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How We Can Apply Modern Portfolio Theory to the Сryptocurrency Marketsby@holderlab
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How We Can Apply Modern Portfolio Theory to the Сryptocurrency Markets

by holderlabJuly 16th, 2019
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Modern Portfolio Theory (MPT) suggests that investors are risk averse, so an investor will choose the one with the lowest risk. An efficient frontier is one that defines the effective set of portfolios on it, respectively, between risk and return. With the existing risk, the other portfolio will have lower returns, so the investor can choose the appropriate risk and select the optimal yield. In this article we will look at the cryptocurrency investment strategies by creating an optimal portfolio using an Efficient Frontier and optimal cryptocurrency weights.
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Hello Holders! In this article we will look at the cryptocurrency investment strategies by creating an optimal portfolio using an Efficient Frontier and optimal cryptocurrency weights.

Let’s take a look at Modern Portfolio Theory (MPT), which suggests that investors are risk averse. We have two or three portfolios with the same yield, so an investor will choose the one with the lowest risk. In accordance with this, if a portfolio has a high portfolio risk, then the investor will choose the portfolio that assumes a higher return. The theory of building optimal investment portfolios was first proposed by Harry Markowitz.

According to Markowitz, any investor should base his choice solely on expected returns and standard deviation when choosing a portfolio. Thus, having carried out an assessment of various combinations of portfolios, he must choose the “best” one, based on the ratio of the expected return and the standard deviation of these portfolios. The ratio of the return-risk portfolio remains normal: the higher the yield, the higher the risk.

The main task of the investor is to make a portfolio of assets with weak or negative correlation. Portfolios with a correlation coefficient of 1 would be risky, whereas with -1 less risky, but in practice it is rare. With a large number of assets, the risk is also correspondingly reduced than with two assets, so we diversify the portfolio

Efficient Frontier

Markowitz put two parameters at the head of his theory – risk and profitability. An efficient frontier is one that defines the effective set of portfolios on it, respectively, between risk and return. Let’s look at an example:

Portfolio 1 – low return and low risk

Portfolio 2 – high return and high risk

Portfolio 3 – effective portfolio

Portfolio 4 – not effective portfolio

All investment portfolios that are on the border will be effective. With the existing risk, the other portfolio will have lower returns. Therefore, the investor can choose the appropriate risk and select the optimal yield.

Thus, the result of MPT using an effective frontier will be the selection of the optimal weights of each asset in the portfolio.

Let’s go research cryptocurrency portfolio!

So, we decided to take the 12 largest cryptocurrency by capitalization and evaluate 5000 possible portfolio options that can be. This is our cryptocurrency investment strategies

With the help of holderlab.io you can find the effective frontier of your portfolio just for free

So we take for research: BTC, ETH, XRP, LTC, BCH, EOS, BNB, BSV, TRX, XLM, ADA, XMR as the largest in terms of capitalization.

First, let’s look at the profile of the correlation matrix for 1 year from 2018 to 2019

The 1-year correlation is very high. Cryptocurrency Asset Correlation Information:

Bitcoin 0,842

Ethereum 0,873

XRP 0,851

Litecoin 0,895

Bitcoin Cash 0,895

EOS 0,861

Binance Coin 0,884

Bitcoin SV 0,797

Cardano 0,834

TRON 0,813

Stellar 0,687

Monero 0,9

We are testing the asset ratio for the last 3 months, starting from April 15 2019

Bitcoin -0,057

Ethereum 0,173

XRP 0,532

Litecoin 0,505

Bitcoin Cash 0,635

EOS 0,493

Binance Coin 0,554

Bitcoin SV 0,565

Cardano 0,561

TRON 0,579

Stellar 0,39

Monero 0,52

The results are already better, Bitcoin has a negative correlation, but this is a fairly short period for analysis using the correlation matrix, however, we will look at the profile of the efficient frontier.

Calculation of the efficient frontier of a cryptocurrency portfolio for 2019

So in cryptocurrency investment strategies we analyzed a sample of portfolios from the beginning of 2019, 5000 cryptocurrency portfolios were analyzed.

Let’s look at the results:

The optimal portfolio distributed weights as follows:

Bitcoin 28,86%

Ethereum 1,26%

XRP 10,23%

Litecoin 7,32%

Bitcoin Cash 3,92%

EOS 0,93%

Binance Coin 11,99%

BitcoinSV 17,8%

Cardano 7,57%

TRON 6,48%

Stellar 0,58%

Monero 3,06%

Returns 0,02886 Volatility 0,0743 Sharpe Ratio 0,38838

We see that, EOS and XLM received a distribution of less than 1%, while Bitcoin was 28.86%, respectively, we have recently seen the dominance of Bitcoin and the fall of altcoins.

In order to evaluate the results let’s test the optimal portfolio and compare it with the proportional distribution of % in the portfolio.

Backtest Cryptocurrency Portfolio

Using the holderlab.io backtesting module (where you can test your cryptocurrency investment strategies), we tested the optimal portfolio from the beginning of 2019, the weights of which were calculated using the efficient frontier and obtained the following results:

Profit 127.21% Max.Profit Peak 227,79% Max. Drawdown -24,26%

Standart Deviation 66,6%

Let’s look at the results of the backtest of proportional distribution:

Profit 94.65% Max.Profit Peak 192,97% Max. Drawdown -18,9%

Standart Deviation 57,88%

Profit was lower at 32.56, but the drawdown decreased by 5.36%. But we assume a high correlation of the cryptocurrency portfolio we have chosen for analysis and the need to further combine altcoins with a medium and medium-small capitalization.

Thus, it can be noted that Modern Portoflio Theory, including the efficient frontier, can be applied to cryptocurrency portfolios and searching for the optimal portfolio weights.

**The examples above are not a recommendation or investment guide.

Holderlab.io is a free service for automated crypto portfolio management with automatic rebalancing of assets (threshold or periodic), searching for efficient frontier and analysing assets using a correlation matrix and other crypto investments tools.