(This is Part IV of an ongoing series on how to analyse cryptocurrency trends using Python and the Gemini API - read Part I, Part II & Part III if you haven't yet!)
Generally, the price and volume data contains quite a lot of information about what drives the thinking of other investors - but we'll need to transform the raw data into what we call technical indicators, which are simply statistical indices that give you some sense how markets have been moving or intend to move in general. In Part IV of this series, we take a pause from Python and the Gemini API and learn about at the general types of technical indicators that are available to us - in future series, we then take a stab at generating all of these indicators.
Technical What?
Typically when investing in a company, you would look at the company's fundamentals - that is, you look at its underlying financials, business model and leadership, and examine whether the company is worth your money or not. Having such an understanding of the company allows you to hold through short-term price movements, and remain invested despite strong market sell-offs.
Cryptocurrency is no different; you look at the underlying fundamentals of a coin as well before making a decision to buy in or not. However, given that the crypto-market is a young one with a relatively small market cap, price movements can be hyper-volatile and prices can be influenced easily by sentiment. There might be some value therefore being interested in short-term price movements and understanding how the market is moving, so as to discern good entry points to buy a good coin at a cheap price. This allows you to hold a coin with much greater confidence, since you would be sitting on a buffer of profits (albeit unrealised) as you watch the markets evolve.
That's where technical analysis comes in - rather than simply looking at the fundamental value of a coin, you also question the price movement you see on the chart, and try to answer the questions: how has the market been moving, how will it move in the short term, and what should I do in the short term? To answer this broad question, we use what we call technical indicators to understand the broad market sentiment (i.e. bullish or bearish) - but keep in mind that they are in no way related to the intrinsic value of the coin you're interested in.
Leading, Or Lagging?
You should understand that there are generally two categories of technical indicators:
- Leading Indicators: allows you to predict when a certain trend will start (i.e. leading the trend) - needless to say, this helps you predict future price
- Lagging Indicators: allows you to determine what the trend has been like thus far (i.e. lagging the trend) - in short, this helps you describe the current price movement
Which one should you use? Well, I would say both - you should use both types of indicators to complement each other, and in some sense confirm each other's predictions. However, there's nothing that makes one better than the other, since both are merely best-effort statistical predictions. In fact, there are traders who use exclusively one of the two indicators. What's more important is recognising the inherent risk in your decisions, and learning how to set stop-losses in your trading or investment strategy (e.g. saving some cash for a DCA move).
How Do We Measure the Market?
Generally, we proxy market sentiment by measuring one of four quantities:
- Price Value: we perform some sort of price-averaging over a period of time to obtain some sort of baseline - when the price moves above this baseline, we say the market is bullish; conversely, when the price moves below this baseline, the market is bearish
- Price Momentum: in this case you're interested in how fast the price changes in a certain direction - the stronger the momentum, the more likely the price movement will be in that direction
- Price Volatility: here you're interested in how fast the price variation takes place between highs and lows - the larger the volatility, the larger the risk you're taking on when you enter at that price, since the market might be more likely to change direction at that point in time
- Transaction Volume: this is based on the idea that huge changes in prices follow huge transaction volumes (e.g. huge buy-in, large sell-offs) - you generally can't use this indicator by itself, and you use it to confirm another indicator
So again, which type of indicator should one use? There is wisdom in not proliferating your playbook with too many indicators - you'll just get lost! Generally, you should just stick to a few indicators, say no more than 4, and make sure they are chosen to complement one another. It also pays to understand more about the mathematical concept behind each of the four proxies and understand the limitations of each type of indicator - for example, transaction volume alone is most definitely limited.
In the next post of this series, we'll start looking at how we can use Python to transform the data we pulled from the Gemini API to generate leading and lagging indicators, which fall into the four proxies above.
