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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
Lioba Heimbach, Eric Schertenleib, Roger Wattenhofer
q-fin.RM
2022/05/18
2022/05/19
2022/05/19
Trade execution on Decentralized Exchanges (DEXes) is automatic and does not require individual buy and sell orders to be matched. Instead, liquidity aggregated in pools from individual liquidity providers enables trading between cryptocurrencies. The largest DEX measured by trading volume, Uniswap V3, promises a DEX design optimized for capital efficiency. However, Uniswap V3 requires far more decisions from liquidity providers than previous DEX designs. In this work, we develop a theoretical model to illustrate the choices faced by Uniswap V3 liquidity providers and their implications. Our model suggests that providing liquidity on Uniswap V3 is highly complex and requires many considerations from a user. Our supporting data analysis of the risks and returns of real Uniswap V3 liquidity providers underlines that liquidity providing in Uniswap V3 is incredibly complicated, and performances can vary wildly. While there are simple and profitable strategies for liquidity providers in liquidity pools characterized by negligible price volatilities, these strategies only yield modest returns. Instead, significant returns can only be obtained by accepting increased financial risks and at the cost of active management. Thus, providing liquidity has become a game reserved for sophisticated players with the introduction of Uniswap V3, where retail traders do not stand a chance.
33
0
0.5
2
https://arxiv.org/abs/2205.08904
Market Making via Reinforcement Learning in China Commodity Market
Open
Junshu Jiang, Thomas Dierckx, Duxiang Xiao, Wim schoutens
q-fin.TR
2022/05/18
2022/05/19
2022/05/19
Market maker is an important role in financial market. A successful market maker should control inventory risk, adverse selection risk, and provides liquidity to the market. Reinforcement Learning, as an important methodology in control problems, enjoys the advantage of data-driven and less rigid assumption, receive great attentions in market making field since 2018. However, although China Commodity market, which has biggest trading volume on agricultural products, nonferrous metals and some other sectors, the study of applies RL on Market Making in China market is still rare. In this thesis, we try to fill the gap. We develop the Automatic Trading System and verify the feasibility of applying Reinforcement Learning in China Commodity market. Also, we probe the agent behavior by analyzing how it reacts to different environment conditions.
32
0
1.25
5
https://arxiv.org/abs/2205.08936
Robust Distortion Risk Measures
Open
Carole Bernard, Silvana M. Pesenti, Steven Vanduffel
q-fin.RM
2022/05/18
2022/05/19
2022/05/19
The robustness of risk measures to changes in underlying loss distributions (distributional uncertainty) is of crucial importance in making well-informed decisions. In this paper, we quantify, for the class of distortion risk measures with an absolutely continuous distortion function, its robustness to distributional uncertainty by deriving its largest (smallest) value when the underlying loss distribution has a known mean and variance and, furthermore, lies within a ball - specified through the Wasserstein distance - around a reference distribution. We employ the technique of isotonic projections to provide for these distortion risk measures a complete characterisation of sharp bounds on their value, and we obtain quasi-explicit bounds in the case of Value-at-Risk and Range-Value-at-Risk. We extend our results to account for uncertainty in the first two moments and provide applications to portfolio optimisation and to model risk assessment.
23
0
0.5
2
https://arxiv.org/abs/2205.08850
Mack-Net model: Blending Mack's model with Recurrent Neural Networks
Open
Eduardo Ramos-Pérez, Pablo J. Alonso-González, José Javier Núñez-Velázquez
q-fin.RM
2022/05/15
2022/05/18
2022/05/17
In general insurance companies, a correct estimation of liabilities plays a key role due to its impact on management and investing decisions. Since the Financial Crisis of 2007-2008 and the strengthening of regulation, the focus is not only on the total reserve but also on its variability, which is an indicator of the risk assumed by the company. Thus, measures that relate profitability with risk are crucial in order to understand the financial position of insurance firms. Taking advantage of the increasing computational power, this paper introduces a stochastic reserving model whose aim is to improve the performance of the traditional Mack's reserving model by applying an ensemble of Recurrent Neural Networks. The results demonstrate that blending traditional reserving models with deep and machine learning techniques leads to a more accurate assessment of general insurance liabilities.
22
0
4
10
http://dx.doi.org/10.1016/j.eswa.2022.117146
Table
Name
Category
Contributors
Created
URL
Forks
Stars
Description
Last Update
activate-linux
Open
Trending Repos
4
2022/03/16
https://github.com/MrGlockenspiel/activate-linux
42
2031
The "Activate Windows" watermark ported to Linux
2022/05/18
resh
Open
Trending Repos
1
2019/03/31
https://github.com/curusarn/resh
15
618
Rich Enhanced Shell History - Contextual shell history for zsh and bash
2022/05/18
sneller
Open
Trending Repos
0
2022/03/25
https://github.com/SnellerInc/sneller
15
380
Vectorized SQL for JSON at scale: fast, simple, schemaless
2022/05/18
fzy
Open
Trending Repos
4
2014/07/12
https://github.com/jhawthorn/fzy
104
2452
:mag: A simple, fast fuzzy finder for the terminal
2022/05/18
open-data-anonymizer
Open
Trending Repos
0
2021/11/03
https://github.com/ArtLabss/open-data-anonymizer
7
97
Python Data Anonymization & Masking Library For Data Science Tasks
2022/05/18
friendlyreminderbot
Open
Trending Repos
0
2022/05/11
https://github.com/ykdojo/friendlyreminderbot
23
34
A friendly reminder twitter bot to keep you healthy and happy
2022/05/18
bud
Open
Trending Repos
2
2022/04/17
https://github.com/livebud/bud
33
1269
The Full-Stack Web Framework for Go
2022/05/18
trl
Open
Trending Repos
0
2020/03/27
https://github.com/lvwerra/trl
54
404
Train transformer language models with reinforcement learning.
