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Trending Research (Top 25)

The trending research page have established filters to look at the research of the last month ordered by standard popularity measures like downloads and social media attention.
Table
Title
Author
Category
Date Published
Date Retrieved
Date Updated
Description
Posts
Readers
Score
Tweeters
URL
Table
Name
Category
Contributors
Created
URL
Forks
Stars
Description
Last Update
Trending Repos
0
2023/01/07
https://github.com/Hello-SimpleAI/chatgpt-comparison-detection
21
315
Human ChatGPT Comparison Corpus (HC3), Detectors, and more!
2023/01/29
dsp
Open
Trending Repos
0
2023/01/09
https://github.com/stanfordnlp/dsp
14
181
The Demonstrate-Search-Predict Framework: Composing retrieval and language models for knowledge-intensive NLP
2023/01/29
MusicBot
Open
Trending Repos
7
2016/08/14
https://github.com/jagrosh/MusicBot
1876
3612
A Discord music bot that's easy to set up and run yourself!
2023/01/28
xorbits
Open
Trending Repos
0
2022/07/27
https://github.com/xprobe-inc/xorbits
12
117
Scalable Python data science, in an API compatible & lightning fast way.
2023/01/29
EVA
Open
Trending Repos
1
2022/11/14
https://github.com/baaivision/EVA
31
515
Exploring the Limits of Masked Visual Representation Learning at Scale (https://arxiv.org/abs/2211.07636)
2023/01/29
GPTZero
Open
Trending Repos
0
2023/01/24
https://github.com/BurhanUlTayyab/GPTZero
11
147
An open-source implementation of GPTZero
2023/01/29
gpt-wpre
Open
Trending Repos
0
2022/12/31
https://github.com/moyix/gpt-wpre
12
209
Whole-Program Reverse Engineering with GPT-3
2023/01/29
v2ray-wss
Open
Trending Repos
1
2021/07/15
https://github.com/yeahwu/v2ray-wss
182
759
2023/01/29
simsity
Open
Trending Repos
0
2021/10/13
https://github.com/koaning/simsity
7
96
Super Simple Similarities Service
2023/01/28
musiclm-pytorch
Open
Trending Repos
0
2023/01/27
https://github.com/lucidrains/musiclm-pytorch
9
326
Implementation of MusicLM, Google's new SOTA model for music generation using attention networks, in Pytorch
2023/01/29
metriport
Open
Trending Repos
0
2022/12/21
https://github.com/metriport/metriport
10
186
Metriport is an open source and universal API for healthcare data.
2023/01/27
SHARK
Open
Trending Repos
0
2022/03/05
https://github.com/nod-ai/SHARK
55
373
SHARK - High Performance Machine Learning for CPUs, GPUs, Accelerators and Heterogeneous Clusters
2023/01/29
Promptify
Open
Trending Repos
0
2022/12/12
https://github.com/promptslab/Promptify
13
333
Prompt Engineering | Use GPT or other prompt based models to get structured output. Join our discord for Prompt-Engineering, LLMs and other latest research
2023/01/29
houston.astro.build
Open
Trending Repos
0
2022/12/03
https://github.com/withastro/houston.astro.build
4
109
Experimental AI assistant trained on the Astro docs
2023/01/29
following-instructions-human-feedback
Open
Trending Repos
1
2022/01/25
https://github.com/openai/following-instructions-human-feedback
71
566
2023/01/29
causalai
Open
Trending Repos
0
2022/11/21
https://github.com/salesforce/causalai
5
32
Salesforce CausalAI Library: A Fast and Scalable framework for Causal Analysis of Time Series and Tabular Data
2023/01/29
100-Days-Of-ML-Code
Open
Trending Repos
79
2018/07/05
https://github.com/Avik-Jain/100-Days-Of-ML-Code
9858
39556
100 Days of ML Coding
2023/01/29
awesome-scalability
Open
Trending Repos
86
2017/12/27
https://github.com/binhnguyennus/awesome-scalability
4913
43369
The Patterns of Scalable, Reliable, and Performant Large-Scale Systems
2023/01/29
microstructure-plotter
Open
Trending Repos
0
2022/12/21
https://github.com/will-thompson-k/microstructure-plotter
2
28
Visualize financial market data and trading system behavior on infinitesimal timescales
2023/01/23
simpsom
Open
Trending Repos
0
2017/05/12
https://github.com/fcomitani/simpsom
29
140
Python library for Self-Organizing Maps
2023/01/29
localsend
Open
Trending Repos
3
2022/12/16
https://github.com/localsend/localsend
71
1613
An open source cross-platform alternative to AirDrop
2023/01/29
carbonyl
Open
Trending Repos
4
2023/01/20
https://github.com/fathyb/carbonyl
27
2330
Chromium running inside your terminal
2023/01/29
sliver
Open
Trending Repos
10
2019/01/17
https://github.com/BishopFox/sliver
711
5089
Adversary Emulation Framework
2023/01/29
howtheytest
Open
Trending Repos
9
2020/03/24
https://github.com/abhivaikar/howtheytest
399
4954
A collection of public resources about how software companies test their software
2023/01/29
readpilot
Open
Trending Repos
1
2023/01/17
https://github.com/forrestchang/readpilot
19
562
Read Pilot analyzes online articles and generate Q&A cards for you. Powered by OpenAI & Next.js.
