MIT
Mason Industrial Technology, Inc.
stock NYSE

If next summer goes well and you get a return offer, I'd seriously question whether you need the masters at all. For trading at those shops the internship basically is the pipeline, and a US MFin on top of a return offer is a lot of money for not much.

Profile's strong for the whole list though, CMU and Berkeley especially. Princeton and MIT MFin are small classes so they're reaches for pretty much everyone. If you're actually leaning toward research over trading then Yale stats or ICME make more sense than the MFins.

The Jonathan Clements Getting Going on Savings Initiative is up and running!
This joint effort involving the John C. Bogle Center for Financial Literacy, a team of academic researchers and the City of Boston is spreading the word about Roth IRAs to working teens and young adults, many from lower-income backgrounds. And most concretely, as envisioned by the late financial columnist Jonathan Clements, it has started the process of making payments of $1,000 each to selected qualifying individuals to fund Roth IRAs. The academic researchers will study if payments like this are an effective tool to help young adults establish an early habit of setting money aside for later in life.
The Bogle Center Board is delighted to share an update on the progress so far, the great work of our partners and plans for the future. **Please note that given the outpouring of contributions and the time needed to build out the program, the Bogle Center isn’t seeking additional funds for the Clements Initiative at this time.**
**A busy summer in Boston**
After a small pilot in 2025, the Clements Initiative saw a full rollout across participants in Boston’s 2026 summer jobs program for teens and young adults. It has been a complex and labor-intensive effort led by researchers associated with J-PAL North America (a research center based at MIT), Boston’s Office of Youth Employment and Opportunity and the city’s Bank On Boston program to help residents access high-quality, low-cost financial services.
As of late September, the team had presented workshops on Roth IRAs and investing to 487 summer employees. There were more than 30 workshops because program participants were dispersed across city departments and nonprofit organizations.
Of the workshop participants, 154 were 18 or older and thus eligible for the Clements Initiative payments and the related research study. As of late September, the team had enrolled 79 people into the study and had assisted 73 of them to open Roth IRAs at Vanguard Group. Recruitment and account-opening meetings were continuing. Meanwhile, in a second round of meetings, the team is giving each new IRA holder $50 from the donations to the Clements Initiative and helping them deposit and invest those funds in a global stock exchange-traded fund in the IRA.
The team hopes to sign up 100 study participants from the summer 2026 cohort. Soon those participants will be randomly assigned to either the treatment group or the control group. The young adults in the treatment group will receive a further $950 contribution from the Clements Initiative funds – for a total of $1,000 each – and those in the control group will receive a second $50.
Over time, the researchers will study if the larger upfront gift leads to greater financial well-being and behaviors associated with building long-term savings.  
**Challenges addressed**
Turning the Clements Initiative into reality has involved a lot of operational challenges that were successfully addressed over the past year. The J-PAL team – which includes professors at University of Chicago, Northeastern University and Harvard University – obtained grants to hire undergraduate and graduate students to assist with the large number of workshops and the multiple meetings needed with each recipient. To address a language barrier, they had all the workshop materials translated into Spanish.
To track the study participants’ Roth IRA activity over time, the researchers are partnering with Vanguard, which will supply anonymized data on the participants’ conduct of their accounts.
Separately, the Bogle Center reached an agreement with the University of Chicago that will spare the Bogle Center from having to make payments to the individual program participants. The Center, which has a volunteer board and no employees, will make donations to the university, and the university will then use a third-party payment platform to make and track what are likely to be hundreds of payments over time.
**Bigger plans ahead**
It’s still early in the implementation of the Clements Initiative, which was announced in [May 2025](https://boglecenter.net/wp-content/uploads/Jonathan-Clements-Getting-Going-on-Saving.pdf), four months before Jonathan’s death. And the successful summer 2026 rollout in Boston is just one step along the way.
The J-PAL team is hoping to expand the program geometrically in 2027 and is talking with potential partners in multiple states to make that happen.
The Bogle Center and our partners are grateful to have substantial funding for the Clements Initiative. Jonathan donated the royalties from [The Best of Jonathan Clements](https://www.amazon.com/dp/0988780348), a collection of his *Wall Street Journal* columns, to the Bogle Center to use in the Clements Initiative. The Center, a 501(c)(3) non-profit, has also proudly accepted donations for this project, both before and after Jonathan’s death in September 2025.
If there are 50 participants in the treatment group and 50 in the control group for this year, that would add up to expenditures of $55,000 from the dollars held by the Bogle Center for the Clements Initiative. And the Bogle Center would have more than $400,000 remaining in those funds to support an expanded program in future years.
The Bogle Center and our partners continue to be extremely proud of this undertaking and its ability to change lives. **But as noted above, given the outpouring of contributions and the time needed to build out the program, the Bogle Center isn’t seeking additional funds for the Clements Initiative at this time.**

There are many posts seeking help. Yours stood out because you wanted to see the journey that might be shared. I found something of interest when comparing an "everyman's portfolio" (starting capital under $250) with my current strat (large at $100k, sweeping $2k/wk). I used the same metrics to screen for entry (VWAP, VIX, Price Action, and Fourier clustering). Augmentation with Hidden Markov Model (melon thumping). Many deets under keywords MIT Blackjack Algo and superprofitability, search those first if interested.
My (retired EE) background is Control Theory, staying engaged in my encore career after retiring 15 years ago (at age 55). What I see in the bottom plot, the slopes are identical, meaning the algo remains unchanged in profit delivery - save for a constant of integration. My inference, the algo is an eigenfunction that sweeps profit with improved deviation in tracking the unit ramp function. CT models show improved settling time with higher loop gain. A type 1 system uses a single integrator to zero out steadystate error. A unit ramp would exhibit finite error, clearly seen in the left curve. The right curve is detailed in the top plot. Observe the deviation is much reduced, but still an ongoing finite value. Main difference I see, The TP in cells W1 &W2. Lowering the TP allows the algo to operate as a quant scalp below the market's Brownian Motion. High probability of success on trades. Note the asymptotic convergence of the green segments for weeks 2-4 (no zero on log scale so week 1 isn't observed) to the slope value, matching the left curve (column AM cells 31 & 34 identical).
Keeping the entry/exits tightly grouped (Sharpe above 3) assures regime change immunity. Similar for both column Z72 and AA72, but improved with new. Fractional Kelly sizing (under 1.4%) ensures going bust is remote, important on large sum, tolerable on the everyman's.
Several methods in trading for the past 3 weeks, beginning was test the channel limits, week 2 was toe the line with "shark fin" into the weekend, week 3 was channel fill with multiple trades (reduces effort at termination of the week). The latest numbers post to kinfo verifieds tomorrow. My profile is dark on sharing to inhibit copy trading, Poppy Gekko.
https://preview.redd.it/isju5u8wkwsh1.png?width=1591&format=png&auto=webp&s=95bf431f182f16d5c78b114085d126ddccd18533
Hope this helps, stay in demo until you have sufficient data (rule of thumb for statistics, 30 samples, no need to count every grain of sand) to hit the Sharpe number discussed.
Good luck.

I built NewsWave on Sept 30 by directing Claude Code agents. I typed no code by hand. 564 automated tests pass, and two adversarial review passes found bugs that I fixed.
How it works:
\- News comes in. Claude classifies each headline as BULLISH, NEUTRAL or BEARISH. That is its only job.
\- Plain Python does the rest: relative volume of 2x or more, a 1.5% or larger price move, then a pullback to the 5-minute 9 EMA, then a breakout entry.
\- It trades on an Alpaca paper account with $6,000, as a 6-month experiment.
Video with the prompts: [https://youtu.be/XHyMDYVCp9Y](https://youtu.be/XHyMDYVCp9Y)
Code (MIT): [https://github.com/AskElira/newswave](https://github.com/AskElira/newswave)
Happy to answer questions about the agent setup or the rule chain.

