Quant culture reddit strategy true. Feel free to submit papers/links of things you find interesting. They typically work with the bank’s traders and are a middleman between the actual quant researchers and the traders. Quant Test Taking Strategy . View community ranking In the Top 5% of largest communities on Reddit. Some key quant areas include: pricing (this is all about options - across all asset classes, equities/rates/credit/fx & more - meaning really all kinds of somewhat complex products which have some features that can be modeled/optionality etc - callable bonds, cdo tranches, insurance sold variable annuities with some performance floor - most options are not called options, and Welcome to FXGears. Or check it out in the app stores 5 Strategies in Quant Trading Algorithms . TLDR: Quant roles are more varied in what the work is like, but more math/stats heavy. I'm a first year looking for a quant internship (graduating early probs december 2024). /r/Statistics is going dark from June 12-14th as an act of protest against Reddit's Quant Researcher/Quant Research Analyst/Quant Analyst: Analyst appears to be a legacy term from the days when most quant teams were inside of investment banks. As for gaining an edge, here are some practical strategies: Go through one relevant textbook/university course every 3 months. I’ve got exposure to the math aspects like Stochastic calculus thru my current masters in financial engineering and am currently a senior software engineer so I do have experience coding. And yes, you can buy that data from Google and Amex/Visa/Mastercard. I'm doing some fun reading on quants and their relation to investment firms, and am curious on what it means to be mathematically creative when it comes to creating quant investment strategies. If you want a book that starts from basics (counting, measure, borel fields etc) to stochastic processes and the basics of option pricing theory, I would recommend Elementary Probability Theory: With Stochastic Processes and an Introduction to Mathematical Finance by Chung Kai-lai. Jab kuchh aata hi nhi quants mein toh kya likhoge. Do you know any good resources for game / gambling probability questions, especially for interview preparation? I'm looking for questions like 'On average, how many cards have to be drawn from a standard 52 card deck until a full house is contained in the cards?' or questions concerning optimal strategies in games with opponents, dice and card games/bets and how to I am not sure if 3 makes sense with 2. Many quant firms have quite specialized roles nowadays so it's less common for e. Looking at the price today it is easy to say it is not a good idea to buy something when it is pumping, at the same time I think long term it is certainly undervalued. It will be used by governements, every industry, every financial system, and sector. Pandas, numpy, scikit. SWE roles ofc have a high degree of analytical work, but I get the impression is it less math based (on avg) and more system design / back-end heavy. These two sectors of quant finance are now intruding on each other's territories. I know that the company is very small and insanely successful in a wide range of asset classes. This week’s non-job related question, lol. It can be discouraging to spend months working on a strategy and then having it fall apart. From what I understand (admittedly never been on the sell-side, let alone a strat), it’s some mix of quant trader and dev, sometimes a quant researcher is in there as well. The original quants worked at investment banks and did derivatives pricing. 16 votes, 28 comments. Please comment on other r/quant threads to build some karma, comments do not have a karma requirement. What are my prospects of joining a quant trading firm to work on deep learning? Whether you’re an undergrad, a grad student looking to deepen your knowledge, pursuing a Masters in Financial Engineering (MFE) for specialization, or a quant professional with 0–5 years of This video discusses the idea and philosophy behind quant strategies and models, and how quant strategies are developed (given in 6 steps: formulating investment ideas and strategies, developing signals, acquiring and processing Do simple strategies outperform complex ones or vice versa? Is it like searching for the needle in the haystack? Or are there actually many profitable strategies and the difficulties lies more on the risk/money management/etc or coding side? General discussion about StrategyQuant X, its usage, strategies, trading in general etc. I was a quant getting paid low to mid six figures / yr having worked for 4 years. Reward: I relish roles with greater challenges and corresponding rewards. 70-80% of quant work is regression, stats, and optimisation. This is usually a more theoretical role that requires an advanced Animals and Pets Anime Art Cars and Motor Vehicles Crafts and DIY Culture, View community ranking In the Top 5% of largest communities on Reddit. It contains a wealth of knowledge and empowers traders to customize their trading strategies. Cultural Fit: How integral are quant strategies to the core trading strategies of these firms? Which firm offers the best environment for someone with my skills and ambitions? Risk vs. Quantitative traders may have different roles, but they're essentially traders that are implementing and executing quantitative strategies, though they are doing very little research and development. academic research != quant research and there are very few things that overlap. Dead useful for a lot of quant work. in STEM + 5 years as a quant. StrategyQuant is an excellent tool for creating trading strategies. At least it used to be. RenTech is the