How to extend ETF prices with mutual fund data using SQL

How to extend ETF prices with mutual fund data using SQL

In this post, we explain how to use SQL to extend back ETF price data with total return data from mutual funds or indexes.   On Zero to Robot Master Bootcamp, we teach how to build a portfolio of three automated systematic trading strategies. One of them is a long term Risk Premia Harvesting strategy […]

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What Would it Feel Like to Invest in RenTech’s Medallion Fund?

Nearly everyone starts trading with unrealistic expectations. “If I make a 0.5% returns every day I can make over $100k in a year on 20k of starting capital.” 0.5% return every day sounds realistic, right? Wrong. Let’s sense check that… If we could make 0.5% returns every day… then our 20k would be worth: $123,000 […]

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Why Aren’t Call Options More Expensive Than Put Options? (In This Toy Example)

In the Robot Wealth Pro Community, we’ve started doing weekend “quant-teasers” where we discuss the solutions to quant problems. Here is a recent one… Why aren’t calls more expensive than puts for an asset which is more likely to go up than down? We have an asset trading at $100 for which the distribution of […]

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Weekly Roundup 29 May – Crash Protection, Sloppy Regressions and Data Munging Skillz

Here’s a round-up of our new articles this week. They cover crash protection, sloppy, noisy regressions, and data-munging skills. Finding Options for Effective Crash Protection Large capital losses can be devastating to your trading account. A couple of weeks ago, we explained how you can use SPY put options to protect your portfolio against severe market […]

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How to Fill Gaps in Large Stock Data Universes Using tidyr and dplyr

When you’re working with large universes of stock data you’ll come across a lot of challenges: Stocks pay dividends and other distributions that have to be accounted for. Stocks are subject to splits and other corporate actions which also have to be accounted for. New stocks are listed all the time – you won’t have […]

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Find Cheap Options for Effective Crash Protection Using Crash Regressions

One way we can quantify a stock’s movement relative to the market index is by calculating its “beta” to the market. To calculate the beta of MSFT to SPY (for example) we: calculate daily MSFT returns and daily SPY returns align the returns with one another regress MSFT returns against SPY returns. This shows the […]

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Weekly Roundup 22 May – Doubling Down in Losing Trades Like a Drunken Hedge Fund Manager

Here’s a round-up of our new articles this week. They cover options trading, digital signal processing, data munging and Kris’s luxurious moustache… Trading Insanity! Every new trader tries out a few insane trading ideas! In a new series on the blog, Kris explores three insane trading strategies that tempted him back when he didn’t know any […]

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Financial Data Manipulation in dplyr for Quant Traders

In this post, we’re going to show how a quant trader can manipulate stock price data using the dplyr R package. Getting set up and loading data Load the dplyr package via the tidyverse package. if (!require(‘tidyverse’)) install.packages(‘tidyverse’) library(tidyverse) First, load some price data. energystockprices.RDS contains a data frame of daily price observations for 3 […]

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How To Get Historical S&P 500 Constituents Data For Free

In this post, we are going to construct snapshots of historic S&P 500 index constituents, from freely available data on the internet. Why? Well, one of the biggest challenges in looking for opportunities amongst a broad universe of stocks is choosing what stock “universe” to look at. One approach to dealing with this is to […]

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How to Find Cheap Options to Buy and Expensive Options to Sell

If you want to make money trading, you’re going to need a way to identify when an asset is likely to be cheap and when it is likely to be expensive. You want to be a net buyer of the cheap stuff and a net seller of the expensive stuff. Thanks, Capitain Obvious. You’re welcome. […]

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