Options Trading: YouTube Channel (Simpler Trading)

I enjoyed listening to Chat with Traders Episode #69 with John Carter, who is an options/futures trader and founder of Simpler Trading and discovered their free video content on YouTube Channel.

John and his team also offer premium content as part of their paid membership service, and the free YouTube channel is a good introduction where they discuss trade setup and execution in detail.

Specifically, they discuss strategies on how to reduce risk using options contrary to the common perception of options as risky due to leverage.

Quantopian on Github: Open-Source Tools

In addition to the powerful platform that Quantopian provides, they have open-sourced some of their tools on Github which means they are able to be cloned for personal use and experimentation.

Their approach to algorithmic trading is very refreshing given the Wall St culture to keep all intellectual property (IP) secret – and rightfully so due to the competitive nature of the markets.

That said, Quantopian is approaching the markets as a crowd-sourced hedge fund and leverages the IP of many to construct profitable algorithmic strategies.

As a result, they are following the culture of many Silicon Valley to open-source their most common tools and social coding to improve upon them.

Chat with Traders #72: Trading Probability (Discovery Trading)

I enjoyed listening to Episode #72 with Rob from Discovery Trading, where he discusses his views on probability when trading the markets.

Although the interview is prefaced with a disclaimer regarding the scalping tactics used by Rob, I found his views on probability very interesting since they are relevant to risk management.

Kudos to Aaron for this interview and Chat with Traders, please keep up the great work!

Chat with Traders #75: Dan Aisen (IEX Stock Exchange)

I enjoyed listening to one of archived Episode #75 with Dan Aisen, who is co-founder of the IEX Stock Exchange.

IEX is a newer stock exchange which introduces features to minimize structural arbitrage tactics used by some High-Frequency Trading (HFT) firms and protect institutional investors.

During the interview, Dan goes into depth about market structure, HFT tactics and dark pool exchanges where IEX started out before being granted status as a stock exchange.

Dan also outlines his work in a detailed Quantopian blog post.

Kudos to Aaron for this interview and Chat with Traders, please keep up the great work!

Trading with Quantopian: Portfolio Rebalancing Strategy & Algorithm Example

Having spent some time with algorithmic trading platforms, I find Quantopian to be one of the most powerful and flexible in its offerings as follows:

1.  Free to sign up, backtest strategies and compete in their trading contest

2. Free plan offers many powerful data feed which are other subscription only

3. Platform is built around a large and growing community of active users

4. Some tools are open-source, and public algorithms can be cloned for use

That said, one of the simpler strategies is a portfolio rebalance across various asset classes. Turns out it is also conservative as well and intended for retirement accounts.

The strategy and algorithm are outlined in this community discussion post; the algorithm can be cloned as follows:

1. Sign up for a free account

2. Clone algorithm and run a backtest over a given time period

3. Once algorithm runs a backtest without errors, then deploy it live

Moving forward, feel free to modify the algorithm, which will then be under the code section of the account.

Chat with Traders #69: John Carter (Options Trading)

I enjoyed listening to Episode #69 with John Carter, who is an options/futures trader and founder of Simpler Trading.

John discusses his trading style using options with focus on concentrated positions while managing risk. In particular, I found his tip on how to covered calls out of the money since they normally expire worthless.

Kudos to Aaron for this interview and Chat with Traders, please keep up the great work!

Brief Introduction to Algorithmic Trading

For anyone without programming experience but interested in learning about algorithmic trading, I would recommend the steps listed below to get off the ground running without getting side-tracked:

Learn Python to Hard Way – A good primer to get going quickly

Install Python with Anacaonda – Easy installation and comes with other useful tools such as iPython notebooks

Quantopian Lectures – Covers theory and implementation in Python; example algorithms can be easily clone and hosted on their platform

Additional Learning – Next steps would be continuing to study programming with books from O’Reilly and Packt which have publications on this topic and consider other languages for implementation

I recommend Python since it is easy to learn, and one can learn other languages once learning the first proficiently. Quantopian is the next choice since they provide valuable data sets for free on their platform and provide hosting, both of which would be side projects to implement by themselves.

This is not a comprehensive list but intended to a brief guide to get up and running in order to explore the topic.

Trading Indicators: Volume/Price, VWAP & MACD

I found lots of useful advice in CWT podcast #56 with Matt Zimberg (Optimus Futures); specifically, focusing on a select number of indicators for making trading decisions.

Kudos to Aaron for this interview and Chat with Traders, please keep up the great work!

As a result, listed below are ones which I have been successfully using over the past several months:

Volume/Price: Candlestick plot on 60-min and 1-day intervals using the Street Smart charting tool

VWAP: Chart in its own plot within Street Smart, which displays well with the 60-min interval

MACD: Refraining from oscillators to keep things simple, I use just one (MACD) to monitor momentum

Python for Finance by Yves Hilpisch

Just wanted to check in with a book recommendation – Python for Finance by Yves Hilpisch, which covers programming for basic financial modeling and algorithmic trading.

Resources are listed below and kudos to O’Reilly and The Python Quants group (founded by Yves Hilpisch) for providing these great resources for those of us researching this topic!

Python for Finance by Yves Hilpisch – O’Reilly

Book Code Examples – Github

The Python Quants Group