2022/05/18
ailia-models
Open
Trending Repos
1
2019/09/07
https://github.com/axinc-ai/ailia-models
125
630
The collection of pre-trained, state-of-the-art AI models for ailia SDK
2022/05/18
Super-mario-bros-PPO-pytorch
Open
Trending Repos
1
2019/10/02
https://github.com/uvipen/Super-mario-bros-PPO-pytorch
161
783
Proximal Policy Optimization (PPO) algorithm for Super Mario Bros
2022/05/18
Awesome-Transformer-Attention
Open
Trending Repos
0
2021/09/15
https://github.com/cmhungsteve/Awesome-Transformer-Attention
34
465
An ultimately comprehensive paper list of Vision Transformer/Attention, including papers, codes, and related websites
2022/05/18
kbd-audio
Open
Trending Repos
10
2018/08/27
https://github.com/ggerganov/kbd-audio
436
5196
Acoustic keyboard eavesdropping
2022/05/18
tensorspace
Open
Trending Repos
9
2018/07/22
https://github.com/tensorspace-team/tensorspace
412
4621
Neural network 3D visualization framework, build interactive and intuitive model in browsers, support pre-trained deep learning models from TensorFlow, Keras, TensorFlow.js
2022/05/18
wazero
Open
Trending Repos
2
2020/05/04
https://github.com/tetratelabs/wazero
73
1306
wazero: the zero dependency WebAssembly runtime for Go developers
2022/05/18
go-clean-template
Open
Trending Repos
3
2021/01/18
https://github.com/evrone/go-clean-template
130
1609
Clean Architecture template for Golang services
2022/05/18
csi-s3
Open
Trending Repos
0
2018/07/14
https://github.com/ctrox/csi-s3
111
460
A Container Storage Interface for S3
2022/05/18
obsidian-dataview
Open
Trending Repos
4
2021/01/13
https://github.com/blacksmithgu/obsidian-dataview
136
2144
A high-performance data index and query language over Markdown files, for https://obsidian.md/.
2022/05/18
EOD
Open
Trending Repos
0
2021/10/22
https://github.com/ModelTC/EOD
32
277
Easy and Efficient Object Detector
2022/05/18
create-react-app
Open
Trending Repos
190
2016/07/17
https://github.com/facebook/create-react-app
24544
95048
Set up a modern web app by running one command.
2022/05/18
Trending Repos
0
2022/02/01
https://github.com/facebookresearch/rl
24
329
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
2022/05/18
rustlings
Open
Trending Repos
48
2015/09/15
https://github.com/rust-lang/rustlings
3903
24465
:crab: Small exercises to get you used to reading and writing Rust code!
2022/05/18
portmaster
Open
Trending Repos
6
2018/11/13
https://github.com/safing/portmaster
107
3078
Love Freedom - Block Mass Surveillance
2022/05/18
codex_py2cpp
Open
Trending Repos
0
2022/05/15
https://github.com/alxschwrz/codex_py2cpp
1
99
Converts python code into c++ by using OpenAI CODEX.
2022/05/18
Web-Dev-For-Beginners
Open
Trending Repos
99
2020/11/10
https://github.com/microsoft/Web-Dev-For-Beginners
7215
49946
24 Lessons, 12 Weeks, Get Started as a Web Developer
2022/05/18
insightface
Open
Trending Repos
23
2017/09/01
https://github.com/deepinsight/insightface
3785
11848
State-of-the-art 2D and 3D Face Analysis Project
2022/05/18
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Table
Title
Author
Award Count
Comment Count
Date Posted
Permalink
Post ID
Score
Subreddit
Upvote Ratio
Algo trading is incredibly hard. Don't beat yourself up if you haven't had success yet. It's so hard that QuantConnect has temporarily scrapped it's optional crowdsourced Alpha Market.
Open
Adderalin
3
34
2022/04/30
https://www.reddit.com/r/algotrading/comments/ufkcl1/algo_trading_is_incredibly_hard_dont_beat/
ufkcl1
190
algotrading
0.98
For beginners: Start with this
Open
GarantBM
2
3
2022/05/14
https://www.reddit.com/r/mltraders/comments/upow12/for_beginners_start_with_this/
upow12
29
mltraders
1
Looking for past 5 years of 1 minute candlesticks on all cryptos
Open
Ok-Trip8259
2
25
2022/05/01
https://www.reddit.com/r/algotrading/comments/ug3lja/looking_for_past_5_years_of_1_minute_candlesticks/
ug3lja
36
algotrading
0.85
Building An Institutional Grade Research Platform
Open
Economathematian
2
11
2022/05/01
https://www.reddit.com/r/algotrading/comments/uga3ed/building_an_institutional_grade_research_platform/
uga3ed
78
algotrading
0.93
REAL Quant Trade Recap; Model-Driven Retail Trade
Open
Macro_Trader_QF
2
36
2022/04/29
https://www.reddit.com/r/algotrading/comments/uercqu/real_quant_trade_recap_modeldriven_retail_trade/
uercqu
139
algotrading
0.93
Market Making for Idiots (Detailed)
Open
Economathematian
2
41
2022/04/27
https://www.reddit.com/r/algotrading/comments/ucskm1/market_making_for_idiots_detailed/
ucskm1
208
algotrading
0.93
Draft - ML Quant Links May 2022
Open
OppositeMidnight
1
2
2022/05/16
https://www.reddit.com/r/quant/comments/ur2wjm/draft_ml_quant_links_may_2022/
ur2wjm
15
quant
0.94
Database structure for pipelines
Open
Jaglyser
1
9
2022/05/15
https://www.reddit.com/r/algotrading/comments/uqez9b/database_structure_for_pipelines/
uqez9b
3
algotrading
0.8
How is your strategy doing?
