Python for DevOps Master Class 2022: CI/CD, Github Actions, Containers and Microservices
https://t.co/X55M2TvBFl
https://www.youtube.com/watch?v=kwZNpieUreA
https://twitter.com/PythonHub/status/1528348734135971842
A Macroprudential Theory of Foreign Reserve Accumulation https://t.co/lcKM8ehV7D #QuantLinkADay https://t.co/dpxG1vi0ms
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4106791
London
https://twitter.com/saeedamenfx/status/1528344932385050624
django-pgpubsub
A distributed task processing framework for Django built on top of the Postgres NOTIFY/LISTEN protocol.
https://t.co/cNBNcseiFz
https://github.com/Opus10/django-pgpubsub
https://twitter.com/PythonHub/status/1528258139388268546
Celery Alternative for Django - Huey
Trying out a lightweight asynchronous task queue as an alternative to Celery with Django.
https://t.co/3gUguhRK0k
https://idiomaticprogrammers.com/post/celery-alternative-for-django-huey/
https://twitter.com/PythonHub/status/1528167542275153920
Extend Pandas with Stumpy Matrix Profile for Time-Series
https://t.co/OcD9fnFMJn
https://github.com/Andy7475/pandas_stumpy
New York
https://twitter.com/carlcarrie/status/1528162157313110017
Matrix Profiles for Financial Time-Series
https://t.co/bahfRt04OS
Paper:
https://t.co/2AOnD1aQBK
SCAMP: SCAlable Matrix Profile, Python GitHub:
https://t.co/629zRqmQsA https://t.co/Gpi4JBXbKO
https://www.cs.ucr.edu/~eamonn/MatrixProfile.html
New York
https://twitter.com/carlcarrie/status/1528160658809815042
Central Bank Digital Currency and Banks https://t.co/nE3iE7hXoz #QuantLinkADay https://t.co/EogVbgHAuL
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4112644
London
https://twitter.com/saeedamenfx/status/1528135526729109507
21May22 / #365APoem / A win for Albanese in Australia,
London
https://twitter.com/saeedamenfx/status/1528119405825204224
Brief Descriptions of a Python to C++ Translator
https://t.co/uIH3YtNAHo
https://www.oilshell.org/blog/2022/05/mycpp.html
https://twitter.com/PythonHub/status/1528076948500520963
FAMA 5 factor model vs CART variant with statsmodels and sklearn
https://t.co/GEY0qvyUkR
https://medium.com/the-quant-journey/five-factor-asset-pricing-model-analysis-b8b0463c8449
New York
https://twitter.com/carlcarrie/status/1528028328598413319
Bitcoin sentiment and volume features
Paper:
https://t.co/NbQdnIEwuY / https://t.co/JSethIIhjs
Python GitHub with datasets:
https://t.co/NPrTH5XLeH
https://t.co/mKUralbV49 https://t.co/llYN6QuHjF
https://jfin-swufe.springeropen.com/articles/10.1186/s40854-022-00352-7
New York
https://twitter.com/carlcarrie/status/1528025383530110979
Knowledge Graph applied to Twitter Sentiment Estimation - paper
Knowledge Graphs supports the analysis of sentiment polarities, based on similarity measurements between the text’s graph and pre-determined polarity graphs.
https://t.co/I74UklnlgV or https://t.co/wf97aRymYK https://t.co/3z42zkiLPo
https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.800.3216&rep=rep1&type=pdf
New York
https://twitter.com/carlcarrie/status/1528023077417779202
Micro-prices as better estimator of price dynamics in a limit order book #lob #obi and order book imbalance framework
Python GitHub:
https://t.co/UefIA2JpXu
Original Paper:
https://t.co/PVG74qIbDf https://t.co/hCOIij4Pir
https://github.com/grayvalley/microprice-calibration
New York
https://twitter.com/carlcarrie/status/1528014546207899650
. @quantpedia reviews a paper on methods used for grading and merging #ESG scores from multiple providers:
https://t.co/i8ovn1P9mu
#SustainableInvesting https://t.co/BdgFEsWgyI
https://www.tradersinsight.news/sho3
Connecticut, USA
https://twitter.com/IBKR_QB/status/1528012739691560960
Pip vs Pipenv: Which is better and which to learn first?
