@farnsy has provided a good answer. I'm only addressing my comment about the data quality.
The portfolio optimization technique you employed is very sensitive to the inputs. In particular, it relies entirely on the mean and (co)variance assumptions (i.e. the first two moments) and the results could change drastically with very small amount of change in the inputs. To see that, you can make up some inputs for the solver you have, and try adjusting the inputs a little bit and see the results.
Therefore if you decide to take this approach, data quality is very crucial.
EDIT: What I meant by "data quality"
- Are the data source you are using (i.e. cryptocompare.com) reliable? Is its data consistent with what was observed in the market?
I have no experience with this website but this should be easy to spot check.
- Does the market data reflect the fair value of the assets?
The answer is usually "yes" for liquid assets. Illiquid assets can often be priced at a level with no volume, and the bid-ask spread could be huge.
Should I close my eyes on the fact that these cryptocurencies aren't perfectly priced in my currency and use another one (such as the dollar)
You seem to have concern about data quality in at least the price quoted in your currency and are thinking about using data quoted in USD, but would it be any better? The law of one price tells us that there shouldn't be any discrepancy between prices in different currencies (otherwise there would be arbitrage).
In addition, (when compared to traditional assets) cryptocurrency price data has a shorter data history, and with lower liquidity in the market. The short history means you have less data to infer the characteristics of the price behavior. Low liquidity means the volatility may well be underestimated.
So we have an input-sensitive technique combined with not-so-perfect data. I wouldn't allocate my money solely based on the result of this exercise.
EDIT: I have quite some reservation about doing portfolio optimization for cryptocurrency. Personally I'm not a fan of the technique as is. The optimization has an underlying assumption that returns follow a certain distribution, and correlation is fixed. I don't know if you can make such assumption for cryptocurrencies. From what I read about BTC for example, it seems to have a high risk exposure concerning Chinese monetary policy. For that kind of assets perhaps a fundamental analysis approach is a better one.
Also if you would like to learn more about portfolio optimization, try quant.SE