paint-brush
We Ran 20,000 Backtests To Determine If HODLing Crypto Was Superior To Periodic Rebalancingby@ShrimpyApp
1,973 reads
1,973 reads

We Ran 20,000 Backtests To Determine If HODLing Crypto Was Superior To Periodic Rebalancing

by ShrimpyApril 19th, 2023
Read on Terminal Reader
Read this story w/o Javascript

Too Long; Didn't Read

Shrimpy shares a case study analyzing the effects of exchange trading fees on crypto portfolios utilizing periodic rebalancing strategies. The purpose of this case study is to compare how rebal balancing performs on exchanges such as Binance, Coinbase, Kraken, and others.

People Mentioned

Mention Thumbnail
featured image - We Ran 20,000 Backtests To Determine If HODLing Crypto Was Superior To Periodic Rebalancing
Shrimpy HackerNoon profile picture


Dear Hackernoon reader,


The Impact of Crypto Trading Fees on Periodic Rebalancing: How Does Your Favorite CEX Fare?


We are pleased to offer you its latest case study analyzing the effects of exchange trading fees on periodic rebalancing.


Trading fees have a massive impact on rebalancing strategies, and as such, we found it necessary to analyze the effects fees have on your performance.


The purpose of this case study is to compare how rebalancing performs on different exchanges, including Binance, Coinbase, Kraken, Bybit, Gemini, and many others.


This case study might also be relevant for those utilizing other crypto strategies that rely on high-frequency trading.


Our conclusions show which exchange brings the best returns and how periodic rebalancing compares to a buy-and-hold (HODL) strategy at various rebalancing frequencies and trading fees.


This case study continues our previous case study on crypto exchanges and rebalancing performance.


This case study was made with the help of Shrimpy’s native backtesting tool. You can use Shrimpy to analyze thousands of cryptocurrencies and compare their performance against different strategies. Backtesting is the easiest way to analyze the potential performance of your portfolio without having to deploy real capital.

Backtest Setup

This case study focuses on the impact of exchange trading fees on the performance of a cryptocurrency portfolio utilizing a periodic rebalancing strategy. Our backtest tracks the portfolio’s performance during a 3-year time period (Jan 1, 2020, to Dec 31, 2022).


We've analyzed 20 settings based on threshold rebalancing tolerance bands and exchange trading fees. We've run 20,000 backtests in total, amounting to 1,000 backtests per setting.


This time we’ve only analyzed a 15-asset portfolio.


Our periodic rebalancing includes the following frequencies:

  • Hourly rebalancing

  • Daily rebalancing

  • Weekly rebalancing

  • Monthly rebalancing


We have carried out the case study by taking the non-VIP taker fee for spot markets for every major exchange and applying it to our rebalancing trades.


The trading fees include five groups:

  • 0.1%  (Binance, Kucoin, Bybit, OKX)

  • 0.2% (Bitfinex & Gate.io)

  • 0.26% (Kraken)

  • 0.4% (Bitstamp & Gemini)

  • 0.6% (Coinbase)


Here’s a comprehensive list of all crypto exchanges and their respective trading fees; feel free to visit the following link.


This case study compares the performance of each rebalancing strategy against HODL (buy-and-hold). We've also compared the performance of each strategy against the initial portfolio value.


Note that the asset selection process during our backtests was completely randomized.

Allocations

The case study includes one portfolio group in terms of portfolio size. The portfolio has 15 assets in total.

The assets in the portfolio group are evenly distributed.


The rebalancing process simulated in the backtest executes trades to keep these initial allocation targets in check. The point of rebalancing is to maintain targeted allocations.


Note that each executed trade includes a trading fee.

Funds

Each portfolio starts with an initial balance of $5,000.

The results of this case study show the value of each portfolio by the end of the backtest period (January 1st, 2020 - December 31st, 2022.)

Asset Selection

The asset selection process in this case study is completely randomized for the purposes of objectivity and accuracy.


Our list of assets includes all cryptocurrencies available on the top 10 crypto exchanges during the backtest period (as per CoinGecko).

Each backtest picked random assets for each portfolio group based on the list of assets available then. This is done so that the focus of our analysis is placed not on the assets themselves but on the strategy.

Performance Calculation

Each backtest outputs two results. One result shows a portfolio's final value if it had been rebalanced, while the other shows a portfolio's final value if it had used the HODL strategy.


