{"id":229937,"date":"2025-09-03T12:06:01","date_gmt":"2025-09-03T16:06:01","guid":{"rendered":"https:\/\/ibkrcampus.com\/campus\/?p=229937"},"modified":"2025-09-03T12:06:56","modified_gmt":"2025-09-03T16:06:56","slug":"finding-edges","status":"publish","type":"post","link":"https:\/\/www.interactivebrokers.com\/campus\/ibkr-quant-news\/finding-edges\/","title":{"rendered":"Finding Edges"},"content":{"rendered":"\n

The article “Finding Edges” was originally published on Robot Wealth<\/a> blog.<\/em><\/p>\n\n\n\n

How do we find edges?<\/p>\n\n\n\n

First, we must be clear about what constitutes a good idea. It isn\u2019t as simple as it having to make money. The risk profile must also be tolerable. This is a personal preference.<\/p>\n\n\n\n

Next, we need to be able to trade it.<\/p>\n\n\n\n

Robinhood won\u2019t let you sell naked options. You can\u2019t trade the Indian markets or crypto derivatives from the US. Retail can\u2019t trade OTC.<\/p>\n\n\n\n

These restrictions will eliminate many things, particularly from academic studies, where they don\u2019t seem to recognise this problem. (As an aside, I recently had a very well-respected academic pitch me a short volatility ETF idea. He thought his observation that the VIX basis was over-valued was the secret sauce. But he also thought that marketing was a trivial problem, and that people would prefer an active solution over a passive one. Basically, he thought the easy bit was the hard bit.)<\/p>\n\n\n\n

Here\u2019s what I think is important for finding ideas.<\/p>\n\n\n\n

Stay current with academic research<\/strong><\/h2>\n\n\n\n

Academic papers are worth reading.<\/p>\n\n\n\n

You will need to read dozens to find anything useful, and even then, it will probably only be the basic observation that is illuminating.<\/p>\n\n\n\n

I browse SSRN habitually. And I think browsing is the key. A targeted search is almost guaranteed to limit you to areas you have already considered. SSRN finds will have references, and you can then put them into Google Scholar and see what papers have cited those. Hours of fun ensue.<\/p>\n\n\n\n

Don\u2019t start with data<\/strong><\/h2>\n\n\n\n

There is too much stuff to test until you have an idea from somewhere else.<\/p>\n\n\n\n

This is related to the na\u00efve view of science, where we start with an observation, then make a theory. But without a theory, what should we observe? Is the sun rising in the east relevant to the double slit problem? Seems unlikely, but we only know that from theory.<\/p>\n\n\n\n

Treat anecdotes as evidence<\/strong><\/h2>\n\n\n\n

I like talking to market-makers and floor traders.<\/p>\n\n\n\n

Even now, the really good ones aren\u2019t particularly quantitative. Instead, they notice stuff. They see patterns a long time before they are picked up by statistics.<\/p>\n\n\n\n

Of course, the obvious downside is that they will also see stuff that turns out to be noise, but good \u201cold school\u201d traders are great observers.<\/p>\n\n\n\n

As one said to me, \u201cI can tell you stuff that you can go and nerdify.\u201d<\/p>\n\n\n\n

The best situations occur when there is a mismatch between what theory predicts and what the trader observes.<\/p>\n\n\n\n

Assumptions we forget are assumptions<\/h2>\n\n\n\n

Think about the assumptions that are so well ingrained that people have forgotten they are assumptions.<\/p>\n\n\n\n

People commonly apply put\/call parity to American options. This is wrong due to carry costs, obviously, but more interestingly, it is wrong due to volatility when there is a steep term structure. The option that is expected to be exercised will see a very different volatility to the non-exercise candidate.<\/p>\n\n\n\n

Everyone has software that can price American options, but no one uses different volatilities for calls and puts of the same strike.<\/p>\n\n\n\n

Cast a wide net<\/h2>\n\n\n\n

People often ask me, \u201cWhat option book do I read next?\u201d They seem to think that there is some deeper knowledge out there. But it only takes three or four books to get to the end of the relevant option knowledge.<\/p>\n\n\n\n

At that point, you should read about lots of stuff.<\/p>\n\n\n\n

Your brain works in a non-linear manner, and giving it random things to ponder often leads to new relevant ideas. Read about gambling, sports, military history, Silicon Valley\u2026<\/p>\n\n\n\n

Just read widely.<\/p>\n\n\n\n

What to do with your ideas?<\/h2>\n\n\n\n

Once you have an idea, be prepared to give up on it quickly.<\/p>\n\n\n\n

If it doesn\u2019t clearly point to money, no amount of tweaking is likely to produce a robust trading idea. You will either over-fit to the data or not even manage that.<\/p>\n\n\n\n

This is particularly true of \u201cinteresting ideas\u201d.<\/p>\n\n\n\n

You may really want the Parrondo\u2019s paradox to be the basis of a successful strategy, but what you want doesn\u2019t matter. You might sometimes prematurely discard a good idea, but that is less likely than wasting time on a bad one.<\/p>\n\n\n\n

Next, apply the rule that you need to be able to give a one-sentence reason why the idea might work.<\/p>\n\n\n\n

Think of yourself as asking for funding for a start-up. Give a convincing elevator pitch to yourself. \u201cI provide liquidity when markets are distressed\u201d could be convincing. \u201cI have a 4-layer neural net\u201d isn\u2019t.<\/p>\n\n\n\n

It doesn\u2019t hurt to ask other people for feedback at this point. It is very unlikely that you have a totally new idea, and that telling someone will kill it.<\/p>\n\n\n\n

If your idea passes these stages, then it is a potential strategy.<\/p>\n","protected":false},"excerpt":{"rendered":"

Your brain works in a non-linear manner, and giving it random things to ponder often leads to new relevant ideas.<\/p>\n","protected":false},"author":1673,"featured_media":151297,"comment_status":"open","ping_status":"closed","sticky":true,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[339,338,341],"tags":[1006],"contributors-categories":[13676],"class_list":{"0":"post-229937","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-data-science","8":"category-ibkr-quant-news","9":"category-quant-development","10":"tag-fintech","11":"contributors-categories-robot-wealth"},"pp_statuses_selecting_workflow":false,"pp_workflow_action":"current","pp_status_selection":"publish","acf":[],"yoast_head":"\nFinding Edges | IBKR Quant<\/title>\n<meta name=\"description\" content=\"Your brain works in a non-linear manner, and giving it random things to ponder often leads to new relevant ideas.\" 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