2023/01/29
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Table
Title
Author
Award Count
Comment Count
Date Posted
Permalink
Post ID
Score
Subreddit
Upvote Ratio
I've aggregated all of my research about quant finance careers into this thread.
Open
n00bfi_97
2
14
2023/01/02
https://www.reddit.com/r/quant/comments/101n4p4/ive_aggregated_all_of_my_research_about_quant/
101n4p4
195
quant
0.99
I'm running the entire stock market through my system and have 10+ ML models that pick the best trades . Page 1 is the highest ranked trades
Open
ariesonthecusp
1
75
2023/01/19
https://www.reddit.com/r/algotrading/comments/10foh25/im_running_the_entire_stock_market_through_my/
10foh25
145
algotrading
0.92
Modern Developments Data Engineers Will Witness in 2023
Open
Emily-joe
0
0
2023/01/27
https://www.reddit.com/r/datascienceproject/comments/10mjpo7/modern_developments_data_engineers_will_witness/
10mjpo7
1
datascienceproject
1
Using algorithms or models from papers for commercial use (r/MachineLearning)
Open
Peerism1
0
0
2023/01/28
https://www.reddit.com/r/datascienceproject/comments/10n1s6t/using_algorithms_or_models_from_papers_for/
10n1s6t
1
datascienceproject
1
A python module to generate optimized prompts, Prompt-engineering & solve different NLP problems using GPT-n (GPT-3, ChatGPT) based models and return structured python object for easy parsing (r/DataScience)
Open
Peerism1
0
0
2023/01/28
https://www.reddit.com/r/datascienceproject/comments/10n1s9p/a_python_module_to_generate_optimized_prompts/
10n1s9p
1
datascienceproject
1
A python module to generate optimized prompts & solve different NLP problems using GPT-n based models and return structured python object for easy parsing (r/MachineLearning)
Open
Peerism1
0
0
2023/01/27
https://www.reddit.com/r/datascienceproject/comments/10m7y7d/a_python_module_to_generate_optimized_prompts/
10m7y7d
2
datascienceproject
1
EvoTorch 0.4.0 dropped with GPU-accelerated implementations of CMA-ES, MAP-Elites and NSGA-II. (r/MachineLearning)
Open
Peerism1
0
0
2023/01/27
https://www.reddit.com/r/datascienceproject/comments/10m7y7u/evotorch_040_dropped_with_gpuaccelerated/
10m7y7u
2
datascienceproject
1
Implementing GPTZero from scratch | Reverse-Engineering GPTZero
Open
BurhanUlTayyab
0
0
2023/01/28
https://www.reddit.com/r/datascienceproject/comments/10ne57v/implementing_gptzero_from_scratch/
10ne57v
2
datascienceproject
1
An interesting major project idea for college level related to data science? (r/DataScience)
Open
Peerism1
0
0
2023/01/28
https://www.reddit.com/r/datascienceproject/comments/10n1sac/an_interesting_major_project_idea_for_college/
10n1sac
3
datascienceproject
1
JANE STREET FTTP
Open
Adrina-1608
0
6
2023/01/27
https://www.reddit.com/r/quantfinance/comments/10mnec0/jane_street_fttp/
10mnec0
0
quantfinance
0.18
JANE STREET FTTP
Open
Adrina-1608
0
1
2023/01/27
https://www.reddit.com/r/quantfinance/comments/10mns6i/jane_street_fttp/
10mns6i
0
quantfinance
0.44
quant job prep for bits cse fresher
Open
Creative-Square4506
0
2
2023/01/28
https://www.reddit.com/r/quantfinance/comments/10naxed/quant_job_prep_for_bits_cse_fresher/
10naxed
0
quantfinance
0.25
One Period Binomial Model
Open
ViditOstwal
0
0
2023/01/28
https://www.reddit.com/r/quantfinance/comments/10nc6hz/one_period_binomial_model/
10nc6hz
0
quantfinance
0.5
Cumulative Return Line Charts Slow
Open
turtlerunner99
0
5
2023/01/27
https://www.reddit.com/r/quantfinance/comments/10mn50h/cumulative_return_line_charts_slow/
10mn50h
1
quantfinance
1
Rust for quant finance
Open
Parking_Landscape396
0
4
2023/01/27
https://www.reddit.com/r/quantfinance/comments/10mcq4z/rust_for_quant_finance/
10mcq4z
7
quantfinance
0.9
What maths are irrelevant in the day to day functions as a Quant
Open
Better-Search155
0
21
2023/01/27
https://www.reddit.com/r/quant/comments/10mc5ko/what_maths_are_irrelevant_in_the_day_to_day/
10mc5ko
0
quant
0.36
Tech, frameworks, and other stuff.
