Introduction to Algotrading (2011) [pdf] | Hacker News

Source: Introduction to Algotrading (2011) [pdf] | Hacker News


Ask HN: How to launch an algo trading side project? | Hacker News

Source: Ask HN: How to launch an algo trading side project? | Hacker News


Build a Day-Trading Algorithm and Run it in the Cloud Using Only Free Services

In this article, I am using Alpaca’s commission-free trading API with their premium data service Polygon. (Please note that, according to their docs, you’ll need to sign up for a brokerage account in order to access the premium data feed used here.) I’ll provide a day-trading script that leverages this premium data for a little technical analysis, and I’ll go over what it does and how to run it yourself.

Source: Build a Day-Trading Algorithm and Run it in the Cloud Using Only Free Services


Forex Trading Diary #1 – Automated Forex Trading with the OANDA API | QuantStart

I previously mentioned in the QuantStart: 2014 In Review article that I would be spending some of 2015 writing about automated forex trading.Given that I myself usually carry out research in equities and futures markets, I thought it would be fun (and educational!) to write about my experiences of entering the forex market in the style of a diary. Each “diary entry” will attempt to build on all those before, but should also be relatively self-contained.In this first entry of the diary I’ll be describing how to set up a new practice brokerage account with OANDA as well as how to create a basic multithreaded event-driven trading engine that can automatically execute trades in both a practice and live setting.

Source: Forex Trading Diary #1 – Automated Forex Trading with the OANDA API | QuantStart


Algorithmic Options Trading 3 – The Financial Hacker

In this article we’ll look into a real options trading strategy, like the strategies that we code for clients. This one however is based on a system from a trading book. As mentioned before, options trading books often contain systems that really work – which can not be said about day trading or forex trading books. The system examined here is indeed able to produce profits. Which is not surprising, since it apparently never loses. But it is also obvious that its author has never backtested it.

Source: Algorithmic Options Trading 3 – The Financial Hacker


CS Fundamentals Unplugged Lessons | Code.org

Source: CS Fundamentals Unplugged Lessons | Code.org


What’s good career advice you wouldn’t want to have your name on? | Hacker News

Source: What’s good career advice you wouldn’t want to have your name on? | Hacker News


Surprising Cities Where You Can Make Lots of Money – Slide 31 | GOBankingRates

. Frisco, TexasMedian household income: $120,701State median income: $57,051Difference between city and state incomes: $63,650Frisco boasts the highest median household income and the biggest difference between city and state incomes on this list. Plus, since it’s located in Texas, you’ll benefit from no state income tax getting imposed on your earnings. Frisco is the best city to live in if you have your sights set on big bucks but want to avoid living in an urban center.

Source: Surprising Cities Where You Can Make Lots of Money – Slide 31 | GOBankingRates


Google AI Blog: ROBEL: Robotics Benchmarks for Learning with Low-Cost Robots

ROBEL: Robotics Benchmarks for Learning with Low-Cost RobotsWednesday, October 9, 2019Posted by Michael Ahn, Software Engineer and Vikash Kumar, Research Scientist, Robotics at GoogleLearning-based methods for solving robotic control problems have recently seen significant momentum, driven by the widening availability of simulated benchmarks (like dm_control or OpenAI-Gym) and advancements in flexible and scalable reinforcement learning techniques (DDPG, QT-Opt, or Soft Actor-Critic). While learning through simulation is effective, these simulated environments often encounter difficulty in deploying to real-world robots due to factors such as inaccurate modeling of physical phenomena and system delays. This motivates the need to develop robotic control solutions directly in the real world, on real physical hardware.

Source: Google AI Blog: ROBEL: Robotics Benchmarks for Learning with Low-Cost Robots


Algorithmic trading based on Technical Analysis in Python

This is the fourth part of a series of articles on backtesting trading strategies in Python. The previous ones described the following topics:introducing the zipline framework and presenting how to test basic strategies (link)importing custom data to use with zipline (link)evaluating the performance of trading strategies (link)

Source: Algorithmic trading based on Technical Analysis in Python