Open
Small-Draw6718
1
54
2022/05/13
https://www.reddit.com/r/algotrading/comments/uoytss/how_is_your_strategy_doing/
uoytss
58
algotrading
0.91
Grad School Advice: Applied Math Ph.D. vs Financial Engineering Masters
Open
TG7888
1
0
2022/05/09
https://www.reddit.com/r/quant/comments/um16oc/grad_school_advice_applied_math_phd_vs_financial/
um16oc
16
quant
0.9
[revised] buying market hours as opposed to purchasing post-retail hours versus purchase and hold ($spy, most recent 2 years) 🥰😄
Open
Um6Ragefutz50
1
41
2022/05/10
https://www.reddit.com/r/algotrading/comments/umk415/revised_buying_market_hours_as_opposed_to/
umk415
145
algotrading
0.9
Hey there! I recently completed a tutorial on training a BERT model to predict movie review scores from a written review. You can find the tutorial and interactive demo by following the link! (r/DataScience)
Open
Peerism1
0
0
2022/05/17
https://www.reddit.com/r/datascienceproject/comments/urasl9/hey_there_i_recently_completed_a_tutorial_on/
urasl9
1
datascienceproject
1
Looking for help (or internet resources) with motion capture/tracking (r/DataScience)
Open
Peerism1
0
0
2022/05/19
https://www.reddit.com/r/datascienceproject/comments/usrjr7/looking_for_help_or_internet_resources_with/
usrjr7
1
datascienceproject
1
Is this a "good" solution to the Shopify Data Science challenge? (r/DataScience)
Open
Peerism1
0
0
2022/05/18
https://www.reddit.com/r/datascienceproject/comments/us148e/is_this_a_good_solution_to_the_shopify_data/
us148e
2
datascienceproject
0.75
Keras Launches a Computer Vision Extension Package (r/MachineLearning)
Open
Peerism1
0
0
2022/05/19
https://www.reddit.com/r/datascienceproject/comments/usrjp1/keras_launches_a_computer_vision_extension/
usrjp1
3
datascienceproject
0.81
Supervised Clustering: How to Use SHAP Values for Better Cluster Analysis (r/DataScience)
Open
Peerism1
0
0
2022/05/17
https://www.reddit.com/r/datascienceproject/comments/uraskx/supervised_clustering_how_to_use_shap_values_for/
uraskx
8
datascienceproject
1
Brooklyn Quant Experience Lecture Series: Sasha Stoikov
Open
_quanttrader_
0
0
2022/05/17
https://www.reddit.com/r/quantfinance/comments/urxzuk/brooklyn_quant_experience_lecture_series_sasha/
urxzuk
4
quantfinance
0.83
After an option skyrockets in price and IV, when will IV decay and drop?
Open
na0p
0
0
2022/05/17
https://www.reddit.com/r/quantfinance/comments/ur9ggq/after_an_option_skyrockets_in_price_and_iv_when/
ur9ggq
5
quantfinance
0.86
Is 3.69 GPA enough to pass GPA filter for Quant Research internships at Jump, Two Sigma, Citadel, and HRT (Algo Dev)?
Open
Alarmed-Special1711
0
5
2022/05/19
https://www.reddit.com/r/quant/comments/usx9wc/is_369_gpa_enough_to_pass_gpa_filter_for_quant/
usx9wc
0
quant
0.45
After an option skyrockets in price and IV, when will IV decay and drop?
Open
na0p
0
1
2022/05/17
https://www.reddit.com/r/quant/comments/ur951l/after_an_option_skyrockets_in_price_and_iv_when/
ur951l
1
quant
1
Next steps for becoming a quant
Open
SeaworthinessScary99
0
6
2022/05/17
https://www.reddit.com/r/quant/comments/ur9qr4/next_steps_for_becoming_a_quant/
ur9qr4
1
quant
0.6
trying to switch from fintech sales to quant
Open
richandlonely24
0
10
2022/05/19
https://www.reddit.com/r/quant/comments/ussoo8/trying_to_switch_from_fintech_sales_to_quant/
ussoo8
1
quant
0.66
Quant Internship Question
Open
idkkkk38389
0
0
2022/05/17
https://www.reddit.com/r/quant/comments/uruemz/quant_internship_question/
uruemz
1
quant
0.56
NYU Tandon Bridge/Other Accelerated Coding "bootcamps"
Open
ariqc
0
1
2022/05/19
https://www.reddit.com/r/quant/comments/usshli/nyu_tandon_bridgeother_accelerated_coding/
usshli
2
quant
1
Market risk interview: Greeks for swap?