Open
cremCake
0
1
2023/01/27
https://www.reddit.com/r/quant/comments/10macy8/tech_frameworks_and_other_stuff/
10macy8
1
quant
0.67
Reliable sources for European, Japanese and EM equity prices and volumes
Open
NachDeR
0
0
2023/01/27
https://www.reddit.com/r/quant/comments/10mpl85/reliable_sources_for_european_japanese_and_em/
10mpl85
2
quant
1
Dollar gamma
Open
WinterAd3357
0
3
2023/01/28
https://www.reddit.com/r/quant/comments/10n5kzk/dollar_gamma/
10n5kzk
3
quant
0.8
One Period Binomial Model
Open
ViditOstwal
0
4
2023/01/28
https://www.reddit.com/r/quant/comments/10napcc/one_period_binomial_model/
10napcc
2
quant
0.58
s&p500 forward earnings
Open
No_Branch_8909
0
0
2023/01/27
https://www.reddit.com/r/quant/comments/10mfoi9/sp500_forward_earnings/
10mfoi9
3
quant
0.72
Moving from UK to US
Open
No_Friendship4988
0
3
2023/01/28
https://www.reddit.com/r/quant/comments/10nc1v3/moving_from_uk_to_us/
10nc1v3
4
quant
1
Does anyone have access to the core us equities dataset from Sharadar?
Open
vacuumcleaner9000
0
0
2023/01/28
https://www.reddit.com/r/quant/comments/10n31cu/does_anyone_have_access_to_the_core_us_equities/
10n31cu
7
quant
0.88
Can anyone recommend a more modern alternative to Joshi's "The Concepts and Practice of Mathematical Finance"?
Open
n00bfi_97
0
7
2023/01/27
https://www.reddit.com/r/quant/comments/10mklr4/can_anyone_recommend_a_more_modern_alternative_to/
10mklr4
12
quant
0.88
Personal Project idea
Open
Mysterious_Can_7570
0
2
2023/01/28
https://www.reddit.com/r/quant/comments/10n1idl/personal_project_idea/
10n1idl
20
quant
0.92
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Table
Name
Comments
Content
Date
Job
Likes
Link
ML Score
Gautier Marti
Open
97
How much does ChatGPT know about quant trading?Let's figure it out!All of the attached book content was generated by ChatGPT from title, to chapters, sections and sub-sections, and the illustration Python/ML/Quant code as well!Even this abstract:"Machine learning has revolutionized the field of quantitative trading, enabling traders to develop and implement sophisticated trading strategies that leverage large amounts of data and advanced modeling techniques. In this book, we provide a comprehensive overview of machine learning for quantitative trading, covering the fundamental concepts, techniques, and applications of machine learning in the financial industry.We start by introducing the key concepts and challenges of machine learning for quantitative trading, including feature engineering, model selection, and backtesting. We then delve into the various machine learning approaches that are commonly used in quantitative trading, including supervised learning, unsupervised learning, and reinforcement learning. We also discuss the challenges and best practices of implementing machine learning models in the live market, including the role of data quality, the importance of risk management, and the need for ongoing model monitoring and validation.Throughout the book, we provide numerous examples and case studies to illustrate the concepts and techniques discussed, and we also include practical tips and resources to help traders and practitioners get started with machine learning for quantitative trading. This book is an essential resource for anyone looking to gain a deeper understanding of how machine learning is transforming the world of finance."#quant #trading #chatgpt #book #ai #ml #machinelearning #learning #finance #data
2022/12/31
Abu Dhabi Investment Authority (ADIA) | Quantitative Research & Development Lead
1167
https://www.linkedin.com/feed/update/urn:li:activity:7014904477610618880
17
jean-philippe bouchaud
Open
92
