This is the second chapter of a learning process that started last September.
The second step is defined for the next 3 months, where the main goal is to define a specific strategy of quantitative trading and work on it with real money on crypto currency market.
Following the V2MOM model:
- Vision: Have a strategy running in crypto currency market.
- Values: have fun, learn a lot, build a team with Dani, do practices and more practices.
- Method: learn about quantitative trading principles and patterns, understand the basis of how blockchain markets work.
- Obstacles: Time.
- Measures: have an account with money and making short/long decisions. Have a lot of data related to the backtesting of different versions of a specific strategy. Accumulate a list of learned lessons and experiences for blockchain, quantitative trading and python.
Death line = March 2018
Results (April 1st, 2018)
- Time to be accountable, let’s go…
- I have traded more than 50 times on LTCEUR and ETHEUR. It’s very
- When you lose, you learn something; when you win, you do not learn anything.
- We have added a thread of lessons learned in the real life of the trader with insights, habits, and other tips.
- We have learned about the need to keep perspective, read the news about the coins and respect the basic rules.
- We have failed in the basic habits and we have learned which triggers where no happening when they should happen (the more important one: set stop-loss).
- I’m still running long-shorts in minutes (3 minutes – 7 minutes), I need to start opening positions at hours rate and be able to put in action an strategy within 20 to 40 hours with an opened position. This is in some way as to play chess: quick games and long games.
- We have learned how to set time-framing exercise before to start trading, draw supports and resistance lines, look for volumes, and other basic things. We need to organize them and value them properly, but they are in our mind already.
- I have read a book, Machine trading from Ernie Chang, that has enabled me to understand the next steps that we should take during the next quarters.
- I have learned a lot of basic concepts on Machine Learning, the basis. If tomorrow someone tell me to manage a project related to that, I know the basis and I will offer myself to manage it.
- I have learned about Quantopian, basic concepts, how it works, how powerfull the environment is, and I have done a couple of backtests. There is a lot of information to read, basic statistics I still need to learn and the most important thing: I need to evolve a scientific mindset.
- I have learned about bias, doing operating on the real environment and reading “Thinking Basketball“; to see the things in a different context provides a valuable insight.
For next quarter I have some ideas, but I still have not been able to concrete what should be the right focus to cover.