The purpose of this study is to determine the performance implications of rebalancing a cryptocurrency portfolio. Specifically, the focus will be placed on the crypto bear market which began in January 2018. In order to conduct a study that fairly evaluates returns from rebalancing a portfolio, we need to carefully think about our backtest, data, and variable inputs.

Recently, our team has also published studies which compare periodic rebalancing to threshold rebalancing. We encourage you to check out that study here:

Data for Study

Trading & Orderbook Data

Complete order book data was collected from Bittrex exchange. Bittrex data was provided by CoinAPI. Using their rest APIs, we were able to compile the 20 best bid and ask prices available on Bittrex at each rebalance interval. Our data set ranges from January 7th, 2018 until January 24th 2019, and actual order book data was used for this study. All trades assumed the standard 0.25% trading fee on Bittrex. For a detailed analysis of the effect of trading fees, please refer to the article below.

We will simplify the trading logic for this study by restricting buys and sells to BTC pairs. Therefore, a trade from ETH to USDT would trade from ETH to BTC and then BTC to USDT. Even though there is an ETH to USDT trading pair on Bittrex, for the sake of this study, we will ignore these alternate trading pairs. In this case, both of these trades will incur a 0.25% fee.

Portfolio Size (# Of Assets)

We will be evaluating a wide variety of diverse portfolios, starting from just 2 assets and going up to 18 assets, with intervals every 4 assets. This sample size range should cover a majority of cryptoassets. Within Shrimpy’s user base, around 68% of users manage portfolios ranging between 2 to 18 assets. For more information about portfolio diversification and the optimal portfolio size, please visit our article below.

Rebalancing Period

Next, we need to set some rebalancing event parameters to backtest our portfolios. The rebalance period determines the time interval between rebalancing events. For instance, a rebalance period of 1 week means that a portfolio rebalances on a weekly basis. A portfolio with a 1 day rebalance period would rebalance daily. In this study, we will explore 1 hour, 1 day, 1 week, and 1 month rebalance periods.

We hypothesize that by changing the rebalance period, our portfolios will experience drastic variations in regards to their performance.

Learn more about portfolio rebalancing for cryptocurrency.

Asset Selection

In order to reduce selection bias during the backtesting process, our study randomly selects assets to include in each portfolio.

The process begins by constructing a list of every available asset on Bittrex from January 7th, 2018 through January 24th, 2019. A script then randomly selects a mix of assets from the list to construct each portfolio.

Each asset in the portfolio is assigned an equal percent weight of the total value. The total portfolio value at the start of each backtest is $5,000.

Backtest

Backtesting is the process of simulating the trading of a strategy over time by using the trade data on an exchange. The purpose of backtesting is to examine the viability of a strategy through stress testing the results across large data sets. Our study will use backtest different rebalancing strategies and compare returns to an identical HODL (buy-and-hold) portfolio.

To prevent outliers from skewing our results, we ran over 1000 backtests for each rebalance period and portfolio size pair. The results were collected, then the values were plotted in a histogram.

We will also provide the median performance across the collective results to provide a simple metric that represents the cumulative performance. Read more about backtests or run your own.

Rebalance vs. HODL: Results

2-asset portfolio

The study begins with a 2-asset portfolio. This is the smallest portfolio size we will evaluate. The result of a 2-asset portfolio is essentially the movement of value back and forth between the two different assets.