Intended as an introduction to risk management for cryptocurrency trading, this article, outlines some basic concepts around probability and statistics, then goes on to look at how they can be used in cryptocurrency trading and investing; primarily using Bitcoin as a case study.
A Little Background on Probability & Chance
The first thing to understand when talking about risk management is probability. Probability is defined as a measure of the likelihood that an event will occur; it can be expressed in quantifiable or statistical terms. As a way to express probability mathematically, we use numbers called "probability distributions". Our primary interest is in two types of probability distributions:
- Continuous Distributions - These describe the outcomes of a process; for example, the number of people in a given age group (age can be thought of as numeric representation of time) or the number of samples needed to yield a given proportion of errors. Continuous distributions are helpful to crypto traders because they can provide insight into the way price moves.
- Discrete Distributions - These are special cases of continuous distributions where the outcomes can be divided only into discrete numbers or categories; for example, a casino has 100 slot machines. Each slot machine is a separate outcome with a different combination of winning and losing symbols on its reels, but they all can be thought of as having the same probability distribution. Discrete distributions are helpful to crypto traders because they can provide insight into how markets behave and what the best strategies might be for trading on the profitable The News Spy that behavior.
A Little Background on Statistics
In our day-to-day lives, we make decisions based on a collection of data that is not necessarily organized in a coherent way. What is more likely to happen, your house being struck by lightning or a flood? In order to collect information about probability distributions and make decisions based on it, we need a method for organizing the data into coherent chunks that we can manipulate mathematically: this process is called "statistical analysis". Statistical analysis has three basic steps:
1. Collecting data
2. Quantifying the data
3. Analyzing the data and making decisions based on it
Crypto traders use statistical analysis to identify key factors that influence crypto prices, develop strategies for trading more successfully within those factors' ranges of influence and evaluate their overall performance as a trader over time. What is more likely to happen, a person making 10k on one trade or a person losing 10k in one trade?
Step 1: Collecting Data -The key to collecting data about price behavior is having sources of information. These can be books, blogs, messages posted online, and any other source of relevant information. Professionals often use the same sources as the general public, because they know that crypto has a large volume of self-hyping and unreliable information.
Step 2: Quantifying Data -This step involves manually or electronically searching through your data sources for patterns of behavior, known as "patterns" from which you can extrapolate (or predict) future price movements. These patterns can be compared to other patterns, as well as with the assorted charts and graphs available online (or created by you) in order to identify optimal trading strategies for that pattern.
Step 3: Analyzing Data and Making Decisions -Based on the patterns observed in Step 2, we can now discuss what kind of strategies might be best for trading within that range of influence. It is also possible that a given pattern may overlap with another pattern; these are called "correlations" in the crypto community and tend to influence price on a larger scale than does the original pattern.
Concluding Thoughts
By using statistical analysis, crypto traders can identify patterns of price behavior that indicate which assets' prices are likely to rise and fall. These insights allow the trader to garner more profits in exchange for fewer losses over time.
