What can be learned from traditional markets and how to apply it in crypto trading.
Trading is about generating positive returns. It is unsurprising then, that many traders make the mistake of focusing on overall profit/loss data and considering their income the only key metric worth their time.
Unfortunately, measuring results according to income and profit/loss data alone lacks relativity and will not guide the improvements needed to increase returns.
In evaluating the success of your trading history, using the overall portfolio size growth is a great start. However, a performance analysis should always be guided by information about the risks behind a given trading strategy.
What is a risk?
Put simply, a risk is a deviance from an expected outcome. In order to find consistently higher returns, a trader has to assume more short-term volatility.
Risk-adjusted returns are crucial to analyzing trading performance in traditional markets because they allow for a direct comparison between portfolios or against a benchmark index with an expected return and risk.
Does performance analysis carryover into crypto?
Although risk-adjusted returns and conventional technical analysis may be applied to cryptocurrency trading strategies, for the majority of crypto-traders it will be an overkill. If we take some common risk measures, such as alpha, beta, R-squared, standard deviation and the Sharpe ratio — it’s quite unclear whether they will be of any use in the cryptocurrency space for now. Cryptocurrency markets are subject to manipulations, greed, and fear — which makes it difficult to analyze the underlying risks using the methods from traditional finance.
Moreover, it is important to consider whether or not these metrics are accurate predictors for smaller datasets at all. By and large, opponents of the use of technical analysis in cryptocurrency trading point to the short history of the crypto asset class as a consistent fallout, as having a reliable set of historical data is essential to the validity of indicators.
In the case of crypto, where sharp movements are habitual and market movements are less understood than those of mainstream financial markets, the usability of indicators is feasibly limited, as factors such as illiquidity can hinder the analysis of digital currencies. With this in mind, it would be unwise to put too much faith in performance indicators surrounding a nascent coin, but conventional technical analysis will nonetheless provide an invaluable set of quantifiable insights for traders.
In fact, using technical analysis for cryptocurrency trading presents an edge over fundamental analysis and valuation, as it is purely a study of the underlying price behavior. Because the price is affected by the interaction of market participants, technical analysis provides an immediate impression of the current trends of an asset or market. Measures of success, then, are interchangeable, but measures of profit differ.
Trading flow comparison between two worlds.
For instance, stock or derivative traders track profits in fiat currency, but pulling out from any positions as a crypto trader and exiting into fiat can be costly. Most exchanges don’t offer fiat pairs, and if they do, they come at the expense of low trading volume and high fees.
To get around this, some traders elect to use stable coins, such as USDT, USDS etc, to fix their income and avoid the value fluctuations of other coins. Despite their proposed stability, a position in a coin like USDT can still be considered a risk exposure, given the market manipulation potential of a fiat-pegged coin. Based on this, many traders opt to fix their profits in bitcoin instead, aiming to increase its amount in their portfolios regardless of its price and adopting a secondary, long-term holding plan. In this case, assuming a hybrid approach between trading and investing is necessary and should be an integral part of any strategy.
Moreover, a cryptocurrency trader should take their desired store of value into consideration. Measuring income and using BTC as a base currency while solely using fiat currency for withdrawals is common, but a strategy which fails to take this into account isn’t grounded. For example, opening a position in a crypto asset traded against ETH may result in a position whose value increases in USD but decreases in ETH, resulting in an essentially unsuccessful trade.
Regularly reviewing trading performance and determining the success of a trading strategy provides a realistic outlook on trading results. In this regard, using a benchmark or an index as a point of comparison will help to determine whether returns are outperforming or underperforming the market and boost the value of risk-oriented metrics. As an example, being up 10–15% may seem like an achievement for any trader, but if the benchmark market is up closer to 20%, trade returns are clearly underperforming against their target.
What is Alpha and why should I use it?
For an active investor’s portfolio, using Alpha is essential to analyzing investment outcomes against an overall market return within a specified time period. Alpha, also known as the active return on an investment, can be represented as a single digit or percentage as a point of positive or negative comparison to a benchmark index that represents the market’s movement as a whole.
For example, a positive Alpha of 0.5% indicates that an investment has outperformed a benchmark index by 0.5%, whereas a negative Alpha indicates that an investment has underperformed this benchmark by the given amount. The excess return of an investment relative to the return of a benchmark index is known as the investment’s Alpha.
Alpha (or α) is also referred to as the abnormal rate of return in allusion to the efficiency of the market and is a must for any trader’s toolkit. In traditional asset management, there exist any number of market indexes relative to different asset classes, like the S&P 500 Index, and using a suitable index is the only way to make risk-adjusted performance metrics worth their salt. Since indexes have yet to be standardized in the cryptocurrency market, Alpha strategies typically rely on market capitalization data.
Tip: In Kattana, the total market cap is used as a benchmark index and can be found in the Trading Performance workspace.
For a performance indicator using historical data, Alpha is likely unsuitable in predicting future returns — it can, however, help to identify assets which tend to perform well on a risk-adjusted basis. When mapping your portfolio to Alpha, be sure to consider your trading intervals: if the average duration of your crypto positions is one month, then tracking your daily Alpha will yield better results than an hourly division. Both trading style and frequency should determine how often an analysis should be performed, as micro-analyzing trading data in excess of your trading activity will only stymie your long-term goals.
Curious about tracking your trading performance? Kattana, a desktop-based crypto-trading terminal, allows you to analyze your own performance compared to a benchmark index.
Kattana is a professional trading terminal for blockchain assets, created by traders for traders to bring individual cryptocurrency trading to a pro level. Trade on multiple crypto-exchanges with the whole range of pro tools, from market analysis to measuring trading performance, available in one place.
Let us know what was your experience in trading micro cap coins and how you integrate them into your trading strategy in the comments below!
The Kattana Team
The Key Metric for Measuring Crypto-Trading Performance was originally published in Hacker Noon on Medium, where people are continuing the conversation by highlighting and responding to this story.