Fat tails & Diversification I have been fascinated by non Gaussian, fat-tailed distributions ever since I began doing science. My very first paper in 1984 (with P. Le Doussal) was on the so-called “Sinai billiard”, i.e. a point particle bouncing off an infinite, regular array of perfectly elastic, circular obstacles. As proven by Y. Sinai, this is an ergodic system, but with a particular property: the particle undergoes super-diffusion, i.e. its mean square displacement grows faster than linearly with time. The reason is that the particle manages to occasionally find itself on trajectories that travel very far before hitting the next obstacle. In fact, the distribution of distances before the next collision has a diverging variance. The resulting motion is a "Lévy flight”, not a Brownian motion (see Figure). Perhaps by accident or perhaps because I have a special penchant for these types of systems, my subsequent work in statistical physics gyrated around fat-tailed distributions, on the shoulder of the great Benoît B. Mandelbrot. (Q: Do you know what the second B. stands for? A: Benoît B. Mandelbrot…). Fat-tailed distributions arise naturally in many physical systems (avalanches, earthquakes, glassy dynamics, etc.) but also of course in economic and financial systems (wealth, firm sizes, price returns, etc.). This is actually what lured me into quantitative finance: the total disconnect between the Gaussian world of Black & Scholes, where perfect hedging is possible, and the fat-tailed world of financial markets that makes perfect hedging impossible and Black & Scholes a very bad theory to account for option smiles. These ideas led me to join CFM and are at the core of our volatility arbitrage program since 2005.  One of the defining feature of fat-tailed random variables is the dominance of rare, but large events. Draw N independent, identically distributed random
2022/12/31
Capital Fund Management | Chairman and Head of research
862
https://www.linkedin.com/feed/update/urn:li:activity:7014904556266364928
4
Álvaro Cartea
Open
1
Really excited to share this work with Bruno Dupire on functional expansions. Bonne lecture! Abstract: Path dependence is omnipresent in social science, engineering, and finance. It reflects the influence of the past on the future, often expressed through functionals. However, non-Markovian problems are often infinite-dimensional, thus challenging from a conceptual and computational perspective. In this work, we shed light on expansions of functionals. First, we treat static expansions made around paths of fixed length and propose a generalization of the Wiener series−the intrinsic value expansion (IVE). In the dynamic case, we revisit the functional Taylor expansion (FTE). The latter connects the functional Itô calculus with the signature to quantify the effect in a functional when a "perturbation" path is concatenated with the source path. In particular, the FTE elegantly separates the functional from future trajectories. The notions of real analyticity and radius of convergence are also extended to the path space. We discuss other dynamic expansions arising from Hilbert projections and the Wiener chaos, and finally show financial applications of the FTE to the pricing and hedging of exotic contingent claims.#quantitativefinance #mathematics
2022/12/31
University of Oxford | Professor
76
https://www.linkedin.com/feed/update/urn:li:activity:7014626200086028288
4
Gautier Marti
Open
0
Happy New Year 2023!My yesterday post on using ChatGPT to write a primer on #quant #trading using #machinelearning got an unexpected reception: 250,000 views! with lots of engagement as well.To continue on the same theme, below some nerdy rap lines on #quant #trading by #ChatGPTVerse 1:I'm all about the numbers, trading with precisionModeling market conditions, with mathematical precisionI leave the emotions at the doorMy strategy is based on algorithms and moreChorus:I'm a quant, trading with my mindData-driven, leaving the emotions behindI let the numbers do the talkingMy portfolio always on the rise, never stallingVerse 2:I analyze market trends and patternsUsing advanced techniques, my returns are never flattenin'I'm constantly learning, always improvingMy portfolio growing, my strategies always movingChorus:I'm a quant, trading with my mindData-driven, leaving the emotions behindI let the numbers do the talkingMy portfolio always on the rise, never stallingBridge:Some may call it cold and calculatedBut to me, it's just how I navigatedThe markets, with a data-driven approachMy success speaks for itself, beyond reproachChorus:I'm a quant, trading with my mindData-driven, leaving the emotions behindI let the numbers do the talkingMy portfolio always on the rise, never stallingMikołaj Bińkowski How is your text-to-speech #AI progressing? Can it turn that to music?
