This initial strategy was developed specifically for larger pools and is based on taking a moving average and deriving Bollinger Bands to create a projected active liquidity range.

Overview

Gamma's Strategy One

This initial strategy was developed specifically for larger pools and is based on taking a moving average and deriving Bollinger Bands to create a projected active liquidity range.

View the simulation folder to view the historic behavior of high fee pools on Uniswap.

View the API-endpoint folder to see how we are collecting and deriving Bollinger Bands for the first strategy. This endpoint uses Uniswap v3 subgraph to analize current and historic pricing at a set interval. With the endpoint, the query returns all pools for a given asset and then pricing data with Bollinger Bands for any pair.

Here is a rendering of the Bollinger Bands for the USDT-ETH pair:

gamma-strat-one

You might also like...
Monocular Depth Estimation - Weighted-average prediction from multiple pre-trained depth estimation models
Monocular Depth Estimation - Weighted-average prediction from multiple pre-trained depth estimation models

merged_depth runs (1) AdaBins, (2) DiverseDepth, (3) MiDaS, (4) SGDepth, and (5) Monodepth2, and calculates a weighted-average per-pixel absolute dept

OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network
OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network

Stock Price Prediction of Apple Inc. Using Recurrent Neural Network OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network Dataset:

A commany has recently introduced a new type of bidding, the average bidding, as an alternative to the bid given to the current maximum bidding
A commany has recently introduced a new type of bidding, the average bidding, as an alternative to the bid given to the current maximum bidding

Business Problem A commany has recently introduced a new type of bidding, the average bidding, as an alternative to the bid given to the current maxim

This is a model made out of Neural Network specifically a Convolutional Neural Network model
This is a model made out of Neural Network specifically a Convolutional Neural Network model

This is a model made out of Neural Network specifically a Convolutional Neural Network model. This was done with a pre-built dataset from the tensorflow and keras packages. There are other alternative libraries that can be used for this purpose, one of which is the PyTorch library.

A command line simple note taking app

Why yet another note taking program? note was designed with a very specific target in mind: me, and my 2354 scraps of paper. It runs from the command

Notes taking website build with Docker + Django + React.
Notes taking website build with Docker + Django + React.

Notes website. Try it in browser! / But how to run? Description. This is monorepository with notes website. Website provides web interface for creatin

Range Image-based LiDAR Localization for Autonomous Vehicles Using Mesh Maps
Range Image-based LiDAR Localization for Autonomous Vehicles Using Mesh Maps

Range Image-based 3D LiDAR Localization This repo contains the code for our ICRA2021 paper: Range Image-based LiDAR Localization for Autonomous Vehicl

 DeFMO: Deblurring and Shape Recovery of Fast Moving Objects (CVPR 2021)
DeFMO: Deblurring and Shape Recovery of Fast Moving Objects (CVPR 2021)

Evaluation, Training, Demo, and Inference of DeFMO DeFMO: Deblurring and Shape Recovery of Fast Moving Objects (CVPR 2021) Denys Rozumnyi, Martin R. O

performing moving objects segmentation using image processing techniques with opencv and numpy
performing moving objects segmentation using image processing techniques with opencv and numpy

Moving Objects Segmentation On this project I tried to perform moving objects segmentation using background subtraction technique. the introduced meth

Owner
Gamma Strategies
An organization dedicated to funding ‘Active LP’ strategies and research. Applications now accepted.
Gamma Strategies
Automatic tool focused on deriving metallicities of open clusters

metalcode Automatic tool focused on deriving metallicities of open clusters. Based on the method described in Pöhnl & Paunzen (2010, https://ui.adsabs

null 2 Dec 13, 2021
FLVIS: Feedback Loop Based Visual Initial SLAM

FLVIS Feedback Loop Based Visual Inertial SLAM 1-Video EuRoC DataSet MH_05 Handheld Test in Lab FlVIS on UAV Platform 2-Relevent Publication: Under Re

UAV Lab - HKPolyU 182 Dec 4, 2022
A tool to analyze leveraged liquidity mining and find optimal option combination for hedging.

LP-Option-Hedging Description A Python program to analyze leveraged liquidity farming/mining and find the optimal option combination for hedging imper

Aureliano 18 Dec 19, 2022
Official Implementation of CVPR 2022 paper: "Mimicking the Oracle: An Initial Phase Decorrelation Approach for Class Incremental Learning"

(CVPR 2022) Mimicking the Oracle: An Initial Phase Decorrelation Approach for Class Incremental Learning ArXiv This repo contains Official Implementat

Yujun Shi 24 Nov 1, 2022
Definition of a business problem according to Wilson Lower Bound Score and Time Based Average Rating

Wilson Lower Bound Score, Time Based Rating Average In this study I tried to calculate the product rating and sorting reviews more accurately. I have

null 3 Sep 30, 2021
Moving Object Segmentation in 3D LiDAR Data: A Learning-based Approach Exploiting Sequential Data

LiDAR-MOS: Moving Object Segmentation in 3D LiDAR Data This repo contains the code for our paper: Moving Object Segmentation in 3D LiDAR Data: A Learn

Photogrammetry & Robotics Bonn 394 Dec 29, 2022
Cockpit is a visual and statistical debugger specifically designed for deep learning.

Cockpit: A Practical Debugging Tool for Training Deep Neural Networks

Felix Dangel 421 Dec 29, 2022
An unofficial personal implementation of UM-Adapt, specifically to tackle joint estimation of panoptic segmentation and depth prediction for autonomous driving datasets.

Semisupervised Multitask Learning This repository is an unofficial and slightly modified implementation of UM-Adapt[1] using PyTorch. This code primar

Abhinav Atrishi 11 Nov 25, 2022
Robustness between the worst and average case

Robustness between the worst and average case A repository that implements intermediate robustness training and evaluation from the NeurIPS 2021 paper

CMU Locus Lab 10 Dec 10, 2021
Cancer-and-Tumor-Detection-Using-Inception-model - In this repo i am gonna show you how i did cancer/tumor detection in lungs using deep neural networks, specifically here the Inception model by google.

Cancer-and-Tumor-Detection-Using-Inception-model In this repo i am gonna show you how i did cancer/tumor detection in lungs using deep neural networks

Deepak Nandwani 1 Jan 1, 2022