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.

Last update: Dec 02, 2022

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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:

Owner

Gamma Strategies

An organization dedicated to funding ‘Active LP’ strategies and research. Applications now accepted.

GitHub Repository

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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.

Related tags

Overview

Gamma's Strategy One

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

Owner

Gamma Strategies

DETReg: Unsupervised Pretraining with Region Priors for Object Detection

Code, final versions, and information on the Sparkfun Graphical Datasheets

A simple editor for captions in .SRT file extension

Compare neural networks by their feature similarity

CTC segmentation python package

HCQ: Hybrid Contrastive Quantization for Efficient Cross-View Video Retrieval

[ICCV'21] Neural Radiance Flow for 4D View Synthesis and Video Processing

[CVPR 2022] Thin-Plate Spline Motion Model for Image Animation.

[ECE NTUA] 👁 Computer Vision - Lab Projects & Theoretical Problem Sets (2020-2021)

Use CLIP to represent video for Retrieval Task

Material related to the Principles of Cloud Computing course.

Versatile Generative Language Model

Code of paper Interact, Embed, and EnlargE (IEEE): Boosting Modality-specific Representations for Multi-Modal Person Re-identification.

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