jackmin97's repositories
Cross-Sectional-Momentum-Strategy
Cross sectional momentum is trend based investment strategy, where you can choose top 'n' percentile to go long and bottom 'n' percentile to go short from the universe of assets.
Cross-Sectional-Momentum-Strategy-using-Fundamental-Data
In this notebook, we will consider the positive moves in fundamentals of the stocks, which is also a measure of strong past performance. We will create cross-sectional momentum strategy considering one of the fundamental factors. We will also combine fundamental momentum with price momentum to create and analyse cross-sectional momentum strategy.
Ichimoku-Cloud-Strategy
In this notebook, we will create a crypto strategy using Ichimoku Cloud.
Bitcoin-Bear-Put-Spread-Payoff
In this notebook, we will build the payoff graph for long 16700 strike put and short 16300 strike put on Bitcoin.
Crypto-Long-Only-Momentum-Strategy
In this notebook, we will create and backtest a long-only momentum strategy using a basket of 10 cryptocurrencies.
Crypto-Pairs-Trading-Strategy
In this notebook, we will create a pairs trading strategy. Pairs trading is a market neutral strategy where we go long on one crypto pair an short on the other one, betting that the spread between the two would eventually converge to their mean.
Cryptocurrencies-Price-Prediction-using-LSTM-Neural-Network-model
Empirical study on applying Long Short-Term Memory (LSTM) model to predict five major cryptocurrencies that are: Bitcoin (BTC), Ethereum (ETH), Cardano (ADA), Solana (SOL) and Polkadot (DOT).
Historical-Bitcoin-Volatility-Calculation
Computation ofthe 20 trading days (or 1 month) Bitcoin historical volatility for the time period starting from September 12, 2014 to December 11, 2022.
Momentum-in-US-Treasury-Bond-ETFs
In this notebook, we will analyse a pattern in treasury bond prices. This pattern produces a significant average returns which increases with maturity. Momentum can be attributed to an increase in investor demand for treasuries due to window dressing and portfolio rebalancing.
Optimal-Lookback-and-Holding-Period
n this notebook, we will find an optimal lookback and holding period for different securities using correlation and p-value..
Technical-Indicators-on-Top-Volatility-Decile-Strategy
In this notebook, we will apply technical analysis not to individual stocks or market indices, but to a custom portfolio which is based on the volatility deciles, i.e. splitting the stocks according to their volatility in 10 equal subsets.
Time-Series-Momentum-Strategy
In this strategy, we will use a lookback period of 12 months and a holding period of 1 month.
Time-Series-Momentum-Strategy-on-Multiple-Asset-Classes
In this notebook, we will code and analyse time series momentum strategy across multiple asset classes. We will use lookback period of 12 months and holding period of 1 month.
Bitcoin-Bull-Call-Spread-Payoff
In this notebook, we will build the payoff graph for long 17400 strike call and short 17860 strike call on Bitcoin.
Bitcoin-Covered-Call-Payoff
In this notebook, we will build a payoff graph for covered call by using the payoff graph of long 17500 Bitcoin spot and short 17500 strike call on Bitcoin.
Bitcoin-Protective-Put-Payoff
In this notebook, we will build a payoff graph for protective put by using the payoff graph of long Bitcoin spot and long 17500 strike put on Bitcoin.
Buy-and-Hold-Strategy
A simple buy and hold strategy through the creation of a portfolio of eight stocks from the US market. The rebalancing is made very month.
Cross-Sectional-Momentum-Strategy-in-Futures-Market
In this strategy, we take position on a large number of futures picked out from a future commodity universe.
Crypto-Trading-Using-Hurst-Exponent
In this notebook, we will create a strategy using the Hurst exponent and the RSI.
Deep-Neural-Network-DNN-Trading-Strategy
This notebook contains the code of a DNN model that predicts the trend of a stock. The prediction of the model is used to create a trading strategy and its returns are compared with market returns.
Divergence-Crypto-Strategy
In this notebook, we will create a strategy using RSI divergence.
Hurst-Exponent-on-Multiple-Asset-Classes
In this notebook, we will show how to calculate the Hurst values for different securities.
Machine-Learning-Tasks
Let's say we have decided that we want to trade in J.P. Morgan. Next, we should decide whether to go long in J.P. Morgan at a given point in time. Thus, the problem statement will be: Whether to buy J.P. Morgan's stock at a given time or not?
MLPClassifier
In this notebook, we will use sklearn's MLPClassifier to create a trading strategy using neural networks..
R-Squared-for-a-Linear-Regression-Model
In this notebook, we will use the R-Squared parameter to measure the goodness of fit of a Linear Regression model.
Roll-Returns-Extraction
Roll returns are the divergence or the difference between the futures returns and the spot returns. Which means that the roll returns are the excess benefit or cost of owning the underlying asset.
Support-Vector-Classifier-Strategy
In this notebook, we will learn to create a Support Vector Classifier (SVC) algorithm on NASDAQ Composite (^IXIC).
The-Day-of-the-Week---Strategy
In this notebook, we will create and backtest a strategy on the Day of the Week anomaly on Bitcoin.
The-Day-of-the-Week-Strategy-
In this notebook, we will create and backtest a strategy on the Day of the Week anomaly on Bitcoin. The strategy aims to exploit the anomaly that the returns on a particular day are significantly higher compared to the other days.