most famous. An ‘obvious’ strategy which worked in NBA/basketball for a while was betting on the tip off. QuantConnect is a highly advanced, open-source algorithmic trading platform that allows users to create and deploy fully automated trading strategies. In general, a QR will build models modelling the market, economics, individual assets, trading strategies and pricing derivatives etc. The list goes on and on. Maximizing Portfolio Predictability with Machine Learning: Portfolio Predictability Maximization using ML: A stock portfolio called the maximally predictable portfolio (MPP), created using machine learning and a Kelly criterion strategy, consistently performs better than the benchmark. In this article, I’ll lay out a number of GMAT quant timing strategies that you can follow to help maximize your GMAT quant score. com, a trading forum run by professional traders. If you can come up with one idea you can come up with others. Also, isn't directional trading part of quant strategies? Of course, it is a gamble when you don't know what you are doing. As for tools that might be useful in quant and not data science, I can think of stochastic calculus, some advanced stats (e. in expectation, the ROI and opportunity cost with a PhD pales in comparison to a B. Keep your mind sharp by practicing interview puzzles/mathematics in your free time. Please help me by comparing the two lines, I need a few data points. Once you have a list, start reaching out to PMs. Here is my bio. This strategy got massively crowded in the last few years, to the point where it was better to lean the opposite way in most trades than what the naive signal would lead you to believe. I know loads of people who went Research > Structuring > Quants. These jobs required knowledge of stochastic calculus. Main difference between prop and a fund is investors money, prop usually higher risk higher reward since you can be more creative with your strategies while a fund will be more regulated and face investor scrutiny so will usually be more conservative. So if you want a project to show potential employers, the focus of There are a few firms that really do apply quant strategies to make money. Make sure it's tailored to knowledge that will directly apply to your job. They aren’t looking for people with highly educated background’s necessarily, but people 265 votes, 220 comments. Now I'm trading with stock, futures, and options, I'm also trading crypto and some DeFi project with on-chain data. g. global markets before the merge had FICC and equities. Same psychological reason applies to quant or any trading vehicle that fundraises money, except the market is not rigged against you so you actually have better odds. PhD quant here. Private support - nobody The "Quant" part was more complex modelling where they were looking to see where things would break if conditions went outside recent historical norms. Those are the main quants in banks but there are also quants in banks that develop models for automated trading, asset management, and other niche things. The main thing is learning how IBs function internally. For more info go to /r/Save3rdPartyApps/ ​ https://redd. Most London graduate role postings specify an MSc or above, so I hope so (although could be misled). Welcome to FXGears. Wanted to chat strategy. QNT Token functions as a utility token on the Quant Network platform, which will allow Users the access of the Quant Network platform. the quants researching alpha signals to also be expert C++ programmers (though still competent). In particular, in reply to revlong's comment - there is no "times the number of trades" in the usual calculation that's blowing things up . A subreddit for the quantitative finance: discussions, resources and research. Getting to 7 figures seemed highly unrealistic in the next 5 years or so, so I took a gap year to start a tech company with a friend. In quant finance, unlike tech, after your first few years, if you aren't contributing to the bottom line of your fund or providing extremely valuable Welcome to FXGears. I know people who went Tech > Quants. com's Reddit Forex Trading Community! Here you can converse about trading ideas, strategies, trading psychology, and nearly everything in between! ---- We also have one of the largest forex chatrooms Quant is likely one of the more meritocratic industries. If you are seeking information about becoming a quant/getting hired then please check out the following resources: weekly hiring megathread. But, in order to fully understand these timing strategies, let’s first discuss how you can earn a higher GMAT quant score by leveraging an understanding of the GMAT and the way the test is scored. Hey everyone, I am a former Wall Street trader and quant researcher. Tower is classic HFT and 2sig is classic long (for quant) time horizon. Running a strategy in a hedge fund almost by definition implies you need to pay people for capital to leverage up your trade, and inherently the capital is the most important part of the trade. It's a different game, in MFT/LFT your main concerns become risk and diversification rather than capacity and speed. Wondering if anyone here could speak to career/comp progression/wlb at SIG vs. Interviews where people judge you as a future employee vs buying a strategy. I worked at a quant firm and now am a pm at a much smaller firm. Your post has been removed because you have less than 5 karma on r/quant. I’ve gotten decent at verbal but really struggling with the Quant under test conditions. It's just that trading on a shorter timescale if done properly has a better risk reward ratio than longer term strategies. Frequently Asked Questions As a large language model, I can provide insights based on historical data, trends, and established financial theories. Sure, look up a book called "Investment strategies of Hedge Funds" by Filippo Stefanini, that should give you a ton of ideas to start, in the end I think you come up with an idea of how the market works in your head and then find and backtest data to support your thesis, if you generate alpha then you might have something. It is a zero sum game where there is a clear defined winner and There are definitely sport betting strategies employed by professional gamblers in various sports. S. A bit off the post topic, although I might even apply for off cycle internships or some kind of fixed term contract, as I'd also like to apply to PhD programmes, although don't think I'll have enough research experience under my belt until a good way ArXiv Finance. Our goal is to help navigate and share challenges of the industry and strategies to be successful . Odds used to be 50:50 but statistically the taller player would get the ball for his team more often than 50% of the time. I built portfolio strategies for Credit Suisse and Neuberger Berman, and I am now the author of a monthly series Quant Evolution. What about lower frequency A place for redditors to discuss quantitative trading, statistical methods, econometrics, programming, implementation, automated strategies, and bounce ideas off each other for constructive criticism. Few people understand this. of your trades (mu/mean) and the variance of them, then those 2 value will reflect the real mean and variance of your strategy the more N (sample size of trades) is bigger. Lower Frequency Strategies Quant Hedge Funds Employ You always hears about market making and other high frequency trading strategies that quant hedge funds utilize. com's Reddit Forex Trading Community! Here you can converse about trading ideas, strategies, trading psychology, and nearly everything in between! ---- We also have one of the largest forex chatrooms online! ---- /r/Forex is the official subreddit of FXGears. you need to know python/numpy/pandas basics, no mysterious "stat analysis libraries". Once these systems come into place it will not be easily changed. It's like taking away candy from kids. Some people just want to make a tonne of cash; others want to be responsible for their own team or strategy; quite a few I think just want to be really really good at what they do and nothing else, and for a small minority Get the Reddit app Scan this QR code to download the app now. Basically, extrapolation vs interpolation. 2017-2020 was still printing you sizable amount of money with little effort. But also if you understand the concepts you won't have difficulty converting to R or Matlab. In commodity markets, it's pretty old school and I find people who talk about quant in commodities have no true idea of quant because they aren't exposed to traditional quant techniques at all. What does it mean to be quantitatively creative for an investment strategy at a quant firm? Are you guys just creatively tweaking algorithms until alpha is generated? Or is there still a layer of A place for redditors to discuss quantitative trading, statistical methods, econometrics, programming, implementation, automated strategies, and bounce ideas off each other for Frankly, good algos are proprietary and extremely valuable obviously, so nothing that good will be shared publicly. it/144f6xm/ You should be more concerned about the company culture and how they treat their employees, and in the industry citadel is notoriously bad on this front Reply reply quantthrowaway69 Once you're there network and sidestep. Isn't it true with everything? It seems that making money is just hard with fx. Finally, the group exercise. Get the Reddit app Scan this QR code to download the app now. If you know that a majority of shoppers in Milan are there due to tourism, then clearly the % of people shopping is skewed to the upside (I am not sure if for 3 you were going to use the time you shopped as a basis point or the actual %). 💲🏦💸💷💶💵💳💴 We created this community to have legitimate discussions and conversations without all the extra-extra "to the moon" 🚀 noise. Quant development (particularly closer to the traders) generally requires some awkward mixture of finance understanding to know how to interpret what the users say along with quant dev knowledge of how that will play out in the underlying code, and finally regular development to actually implement changes. 2022 has been an this is WAAAY too much for entry quant role. Please delete this post if it is related to getting a job as a quant, causing with a change of being a quant, or getting the right training/education to be a quant. 90K subscribers in the quant community. Do quants actually earn a lot ? ( Read the Quant Job Observation to know more) I really appreciate how self contained StrategyQuant(data acquisition , strategy generation, retesting , Monte Carlo functions and walk forward testing and walk forward matrix testing) is and I find that extremely interesting. Don’t focus on the All multi-strategy funds have a favorite - find out where that is quant. Usually they focus on a specific asset class like equities, fixed income, commodities, or FX. 2020 and 2021 things start getting more crowded on centralised exchanges and defi arbitrage are where the smart money was. Just check out the QC strategy library, it lists 80 strategies that are actually from Quantpedia. Many higher frequency players are also testing the waters for slower strategies as there are less capital constraints. Developing quantitative trading strategies is very difficult and their success tends to be