Pipenv and pip are both excellent tools for installing and managing Python dependencies that are ...
https://t.co/3gcYqTOkzp
https://codesolid.com/pip-vs-pipenv-which-is-better-and-which-to-learn-first/
https://twitter.com/PythonHub/status/1527986349382545408
Simple example code for "applying Monte Carlo simulation to price both a European Call and Put Option [in Python], following the Black-Scholes Market Model using Risk-Neutral Pricing." https://t.co/LytZItFS4p
https://t.co/ZGsIbM5Vnt https://medium.com/the-quant-journey/monte-carlo-simulation-for-black-scholes-option-pricing-fd98a669c029
London, England
https://twitter.com/macro_srsv/status/1527921559867883522
My First Impression Trying Python on Browser
The only missing piece to make Python a universal programming language is hereContinue reading on ...
https://t.co/QxHkwppr6E https://t.co/WMjLUTcWFB
https://towardsdatascience.com/pyscript-tutorial-a8fba77abd1b
https://twitter.com/PythonHub/status/1527805168582000643
TensorFlow and Scipy are used in this Deep Learning based Credit Modeling Framework
Paper:
https://t.co/wWaV0SwD2o
Python GitHub:
https://t.co/4cLATOG9dl https://t.co/gxZe2UCT9P
https://doi.org/10.3905/jfi.2021.1.121
New York
https://twitter.com/carlcarrie/status/1527793581397770242
Paper applys signature transformations to model the underlying shape of the input equity returns; further assuming the underlying shape remains the same, predicting future values based on that shape.
https://t.co/7jueqgGK2k https://t.co/kk868uPlFF
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4107756
New York
https://twitter.com/carlcarrie/status/1527791454009147394
20May22 / #365APoem / Now monkey pox, and never have we won,
London
https://twitter.com/saeedamenfx/status/1527755026042605571
If you made it this far, please retweet and help promote Amromin and Sharpe's work!
Washington, DC
https://twitter.com/achenfinance/status/1527715324614914049
5/5 The titans Greenwood and Shleifer draft a paper on this in 2012. As usual, their writing and analysis are a level above the others (sorry Steve). Perhaps that's why they get 10x as many cites as the previous paper. Or perhaps it's just the Matthew effect. https://t.co/GBlwcgP9vB
Washington, DC
https://twitter.com/achenfinance/status/1527715323071414279
4/5 You can imagine that such heresy will be hard to publish. Well, to be honest it's hard for me to imagine how hard it must have been. Amromin and Sharpe 2005 was not published until 2013. https://t.co/NO9IcsmaAv
Washington, DC
https://twitter.com/achenfinance/status/1527715319111884803
3/5 But Amromin and Sharpe 2005 show that if you actually ask people (instead of solve for a stochastic-general-equilibrium), they'll say the opposite. Bad economic times mean low future returns. Realizing this requires being smarter than the market is too hard for most people. https://t.co/oHrfu2hbbg
Washington, DC
https://twitter.com/achenfinance/status/1527715315068575745
2/5 I was taught that expected returns are high in recessions. In recessions, risk is high, so returns are high. My JMP (and first pub) is a quantitative GE model of this fundamental idea.