2023/01/01
Abu Dhabi Investment Authority (ADIA) | Quantitative Research & Development Lead
38
https://www.linkedin.com/feed/update/urn:li:activity:7015286012662673408
4
Igor Halperin
Open
2
The #NFT to the MIT Sloan School of Management Quant & Ai Conference created by the awesome Samson Qian !One last huge thanks to the many brilliant speakers that made it such a special experience!!Igor Halperin Matthew Dixon Gary Marcus Ruchir Puri Carson Boneck, CFA Tony Berkman Raphael Douady Gordon Ritter Alfred Spector Jim Kyung-Soo Liew, Ph.D. Sondra Campanelli Lisa Huang Gilbert Haddad Joseph Simonian, Ph.D. Saeed Amen Christina Qi Yevgeniy Vahlis Philip Ndikum Carol Alexander Dhagash Mehta, Ph.D. Nikita Fadeev Gregory Pelts Bart BaesensJeff Adams Swagato Acharjee George Mylnikov Larry Tabb Mika Kastenholz Mike Agne Kathryn Zhao Arik Ben Dor Peng Cheng Daniel NewmanHan CuiGene Ekster Divya Narendra Joe Marenda
2023/01/01
Fidelity Investments | AI Asset Management
29
https://www.linkedin.com/feed/update/urn:li:activity:7015125707768881152
3
Antoine Savine
Open
1
I’m happy to share that I’m starting a new position as Head of Macro Analytics at Hudson River Trading!
2023/01/01
Chief Quantitative Analyst |
62
https://www.linkedin.com/feed/update/urn:li:activity:7015297223349403649
3
Jonathan Regenstein
Open
3
just making my way through Housing is the Business Cycle by Edward Leamer, and thanks for the recommendation Francois Trahan.I will reproduce a few results from the paper over the weekend. Attached is a quick chart showing residential investment as percent of GDP, with recessions shaded pink. The time series goes back to 1950. This time series tends to peak in advance of recessions and trough at the end of recessions. If the current trend continues downward, it's further confirmation of a recession in 2023. This chart wasn't on my radar until now. Highly recommend the Leamer paper!
2022/12/31
Truist Securities | Head of Data and Quantamental Research
36
https://www.linkedin.com/feed/update/urn:li:activity:7014673051501948928
3
Markus Leippold
Open
11
As an #NLP and #AI enthusiast, I am always eager to learn about the latest developments in large language models (#LLM) like #chatgpt. I already interviewed #GPT3 (#davinci-002) about #climatechange last September. Now #openaccess at #Finance Research Letters: https://lnkd.in/eMGC-aXQ But we must remember what exactly these models do and how they work. Sometimes, it reminds me of my time as a student before the big exams, when we had to memorize tons of material (admittedly) without having the time to understand everything. I guess it's kind of like that with LLMs. Also, certain classification tasks can't (yet) be solved as well with LLMs as with, e.g., a fine-tuned BERT model. So I'm excited to see where LLMs will take us in the world of NLP, and I look forward to exploring their potential even further in the future. Happy New Year!#research #future #work #language #climatechange University of Zurich - Department of Banking and FinanceSFI Swiss Finance Institute
2022/12/31
University of Zurich - Department of Banking and Finance | Professor, Chair in Financial Engineering
68
https://www.linkedin.com/feed/update/urn:li:activity:7014876430840823808
3
Ariel Silahian
Open
6
We are doing #AI the wrong way. It is a dead-end road.Terminators are not coming anytime soon.Having learned about the basics of the human brain (#neuroscience) and its mechanisms, I strongly believe that what we know about Artificial Intelligence is all wrong.I also believe that digital computing is not the way. Probably, an unknown technology (but not digital).Clearly, we are way behind on the available technology (probably 1000s of years)Computing AI and Deep Learning could be way faster than a human being's brain... but by no means smarter. This is not a recommendation, is just my humble opinion.#technology #artificialintelligence #deeplearning #computing #digital Tesla
2022/12/31
Quant Developers | High Frequency Trading solutions | Founder & CTO / Lead Tech
19
https://www.linkedin.com/feed/update/urn:li:activity:7014235170559909888
2
Joris Bastien
Open
3
Quantaraxia, LLC, Joris Bastien, me, myself and I wish you all a happy new year !!!I also specifically want to thank my clients for their continued support. This is very much appreciated, as truth, loyalty and integrity is everything to me.Let's keep building in 2023 on the momentum we've already build this year, specifically in the crypto space. 2023 is the one when everything changes.Only a selected few will be part of this journey, as I need partners, not only investors.I'm excited for what's coming and if you want to know more, please reach out.In the meantime, enjoy your time with family and friends, and again, HAPPY NEW YEAR !!!#quantaraxia #money #management #investing #markets #hedgefunds #business #entrepreneurship
2022/12/31
Quantaraxia, LLC | Founder, CEO
11
https://www.linkedin.com/feed/update/urn:li:activity:7014637476690415616
2
Gautier Marti
Open
5
For a few years now #machinelearning mind Gautier Marti has impressed me. Now he has written I believe to be the first book I've seen using ChatGPT! Super cool Gautier!!!