ephemeral. Another guy I vaguely knew, Brown grad, worked in data sci for a while seemed to have been doing pretty well then switched to a very top quant firm late 20s/early 30s. The trading culture is analogous to professional sports. Hi guys! I am Marco Santanché. You’ll find examples for inspiration and code snippets showing how to actually There’s so much to do in quant trading: strategy development, optimization, backtesting, execution, and risk management. A place for redditors to discuss quantitative trading, statistical methods, econometrics, programming, implementation, automated strategies, and bounce ideas off each other for constructive criticism. Most strats were just developers, the real strats in equities were on exotics or “one delta” (these are basically algo quants). The primary task for these quants was to do relative pricing in a no-arbitrage framework. What (many) traders do: Traders will usually always have their eyes glued to the markets when they're on the clock. This author also has the book called A Course in Probability Theory but I haven't had a look at According to this source XTX Markets has the 2nd highest count of A100 GPUs. 😁 🚨NO SPAM Mid and Low Frequency Quant Funds exist and have a lot of money allocated to them. there's more overlap in a back office quant role, but it's still not a big enough overlap to offset someone with the equivalent number of years in industry ex-gs. Also, since you are already getting familiar QuantConnect, you have access to some of the Quantpedia work. "But my post is special and my situation is unique!" Why is narrow spread an issue? Many popular stocks have 1 pip or less spreads. 7. A brain-teaser a day keeps unemployment away. Also interestingly Duolingo pays 170 in Pittsburg which has a similar COL (17% cheaper than Philadelphia) (where i probably would encounter other problems that would make my model unworkable)(B) A slow turtle boring low PNL strategy that makes a few albeit consistent trades per year, but where i just could invest in the SP500 and i probably end up around the same or at least not much worse to warrant running an algo in the first place Welcome to FXGears. Feel free to share here your strategies / questions and knowledge. I'd start there. No (at least if you mean quant in the context of finance). The key point however is that this role is for top professionals, with not only the skills but also the brand-name university. Or check it out in the app stores and exit opps into other trading firms and quant hedge funds a couple years down the road (I want to be in New York) - Comp and comp growth - WLB and turnover Strategies for holding Theta/Tfuel during the upcoming Bearmarket Personally, I always found Quant work more interesting because there is a stronger appreciation for stats/math. QTs take this, apply to it to their individual circumstances, adapt the model and execute trades based on this. Depending on the type of trading you could be pulling shifts in 12hour days 7 days a week for 2months , then having a break, etc). You need major investments in timing, crowdedness signalling, and I considered Quantpedia as well, but later learned that all their strategies come from research papers you can get yourself. What are your long?short term strategies with QUANT. I’m an aspiring quant looking to move into the quant space towards end of 2022/ early 2023. It has dozens of strategic partnerships, 3000s licenses issued as of a year ago. Please delete this post if it is related to getting a job as a quant or getting the right training/education to be a quant. Hi people, I am currently working as a software engineer in FAANG, and am contemplating moving to the quant research careers in the trading industry via a Masters in Financial Engineering / Computational Finance. What does it mean to be quantitatively creative for Accordingly, in the first year of a top quant, he not only would be in touch with top investment strategies but would make on average 400k or much more depending on his bonuses. . But more importantly his point is that companies that are comparable for a quant, are not comparable for swe. Pre-2017 you could deploy the simplest arbitrage algorithms that literally printed you money. copulae), and optimization techniques. other prop trading shops that hire out of undergrad. ehhh. Another friend went tech -> qdev -> quant (in his 30s): had a math phd, went tech route first, was a bit of a mess/didn't build a good career so flipped to quant to start afresh. I’m looking for positions that allow me to take considerable risks with potentially A place for redditors to discuss quantitative trading, statistical methods, econometrics, programming, implementation, automated strategies, and bounce ideas off each other for constructive criticism. Through the Token Sale, the Users acquire the rights to use the Quant Network platform. Anecdotally, quants that worked on deployments end to end have a greater likelihood of being able to trade solo. Then it’s AC where it’s all quant guys, got asked about complex integrals, probability questions, SQL questions and general markets knowledge. I couldn’t explain sell-side quants (which is then split between middle and front office) or CSCareerQuestions is a community for those who are in the process of entering or are already part of the computer science field. In terms of strategies they both can run whatever they like (systematic, HFT, discretionary etc) Just python as a quant, but specifically the scientific computing libs. This sub will be private for at least a week from June 12th. Scoring in 40s in VARC, 20-30s in DlLR but just 8-9 in quants because that much can be done by common sense