As a trader, I need to understand when to buy and when to sell. I need to understand what to buy and what to sell. I need to understand how much to buy and how much to sell.
Simple. Not easy.
In order to answer the question of what to buy I need to identify a set of assets that have certain properties and characteristics that can be identified and from which information can be extracted and signals about which action can be drawn.
In order to answer the question of when to buy, I need to construct models of price behavior and then apply these models to current price behavior in order to predict whether to buy or sell a particular asset at a given time.
The question of how much to buy is concerned with an asset allocation strategy and that is intended to address the question of diversification of risk.
If we are in a discretionary trading environment, I suspect much of this knowledge will be internalized in my head through experience.
In an algorithmic trading scenario, this knowledge will be mostly something captured in a routine or algorithm.
Much of this work will focus on algorithmic trading.
Exposure to risk and opportunity are the two sides of the sword.
How shall we think about this?
The question of what and how much are related in the sense that we want to be maximally exposed to upside behavior and minimally exposed to downside movement. So how much and to what shall we allocate our resources would be answerable if we understood the relationship certain assets have to one another.
What is portfolio gamma? What happens when you need to do something critical but everyone else is doing the same thing and true scarcity emerges? The cost of surviving such a moment, when everyone faces existential threat, is this gamma.
When an idea that is intended to create some benefit or safety net actually generates non-linear risk because the cost of backstopping/redeeming obligations triggered by the event ocurrence reveals itself to be too high and the exposure too widespread.
Persistent agent behaviour generates the belief that agent behaviour will be predictable and stable leading to resetting some price/terms of interaction with the agent.
For now, out of curiosity and ignorance I will focus on cryptocurrencies.
The purpose of this is for me to develop the knowledge, skills and disposition to be a full-time trader.
Intermediate outcomes will be the stepping stones on that path. These outcomes will be demonstrated as python modules and jupyter notebooks.
With each notebook, the intent will be to focus on a particular knowledge or skill and use the notebook as a place for reflection, discussion and demonstration of the learning process.
Python modules will be used for script development and demonstration of wider programming and software development knowledge.
Additional items will be added if necessary.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent