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Advance Detection Of Bull And Bear Phases In Cryptocurrency Markets

Rahul Arulkumaran, Suyash Kumar, Shikha Tomar, Manideep Gongalla, Harshitha

Abstract

Cryptocurrencies are highly volatile financial instruments with more and more new retail investors joining the scene with each passing day. Bitcoin has always proved to determine in which way the rest of the cryptocurrency market is headed towards. As of today Bitcoin has a market dominance of close to 50 percent. Bull and bear phases in cryptocurrencies are determined based on the performance of Bitcoin over the 50 Day and 200 Day Moving Averages. The aim of this paper is to foretell the performance of bitcoin in the near future by employing predictive algorithms. This predicted data will then be used to calculate the 50 Day and 200 Day Moving Averages and subsequently plotted to establish the potential bull and bear phases.

Advance Detection Of Bull And Bear Phases In Cryptocurrency Markets

Abstract

Cryptocurrencies are highly volatile financial instruments with more and more new retail investors joining the scene with each passing day. Bitcoin has always proved to determine in which way the rest of the cryptocurrency market is headed towards. As of today Bitcoin has a market dominance of close to 50 percent. Bull and bear phases in cryptocurrencies are determined based on the performance of Bitcoin over the 50 Day and 200 Day Moving Averages. The aim of this paper is to foretell the performance of bitcoin in the near future by employing predictive algorithms. This predicted data will then be used to calculate the 50 Day and 200 Day Moving Averages and subsequently plotted to establish the potential bull and bear phases.

Paper Structure

This paper contains 10 sections, 7 equations, 6 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Predictive Modelling And Advance Phase Detection
  3. Data Collection
  4. Data Generation And Technical Indicators
  5. Data Pre-processing and Exploratory Data Analysis
  6. Model Formulation And Data Splitting
  7. Formulation and Implementation of Multiple Linear Regression
  8. Formulation and Implementation of LSTM
  9. Results and Discussions
  10. Conclusion

Figures (6)

  • Figure 1: Graphical Representation Of Golden Cross and Death Cross.
  • Figure 2: Project Architecture
  • Figure 3: Predicted 50-day and 200-day Moving Average By LSTM.
  • Figure 4: Actual 50-day and 200-day Moving Average.
  • Figure 5: Predicted 50-day and 200-day Moving Average By MLR.
  • ...and 1 more figures