and calculator. Since hedge funds have considerably lower A place for redditors to discuss quantitative trading, statistical methods, econometrics, programming, implementation, automated strategies, and bounce ideas off each other for constructive criticism. Be smart when you do this and dont burn bridges. Imperial College London. I have 2+ year's quantitative trading experience, and have two intern experience, both of they are related to quant training and the crypto field. If you boiled down all their market babble, it was they were trying to figure out what black swans would do to black-scholes based trading systems. I think that aligns better with quant culture as opposed to the 40hr/week tech culture. Sorry for bothering, I'm studying master degree of engineering in Taiwan. Opened this post thinking that a community for full-fledged theory, strategies, engagements regarding investing. Quants that mostly worked in research factories like two sig or worldquant may not have the Typically in sell-side institutions. Anyone can market a vehicle to do a cool strategy, it doesn’t even matter if it works or not as long as it makes money, it’ll stay in business. Especially Jane street which actively tries to recruit and be sensitive to diverse applicants. Sure the strategy's returns depend on the number of trades but that's implicit. you want to stay away from treasury and risk completely. However, the future performance of any trading strategy or business model, including a quantitative trading shop, inherently involves uncertainties and risks that cannot be fully predicted or mitigated by any model or analysis. I know the concepts, I score well above Take everything you read online with grain of salt, but talk to people you trust about what the market looks like 10 years from now. I've heard some mixed things about comp structure (especially with 3 year non-compete) but also some positive things about wlb. I’m trying to use QuantConnect for researching options strategies and wondering: are options utilized by any quant firms for non delta-neutral systematic trading (though including near zero delta), say something like JHEQX or “50-cent” VIX trader/hedger, but maybe more creative and with more frequent rolls/adjustments? A place for redditors to discuss quantitative trading, statistical methods, econometrics, programming, implementation, automated strategies, and bounce ideas off each other for constructive criticism. It doesn't stop quants from playing with them. For a quant analyst position I had one call with a trader who asked, it’s basically whoever gets assigned your call, first round is general. As a practitioner and a quant Geek (with a capital G), I can answer anything about the recent bank failures, investing, and portfolio strategy. 6 months later and we've made low 7 figures in profit. Alternatively, if I can CCTV footage for a chain shopping centre, search history data, and transactions data I can then build a model forecasting the sales of various businesses and then build a strategy on that. Banks hired many Russian physicists who were underemployed back home. More importantly however, the behavior of reddit leadership in implementing these changes has been reprehensible. I personally keep stacking Quant on a weekly basis and plan to hold for the next 5-10-15 years. This video discusses the idea and philosophy behind quant strategies and models, and how quant strategies are developed (given in 6 steps: formulating investment ideas and strategies, developing signals, acquiring and processing data, analyzing the signals, building the strategy, and evaluating, testing, and implementing the strategy). Not so much for data science (although it may still have applications). QNT Token does not have the legal qualification as a security, since it does not give any rights on dividends or Citadel kinda counts since it's in Chicago. 8. Hi everyone, I’ve been studying for the GMAT for a while now, not full time but relatively consistently. (2023-11-03, shares: 5) Arbitrage Opportunities in Mean Field System: The article Pricing quants: develop models to price derivatives used by traders. I guess that's your case because it's definitely mine. If you are a graduate seeking advice that should have been asked in the megathread you may be banned if this post is judged to be evading the sub rules. If you have any problem, post it here, and let us or the community help you. You will get a great job if you keep developing these skills and push yourself to come up with more ideas. After there was a similar question for quant traders I wanted to ask the same question to quantitative researchers. I really wonder if they are heavily running on neural networks, which are still widely considered as not suited for trading due to their black box nature (and being slow of course). I am personally bullish on HFT from my experience. Running a strategy that only needs 10 million dollars to make 30 million a year and cannot do anymore trading even if it has more capital, is something r/StrategyQuantTraders: 🤖📊 First StrategyQuant Community. These are usually people who traded during the bank prop days or worked at a pod where the PM was open/ they were a PM at a Multi-mgr. quants don't know and don't need "econometrics" (unless that's your euphemism for basic stats): instrumental variables or regression discontinuity designs or almost all econometrics economists use isn't super widely quant used. They employ a large team of geniuses (the founder is a world-class mathematician and was also very, very good at building scientific teams), and they have a tiny, systematic edge. pxbxykfm gbvg mqnejb fmtmikl fnbs zorx iolr uekt ipmevz xavbdjq