To determine how these strategies compare, we calculate the performance of the rebalancing strategy against the HODL strategy by using the following formula:


Performance = ((R - H) / H) x 100


You can read the formula in the following way:

  • R is the final value of the portfolio that used a rebalancing strategy.

  • H is the final value of the portfolio that used the HODL strategy.

  • The result is multiplied by 100 to convert from a decimal to a percent.


Our results contain graphs that show the relationship between exchange trading fees and periodic rebalancing with the median value of the portfolio by the end of the backtesting range. We have results for the following trading fees: 0.1%, 0.2%, 0.26%, 0.4%, and 0.6%.


Our final results (Portfolio Rebalancing vs. HODL) compare portfolio rebalancing against the HODL strategy. This section focuses not on the median value of each portfolio by the end of the backtest but on the performance of a rebalanced portfolio compared to the same portfolio utilizing a HODL strategy.


Please note that any values displayed in this section are not relative to the starting value of a portfolio but to the same portfolio had it been HODL’ed. If a value of 5% is displayed, that means the final result for the rebalanced portfolio is 5% higher than the HODLed portfolio and not 5% higher than the initial portfolio fund.

Backtest Period

Our case study focuses on the following market period: Jan 1, 2020 - Dec 31st, 2022.


Given the nature of the market during that period, our case study predominantly analyzes the price data of a bull market.

The market has seen extremely volatile price action during this backtest period. Bitcoin has seen a price increase of 851% from Jan 1st, 2020, to the November ATH of 2021. The market has also seen a 76% price decrease from the ATH to Dec 31st, 2022.

Considering that our case study involves mostly altcoins (due to the nature of diversification), the results are far more volatile.

Results

Our results start by analyzing the effects of different exchanges and their trading fees on each periodic rebalancing frequency.


The list of rebalancing frequencies includes:

  • Hourly
  • Daily
  • Weekly
  • Monthly


We use the following trading fees: 0.1%, 0.2%, 0.26%, 0.4%, and 0.6%


Our combined results section compares the combined performance of all the abovementioned strategies. Note that the performance in the combined results section is denominated in dollars. Their performance is relative to the initial portfolio value (IPV).


Our final results compare the combined performance of each rebalancing strategy against HODL.

The values in the final results section are percentages, not dollars. The values are relative to a portfolio utilizing HODL – the performance difference between a rebalanced portfolio and a HODL’ed portfolio – and not to the initial value of a portfolio.

0.1% Trading Fee (Binance)

This graph shows the results of a $5,000 portfolio utilizing periodic rebalancing combined with 0.1% trading fees after three years. The X-axis shows the rebalancing frequency used. The Y-axis shows the portfolio's final dollar value at the end of the backtest period.

The results above show the effects of a 0.1% trading fee on four periodic rebalancing frequencies. This portfolio group includes Binance, Kucoin, Bybit, and OKX.

Daily rebalancing produced the best results, scoring 2.78% higher than hourly rebalancing, 5.83% higher than weekly rebalancing, and 19.16% higher than monthly rebalancing.

0.2% Trading Fee (Bitfinex)

This graph shows the results of a $5,000 portfolio utilizing periodic rebalancing combined with 0.2% trading fees after three years. The X-axis shows the rebalancing frequency used. The Y-axis shows the portfolio's final dollar value at the end of the backtest period.

The results above show the effects of a 0.2% trading fee on four periodic rebalancing frequencies. This portfolio group includes Bitfinex and Gate.io.


Daily rebalancing produced the best results, scoring 10.58% higher than hourly rebalancing, 8.44% higher than weekly rebalancing, and 11.88% higher than monthly rebalancing.

0.26% Trading Fee (Kraken)

This graph shows the results of a $5,000 portfolio utilizing periodic rebalancing combined with 0.26% trading fees after three years. The X-axis shows the rebalancing frequency used. The Y-axis shows the portfolio's final dollar value at the end of the backtest period.

The results above show the effects of a 0.26% trading fee on four periodic rebalancing frequencies. This portfolio group includes Kraken.


Daily rebalancing produced the best results, scoring 18.38% higher than hourly rebalancing, 5.6% higher than weekly rebalancing, and 13.78% higher than monthly rebalancing.

0.4% Trading Fee (Bitstamp & Gemini)

This graph shows the results of a $5,000 portfolio utilizing periodic rebalancing combined with 0.4% trading fees after three years. The X-axis shows the rebalancing frequency used. The Y-axis shows the portfolio's final dollar value at the end of the backtest period.