Washington, DC
https://twitter.com/achenfinance/status/1527715311897780226
One fav papers, of the few that changed my views, is Amromin and Sharpe 2005. They show that households have exactly the -opposite- view on expected returns and recessions that I was taught in my Ph.D. This paper is also the saddest example of the Matthew effect I know of.
https://t.co/at3CQ3YCWH Washington, DC
https://twitter.com/achenfinance/status/1527715310094123008
I used a new dataframe library (polars) to wrangle 300M prices and discover some of the most expensive hospitals in America. Code/notebook in article
https://t.co/fZvglPJ098
https://www.reddit.com/r/Python/comments/ululk1/i_used_a_new_dataframe_library_polars_to_wrangle/
https://twitter.com/PythonHub/status/1527714560588795907
In this featured article, Benjamin Smith from bensstats shows us how to fix R's "messy string concatenation" with a special function:
https://t.co/dl61ODW6ep
#DataScience #rstats https://t.co/XTcoKKeGnD
https://www.tradersinsight.news/1e2f
Connecticut, USA
https://twitter.com/IBKR_QB/status/1527682460238102528
In this @QuantInsti tutorial, Anshul Tayal offers step-by-step instructions on getting started with Julia Programming.
Learn how to perform basic arithmetic operations and work with data structures: https://t.co/eGchy9HXwO
#DataScience #DataAnalytics #DataVisualization https://t.co/YTI9lBqFJk
https://www.tradersinsight.news/b3ji
Connecticut, USA
https://twitter.com/IBKR_QB/status/1527650357744132097
Slik: A data processing and modelling Python library
https://t.co/r2LW3Vp6Br
https://slik-wrangler.medium.com/introducing-slik-a-data-processing-and-modelling-python-library-5cfd837ce01b
https://twitter.com/PythonHub/status/1527623965404962817
Russia's Ruble during the onset of the Russian invasion of Ukraine in early 2022: The role of implied volatility and attention https://t.co/r0Xw0vJanA #QuantLinkADay https://t.co/F03uAJb4q8
https://arxiv.org/abs/2205.09179
London
https://twitter.com/saeedamenfx/status/1527617388342042625
Join SESAMm on a deep dive into their financial intelligence platform TextReveal
Streams, which is used by quantitative and fundamental asset managers to optimise trade timing and identify new investment opportunities. https://t.co/HtrtdviEaQ http://spr.ly/6018zzcfI
Global
https://twitter.com/QuantMinds/status/1527602032042967040
"A Machine Learning Framework for Asset Pricing": "Building on [mathematical] representations of asset prices…we develop a solution strategy using neural networks and further machine learning techniques." https://t.co/PRi9bVza7k
https://t.co/1JAajXFkm0 https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4097100
London, England
https://twitter.com/macro_srsv/status/1527538021536518145
Pandas Tutor - visualize Python pandas code
https://t.co/47SirC2J2a
https://www.reddit.com/r/Python/comments/upbhyh/pandas_tutor_visualize_python_pandas_code/
https://twitter.com/PythonHub/status/1527533364969979906
Python Weekly - Issue 550 https://t.co/svrM90OuSD #python #flask #django #machinelearning #datascience #kubernetes #deeplearning #pytorch #jupyter #deepnote #lowcode #nltk #huggingface #json #restapi #cli #tensorflow #artificialintelligence #ai #pdf #drf https://t.co/MLkE8B6rs0
https://buff.ly/3wDPQuo
https://twitter.com/PythonWeekly/status/1527469247735136262
"lens on retail participation" - weekly expiry bandh na karde !!!!!!!!!
SEBI ‘lens on retail participation in the F&O segment’ https://t.co/jHwdN3Iosm
https://www.thehindubusinessline.com/news/sebi-lens-on-retail-participation-in-the-fo-segment/article65426666.ece
Mumbai, India
https://twitter.com/JigneshTrade/status/1527468322308395008
Web applications 101 https://t.co/F6gth3WyYH https://t.co/7aOumJOi2r
https://www.robinwieruch.de/web-applications/
https://twitter.com/fullstackpython/status/1527415311653294080
Boring Python: dependency management
This is the first in hopefully a series of posts I intend to write about how to ...