Open
txiang
0
3
2022/05/18
https://www.reddit.com/r/quant/comments/urz8ve/market_risk_interview_greeks_for_swap/
urz8ve
6
quant
0.99
Load 50 more
Table
Name
Comments
Content
Date
Job
Likes
Link
ML Score
jean-philippe bouchaud
Open
38
Prices are very, very far from (geometric) Brownian motions. Return distributions are fat-tailed, volatility is “rough”, i.e. clustered in a scale invariant way, negative returns increase future volatility and trends, either up or down, also increase future volatility.  Some mathematical models, such as the recent Multifractal Random Walk or the Quadratic Rough Heston Model, come close to reproducing all these stylized facts.But another, data driven approach is also possible. Look below at the wavelet representation of the S&P500 in the years 2000-2018.  Both intriguing and beautiful no?Wavelet transforms are the appropriate tool to study scale invariant objects, such as turbulence flows, fracture surfaces, galaxies and financial time series. Using only low moments, non-linear correlations between wavelets, Rudy Morel has come up with a parsimonious representation (that rely on scale invariance) which requires only log^2(T) coefficients for a time series of length T. Such a compressed representation can then be used to generate synthetic time series that faithfully capture all the above stylized facts – see our recent preprinthttps://lnkd.in/gJKzae6ZWavelet analysis can be seen as an educated way to deep learn the data, in a way that leverages a priori knowledge -- here about financial time series. The next step will be to compare with brute force deep learning techniques.  #wavelets #volatility #syntheticdata #scaling #stockmarket
2022/04/27
Capital Fund Management | Chairman and Head of research
575
https://www.linkedin.com/feed/update/urn:li:activity:6925031108455649280
11
Jacques Joubert
Open
0
*** Market Microstructure - Quantitative Research ***I am happy to share my last paper on market impact which completes the previous ones that I published on equity and options market during the last years (links in comments). This third paper completes the two previous ones and closes this market impact trilogy I started 6 years ago. In this paper, we propose a theory of the market impact of metaorders based on a coarse-grained approach where the microscopic details of supply and demand is replaced by a single parameter ρ ∈ [0, +∞] shaping the supply-demand equilibrium and the market impact process during the execution of the metaorder. Our model provides an unified explanation of most of the empirical observations that have been reported and establishes a strong connection between the excess volatility puzzle and the order-driven view of the markets through the square-root law.I would like to thank Marcos Lopez de Prado and Prof. Alexander Lipton for their comments on the preliminary version of this paper. I am also particularly grateful to Charles-Albert Lehalle for his careful reading, comments and the many interesting discussions we had about it.
2022/05/18
Shell | Systematic Trader
0
https://www.linkedin.com/feed/update/urn:li:activity:6932772811241316352
10
Charles-Albert Lehalle
Open
5
venez échanger le mardi 31 mai à Paris sur les stratégies d'investissement systématiques avec Marcos Lopez de Prado, Gautier Marti, Marie Brière, Hugues Langlois, Jeroen VK Rombouts et votre serviteur à ce workshop organisé par l'ILB. Au programme: Open Problems in Quantitative Asset Management, Alternative Data et Machine Learning.
2022/05/20
Abu Dhabi Investment Authority (ADIA) | Quantitative R&D Lead
87
https://www.linkedin.com/feed/update/urn:li:activity:6933433694275653634
9
Harvey Stein
Open
66
I’m happy to share that I’m starting a new position as Senior VP, Quant Research at Two Sigma!
2022/05/03
Bloomberg LP | Head, Quantitative Risk Analytics
500
https://www.linkedin.com/feed/update/urn:li:activity:6927035427002449921
9
Prof. Alexander Lipton
Open
2
Continuing my previous post, I'm happy to present the latest episode of Quantcast with the quant finance editor at Risk.net, Mauro Cesa, https://lnkd.in/dYp4hA2r). In addition to stablecoins, we also discussed my recent paper with Artur Sepp of Sygnum Bank on automated market-making in FX, https://lnkd.in/ddVw7RnR. It describes "how central bank digital currencies or stablecoins can be exchanged through a smart contract on the blockchain while retaining pricing consistent with a traditional centralized market." I also argue that "the approach would make FX markets more transparent, retaining the monetary incentives for market-makers while improving efficiency for other players." It also allows direct exchange of relatively illiquid currencies without the need for US dollar transactions.Index: 00:00 Introduction 05:00 Automated FX market-making 09:10 On-chain and off-chain interaction 11:25 Applications of the framework 12:25 The problems with algorithmic stablecoins 20:00 The collapse of TerraUSD 22:55 Viable blockchain applications in finance 29:30 The limits of DeFi 34:35 Non-financial applications#blockchain #stablecoins #fx
2022/05/13
Sila | Co-Founder, Chief Information Officer
42
https://www.linkedin.com/feed/update/urn:li:activity:6930869869294804992
8
jean-philippe bouchaud
Open
1
In 1972, the future Nobel Prize winner Philip Anderson published an article in "Science" entitled "More is Different", in which he explained the concept of emergence in a remarkably clear manner: the behaviour of assemblies of interacting particles cannot be understood as a simple extrapolation of the behaviour of isolated particles. On the contrary, original and surprising behaviours can appear, and their understanding requires specific concepts and new tools. The whole is not greater than the sum of its parts, it is different.  Anderson had in mind, in particular, the surprising collective behaviours in condensed matter systems such as superfluidity, which does not exist at the atomic level, and can only appear at the macroscopic level. This phenomenon of emergence concerns many fields outside physics: collective behaviour of neurons (memory, consciousness), starling murmurations, social unrest, economic crises, financial panics...  I thought that a conference on this theme would be a perfect epilogue to my course on the links between statistical physics - which is precisely the science of emergence - and the social sciences. My hope is to bring together, on June 2nd and 3rd 2022 at the Collège de France, physicists, economists and mathematicians specialised in these ideas, to allow, who knows, the emergence of new research directions.  https://lnkd.in/eG4Y4_9E#research #collective #emergence #crises #panic #collegedefrance
2022/05/05
Capital Fund Management | Chairman and Head of research
18
https://www.linkedin.com/feed/update/urn:li:activity:6928079984494317568
7
Artur Sepp
Open
9
I will talk about modeling the dynamic of implied volatility surfaces of crypto assets (#btc, #eth ) at Imperial College in London on Wednesday the 18th May. I will present an arbitrage-free framework equipped with a stochastic volatility model for the arbitrage-free dynamics and valuation of different types of crypto options. I will illustrate applications for calibrating and modeling of Bitcoin and Ether volatility surfaces using Deribit options exchange data.This talk is based on joint work with Parviz Rakhmonov.