2022/12/31
Abu Dhabi Investment Authority (ADIA) | Quantitative Research & Development Lead
68
https://www.linkedin.com/feed/update/urn:li:activity:7014858242497363968
2
Carl Wells
Open
54
Picture an army of grey-haired people.Done? This will be our reality in 2050.Over the next 30 years, most economies in the world will experience a reduction in their working age population between 20 and 30%.This is massive.Long-term economic growth is a function of labor supply growth and productivity growth.If the amount of people actively contributing to economic growth shrinks (!) by 20-30%, what does it tell us about the direction of GDP growth?It tells us it’s going down, and that’s not socially acceptable.Which means policymakers are going to try and fix it - how?More debt, of course.Debt per se is not an issue, but we don’t have a great track record in productively using debt and leverage.In this hectic macro cycle, don’t forget the big picture.
2022/12/31
Systematic Equity Partners | Founder
257
https://www.linkedin.com/feed/update/urn:li:activity:7014944891344416768
1
Joris Bastien
Open
6
This concept has saved my clients million of dollars...It can help any investor, regardless of their experience...Here is the scoop... "𝑰 𝒌𝒏𝒐𝒘 𝒘𝒉𝒆𝒓𝒆 𝑰’𝒎 𝒈𝒆𝒕𝒕𝒊𝒏𝒈 𝒐𝒖𝒕, 𝒃𝒆𝒇𝒐𝒓𝒆 𝑰 𝒈𝒆𝒕 𝒊𝒏."- Bruce Kovner, hedge fund legendThe concept is straightforward and yet extremely important. You as an investor need to determine, b̳e̳f̳o̳r̳e̳ you invest, what would change your mind and sell. It can be a predetermined price level, deteriorating fundamentals, changes in regulation or macroeconomics. The key is to do this in a "cold state" where you are more rational. Write down your reasoning. 𝗪𝗵𝘆 𝗶𝘀 𝘁𝗵𝗶𝘀 𝗶𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁? - Keeping losses small is critical if you want to make any money investing. Stocks can go much higher than you think...and also much lower than you can fathom (ARKK anyone?). - Once you are already invested, it becomes 𝐯𝐞𝐫𝐲 𝐡𝐚𝐫𝐝 to be rational about your reasons for owning that stock. Emotions take over. If you instead set your criteria for changing your mind, b̲e̲f̲o̲r̲e̲ you act, it becomes much easier to cut your losses if an investment doesn't work out. So remember...Before you invest, know what you need to see to change your mind and cut your losses. Write it down.What else do you want know about this concept? Drop it in the comments.#money  #moneymanagement  #markets #investing #macroeconomics #experience  #hedgefunds
2022/12/31
Quantaraxia, LLC | Founder, CEO
13
https://www.linkedin.com/feed/update/urn:li:activity:7014639170941779968
1
Table
Name
Tweet
Favourite Count
Follower Count
Location
Profile URL
Published
Retweet Count
Text URL
Tweet URL
User
pyquantnews
Open
Nobody taught me how to backtest a trading strategy. So I read all the books, documentation, and blogs. Then, I distilled what I learned into a simple step-by-step guide. But unlike a 300-page book, this won't take you a month to read. Here it is in 2 minutes:
97
88793
Get started with Python now →
https://t.co/f6vFvgzqCc
2023/01/29
15
https://twitter.com/pyquantnews/status/1619507701028982784
pyquantnews
pyquantnews
Open
7 books for automated trading you should read in 2023:
85
88559
Get started with Python now →
https://t.co/f6vFvgzqCc
2023/01/24
22
https://twitter.com/pyquantnews/status/1617693977188208640
pyquantnews
QuantSymplectic
Open
Today's reading list: 1. https://t.co/OVsyeaAObM 2. https://t.co/7j9YqrQzg8 3. https://t.co/rjv4km7MVY 4. https://t.co/E8ZJZiuI5h 5. https://t.co/5qBLTjpPdH 6. https://t.co/ioFoubBSpX https://t.co/RKvIJisYDC
28
13683
2023/01/30
6
https://bit.ly/3Hlj2vohttps://twitter.com/QuantSymplectic/status/1619867944879800320
QuantSymplectic
pyquantnews
Open
Time series are made up of level, trend, seasonality, and noise. If your forecast is broken, it may be time to take a new approach. Decomposing time series into those parts can help you improve forecasts. Here’s how with Python:
28
88767
Get started with Python now →
https://t.co/f6vFvgzqCc
2023/01/28
3
https://twitter.com/pyquantnews/status/1619144333818576897
pyquantnews
pyquantnews
Open
Everyone that wants to get started with Python should be able to. The problem? Most people don't know where to start. Here are 6 steps that might help you get started. ↓
23
88779
Get started with Python now →
https://t.co/f6vFvgzqCc
2023/01/28
5
https://twitter.com/pyquantnews/status/1619326259086999552
pyquantnews
lopezdeprado
Open
Thank you to the over 1,500 people who registered to ADIA Lab's inaugural seminar, titled "Can Factor Investing Become Scientific?" To learn more, visit: * Slides: https://t.co/wbY0h7H55J * Manuscript: https://t.co/5kDHBLna8i * Paper: https://t.co/kbF0ORWw0L https://t.co/Ipz9NKMozl
17
20213
New York, USA
https://t.co/Z4v60tIcah
2023/01/29
4
https://bit.ly/3HBenXzhttps://twitter.com/lopezdeprado/status/1619611869345648642
lopezdeprado
pyquantnews
Open
Sometimes, getting started with Python is less about brilliant solutions, beautiful code, and bonkers productivity. It's about getting the job done. Learn enough to make progress, every single day, for like 365 days.
