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Delta-Neutral Volatility Trading Report

Last Update September 17, 2021

Matteo Bottacini, [email protected]

Project description

In this report are show the results obtained for the Delta-Neutral Volatility Trading section.

The codes described are in ../deliverables/run-delta-hedged-strategy.py which is the only script you need to run to perform the analysis. The images, tables and data are in ../reports/.

Note: all the images in this GitHub repo are .png instead of .pdf. The reason is to make it easier for GitHub to render the results.

Table of contents

  1. Load data and data pre-processing
  2. Back-test all strategies
  3. Quantitative strategy performance

Load data and data pre-processing

The first step is to load the data into the working environment and to pre-process them using the function load_data() for both BTC and ETH.

# import modules
from DeltaHedging.src.utils import *

# load data
btc_data = load_data(coin='btc', cwd='DeltaHedging/deliverables')
eth_data = load_data(coin='eth', cwd='DeltaHedging/deliverables')

Back-test all strategies

The second step is to back-test all the strategies for both BTC and ETH, the function is all_strategies().

# import modules
from DeltaHedging.src.utils import *
from DeltaHedging.src.variables import *

# evaluate all strategies performance
btc_all_strategies = all_strategies(lag=lag, coin_df=btc_data, quantile_iv=quantile_iv, coin='BTC',
                                    fee=fee, margin=margin)
eth_all_strategies = all_strategies(lag=lag, coin_df=eth_data, quantile_iv=quantile_iv, coin='ETH',
                                    fee=fee, margin=margin)

This function will return 2 .parquet files one containing the time-series with the portoflios' values and the other one with the trading positions for each delta-neutral straddle.

The BTC data are:

The ETH data are:

Quantitative strategy performance

The third step is to evaluate the performance of the equally weighted portoflios of delta-neutral long and short straddles. The function is strategy_performance() and it is done for both BTC and ETH.

# import modules
from DeltaHedging.src.utils import *
from DeltaHedging.src.variables import *

# quantitative strategy performance
btc_strategy = strategy_performance(coin='BTC', transaction_cost=transaction_cost)
eth_strategy = strategy_performance(coin='ETH', transaction_cost=transaction_cost)

Then, this function will first return a plot with the number of instrument in a portfolio every 5 minutes.

Then, the number of long and short delta-neutral straddles entered in comparison to the total number of straddles available.

Then, it returns a table with a summary of the descriptive statistics for both BTC and ETH:

And the summary of the daily log-returns of the quant-portfolios:

Visualize strategy performance

Finally, we visualize the strategy performance using the function plot_strategy():

# import modules
from DeltaHedging.src.utils import *

# plot final results
plot_strategy(coin='BTC', ret=btc_strategy[0], cum_ret=btc_strategy[1])
plot_strategy(coin='ETH', ret=eth_strategy[0], cum_ret=eth_strategy[1])

And the results are: