QuantDare

Second chances with #Momentum #sp500 #assetmanagement bit.ly/36YeCJq

The Signature of a #timeseries is a universal description for a stream of data derived. Over the last years, this technique has been used successfully applied in a wide array of #MachineLearning tasks dealing with sequential data by @meer_pardo bit.ly/3hUzBj2

The #Kellycriterion first described by John Kelly is one of the most useful techniques when it comes to #assetallocation strategies in the #stockmarket. Would you like to know more? #portfoliomanagement bit.ly/2ZCMxns?platform=hoot…

Variational autoencoder as a method of #dataaugmentation #MachineLearning #ArtificialIntelligence bit.ly/2XU2CU9

Probabilistic #SharpeRatio example coded in Python. Breakdown of @lopezdeprado 's paper. Dealing with non-Normal returns (skewness and kurtosis). bit.ly/36iP4Fq #Python #Riskmanagement

What is the difference between #parameters and #hyperparameters? by @anitaporr #MachineLearning #Datascience bit.ly/35WYBSg

We use BERT, a #deeplearning network for #NLP tasks, to do sentiment analysis of newspaper text in order to predict stock market returns. bit.ly/2zjLEFU #QuantDare #Neuralnetwork

Artificial Neural Networks (ANN) complexity makes hard to understand them. Visual representations of its training process can help to show how they work. #AI #ML #Python bit.ly/2YsMGKx

The #BlackScholes formula can be used to create a hedge for an #option. But is this model accurate when we use it in discrete-time? #riskmanagement #assetmanagement bit.ly/3bym7qU

Even if only investing in local assets, one can be exposed to foreign #currencyrisks. We discuss how to measure this risk in order to prevent it. #riskmanagement bit.ly/2RGnewG

Towards acceptance testing in #Finance. What acceptance testing is and how to simply build returns with a specific #correlation matrix. #Riskmanagement bit.ly/2XijtkJ

Was the March #VIX explosion correctly forecast by #DeepLearning models? We revisit an experiment presented last year that did warn us of the perils ahead by @meer_pardo bit.ly/2USR8yM #MachineLearning #volatility

Comparing results. Simple moving average vs simple moving median. Is it better to have robust estimators in our strategies? bit.ly/2TXtKAI #QuantDare #robuststrategies #forex #tradingstrategy

How an active portfolio is exposed to financial factors? Let's see an alternative way of defining the #factorexposure in comparison with a #benchmark. #activeshare #spiderchart #finance bit.ly/2SDzTBu

Let's see how to implement a simple function using #TensorFlow 2 to obtain the #derivatives of any function in an easy way by @mmngreco #Python bit.ly/2HkE0fy

There are several dimensionality reduction techniques to visualise ETFs. Let's compare the ability to visualise ETFs using UMAP instead of t-SNE by @jvicentem93 bit.ly/36WrPj5 #DataScience #Dataanalysis #FinancialTimeSeries

@gvarnu & @meer_pardo have written the following post to explain how to use #GANs to generate Open-High-Low-Close synthetic bars that help us to mitigate overfitting. #AI #ML #DL bit.ly/2Uf05U6?platform=hoot…

Detection of outliers in FOREX series using autoencoders to avoid problems when applying machine learning techniques to them. #ArtificialIntelligence #MachineLearning #Python ⬇️ bit.ly/2R0NoKB

There are several methods to reduce dimensions, such as #PCA or #autoencoders. Here we explain how to use autoencoders as dimensionality reduction method. #MachineLearning #AI bit.ly/2RGvX32

Mitigating #overfitting on Trading Strategies bit.ly/3639Kjg #MachineLearning #Python #Assetmanagement #riskmanagement