17
88726
Get started with Python now →
https://t.co/f6vFvgzqCc
2023/01/26
0
https://twitter.com/pyquantnews/status/1618600218353696769
pyquantnews
carlcarrie
Open
Astock: A New Dataset and Simulated Stock Trading based on Stock-specific News Analyzing Model Paper: https://t.co/LcZuDphr2P Python GitHub: https://t.co/XBWh8wq0oR Notebook: https://t.co/XBWh8wq0oR https://t.co/2hYZWY30Pr
17
13174
New York
https://t.co/RKDfeDu90F
2023/01/24
2
https://arxiv.org/abs/2206.06606https://twitter.com/carlcarrie/status/1617877985444646913
carlcarrie
robertmartin88
Open
Must read books in 2023: The Brothers Karamazov, Gödel Escher Bach, and https://t.co/Z7WmhiN35k
16
9229
Manhattan, NY
https://t.co/cyX6zqG4jq
2023/01/26
0
https://twitter.com/robertmartin88/status/1618419348724666371
robertmartin88
pyquantnews
Open
Every Python quant should have a library of analysis tools. The problem? Most people don’t know where to begin. Here’s a quick walkthrough of the Kalman filter that might help. ↓
16
88691
Get started with Python now →
https://t.co/f6vFvgzqCc
2023/01/25
3
https://twitter.com/pyquantnews/status/1618234801252614145
pyquantnews
ArturSepp
Open
3 strategies for shorting 1) sell & hold fixed units sold at starting price: can default 2) sell at constant notional - rebalance short exposure to a fixed notional: may default 3) sell at NAV - inverse ETF style: cannot default #Python code for simulation https://t.co/PyGQyIpfhF https://t.co/vBdpg0KZC3 https://t.co/8AUPeNovif
14
7234
Zurich, Switzerland
https://t.co/MHslB4a6i1
2023/01/24
2
https://github.com/ArturSepp/QuantInvestStrats/blob/master/qis/examples/constant_notional.pyhttps://twitter.com/ArturSepp/status/1617985769511219200
ArturSepp
pyquantnews
Open
Algorithmic Trading with Python: Quantitative Methods and Strategy Development Lessons: • Modern quant trading methods in Python • Focus on pandas, numpy, and scikit-learn https://t.co/VTsd420Rtb
14
88559
Get started with Python now →
https://t.co/f6vFvgzqCc
2023/01/24
1
https://twitter.com/pyquantnews/status/1617694236052230144
pyquantnews
pyquantnews
Open
It's amazing how fast people can make progress with Python because they believe in an idea, start working on it, and don't stop. Getting started doesn't mean having the perfect setup or a Ph.D. It means *getting started*.
11
88660
Get started with Python now →
https://t.co/f6vFvgzqCc
2023/01/25
0
https://twitter.com/pyquantnews/status/1618053849884889088
pyquantnews
macro_srsv
Open
Fiscal policy criteria for fixed-income allocation: Evidence from 20 countries over 20 years shows that indicators of fiscal stances have been timely, theoretically plausible, and profitable criteria for fixed-income allocations across currency areas. https://t.co/Bq5HfweDua https://t.co/t8OtpIRumx
9
9900
London, England
https://t.co/Ad7SPhJxME
2023/01/28
0
https://research.macrosynergy.com/fiscal-policy-criteria-for-fixed-income-allocation/https://twitter.com/macro_srsv/status/1619248915353686016
macro_srsv
carlcarrie
Open
DataSloth Natural language Pandas queries and data generation powered by GPT-3 Python GitHub: https://t.co/iwjqiuq8TQ https://t.co/w96pOxw8Hj
9
13190
New York
https://t.co/RKDfeDu90F
2023/01/27
1
https://github.com/ibestvina/dataslothhttps://twitter.com/carlcarrie/status/1618924522647986176
carlcarrie
pyquantnews
Open
1/ Learn the basics of Python This includes understanding data types, control flow, and basic functions and libraries.
