# options

Posted on Oct 28, 2020 by
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You've probably noticed that there's a US election on the horizon. This is an event of known uncertainty: a "known unknown" in the now immortal language of Donald Rumsfeld. In trading, we sometimes observe marginal pricing inefficiencies around these "known unknowns". For example, ahead of  stock earnings announcements or significant economic or policy announcements, we tend to find: more significant trend effects (auto-correlations in asset returns) enhanced risk premia (the returns to holding risk positions tend to be higher, on average, perhaps as a premium for taking extra risk) implied volatility tends to become expensive (post hoc vs subsequent realized volatility.) What does this mean for stocks ahead of the coming US Election? In our new Robot Wealth Research Lab - one of our members, Ben, has analyzed stock index return patterns ahead of an election. With the limited data available, he finds evidence of significant excess returns to holding the SPX index for the 5 days before the US Election Day. These excess returns tend to reverse in the 10 days following the election day. Using: US election dates scraped...

Posted on Sep 16, 2020 by
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Posted on Jun 04, 2020 by
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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
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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
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Posted on May 11, 2020 by
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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
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...