options

Posted on Jun 04, 2020 by Robot James
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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 future returns is a known fact. It has annual returns described by a normal distribution with mean 5% and standard deviation 10%. This is, therefore, an asset with positive drift. It is more likely to go up than down. Because we are certain about our return distribution, we can calculate the probability of this year's return being negative, as follows: pnorm(0, mean = 0.05, sd = 0.1) [1] 0.3085375 So in a year's time, there's a 31% chance it's trading below $100, and a 69% chance it's trading above $100. Now consider a call and a put option, each with a strike price of $100, expiring in a year's time. At expiry: The call will be valuable 69% of the time. The put will be...

Posted on May 29, 2020 by Robot James
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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 downside. If you're prepared to take on a little more sloppiness, there are often cheaper approaches available... https://robotwealth.com/finding-effective-crash-protection-using-downside-regressions/ Quant Skills Data manipulation skills are crucial to efficient quant trading. In the following posts, Ajet, Kris and I explain some of the skills you need to work with modern financial datasets. It's important not to use data from the future to analyse the past. Rolling and expanding windows are essential tools to help "walk your data forward" to avoid these issues. https://robotwealth.com/rolling-and-expanding-windows-for-dummies/ When you're working with large universes of stock data then you'll come across a lot of challenges. This article explains a trick to help deal with missing stock data. https://robotwealth.com/how-to-fill-gaps-in-large-stock-data-universes-using-tidyr-and-dplyr/ The kind of stuff that makes money tends to involve looking for edge in...

Posted on May 22, 2020 by Robot James
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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 better. First, he looks at the Martingale betting scheme. Is doubling your bet size after a losing trade really a good idea? https://robotwealth.com/get-rich-quick-trading-strategies-and-why-they-dont-work/     Non-Stupid Option Trading Most approaches to options trading are stupid. Here is a non-stupid approach. Options trading is just like anything else. You've got to buy the cheap stuff and sell the expensive stuff. https://robotwealth.com/how-to-find-an-edge-trading-equity-options/ Digital Signal Processing in Quant Trading In this monster post, Kris explores techniques from the field of digital signal processing, and whether they can be useful to us as systematic traders. https://robotwealth.com/using-digital-signal-processing-in-quantitative-trading-strategies/ How to Get Historical S&P 500 Constituents for Free One of the biggest advantages you can have in equity trading is going broad... But how do you pick a broad bias-free universe for equity strategy...

Posted on May 11, 2020 by Robot James
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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. How does this relate to equity options? If we take the (liquid) US Equity options market as an example then there are an absolute ton of options contracts you could be trading. 95% of them are sufficiently fairly valued that you won't make much money trading them once you've paid all the costs to buy and sell them and hedge your risk. The remaining 5% are worth looking for. Options have a positive dependency on volatility. In looking for "cheap" or "expensive" options, we're really looking for cheap or expensive "volatility". So we ask the following questions: When does the forward volatility "implied" by options prices tend to be lower than the volatility that realises in the subsequent stock price process? We would look to buy...

Posted on May 08, 2020 by Robot James
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There are 2 good reasons to buy put options: because you think they are cheap because you want downside protection. In the latter case, you are looking to use the skewed payoff profile of the put option to protect a portfolio against large downside moves without capping your upside too much. The first requires a pricing model. Or, at the least, an understanding of when and under what conditions put options tend to be cheap. The second doesn't necessarily. We'll assume that we're going to have to pay a premium to protect our portfolio - and that not losing a large amount of money is more important than the exact price we pay for it. Let's run through an example… We have a portfolio comprised entirely of 100 shares of SPY. About $29k worth. We can plot a payoff profile for our whole portfolio. This is going to show the dollar P&L from our portfolio at various SPY prices. At the time of writing, SPY closed at $287.05 if (!require("pacman")) install.packages("pacman") pacman::p_load(tidyverse, rvest, slider, tidyquant, alphavantager, kableExtra) SPYprice <- 287.05...

Posted on Apr 02, 2020 by Robot James
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Options are non-linear financial products that allow you to do useful things that you can't easily do with other financial instruments. Let me give a specific illustration of options being useful... The chart below shows the monthly cumulative % performance of our RW systematic trading portfolio since we started trading it in October 2018. The orange line shows our  performance. The blue line shows the performance of global stocks (VT) over the same period: You can see we've done pretty well over the period. But I don't show you this just to brag. There's a point coming, I promise... What's in that portfolio? We're maximalists. We run a diversified range of multi-asset, multi-style strategies in there. There are a few risk premia harvesting strategies - including the one from our public Risk Premia Bootcamp. There are a number of systematic alpha strategies - including the FX strategies and pairs trading strategies from our Bootcamps, as well as some other systematic and semi-systematic alphas in stocks, futures and options. There is a little bit of discretionary trading. There are static and...