8
88779
Get started with Python now →
https://t.co/f6vFvgzqCc
2023/01/28
0
https://twitter.com/pyquantnews/status/1619326501018533890
pyquantnews
carlcarrie
Open
#MLOps via Automated Pipelines using Python, SQL and standard tools https://t.co/QxWm9ho1n8 Crypto example: 'phi wf run crypto/prices' Terminal and Jupyter integration: https://t.co/Ns8v7FLeaW
7
13301
New York
https://t.co/RKDfeDu90F
2023/01/29
0
https://www.phidata.com/https://twitter.com/carlcarrie/status/1619810977528287232
carlcarrie
carlcarrie
Open
GitHub Copilot Deconstruction https://t.co/xwSql2AlZh Co-Pilot Explorer - JavaScript and Python Code: https://t.co/N7QrdiB4Gd https://t.co/acPJFv0ich
7
13292
New York
https://t.co/RKDfeDu90F
2023/01/29
3
https://thakkarparth007.github.io/copilot-explorer/posts/copilot-internalshttps://twitter.com/carlcarrie/status/1619536098216271873
carlcarrie
pyquantnews
Open
Start by importing pandas, the OpenBB SDK, QuantStats, and Backtrader. https://t.co/twl63o8yjX
7
88793
Get started with Python now →
https://t.co/f6vFvgzqCc
2023/01/29
0
https://twitter.com/pyquantnews/status/1619508959580246016
pyquantnews
carlcarrie
Open
Sketch Sketch is an AI code-writing assistant for pandas - normalize, clean, plot E.g. df.sketch.howto("Plot the sales versus time") Python GitHub: https://t.co/XTFIX4h9hR Google Colab Notebook Demo: https://t.co/pRgTxjAegc https://t.co/7pdmYo1Aob
7
13190
New York
https://t.co/RKDfeDu90F
2023/01/27
1
https://github.com/approximatelabs/sketchhttps://twitter.com/carlcarrie/status/1618925884110684160
carlcarrie
macro_srsv
Open
"Pricing of regime shifts and [related] nonlinearities... generates a strong connection between bond risk premia and the macroeconomy as summarized by variables such as inflation, industrial production, and unemployment." https://t.co/T9ODUmdhwr https://t.co/pnIL6Fd58W
7
9879
London, England
https://t.co/Ad7SPhJxME
2023/01/25
2
https://rednie.eco.unc.edu.ar/files/DT/200.pdfhttps://twitter.com/macro_srsv/status/1618153482216964098
macro_srsv
pyquantnews
Open
Python for Algorithmic Trading: From Idea to Cloud Deployment Lessons: • Ways to apply Python to algorithmic trading • Interacting with online trading platforms. https://t.co/0r175af2N7
7
88559
Get started with Python now →
https://t.co/f6vFvgzqCc
2023/01/24
0
https://twitter.com/pyquantnews/status/1617694980755136513
pyquantnews
pyquantnews
Open
This thread is packed with information. If you can't get to it all now, click the link to hop to the top tweet. Then retweet it (with a comment!) so you can come back to it later. https://t.co/HzD6RVhNzv
6
88799
Get started with Python now →
https://t.co/f6vFvgzqCc
2023/01/29
1
https://twitter.com/3187132960/status/1619507701028982784https://twitter.com/pyquantnews/status/1619511469195902978
pyquantnews
pyquantnews
Open
Trading takes time, money, and effort. To make sure you're better off not being long TLT, compare the strategy results to a long-only strategy. QuantStats makes it easy. Here’s how to use it. https://t.co/NenvTCphIA
6
88799
Get started with Python now →
https://t.co/f6vFvgzqCc
2023/01/29
1
https://twitter.com/pyquantnews/status/1619510474520887297
pyquantnews
carlcarrie
Open
Deep Generative Neural Net applied to sparse stock index portfolio optimization Python GitHub: https://t.co/RhzzBlZG2m https://t.co/UbRHkq3KS3
6
13283
New York
https://t.co/RKDfeDu90F
2023/01/28
0
https://github.com/kayuksel/generative-opthttps://twitter.com/carlcarrie/status/1619402176660647936
carlcarrie
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