Bitcoin Halving — Historical Scenario Analysis Charts in Excel & Googlesheets
By: Chris Ware
Tags: Bitcoin, Crypto, Blockchain, Cryptocurrency

Any seasoned professional trader or portfolio manager will tell you that all market moves are relative to the context of the prevailing market.

One of the most frustrating things about most Bitcoin halving predictions and models is that they ignore this context almost entirely, instead relying purely on what the trendiest technical indicator chart from a TradingView chart ‘implies’.

For example - thought exercise: Can you really compare today’s market with 2012 where institutional participation was effectively zero?

Using an approach that seeks to identify changes, patterns or correlations in the broader holistic context (aka looking at the absolute and relative/weighted changes of relevant metrics in the context of the prevailing market) can help identify tradable patterns, relationships and trends for the upcoming halving in May 2020.

Using the Cryptosheets template gives you substantial flexibility and variability over metrics, time period, lookback/forward and much more

This article highlights a few examples of those pitfalls and provides a (hopefully) more flexible and holistic tool to use. You can download the Bitcoin Halving Historical Scenario Charts Template here

EXAMPLES — COMMON (APPROACH) SCENARIOS

Prediction #1: History will repeat itself… right?

@SomeTwitterExpert

“Bitcoin returned an average of XYZ% in the 30, 60 and 90 days following the last two halvings. That means buying $100 BTC right now should yield you ~XYZ% returns in the same period… give or take…ish…”

Pitfalls

How many algo trading bots were actively arbitraging the markets during the last two halving events? What was the average bid/ask spread, market depth and overall liquidity during the prior events compared to now?

10 days before & after the 2016 Bitcoin halving

Prediction #2: Supply/Demand is a universal law and also 100% applicable to a commodity/asset/blockchain/(rat poison?) like Bitcoin (cough) — and thus scarcity will drive the price action… right?

@SomeTwitterExpert

“After the 3rd halving there will only be XYZ BTC remaining and assuming XYZ inflation schedule based on the ‘code’ + increased demand, the demand will cause a supply squeeze and drive the price up…”

Pitfalls

How many derivatives exchanges were active during the last two halving events? (or total exchanges) How many retail/institutional investors could instantly put on 100–400x downside leveraged trades on Bitcoin? Scarcity — how many altcoins (aka investment alternatives) were there available for investment during the last two halvings?

This example of 30 days before/after looks like pump -> hype -> spike -> dump -> fadeeee

Prediction #3: XYZ onchain metrics have increased by XYZ% vs. the last two halvenings, this implies an upside of XYZ% for the third halving event… right?

@SomeTwitterExpert

“Because the ABC (insert buzzword) price/metric ratio during the prior two events was X and the (insert buzzword) metric increased after the prior halving events then the price should follow (aka mean revert) and trade up XYZ%…”

Pitfalls

What else changed since the prior halving events relative to the [insert buzzword] metric or price/metric ratio? Does your chosen [insert buzzword] metric have an input that may have changed since the last event…? Does your chosen [insert buzzword] metric have multiple providers, sources or versions?

Looking only at a longer period after the event certain trends start to clearly stick out, this volume pattern is an interesting divergence from # of transcations…. hmm..

This isn’t intended to be a market prediction or guidance on how to trade the market (no trading advice ever*)-but it is supposed to help you think about your own analytical context and approach to these events.

HOW TO USE THE TEMPLATE

(WATCH THE QUICK VIDEO)

Using the Cryptosheets template you can easily select various periods before & after the previous halvings to measure the changes in the holistic context of other network & activity metrics