The results above show the effects of a 0.4% trading fee on four periodic rebalancing frequencies. This portfolio group includes Bitstamp and Gemini.


Weekly rebalancing produced the best results, scoring 24% higher than hourly rebalancing, 0.78% higher than daily rebalancing, and 8.41% higher than monthly rebalancing.

0.6% Trading Fee (Coinbase)

This graph shows the results of a $5,000 portfolio utilizing periodic rebalancing combined with 0.6% trading fees after three years. The X-axis shows the rebalancing frequency used. The Y-axis shows the portfolio's final dollar value at the end of the backtest period.


The results above show the effects of a 0.6% trading fee on four periodic rebalancing frequencies. This portfolio group includes Coinbase.

Weekly rebalancing produced the best results, scoring 49.22% higher than hourly rebalancing, 2.39% higher than daily rebalancing, and 7.93% higher than monthly rebalancing.

Combined Results

This graph shows the combined results of all the previous threshold strategies and trading fees for a $5,000 portfolio after three years. The X-axis shows the rebalancing frequency for each portfolio group. The Y-axis shows the portfolio's final dollar value at the end of the backtest period.


X-Axis for each bar inside a rebalancing frequency from left to right: Binance, Bitfinex, Kraken, Bitstamp, Coinbase.


The results show that daily rebalancing performed the best out of all the other groups. Hourly rebalancing is most affected by increased trading fees, bringing massive drawdowns with higher fees. In this regard, hourly rebalancing has the worst performance on average (apart from the 0.1% trading fee).

The image above shows the impact of each trading fee on each periodic rebalancing strategy. The best returns are concentrated around the 0.1% trading fee and daily rebalancing frequency.


Our results show that an hourly rebalanced portfolio combined with a 0.6% trading fee performed the worst. A daily rebalanced portfolio with a 0.1% trading fee performed the best.

Periodic Rebalancing vs. HODL

The graph above compares how well each rebalancing strategy has performed against HODL at varying trading fees. The X-axis shows the trading fee used. The Y-axis shows the performance, defined in percentages, of a periodic rebalancing strategy compared to a HODL strategy at the end of the backtest period.

X-Axis from left to right: Binance, Bitfinex, Kraken, Bitstamp, Coinbase.


Our results show that all periodic rebalancing strategies have outperformed HODL, except the 0.4% and 0.6% trading fee portfolios utilizing hourly rebalancing.


Daily rebalancing at 0.1% trading fees brings the best results at 28.59%. The worst results can be seen with the 0.6% hourly rebalancing group, which performed -23.67% worse than HODL.


In general, the best-performing portfolios were the ones utilizing daily and weekly rebalancing, with trading fees ranging from 0.1% to 0.4%.


An exchange with 0.1% trading fees, like Binance, offers the best results – as expected. However, you can still expect great results even when using exchanges with slightly higher fees, such as Bitfinex, Kraken, and Bitstamp.


You can guess by now that hourly rebalancing performed the worst because it executed the most trades and, as such, incurred higher trading fees than other groups.

The image above shows how well each threshold strategy performed with each trading fee versus a HODL strategy.

Conclusions

Periodic rebalancing performs best on exchanges with low trading fees. Daily rebalancing offers the best and most consistent results. The second best rebalancing group is weekly rebalancing, which isn’t affected much by increased fees. As expected, hourly rebalancing is the most affected group by trading fees.

We conclude that trading fees ranging from 0.1% to 0.4% offer the best results for a portfolio utilizing periodic rebalancing. Exchanges that offer such trading fees include Binance, Bitfinex, Bybit, Bitfinex, Bitstamp, Kraken, Kucoin, Gemini, OKX, and Gate.io.

We also conclude that periodic rebalancing outperforms HODL on all exchanges across all periodic frequencies apart from hourly rebalancing.


To optimize your periodic rebalancing strategy, you will want to trade on an exchange with 0.1% trading fees. These exchanges tend to have the best liquidity, meaning there’s no reason to rebalance your portfolio on more expensive exchanges.

Use Shrimpy to Your Advantage!

The backtests and rebalancing strategies were carried out using our portfolio rebalancing tool, Shrimpy.

Shrimpy is an automated portfolio management platform that helps you not only rebalance but also diversify your crypto portfolio.

You can connect over 25 exchange accounts and wallets with Shrimpy and start rebalancing your portfolio right away. Shrimpy is one of the easiest-to-use rebalancing tools in the industry.


Sign up now__by clicking here.__