I've been building an open-source matching engine in Go for a while. This is the worst bug it has had, and it's exactly the kind that would sit unnoticed in a backtester for months.
Four orders, default settings:
1. Seller A rests 3 @ 100.
2. Seller A rests 5 @ 105.
3. Trader B rests a buy stop at 100, market for 2. Nothing has traded yet, so it waits.
4. Trader C sends a fill-or-kill buy for 5 @ 100. Only 3 are available at 100, so the order can't fill. The 3 it matched get reversed and C is rejected.
B's stop fired anyway. B bought 2 @ 100 from A, a real fill that took A's order from 3 lots down to 1, and the only message anyone got was "C rejected". A and B were never told.
It was two bugs on top of each other. Reversing C's fills didn't roll back the last trade price, so the engine thought 100 had traded, and stops trigger on last price. Then the rejection threw away every event from that command, B's trigger and B's fill included.
If you run your own sim, it's worth checking what "last price" means after fills get unwound. The price of the last attempted match and the price of the last trade anyone was told about are different numbers. In my engine, stops, trailing stops and the price collar (when no mark price is set) all used the wrong one. So did the reference price my own backtest package falls back to.
None of my tests caught it, because nothing impossible happened. The book never crossed and every lot was accounted for, so all the invariant checks passed. They're good at catching an engine that breaks the rules and useless against one that applies a wrong rule the same way every time.
So I wrote a second matcher that's deliberately slow and dumb. Two sorted lists, linear scans, and no code shared with the real engine. Both get the same random order streams, and after every single order I compare everything: fills, the whole book in queue order, depth, events. When they disagree, the failing stream gets shrunk down to a few orders I can paste straight into a test.
To check that it actually works, I planted 21 bugs in the real engine (LIFO instead of FIFO, fills at the wrong side's price, depth totals that drift). It caught all 21, each with a repro of 1 to 4 orders.
It did not catch the stop bug, though. I found that one myself while writing the spec for the harness, just from reading the code, and then the slow matcher ended up copying the same behaviour. When both sides share the same wrong idea they agree, and the comparison says everything's fine. I pinned it with a failing test and fixed it separately.
The random streams did find something I hadn't seen. Under pro-rata matching, a trader buying into their own resting sell left the book crossed at 100 bid / 99 ask, and the venue's self-trade setting was ignored in all five modes. A venue set to allow self-trades didn't even get the self-trade.
Write-up with the details: [https://intrepidkarthi.github.io/orderbook/docs/differential-testing.html](https://intrepidkarthi.github.io/orderbook/docs/differential-testing.html)
Code (MIT): [https://github.com/intrepidkarthi/orderbook](https://github.com/intrepidkarthi/orderbook)
For those of you running your own backtester: when an order's fills get unwound or rejected, what does your engine use as last price? I'm curious how common this hole is.

If next summer goes well and you get a return offer, I'd seriously question whether you need the masters at all. For trading at those shops the internship basically is the pipeline, and a US MFin on top of a return offer is a lot of money for not much.

Profile's strong for the whole list though, CMU and Berkeley especially. Princeton and MIT MFin are small classes so they're reaches for pretty much everyone. If you're actually leaning toward research over trading then Yale stats or ICME make more sense than the MFins.

The Jonathan Clements Getting Going on Savings Initiative is up and running!
This joint effort involving the John C. Bogle Center for Financial Literacy, a team of academic researchers and the City of Boston is spreading the word about Roth IRAs to working teens and young adults, many from lower-income backgrounds. And most concretely, as envisioned by the late financial columnist Jonathan Clements, it has started the process of making payments of $1,000 each to selected qualifying individuals to fund Roth IRAs. The academic researchers will study if payments like this are an effective tool to help young adults establish an early habit of setting money aside for later in life.
The Bogle Center Board is delighted to share an update on the progress so far, the great work of our partners and plans for the future. **Please note that given the outpouring of contributions and the time needed to build out the program, the Bogle Center isn’t seeking additional funds for the Clements Initiative at this time.**
**A busy summer in Boston**
After a small pilot in 2025, the Clements Initiative saw a full rollout across participants in Boston’s 2026 summer jobs program for teens and young adults. It has been a complex and labor-intensive effort led by researchers associated with J-PAL North America (a research center based at MIT), Boston’s Office of Youth Employment and Opportunity and the city’s Bank On Boston program to help residents access high-quality, low-cost financial services.
As of late September, the team had presented workshops on Roth IRAs and investing to 487 summer employees. There were more than 30 workshops because program participants were dispersed across city departments and nonprofit organizations.
Of the workshop participants, 154 were 18 or older and thus eligible for the Clements Initiative payments and the related research study. As of late September, the team had enrolled 79 people into the study and had assisted 73 of them to open Roth IRAs at Vanguard Group. Recruitment and account-opening meetings were continuing. Meanwhile, in a second round of meetings, the team is giving each new IRA holder $50 from the donations to the Clements Initiative and helping them deposit and invest those funds in a global stock exchange-traded fund in the IRA.
The team hopes to sign up 100 study participants from the summer 2026 cohort. Soon those participants will be randomly assigned to either the treatment group or the control group. The young adults in the treatment group will receive a further $950 contribution from the Clements Initiative funds – for a total of $1,000 each – and those in the control group will receive a second $50.
Over time, the researchers will study if the larger upfront gift leads to greater financial well-being and behaviors associated with building long-term savings.  
**Challenges addressed**
Turning the Clements Initiative into reality has involved a lot of operational challenges that were successfully addressed over the past year. The J-PAL team – which includes professors at University of Chicago, Northeastern University and Harvard University – obtained grants to hire undergraduate and graduate students to assist with the large number of workshops and the multiple meetings needed with each recipient. To address a language barrier, they had all the workshop materials translated into Spanish.
To track the study participants’ Roth IRA activity over time, the researchers are partnering with Vanguard, which will supply anonymized data on the participants’ conduct of their accounts.
Separately, the Bogle Center reached an agreement with the University of Chicago that will spare the Bogle Center from having to make payments to the individual program participants. The Center, which has a volunteer board and no employees, will make donations to the university, and the university will then use a third-party payment platform to make and track what are likely to be hundreds of payments over time.
**Bigger plans ahead**
It’s still early in the implementation of the Clements Initiative, which was announced in [May 2025](https://boglecenter.net/wp-content/uploads/Jonathan-Clements-Getting-Going-on-Saving.pdf), four months before Jonathan’s death. And the successful summer 2026 rollout in Boston is just one step along the way.
The J-PAL team is hoping to expand the program geometrically in 2027 and is talking with potential partners in multiple states to make that happen.
The Bogle Center and our partners are grateful to have substantial funding for the Clements Initiative. Jonathan donated the royalties from [The Best of Jonathan Clements](https://www.amazon.com/dp/0988780348), a collection of his *Wall Street Journal* columns, to the Bogle Center to use in the Clements Initiative. The Center, a 501(c)(3) non-profit, has also proudly accepted donations for this project, both before and after Jonathan’s death in September 2025.
If there are 50 participants in the treatment group and 50 in the control group for this year, that would add up to expenditures of $55,000 from the dollars held by the Bogle Center for the Clements Initiative. And the Bogle Center would have more than $400,000 remaining in those funds to support an expanded program in future years.
The Bogle Center and our partners continue to be extremely proud of this undertaking and its ability to change lives. **But as noted above, given the outpouring of contributions and the time needed to build out the program, the Bogle Center isn’t seeking additional funds for the Clements Initiative at this time.**