https://t.co/FxFP3KOVjG
https://www.b-list.org/weblog/2022/may/13/boring-python-dependencies/
https://twitter.com/PythonHub/status/1527412564707229696
19May22 / #365APoem / More fines given, but no more for Johnson,
London
https://twitter.com/saeedamenfx/status/1527395564794564612
Do Yield Curve Inversions Predict Recessions in the Euro Area? https://t.co/rEHCUFm0W2 #QuantLinkADay https://t.co/jiB5o40XRH
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4106825
London
https://twitter.com/saeedamenfx/status/1527361790291521541
Central Bank Swap Lines: Micro-level Evidence https://t.co/6upjEbQ6AY #QuantLinkADay https://t.co/FETSDxDvFJ
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4106664
London
https://twitter.com/saeedamenfx/status/1527361354415603713
Market Impact: Empirical Evidence, Theory and Practice https://t.co/wnLOh81ern #QuantLinkADay https://t.co/0p5oZJNoIh
https://arxiv.org/abs/2205.07385
London
https://twitter.com/saeedamenfx/status/1527360795595575301
Python decorator patterns
This post shows you toy implementations of Python decorator patterns such as @measure, @repeat, @trace, @count, @singleton, and @app.route (made famous by Flask).
https://t.co/wLc77Uikm3
https://bytepawn.com/python-decorator-patterns.html
https://twitter.com/PythonHub/status/1527352171599056901
Counterpoint to a16z Crypto perspective by Amy Castor - @ahcastor -
https://t.co/d2Dh3qPlGL
https://amycastor.com/2022/05/19/a16zs-state-of-crypto-report-a-rehash-of-bad-crypto-market-pitches/
New York
https://twitter.com/carlcarrie/status/1527351586824998923
Missing a16z Crypto Slide Deck
https://t.co/jnC6ybyhF8
https://a16z.com/wp-content/uploads/2022/05/state-of-crypto-2022_a16z-crypto.pdf
New York
https://twitter.com/carlcarrie/status/1527351585315389447
Love this 2019 HBR article on balancing efficiency with effectiveness
https://t.co/jMkNAunaZm
https://hbr.org/2019/02/why-highly-efficient-leaders-fail?utm_medium=social&utm_campaign=hbr&utm_source=LinkedIn&tpcc=orgsocial_edit
New York
https://twitter.com/carlcarrie/status/1527344737400737800
Python Weekly - Issue 550 https://t.co/svrM9165Kb #python #django #flask #machinelearning #datascience #kubernetes #deeplearning #pytorch #jupyter #deepnote #lowcode #nltk #huggingface #json #restapi #cli #tensorflow #artificialintelligence #ai #pdf #drf https://t.co/3LWdqKEu5s
https://buff.ly/3wDPQuo
https://twitter.com/PythonWeekly/status/1527308107721760768
Today's reading list:
1. https://t.co/bdRpbsM385
2. https://t.co/FPx4G5q2XS
3. https://t.co/cTlnzPJCFw
4. https://t.co/ojNUOsVEwW
5. https://t.co/mZpoMp8w5O
6. https://t.co/qYN3FVDJRO
7. https://t.co/95lvIoXsp9
8. https://t.co/i6V7tfqq2r https://t.co/eZmOgZ1oln
https://bit.ly/3wvwZTv
https://twitter.com/QuantSymplectic/status/1527291991222013953
Sorting lists in python: sorted() vs sort()
https://t.co/IMygTQBwWP
https://www.reddit.com/r/Python/comments/uqqseh/sorting_lists_in_python_sorted_vs_sort/
https://twitter.com/PythonHub/status/1527291772690386944
Interested in using Excel and the @IBKR TWS API? Our tutorials will help you get started: https://t.co/GBZVJ13T1G
#FinTech #algorithmictrading https://t.co/Ad7wXRfZ1M
https://www.tradersinsight.news/veel
Connecticut, USA
https://twitter.com/IBKR_QB/status/1527287969857478657