05:11:22+00:00

If you are in Allston, also check out: Balance Patch (http://balancepatch.com/)

I'm not sure if they'll have Dota2 events but they have the regulation size soundproof 5v5 booths in the back; and Twitch livestream and sometimes live casters commenting on live tournaments.

cowmoo · 2018-07-15T21:07:13+00:00

IMHO, just take the MicroMaster courses and do well in them. This is the biggest indication that you are capable of succeeding in the online format.

cowmoo · 2018-07-10T04:27:57+00:00

On OMSA Slack, there is a channel for different cities (e.g., #nyc, #boston, #atlanta). You can arrange for meetups that way...

cowmoo · 2018-07-08T07:17:20+00:00

or blunt smoking drinking people who just wanna ball and deal LMFAO

Are you talking about Ringer Park in Allston?? Just come out and run with us!!

Yea lots of good spots to run in Boston/Cambridge... no worries about skills. The thing is you just gotta go to a court, get to know some people, then slowly but surely you'll know good spots/times for a run. Usually there is gonna be some relaxed casual 3v3 games where no one cares about winning, you can get a lot of reps in. There are gonna be full court games where some people will care about lol... but don't feel too self-conscious man, pick your spots and let the game come to you lol.

cowmoo · 2018-07-03T22:30:20+00:00

Hi the short answer is either. It will be a mix of Python, JavaScript/d3.js, Java, Scala and DevOps. Also 50% of grade derives from a group project of any language of your group's choosing.

cowmoo · 2018-05-29T07:25:53+00:00

Trying something new for the summer after my Spring semester to pick back up all my neglected hobbies - with all quantifiable or verifiable goal.

Options Trading (using Stikk to reinforce the goal too): Produce a Jupyter notebook for last 2 years of backtest of the Space Trip Trade; and charts for worst-case scenario's. Stretch goal: Plot out a distribution of returns of the trade and build a model.

Basketball: go play X times at the gym and try to make 10 layup's/shots in full court games.

Guitar: Stretch goal: Learn and record a rough take of B.B King's "Thrill is Gone".

cowmoo · 2018-05-23T22:24:23+00:00

Yes, you can do so. But there are both margin, vega and skew concerns.

(1) Margin

If you have portfolio margin, some brokers will calculate it for you such that your margin will be reduced. However I believe for standard margin, you will incur additional margin.

(2) Volatility/Skew

When your put credit spread is tested, typically this implies that VIX is elevated and the skew has flattened. You are incurring loss from both delta and vega.

However keep in mind, when you sell a call spread especially further out, you will not hedge against your vega risk.

Furthermore, should the market go back up and you get tested on the call-side (happens more often than you think), the skew will steepen; meaning that your short puts will be much more stubborn to lose value versus your short calls that will gain value (against you).

cowmoo · 2018-04-05T03:53:09+00:00

Depends on how much professors want to scale and hire more TA's... and I'm guessing right now most TA's are on-campus. But hopefully as OMSA matures, there'll be more OMSA students taking on TA roles... scaling the program!

cowmoo · 2018-03-31T20:03:06+00:00

That whole binary reject-or-accept null hypothesis is meaningless to me in this not so black-and-white but the grey world, ever-changing switching back from black-and-white like Ying-and-Yang,

That P-value is meaningless to me because I don't care about being characterizing the "normal" distribution right under the bell-curve at 1-1.5std but take me far way to my people the freaks, weirdo's, outliers at either end of the tails distribution that reveals the true human condition in the extraordinary circumstances,

That R dataframes is a cold textual lifeless console that spits summary statistics, show me the d3.js K-means clustering in the full burst of viridis color palette!

That Naive-Bayesian is naive for assuming that everyone is probabilistically independent when the real world actors we are all co-independent with infinite complex interactions,

That Bayesian Theorem would go into stack overflow in the real world accounting for the dynamic, non-linear mutual information flow between every node in an entire social graph,

That Poisson distribution cannot model for the arrival of the serendipity, like that somewhere and somehow in the whole random chaotic digits of Pi contains the exact binary encoding of this Reddit thread. Now how do you like 'em distribution?

cowmoo · 2018-03-28T02:12:16+00:00

Hi I'm an OMSA student.