There are many posts seeking help. Yours stood out because you wanted to see the journey that might be shared. I found something of interest when comparing an "everyman's portfolio" (starting capital under $250) with my current strat (large at $100k, sweeping $2k/wk). I used the same metrics to screen for entry (VWAP, VIX, Price Action, and Fourier clustering). Augmentation with Hidden Markov Model (melon thumping). Many deets under keywords MIT Blackjack Algo and superprofitability, search those first if interested.
My (retired EE) background is Control Theory, staying engaged in my encore career after retiring 15 years ago (at age 55). What I see in the bottom plot, the slopes are identical, meaning the algo remains unchanged in profit delivery - save for a constant of integration. My inference, the algo is an eigenfunction that sweeps profit with improved deviation in tracking the unit ramp function. CT models show improved settling time with higher loop gain. A type 1 system uses a single integrator to zero out steadystate error. A unit ramp would exhibit finite error, clearly seen in the left curve. The right curve is detailed in the top plot. Observe the deviation is much reduced, but still an ongoing finite value. Main difference I see, The TP in cells W1 &W2. Lowering the TP allows the algo to operate as a quant scalp below the market's Brownian Motion. High probability of success on trades. Note the asymptotic convergence of the green segments for weeks 2-4 (no zero on log scale so week 1 isn't observed) to the slope value, matching the left curve (column AM cells 31 & 34 identical).
Keeping the entry/exits tightly grouped (Sharpe above 3) assures regime change immunity. Similar for both column Z72 and AA72, but improved with new. Fractional Kelly sizing (under 1.4%) ensures going bust is remote, important on large sum, tolerable on the everyman's.
Several methods in trading for the past 3 weeks, beginning was test the channel limits, week 2 was toe the line with "shark fin" into the weekend, week 3 was channel fill with multiple trades (reduces effort at termination of the week). The latest numbers post to kinfo verifieds tomorrow. My profile is dark on sharing to inhibit copy trading, Poppy Gekko.
https://preview.redd.it/isju5u8wkwsh1.png?width=1591&format=png&auto=webp&s=95bf431f182f16d5c78b114085d126ddccd18533
Hope this helps, stay in demo until you have sufficient data (rule of thumb for statistics, 30 samples, no need to count every grain of sand) to hit the Sharpe number discussed.
Good luck.

I built NewsWave on Sept 30 by directing Claude Code agents. I typed no code by hand. 564 automated tests pass, and two adversarial review passes found bugs that I fixed.
How it works:
\- News comes in. Claude classifies each headline as BULLISH, NEUTRAL or BEARISH. That is its only job.
\- Plain Python does the rest: relative volume of 2x or more, a 1.5% or larger price move, then a pullback to the 5-minute 9 EMA, then a breakout entry.
\- It trades on an Alpaca paper account with $6,000, as a 6-month experiment.
Video with the prompts: [https://youtu.be/XHyMDYVCp9Y](https://youtu.be/XHyMDYVCp9Y)
Code (MIT): [https://github.com/AskElira/newswave](https://github.com/AskElira/newswave)
Happy to answer questions about the agent setup or the rule chain.

I've been building an open-source matching engine in Go for a while. This is the worst bug it has had, and it's exactly the kind that would sit unnoticed in a backtester for months.
Four orders, default settings:
1. Seller A rests 3 @ 100.
2. Seller A rests 5 @ 105.
3. Trader B rests a buy stop at 100, market for 2. Nothing has traded yet, so it waits.
4. Trader C sends a fill-or-kill buy for 5 @ 100. Only 3 are available at 100, so the order can't fill. The 3 it matched get reversed and C is rejected.
B's stop fired anyway. B bought 2 @ 100 from A, a real fill that took A's order from 3 lots down to 1, and the only message anyone got was "C rejected". A and B were never told.
It was two bugs on top of each other. Reversing C's fills didn't roll back the last trade price, so the engine thought 100 had traded, and stops trigger on last price. Then the rejection threw away every event from that command, B's trigger and B's fill included.
If you run your own sim, it's worth checking what "last price" means after fills get unwound. The price of the last attempted match and the price of the last trade anyone was told about are different numbers. In my engine, stops, trailing stops and the price collar (when no mark price is set) all used the wrong one. So did the reference price my own backtest package falls back to.
None of my tests caught it, because nothing impossible happened. The book never crossed and every lot was accounted for, so all the invariant checks passed. They're good at catching an engine that breaks the rules and useless against one that applies a wrong rule the same way every time.
So I wrote a second matcher that's deliberately slow and dumb. Two sorted lists, linear scans, and no code shared with the real engine. Both get the same random order streams, and after every single order I compare everything: fills, the whole book in queue order, depth, events. When they disagree, the failing stream gets shrunk down to a few orders I can paste straight into a test.
To check that it actually works, I planted 21 bugs in the real engine (LIFO instead of FIFO, fills at the wrong side's price, depth totals that drift). It caught all 21, each with a repro of 1 to 4 orders.
It did not catch the stop bug, though. I found that one myself while writing the spec for the harness, just from reading the code, and then the slow matcher ended up copying the same behaviour. When both sides share the same wrong idea they agree, and the comparison says everything's fine. I pinned it with a failing test and fixed it separately.
The random streams did find something I hadn't seen. Under pro-rata matching, a trader buying into their own resting sell left the book crossed at 100 bid / 99 ask, and the venue's self-trade setting was ignored in all five modes. A venue set to allow self-trades didn't even get the self-trade.
Write-up with the details: [https://intrepidkarthi.github.io/orderbook/docs/differential-testing.html](https://intrepidkarthi.github.io/orderbook/docs/differential-testing.html)
Code (MIT): [https://github.com/intrepidkarthi/orderbook](https://github.com/intrepidkarthi/orderbook)
For those of you running your own backtester: when an order's fills get unwound or rejected, what does your engine use as last price? I'm curious how common this hole is.

