This study will stand as the first major analysis of threshold based rebalancing for cryptocurrency portfolios. The objective of this study is to not only accurately describe the historical performance of threshold rebalancing, but compare the results to those of a simple buy and hold strategy as well as periodic rebalancing. Due to the recent announcements of our support for threshold rebalancing in our portfolio management application, it is appropriate for us to thoroughly understand the historical implications of executing this strategy over long time periods.
To provide a foundation for understanding of how threshold rebalancing works, we’ve published a brief explanatory piece which will walk you through the strategy and how it has been implemented in Shrimpy. Before continuing, we recommend at least skimming that article here:
Threshold Rebalancing - The Evolution of Cryptocurrency Portfolio Management
Now that you have a general understand of how threshold based rebalancing works, stay up to date with all the studies we release on portfolio strategies by joining our Telegram group.
Past studies which evaluated the performance of periodic rebalancing can be found on our blog here.Introduction
Before we get to the data, let’s discuss the methods for how this study was set up. Without a robust understanding of the way the study was conducted, we can’t rely on the accuracy of the results.Data & Trade Calculations
The data for this study was collected directly from the Bittrex cryptocurrency exchange through the third party service CoinAPI. CoinAPI is a data provider which collects and archives order book data across every major cryptocurrency exchange. Using the data APIs, developers are able to access this data for backtests, market analytics, and even real-time pricing data. Our team collected each historical order book snapshot from CoinAPI such that we were provided with exact bid-ask pricing data. Th...