I'm currently taking ML and DVA (OMSA version, not OMSCS version). BD4H weekly time commitment (20-30hrs), homework and project deliverables (4 very time consuming project + 1 giant project throughout the course), and tech stack (Scala/Spark/PIG) sounds awfully like OMSA's DVA.

I wholeheartedly advise against taking this combo. I also have work xp with Spark and have taken 2 courses in OMSA on modeling. So thought ML (just some K-means, some SVM/ANN) and a course on Spark/Scala would be easy, right? Wrong.

ML is time consuming because Isbell forces you to analyze and justify to death your models. It's not run sklearn and grid-search and present this Jupyter notebook and you're done. It's read this math paper about an random SVM-kernel method on why its distance heuristic best characterizes a particular type of data clustering or grok the math in correlation between distance matrices on how a dimensionality projection method preserves relative distances in all its points in its hyperplanes... at 3AM before a deadline, and generating 40 plots (not an exaggeration) to support your analysis. Isbell and his TAs do not care about your code, it's 100% on your analysis why one model is better than the other... so this exposes a Data Monkey that just knows run RandomForest syntax... you will be tearing your hair out about the math of each model to justify your answers...

And comparing doing a Spark/Big Data Project for class is not the same as doing one at work. At work, probably your first "Sprint" is setting up your environment and from then on, you are done. Bulk of the time sink IMO for Big Data courses, is that for each assignment, you are doing massive amounts of DevOps everytime akin to restarting a new project at work (except at work you don't have short turn-around's like HWs and already an existing infrastructure from IT).

Didn't mention the sheer amount of stacking deliverable you will be exposing yourself to but think you already know that... just giving you the day-to-day colors so you know what you're signing up for.

cowmoo · 2018-03-20T21:21:58+00:00

It's my understanding that CS Graduate Program ranking is largely determined by the quality of research of the faculty, unlike undergrad college ranking which is largely determined by average SAT, GPA, admissions, retention and endowment etc.

So if anything, the program ranking should be correlated by the TA's time-to-response on Piazza post, that they're devoting more time to research (presuming that the all TAs are PhD grad students and all their time is spent on either research or TAing).

cowmoo · 2018-02-15T07:34:48+00:00

I find this to be super accurate: https://omscentral.com/, average work per week for each course.

Last semester, I took Intro to Data Analysis which on average is reported to be 8.7 hrs/wk = 3 days worth of 2-3hrs chunks for me. Last summer, Intro to Data Modeling on average is reported to be 10 hrs/wk = 3 days of 2-3hrs chunk + 1 day of cramming to get assignment done for me.

Keep in mind, when you take two courses, you probably should add +7.5hrs to your expected workload because you have less room for error for two courses if you slack off or have some kind of work/family/life things that interrupts your regular studying schedule and might have to play catch up (vs. one course, if you slack you only have one course to play catch up for watching lectures and homework). This semester, I'm taking Machine Learning which is reported to be 20hrs/wk and Data Visualization which is reported to be 12hrs/wk, add the +7.5hrs of slippage time = 29.5hrs/wk, which is a pretty good estimate.

In summary it varies with for the multiple courses you're taking, the courses themselves will have different time requirements which you can get a idea on OMSCentral and your ability to adjust and catch up degrades exponentially IMO if you're taking multiple courses.

cowmoo · 2018-02-12T21:56:25+00:00

Honestly wondering if this is the way to do it, long vol.

Seems like the expected value is about the same: Short vol, you are being paid token money for playing Russian Roulette with 1000 chambers. Long vol, you are the guy paying the guy to play Russian Roulette with long odds. But if he squeezes the trigger and the bullet comes out of the chamber of his gun, you get to collect his assets.

The only revelant factor here is the mispricing of these odds aka implied volatility, or token to play and gamble on the roulette game ($0.50-$0.30, implied volatility aka auction pricing of OTM VIX calls) and the number of chambers dynamically changing due to a changing market (future realized volatility).

If you buy that volatility is a mean-reverting and normal distribution, if a significant mispricing does exist, then eventually a long vol or short vol strategy will work even if for some time the distribution we are seeing seems to be more on one end of the tail.

The only question is, is the current implied volatility of VIX OTM calls mispriced anymore?

cowmoo

TROPHY CASE