2022/05/04
Sygnum Bank | Head Systematic Solutions and Portfolio Construction
170
https://www.linkedin.com/feed/update/urn:li:activity:6927641787884830720
7
Gautier Marti
Open
1
come and join us in Paris Thursday the 31st of May in Paris for this workshop organized with the Finance and Insurance Rebooted (FaIR) initiative of the Institut Louis Bachelier.It will be great to discuss scientific investment with Marie Brière, Marcos Lopez de Prado, Gautier Marti, Thierry Foucault and Jeroen VK Rombouts. A very interesting Paris + Abu Dhabi meeting!
2022/04/26
Abu Dhabi Investment Authority (ADIA) | Quantitative Research & Development Lead
33
https://www.linkedin.com/feed/update/urn:li:activity:6924572061696724992
7
Igor Halperin
Open
8
Tuesday, May 24, 5:30PM-6:45PM (Eastern Time): Join us for Igor Halperin's online talk "Combining Reinforcement Learning and Inverse Reinforcement Learning for Asset Allocation Recommendations" in NYU Courant's Mathematical Finance & Financial Data Science Seminar. This online event is open to the public, but requires registration. Registration & more details:https://lnkd.in/dzF832kmAbstract: We suggest a simple practical method to combine the human and artificial intelligence to both learn best investment practices of fund managers, and provide recommendations to improve them. Our approach is based on a combination of Inverse Reinforcement Learning (IRL) and RL. First, the IRL component learns the intent of fund managers as suggested by their trading history, and recovers their implied reward function. At the second step, this reward function is used by a direct RL algorithm to optimize asset allocation decisions. We show that our method is able to improve over the performance of individual fund managers.#nyucourant #nyu New York University Courant Institute of Mathematical Sciences NYU Courant Institute of Mathematical Sciences M.S. in Mathematics in Finance, NYU Courant New York University #reinforcementlearning #machinelearning #trading #inversereinforcementlearning
2022/05/13
Fidelity Investments | AI Asset Management
86
https://www.linkedin.com/feed/update/urn:li:activity:6930860574595571712
6
Charles-Albert Lehalle
Open
4
I am very happy that three years after the preprint, our paper "Transaction cost analytics for corporate bonds" with Renyuan Xu and Xin Guo is now published in Quantitative Finance.We started this work long ago at UC Berkeley, convinced that Corporate Bonds deserves systematic and quantitative Transaction Costs Analyses at the level of Equities. Nowadays, with the low yield environment, controlling the cost of buying and selling them is more important than ever.
2022/04/27
Abu Dhabi Investment Authority (ADIA) | Quantitative R&D Lead
208
https://www.linkedin.com/feed/update/urn:li:activity:6924934805113434112
6
Petter Kolm
Open
0
I am looking forward to presenting at the Machine Learning and Quantitative Finance Workshop on June 1 at the Oxford-Man Institute of Quantitative Finance, University of Oxford. More info here:https://lnkd.in/gr9NhMBk#nyu #nyucourant #machinelearning #financialdatascience #trading
2022/05/20
Courant Institute of Mathematical Sciences | Clinical Full Professor of Mathematics
55
https://www.linkedin.com/feed/update/urn:li:activity:6933461572040232961
5
Harvey Stein
Open
1
Our white paper on default modeling is on https://lnkd.in/eUMAPYHU. Nick Costanzino, Albert Cohen and I found that looking at stopping times in terms of their conditional survival curves yields a general framework for default modeling that encompasses both structural and reduced form models. Moreover, whether the stopping time is predictable or totally inaccessible can be directly read off of the survival curves.#default #creditrisk #stoppingtime #predictable #inaccessible #whitepaper
2022/05/17
Bloomberg LP | Head, Quantitative Risk Analytics
75
https://www.linkedin.com/feed/update/urn:li:activity:6932077933444407296
5
Jacques Joubert
Open
0
ML-Quant now has 6 additional web scrapers, for a total of 30 scrapers working 24/7 to 'find' trending content in the quant finance and machine learning space. Today, I added a script to find the top general ML papers as per their social media metrics (twitter, news, YouTube etc.) https://www.ml-quant.com/
2022/05/17
Shell | Systematic Trader
3
https://www.linkedin.com/feed/update/urn:li:activity:6932378149317939200
5
Matthew Dixon
Open
7
For me personally, one of the holy grails is to tie machine learning and finance to climate change - that is using ML in finance to tackle some of the most challenging problems of our time. In addition to ESG investing, providing financial protection against climate risk is another key ingredient - we need to protect society while figuring out our sustainability transition plan. Natural disasters could otherwise wipe out budgets set aside for R&D, e.g. Hurricane Katrina devastated New Orleans. That, perversely, over time gives fossil fuel companies the upper hand.Destruction -> poverty-> lack of education-> poor personal sustainability hygiene and lack of local opposition to fossil fuel companies (fossil fuel jobs>perceived environmental damage)While not a climate solution, there is a growing contingent claim product area for managing climate change and natural disaster risk and one area where richer datasets (e.g. satellite imagery) and ML can ultimately make a significant difference in ensuring fair pricing and more robust uncertainty quantification. Our latest technical paper on embedding clustering into a unified Hierarchical Bayesian modeling framework for catastrophe and interest rate risk premia adjusted CAT bond pricing is available on arXiv: https://lnkd.in/dQivqGXW This is joint work with co-authors Chatterjee and Domfeh. #climaterisk #machinelearning #environmentalfinance #bayesianstatistics #insuretech #quantitativefinance #weatherforecasting Peter Adriaens Dixon Domfeh Morton Lane Runhuan Feng, PhD, FSA, CERA Todd Ringler Swami Sethuraman Joydeep Lahiri Maura Feddersen Larry Eisenberg Dr. Sebastian Rath Richard Matsui Lawrence Habahbeh
2022/05/12
CFX Labs Inc. | Co-Founder
92
https://www.linkedin.com/feed/update/urn:li:activity:6930361958030270464
5
Peter Cotton, PhD
Open
52
Coinbase said in its earnings report Tuesday that it holds $256 billion in both fiat currencies and cryptocurrencies on behalf of its customers. Yet the exchange noted that in the event it ever declared bankruptcy, “the crypto assets we hold in custody on behalf of our customers could be subject to bankruptcy proceedings.” Coinbase users would become “general unsecured creditors,” meaning they have no right to claim any specific property from the exchange in proceedings. Their funds would become inaccessible.Coinbase is down 70% YTD.FUD?