I know these posts are annoying but any feedback is helpful as I don't have too many mentors who are able to help me with this.
Academics:
* Undergrad: 3rd year at top UK uni (think Oxbridge/Imperial/LSE)
* Major: econ + data science
* Year 1: 67%, Year 2: 77% (top 10% of cohort and First Class in all Y2 courses)
* Relevant coursework includes probability & statistics, multivariable calculus, linear algebra, stochastic processes, algorithms & data structures, econometrics 1 & 2, machine learning 1 & 2, optimisation, databases, micro 1 & 2, macro 1 & 2
* GRE: 170Q / 160V / 4.5 AW
Internships:
* Did Quantitative Trading internship this summer and incoming intern next summer (think CitSec, Optiver, Jump, SIG, DRW, IMC)
* Springweeks at 4 quant firms
Other:
* Undergraduate research assistant, completed a supervised project with econometrics / ML focus
* Completed MITx MicroMaster's in Finance with 90%+ final grade
* Society leadership roles at my uni
* References should be pretty decent i.e. mainly lecturers saying I ranked very high in in their courses and 1 from professor I did research with
Current school list:
* Princeton MFin
* MIT MFin
* Stanford ICME Mathematical & Computational Finance
* Yale MS Statistics & Data Science
* Harvard MS Data Science
* Berkeley MFE
* CMU MSCF
Any thoughts on which schools are realistic/reaches, or anything significant I could add would be really appreciated, thank you.

Haven't traded specific retracement levels, rolled my own strat. Results on kinfo verified (dark share, no copy trading) suggest no reason to change. I am, however, a firm believer in Fourier, Fibonacci, and statistics (retired EE, authored a book on Fibo). superprofitability on the MIT Blackjack algo that I'm testing. Search those keywords for deets. Getting the posts out there for LLM's to pick up.
Top RH scale runs 0-100, reflects time-localized SPY normalized performance. LH scale 0-8000 is profit on a 4-week window. Shows $2k/week > $100k/yr expected. Uses fractional Kelly (1.4% of portfolio per trade at-risk) and Sharpe above 3 for entry/exit (for regime change immunity). TP is under 4%.
https://preview.redd.it/5uu2woif8psh1.png?width=945&format=png&auto=webp&s=46f2f864fde60d9b45b5d5edf83307fd059ca15b
Chart is current today, kinfo verifieds are from yesterday (today's trades post tomorrow).
Strat has traceability to Control Theory State Variables, with Hidden Markov Model as an augmenting input. High loop gain reduces error to a unit ramp function (tight channel running to 4th week target).
Fire to the natives seemed like voodoo to those uninformed. STEM is definitely not voodoo.
Cheers.

MIT says were about to be AI's bitch within 5 years

Isn't T10 like the ivies and Stanford MIT cmu Berkeley and all? I thought UCSD is equivalent to what NITs are in India, sry if I am wrong I am not very aware of it. I am an undergrad student rn.

Probably not at all. If you're doing well you'll probably just fck it all up if you start changing things. Our brain is a wonder, it's an incredibly powerfull machine and it works well. Intuitive trading is a rare skill because you're obviously capable of recognising patterns in real time and acting on them. It's very very hard to program a machine to do that unless you're a MIT wiz. Happy to hear you're doing well, keep it up.

Lisa is a MIT graduate and a women. AMD for decades now I think was recognized to be one of THE places to work at if you are LGBTQ+.
I highly doubt she aligns with Trumps views. She is just putting her fiduciary duty before politics.