Options, futures, and other derivatives

What Hacker News says

1. guard0gApr 2021
   Nowadays RL and Gaussian processes are very popular on the trading side, as is applying attention-based NLP techniques for pattern recognition. If you are interested in stochastic calculus and convex strategies, John Hull's "Options, Futures and Other Derivatives" is a classic read. Another good book is Marcos Lopez de Prado's "Advances in Financial Machine Learning."
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2. NWChenJan 2020
   You can start at the About page as a root node: https://omnieq.com/about

   Recommend Hull's Options, Futures, and Other Derivatives as reference text.

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3. jkqwzsooDec 2018
   I'm far from an expert. I don't trade professionally (i.e. I don't derive my income from it), and I'm a chemical engineer by day.

   I think the best resource for anyone starting out investing would be "A Random Walk Down Wall Street" (Burton Malkiel), and maybe "The Intelligent Investor" (Benjamin Graham), even if you don't intend to be a traditional value investor. I think these books (I'll admit I haven't read all of The Intelligent Investor) set your expectations. I also listen to Masters in Business, Odd Lots, and P&L podcasts by Bloomberg (P&L is more short-term, while MiB and Odd Lots are more generally applicable). Both of those books might be floating around the internet.

   I also really enjoyed "The Physics of Wall Street" (James Weatherfall). It's a look into how financial mathematics got started and how it has grown and been increasingly applied in modern finance.

   If you're interested in options and other derivatives (I find derivatives to be the most interesting, and least arbitrary, financial product), I'd start with John Hull's "Options, Futures, and Other Derivatives", which is a textbook at maybe the sophomore or junior level. I hear the PDF is freely circulated online. I think understanding how options and futures work is essential for understanding finance. A slightly more technical text, "Dynamic Hedging" (Nassim Nicholas Taleb) is also good (and maybe also available online somewhere...). It is less philosophical and polemic than his other books, but doesn't resist calling you an idiot either, as is Taleb's style.

   You might also find work on non-ergodicity (Ole Peters), the Kelly criterion, universal portfolios (Thomas Cover, 1991), and Ed Thorpe (a mathematician who derived a precursor to the famous Black-Scholes model) of interest (Ed Thorpe is an incredibly interesting person in his own right). If you find yourself wanting to get into technical analysis, I'd recommend "Evidence-Based Technical Analysis" by David Arons (a spoiler: the evidence is not good). If you're interested in ML applied to trading, I keep seeing references to Advances in Financial Machine Learning (Marcos Lopez de Prado), although I haven't actually read it.

   Regarding other financial products, CME has a large number of resources available for understanding futures trading, although futures are generally too high value for regular traders to use safely (the highly liquid /ES contract controls ~$130,000 exposed to the S&P500 and allows one to take about 22x margin, or even as high as 250x for intraday trading). Similarly, there are some nice introductions to the forex market, but again I'd caution you to stay away. And as much as I'd similarly caution you about blindly following their advice (and in general about being a "volatility seller"[1,2] -- see Taleb's book), TastyTrade produces a ton of videos on options trading (particularly retail options trading), which include the mechanics of options trading and how their trading platform works (which is similar to TD's platform -- the CEO/Founder, Sosnoff, was involved in the development of it when he was at TD). You can download TD's ThinkorSwim and paper trade options, or just "preview" their application with delayed prices and see how options work.

   Finally, rather than r/wallstreetbets (which is now 99% low quality memes and loss porn), I'd recommend checking out r/options and r/thewallstreet, which are more professional forums, and potentially forums such as EliteTrader and Nuclear Phynance as well.

   [0] https://www.bloomberg.com/news/audio/2018-12-07/why-part-of-...

   [1] https://www.bloomberg.com/news/articles/2018-11-29/broker-se...

   [2] https://www.bloomberg.com/news/articles/2018-02-06/credit-su...

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4. dsaccoJul 2017
   It's hard to provide very detailed advice without knowing what exactly you're doing - are you developing market making algorithms? Working on execution algorithms? Implementing strategies developed by researchers? Is this a hedge fund or a prop trading firm? There is a lot that can encompass "quantitative developer" in the front (and back!) office.

   There are three standards that you can think of as the Cracking the Coding Interview of quant finance (insofar as that is a homogenous field, which it isn't):

   1. Heard on the Street

   2. Quant Job Interview Questions and Answers

   3. A Practical Guide to Quantitative Finance Interviews

   You want to also practice algorithms as you would for a Google/Facebook whiteboard interview, but alongside that drill down on statistics. If you have the time review your linear algebra.

   Higher math will be less necessary if you're a developer as opposed to a researcher, but they'll still want it. It's probably in your best interest if you know at least one "serious" language used for performance (C++, Java typically) while also being familiar with the data analysis libraries of Python.

   If you have no experience with finance and you're coming in to that cold, give Options, Futures and Other Derivatives a read. I'm assuming you're in this boat because you're asking the question.

   This is sort of catch-all advice. If you're working at Virtu or Jump, you're going to want to know as much as you can about low level programming with regards to latency, networking and memory, because those are HFT firms. If you're working at a place like Two Sigma, Java will be more applicable and you want to know more about statistics and data analysis on a practical level, because you're be implementing the strategies developed by quantitative researchers.

   Tailor your approach to the type of trading the firm engages in. I've made two assumptions here - 1) you're interviewing with a firm considered "quantitative" as opposed to discretionary and 2) you're interviewing for a front office role, not a back office role (support, farther from money).

   If you give more information about the type of firm and the type of role we can provide much more constructive advice.

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5. dsaccoJun 2017
   This is utterly the wrong way to learn finance for quantitative trading. That would be an unproductive use of time.

   Read Options, Futures and Other Derivatives and Algorithmic Trading and DMA and you basically know everything you'll get from public sources that could be meaningful for trading.

   If he knows how to code and is looking for "mathematics of finance" he should start with those, not the CFA.

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6. d--bApr 2017
   Quantitative finance: Options, Futures, and Other Derivatives by John Hull
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