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pyTSA
TENET
TENET: Tail-Event driven NETwork RiskMLvsGARCH
MVA
Quantnet: MVA quantletsTXT
Quantlets of textmining projectsSFE
Quantnet: SFE quantletsDEDA_Class_2017
This repository is for DEDA class in 2017.EmbeddingPortfolio
A repository for portfolio allocation based on embedding data representationGrangerCausalityTestInQuantile
hedging_cc
DataGenerationForCausalInference
Generates synthetic data to apply simulations for causal inferenceSVCJ
SDA_2020_NCTU
STF
Quantnet: STF quantletsBitcoinPricingKernels
GANTimeSeries
This repository contains supplementary material for the talk GAN for Time SeriesDEDA_class_SoSe2023
Quantlet
BCS
FittingElephant
SVCJ_MC
SPM
Quantnet: SPM quantletsSIFI
XFG3
Q for Applied Quantitative Finance (3rd edition)LETF-Moneyness
DEDA_Class_SS2018
CCP
Codes for replicating results in the research paper "Risk-based versus target-based portfolio strategies in the cryptocurrency market"DEDA_class2019_SYSU
This is the SDA DEDA Class in SYSU GuangzhouSDA_2021_St_Gallen
Blockchain_mechanism
This repository consists the codes that are used in the paper 'Blockchain mechanism and distributional characteristics of cryptos' published in 'Advances in Quantitative Analysis of Finance & Accounting (AQAFA)'MPF-Electricity
Codes for the paper "Multivariate probabilistic forecasting of electricity prices with trading applications" ( I Agakishiev, WK Hรคrdle, M Kopa, K Kozmik, and A PetukhinaSVCJOptionApp
Final Thesis of Ivan Perez! R code used in the Master Thesis "Graphical User Interface for pricing Cryptocurrency Options under the SVCJ model"OI_Crypto
Order Imbalances and Returns in Cryptocurrency MarketsSDA_2019_St_Gallen
TERES
TERES - Tail Event Risk Expectile based ShortfallSVCJrw
SFE_class_2015
Code contributed by students in the SFE class WS 2015/2016SPL_class_WS1617
DEDA-SoSe2021
MediaNews
Media News and Financial MarketXFG
Quantnet: XFG quantletsBLEM
Quantlets for Master Thesis of Michael KostmannGeoCopula
Spatial-temporal copula model for spatial-clustered dataCRIX_Cointegration
PyIntro
Introduction to Python (Crash Course)exgb
Ensemble of XGB models with artificial features creationSFS
Quantnet: SFS quantletsPCA-in-an-Asymmetric-Norm
This is the application of TopDown, BottomUp and PrincipalExpectile algorithms to the Chinese weather dataCryptocurrencies-and-Stablecoins-a-high-frequency-analysis
Repository for Cryptocurrencies and Stablecoins - a high frequency analysisMVA-ToDo
Quantlets to update for MVAStyleguide-and-FAQ
Includes the Styleguide and Frequently Asked Questions (FAQ)cryptocollect
Collect data from different crypto exchanges & deribit option data and write them into a MongoDB. Triggered via 'start_ws.sh' to make sure the scripts keep runningSupervised-Randomization
Experiments showing the profit efficiency of targeted randomized sampling in comparison to standard A/B testingCOP
CSC_Dapps
RCVJ_Forecasting
SDA_2020_Giessen
Smart Data Analytics Course OCT 2020 GiessenShapley_Smoothing
NAR
Metcalfe_Law_and_LPPL_Crypto
network_BTC_exchanges
mvcaviar
Multivariate CAViaR with time varying parameterNIC_class_2015
Numerical Introductory Course WS15/16 - Sample of codes provided by studentsHedging-Cryptos-with-Bitcoin-Futures
CRIXdeeplearning
Deep learning methods for cryptocurrencies price predictionsTEDAS
TEDAS codesNextUnicorn
This folder contains 10 quantlets for the master thesis "Searching for a unicorn: A ML approach towards predicting startup success"SPL
Codes provided by students of the course "Statistical programming languages"Quantinar-Staking-Simulation
DEDA_Class_2019SS
Blockchain seminarBitcoinOptions
Local_Quantile_Regression
Codes for Local Quantile RegressionTalesSentimentTails
Tales of Sentiment driven Tailsquantinar_nft
Issue NFTs on your Quantlets on www.quantinar.comVCRIX
Volatility Index on the basis of CRIX (Master Thesis).MSM
for teachingDEDA_Class_2019WS
DEDA class 2019 winter semesterDEDA_class_WS21
This repository is for Digital Economy and Data Analytics class of WS 2021/22MSE
Quantnet: MSE quantletsSPL_class_SS17
RobustM
DEDA-PY-INTRO
SDC
Smart Derivative ContractsDEDA_2022_NYCU
The course open in 2022 at NYCU (National Yang Ming Chiao Tung University), where students can upload their projects hereOutcome-adaptive-Random-Forest
Non-parametric variable selection and inference via the outcome-adaptive Random Forest (OARF). Uses the IPTW estimator to estimate the ATE while the propensity score is estimated via OARF. This leads to smaller variance and bias. Only variables that are confounders or predictive of the outcome are selected for the propensity score.Love Open Source and this site? Check out how you can help us