2022/05/11
Intech Investment Management LLC | Senior Vice President. Chief Data Scientist.
53
https://www.linkedin.com/feed/update/urn:li:activity:6930191486651179008
5
Prof. Alexander Lipton
Open
18
Section 8.4.5 of my and Adrien Treccani, Ph.D.'s book Blockchain And Distributed Ledgers: Mathematics, Technology, And Economics, https://lnkd.in/dPuCJjxf published in 2021, is called Dynamically Stabilized Coins. It is exclusively devoted to critiquing dynamic stabilization schemes despite VC's keep throwing money at them. (Why not simply make an effort to read the book instead of believing an army of salespeople and techies without the slightest idea of the whole concept?) We clearly stated, "This stabilization scheme represents yet another pure theoretical construct that cannot and does not work in practice and will collapse..." We even compared these algorithms to Baron Munchausen, who famously described to the trusting crowd how he pulled himself and his horse out of a mire by his hair. To those who did not want to listen, enjoy the Terra ride now! In the interest of the community, please see this section in full#blockchain #economics #dynamicallystabilizedcoins #terra
2022/05/10
Sila | Co-Founder, Chief Information Officer
73
https://www.linkedin.com/feed/update/urn:li:activity:6929809150734405632
5
Ariel Silahian
Open
9
!
2022/05/19
Quant Developers | High Frequency Trading solutions | Founder & CTO / Lead Tech
17
https://www.linkedin.com/feed/update/urn:li:activity:6932817352912769024
4
Dr Miquel Noguer i Alonso
Open
0
We released a new paper : " Deep Signature models for Financial Equity Time Series prediction" along with Sonam Srivastava and Himanshu AgrawalWe explore in this paper the use of deep signature models to predict equity financial time series returns. First, we use signature transformations to model the underlying shape of the input equity returns; further assuming the underlying shape remains the same, we predict future values based on that shape. Finally, different neural networks are used to process the output from signature transformation to predict equity returns: Long Short Term Memory Networks, Signet Model, and Deep Signature Model. Feeding signature transformations to a neural network brings significant improvement in prediction. Using signature transformation and Long Short Term Memory Networks proves to be the best performing model in accuracy and precision. In contrast, on RMSE terms, all three models offer very comparable performance.You can download the paper here:https://lnkd.in/gWqHeBn5www.aifinanceinstitute.com AIFI - Artificial Intelligence Finance Institute
2022/05/17
Artificial Intelligence Finance Institute - AIFI | Founder at Artificial Intelligence Finance Institute
50
https://www.linkedin.com/feed/update/urn:li:activity:6932364172722655233
4
jean-philippe bouchaud
Open
35
I am not sure I know enough about blockchains to say anything relevant at all. But sometimes silly ideas turn out to be useful, so here we go and bear with my naiveté, as I know I am out of my depth here. One of the main problem of the proof of work protocol is the uncanny amount of energy used to solve (by brute force computation) difficult but totally pointless mathematical riddles. On the other hand, scientific computation for a purpose (academic or industrial) also require tremendous amounts of CPU time.So would it be possible to create a kind of market where snippets of real computation tasks of different complexity are submitted and “solved” by miners, thereby *simultaneously* validating transactions and performing something else that is useful? Of course, the difficulty would be to be sure that the task has actually been performed, which is easy when the solution of the riddle is already known. One would have to come up with a way to embed an easy auxiliary task that can be quickly checked but that can only be completed when the main (useful) task is done.OK perhaps this is totally unpractical, and other protocols with (much) less carbon footprint may turn out to solve the problem. But if proof of work is somehow here to stay, I would find some comfort in thinking that all this computer power isn’t only burnt on trivia.#blockchain #bitcoin #computing #carbonfootprint #scientificresearch
2022/05/17
Capital Fund Management | Chairman and Head of research
117
https://www.linkedin.com/feed/update/urn:li:activity:6932359607289847809
4
Mauro Cesa
Open
2
For the latest Quantcast, I’m joined by Prof. Alexander Lipton, global head of quantitative R&D at ADIA. He talks about his latest work with Artur Sepp on their automated market making framework for currencies that uses smart contracts and central bank digital currencies or stablecoins. From stablecoins, the conversation inevitably moves to the flaws of algorithmically stabilised coins like Terra UST, and why their design cannot work.
2022/05/13
Infopro Digital | Quant finance editor, Risk.net
35
https://www.linkedin.com/feed/update/urn:li:activity:6930818141681819648
4
Saeed Amen
Open
4
“In this period of dramatic structural change, I do not care about technology. Tech is the least important part of the next 20 years.” Paul Donovan, Chief Economist at UBS Global Wealth Management, said at Calcalist’s Meet &Tech event. “The economic transformation, the economic change, does not come from technology, but how we use it.”
2022/05/12
Cuemacro | Founder
82
https://www.linkedin.com/feed/update/urn:li:activity:6930458226031271936
4
Álvaro Cartea
Open
0
New paper "Algorithmic Collusion in Electronic Markets: The Impact of Tick Size". This is joint work with Patrick Chang (Oxford-Man Institute) and Jose Penalva (Universidad Carlos III de Madrid & Associate member of the Oxford-Man Institute). All comments welcome. #algorithmictrading #machinelearning #machinelearningalgorithms #microstructure #regulation #reinforcementlearning #gametheory #quantitativefinance #artificialintelligence
2022/05/11
University of Oxford | Professor
64
https://www.linkedin.com/feed/update/urn:li:activity:6930141738711855104
4
Matthew Dixon
Open
2
If you enjoy doing quantitative financial research, have an advanced degree in a highly quantitative field, and have proven experience working with fundamental, market, analytics, and/or alternative data, come and join ADIA and its formidable quant team at https://lnkd.in/eYtHTVuq #quantitativeresearch #datascience
2022/05/08
CFX Labs Inc. | Co-Founder
79
https://www.linkedin.com/feed/update/urn:li:activity:6929163917130690560
4
Alec Schmidt
Open
20
Is volatility "rough"?A series of papers in the last few years have suggested that 'volatility' is best modeled using fractional processes with Hurst exponent H< 0.5, so with paths 'rougher' than Brownian motion.Prior to that, many in the 1990s and early 2000s had advocated modeling volatility with fractional processes exhibiting long-range dependence, so with Hurst exponent H > 0.5 ....A slightly confusing situation, to say the least.We revisit these claims by applying a nonparametric, model-free method for estimating the roughness of a signal. Using detailed simulation experiments in rough and non-rough stochastic volatility models, as well as high frequency market data (in fact, the same data sets used in 'rough volatility' studies),we find that the origin of the apparent 'roughness' observed in realized volatility time-series lies in the estimation error rather than the volatility process itself.A subtle point is that 'volatility' is not a directly observed quantity and needs to be estimated, and the estimation error seems to be all but nicely behaved...#volatility #quantitativefinance
2022/05/08
Financial Risk and Engineering, NYU School of Engineering | Adjunct Professor
191
https://www.linkedin.com/feed/update/urn:li:activity:6929147750932484096
4
Matthew Dixon
Open
5
I might have long forgotten what a time-changed Brownian motion is, but I still remember the image of an energetic scholar riding his bike on campus; and I still remember his last words to a graduating class of students who would inevitably enter the capitalist world: that we should not forget, we owe more to society than to the company we work for. This, I will not forget. Goodbye.
2022/05/07
CFX Labs Inc. | Co-Founder
60
https://www.linkedin.com/feed/update/urn:li:activity:6928771707621048320
4
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Table
Name
Tweet
Favourite Count
Follower Count
Location
Profile URL
Published
Retweet Count
Text URL
Tweet URL
User
QuantSymplectic
Open
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
25
10073
2022/05/19
0
https://bit.ly/3wvwZTv
https://twitter.com/QuantSymplectic/status/1527291991222013953
QuantSymplectic
PythonHub
Open
Web Scraping with Python: Everything you need to know https://t.co/LbYlIjP1xO
16
90225
https://t.co/bCW8eigFCZ
2022/05/19
7
https://www.scrapingbee.com/blog/web-scraping-101-with-python/
https://twitter.com/PythonHub/status/1527110577054748672
PythonHub
carlcarrie
Open
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
14
9776
New York
https://t.co/RKDfeDu90F
2022/05/21
3
https://github.com/grayvalley/microprice-calibration
https://twitter.com/carlcarrie/status/1528014546207899650
carlcarrie
JigneshTrade
Open
#OptionsTrading #BankNiftyOptions Smoothest decay in premium, in recent time. https://t.co/85U5QLvrKO
13
10212
Mumbai, India
https://t.co/6tvFcbiHLF
2022/05/19
0
https://twitter.com/JigneshTrade/status/1527189828592631809
JigneshTrade
achenfinance
Open
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
10
1251
Washington, DC
https://t.co/fF9aiHSJz6
2022/05/20
0
https://twitter.com/achenfinance/status/1527715310094123008
achenfinance
PythonHub
Open
Pandas Tutor - visualize Python pandas code https://t.co/47SirC2J2a
10
90484
https://t.co/bCW8eigFCZ
2022/05/20
4
https://www.reddit.com/r/Python/comments/upbhyh/pandas_tutor_visualize_python_pandas_code/
https://twitter.com/PythonHub/status/1527533364969979906
PythonHub
PythonHub
Open
Python for DevOps Master Class 2022: CI/CD, Github Actions, Containers and Microservices https://t.co/X55M2TvBFl
9
90781
https://t.co/bCW8eigFCZ
2022/05/22
1
https://www.youtube.com/watch?v=kwZNpieUreA
https://twitter.com/PythonHub/status/1528348734135971842
PythonHub
PythonHub
Open
Python in Visual Studio Code – May 2022 Release With this release we’re introducing three new extensions: Black, isort, and Jupyter Powertoys. https://t.co/wQyYwjKQ1N
9
90270
https://t.co/bCW8eigFCZ
2022/05/19
4
https://devblogs.microsoft.com/python/python-in-visual-studio-code-may-2022-release/
https://twitter.com/PythonHub/status/1527231373735600133
PythonHub
PythonHub
Open
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
8
90414
https://t.co/bCW8eigFCZ
2022/05/19
4
https://www.b-list.org/weblog/2022/may/13/boring-python-dependencies/
