Skip to main content

Day Eight

 Hey everyone,

It's been a bit of a frustrating week on the algo trading front, and it highlights a common dilemma for beginners like myself: the constant tug-of-war between actually building the strategy and getting bogged down in infrastructure and deployment issues.

I've realized I've been spending a disproportionate amount of time and mental energy lately worrying about how I'm going to deploy my news straddle strategy once it's ready. We talked about my Linux concerns in a previous post, and that's been a persistent background hum. While it's crucial to think about deployment eventually, I'm starting to feel like it's becoming a significant distraction from the core task: making the strategy itself robust and profitable.

Wasting Effort on "How" Instead of "What"

My main focus right now should be on refining my strategy's logic, optimizing parameters, and thoroughly backtesting it. That's the engine of the whole operation. But instead, I find myself researching cloud VPS options, debating virtual machine setups, and sifting through forum posts about Linux compatibility for various trading APIs.

It's a classic case of getting ahead of myself. A brilliant deployment solution is useless if the strategy it's running isn't profitable. I need to remind myself to prioritize the what (the strategy) over the how (the deployment) for now. The "how" will come, and there will be solutions, but the strategy needs to be sound first.

Investpy Woes: Another Data Hiccup

Adding to the frustration, I've run into a specific technical roadblock with investpy. For those unfamiliar, investpy is a Python library that allows you to retrieve financial data from Investing.com. It's a fantastic resource for getting historical data on stocks, indices, currencies, and more, which is crucial for backtesting and analysis.

However, lately, I've been hitting persistent 403 Forbidden errors when trying to use it. After a quick dive into online forums and GitHub issues, it seems I'm not alone. It appears Investing.com may have implemented some new anti-scraping measures, or perhaps there's a change in how investpy interacts with their site, causing it to break.

This is a real pain, as investpy was a convenient source for some of the historical data I needed. It means I now have to spend time looking for alternative data sources, figuring out how to get clean data, and potentially adapting my data ingestion pipelines. It's yet another example of an "infrastructure" problem diverting attention from strategy development.

Back to Basics (Literally)

So, moving forward, my new mantra is: Strategy First. I'm going to deliberately pull back from the deployment rabbit hole for a while. The Linux challenges and data sourcing issues are real, but they can wait until I have a strategy that's actually worth deploying.

My focus will be entirely on:

  • Refining my news straddle strategy's entry/exit logic.
  • Thoroughly backtesting it with the libraries I'm exploring (QStrader/backtestpy).
  • Finding and implementing reliable alternative data sources for my backtests.

It's a tough lesson to learn, but sometimes, the best way forward is to simplify and prioritize. Wish me luck in staying disciplined!

Have you ever found yourself getting distracted by deployment issues before your strategy was ready? Or run into similar frustrating data source problems? Share your experiences in the comments!

Happy (and focused) algo trading,

Comments

Post a Comment

Popular posts from this blog

Day Seventeen

 Hey everyone, After the eye-opening (and somewhat humbling!) experiences with my manual backtesting, and having re-prioritized my learning journey, I've come to a crucial realization: one of the most fundamental skills I need to truly master is proper backtesting methodology. It's not enough to just scroll charts and count pips. To truly validate a strategy and understand its edge, you need a systematic, unbiased, and thorough approach to historical data. This is where many aspiring traders, myself included, often fall short. Why Proper Backtesting is My Next Big Focus You might recall my previous posts about the pain of manual backtesting and the frustration of realizing my news straddle strategy "sucked." While those were valuable lessons, they also highlighted a gap in my knowledge: how to design and execute a truly effective backtest. That's why my immediate next step is to learn how to backtest properly via The Trading Cafe's dedicated course on the sub...
Post a Comment
Read more

Day Sixteen

 Hey everyone, It's been a week of reflection and some important re-calibrations on my trading journey. You know how it goes – sometimes you make a decision with good intentions, and then, with more knowledge and perspective, you realize it might not be the best path forward right now . That's exactly what happened with a trading contest I recently signed up for. The Contest: A Good Idea... Eventually I initially thought signing up for a trading contest would be a great way to test my mettle, push myself, and get some real-time practice. After all, the competitive element can be a strong motivator. I discovered this particular contest through The 5%ers , a prop firm that has quickly become a favourite in my research, especially with recommendations from members of The Trading Cafe community. However, after a lot of thought and reviewing my recent progress, I've come to a clear conclusion: it was a terrible idea to sign up for a contest right now. And with that realization,...
Post a Comment
Read more

Day Four

 Sometimes, the most productive days in algo trading aren't spent coding or backtesting, but simply absorbing knowledge. Today was one of those quieter days for me, and I finally carved out some dedicated time to dive into a new resource. Diving into TradingCafe I've finally cracked open the TradingCafe book ! I've heard a lot about it in various trading circles, and I'm excited to start digging into its insights. It's easy to get caught up in the technical aspects of building bots and analysing data, but understanding the underlying market dynamics and trading psychology is just as crucial. I'm hoping to gain some fresh perspectives and perhaps even discover new strategy ideas from its pages. It's a reminder that continuous learning is paramount in this ever-evolving field. Babypips School of Pipsology: A Game-Changer! On another exciting note, I made a fantastic discovery today: the Babypips School of Pipsology is available in audio format! Seriously, wha...
Post a Comment
Read more