https://twitter.com/PythonHub/status/1527412564707229696
PythonHub
macro_srsv
Open
"Sentiment Analysis of Economic Text: We use [a] dictionary to construct a measure of economic pessimism...It captures the business cycle and correlates with economic and financial uncertainty." https://t.co/AV6Nhe48O5 https://t.co/UGodTEt5dI
8
7845
London, England
https://t.co/Ad7SPhJxME
2022/05/18
1
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4106936
https://twitter.com/macro_srsv/status/1526815048861208577
macro_srsv
fullstackpython
Open
Web applications 101 https://t.co/F6gth3WyYH https://t.co/7aOumJOi2r
7
77099
https://t.co/lolwlhkqya
2022/05/19
2
https://www.robinwieruch.de/web-applications/
https://twitter.com/fullstackpython/status/1527415311653294080
fullstackpython
macro_srsv
Open
"While investors demand a premium to hold stocks with high illiquidity...they underreact to stock-level liquidity shocks... A long-short [idiosyncratic] liquidity shocks strategy earns significantly high returns during abnormal market states." https://t.co/SCslAvJyN5 https://t.co/EHwNgPIlp1
7
7852
London, England
https://t.co/Ad7SPhJxME
2022/05/19
1
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4099584
https://twitter.com/macro_srsv/status/1527176655713837056
macro_srsv
PythonHub
Open
Freshenv A cli to provision and manage local developer environments. https://t.co/gkgiTDBBm4
7
90180
https://t.co/bCW8eigFCZ
2022/05/18
1
https://github.com/raiyanyahya/freshenv
https://twitter.com/PythonHub/status/1526989781221220354
PythonHub
carlcarrie
Open
Optimal Execution and Market Making Paper: https://t.co/aWlpBv1YOt Python GitHub: https://t.co/4MIVvu02YK
7
9696
New York
https://t.co/RKDfeDu90F
2022/05/17
0
https://github.com/layoups/microstructure-and-liquidity/blob/main/report.pdf
https://twitter.com/carlcarrie/status/1526352548696887297
carlcarrie
PythonHub
Open
Deploying Django To App Engine With Github Actions https://t.co/cSWnk8ph5D
6
90245
https://t.co/bCW8eigFCZ
2022/05/19
1
https://cjoshmartin.com/blog/deploying-django-to-app-engine-with-github-actions/
https://twitter.com/PythonHub/status/1527170975288147968
PythonHub
robertmartin88
Open
1/2 Shakespeare on diversification (Merchant of Venice): “My ventures are not in one bottom trusted, nor to one place; nor is my whole estate upon the fortune of this present year. Therefore my merchandise makes me not sad”
6
5872
London, England
https://t.co/cyX6zqG4jq
2022/05/18
0
https://twitter.com/robertmartin88/status/1526914110562213889
robertmartin88
carlcarrie
Open
Entropy in stock indexes with R, Shiny and Tidy #Rstats GitHub https://t.co/FIVZCW4i3z https://t.co/1ROwYR0kMo
6
9737
New York
https://t.co/RKDfeDu90F
2022/05/17
2
https://aikia.org/2022/05/14/index-entropy/
https://twitter.com/carlcarrie/status/1526657702901989381
carlcarrie
macro_srsv
Open
"We...review recent advancements in research on predictive models of [equity] earnings and returns...[including] statistical, econometric, and machine learning advancements." https://t.co/TBljeOfBjE https://t.co/riavSpZixA
6
7838
London, England
https://t.co/Ad7SPhJxME
2022/05/17
2
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4095277
https://twitter.com/macro_srsv/status/1526453268775415808
macro_srsv
PythonHub
Open
Celery Alternative for Django - Huey Trying out a lightweight asynchronous task queue as an alternative to Celery with Django. https://t.co/3gUguhRK0k
5
90742
https://t.co/bCW8eigFCZ
2022/05/22
0
https://idiomaticprogrammers.com/post/celery-alternative-for-django-huey/
https://twitter.com/PythonHub/status/1528167542275153920
PythonHub
carlcarrie
Open
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
5
9776
New York
https://t.co/RKDfeDu90F
2022/05/21
1
https://jfin-swufe.springeropen.com/articles/10.1186/s40854-022-00352-7
https://twitter.com/carlcarrie/status/1528025383530110979
carlcarrie
carlcarrie
Open
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
5
9772
New York
https://t.co/RKDfeDu90F
2022/05/21
1
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4107756
https://twitter.com/carlcarrie/status/1527791454009147394
carlcarrie
PythonHub
Open
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
5
90560
https://t.co/bCW8eigFCZ
2022/05/20
2
https://www.reddit.com/r/Python/comments/ululk1/i_used_a_new_dataframe_library_polars_to_wrangle/
https://twitter.com/PythonHub/status/1527714560588795907
PythonHub
macro_srsv
Open
"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
5
7861
London, England
https://t.co/Ad7SPhJxME
2022/05/20
0
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4097100
https://twitter.com/macro_srsv/status/1527538021536518145
macro_srsv
PythonHub
Open
Sorting lists in python: sorted() vs sort() https://t.co/IMygTQBwWP
5
90306
https://t.co/bCW8eigFCZ
2022/05/19
3
https://www.reddit.com/r/Python/comments/uqqseh/sorting_lists_in_python_sorted_vs_sort/
https://twitter.com/PythonHub/status/1527291772690386944
PythonHub
robertmartin88
Open
2/2 Though funnily enough there’s also a lesson about the dangers of apparent diversification. All of Antonio’s supposedly uncorrelated ventures failed at the same time (too much exposure to the shipwreck factor?) and he almost got his heart cut out as a result!
5
5872
London, England
https://t.co/cyX6zqG4jq
2022/05/18
0
https://twitter.com/robertmartin88/status/1526914112051093506
robertmartin88
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