{"id":241677,"date":"2026-04-17T11:40:48","date_gmt":"2026-04-17T15:40:48","guid":{"rendered":"https:\/\/ibkrcampus.com\/campus\/?p=241677"},"modified":"2026-04-23T09:45:18","modified_gmt":"2026-04-23T13:45:18","slug":"algo-advantage-050-samir-varma-the-pre-trading-show-on-quantum-physics","status":"publish","type":"post","link":"https:\/\/www.interactivebrokers.com\/campus\/ibkr-quant-news\/algo-advantage-050-samir-varma-the-pre-trading-show-on-quantum-physics\/","title":{"rendered":"Algo Advantage 050 – Samir Varma – The Pre-Trading Show (on Quantum Physics)"},"content":{"rendered":"\n

Contributor Podcast<\/h2>\n\n\n\n

Algo Advantage Episode 050<\/h3>\n\n\n\n

In this Algo Advantage guest podcast, Simon chats with Samir Varma. The episode is available on Algo Advantage blog: https:\/\/www.algoadvantage.io\/podcast\/050-samir-varma\/<\/a><\/p>\n\n\n\n

\n\n\n\n

Simon’s thoughts below supplement the discussion in the above episode<\/em>:<\/p>\n\n\n\n

Samir\u2019s Substack has some wonderful material, and today\u2019s write up in inspired by his article \u201cThe Emperor Has No Alpha \u2013 What Data Mining Reveals About Academic Finance\u201d. Forgive me for drawing heavily from it, but it\u2019s great, and you should read it in full here:<\/p>\n\n\n\n

Samir Varma \u2013\u00a0The Emperor Has No Alpha<\/a><\/p>\n\n\n\n

In his article he references a paper from the Federal Reserve Board: \u201cDoes Peer-Reviewed Research Help Predict Stock Returns?<\/a>\u201d<\/p>\n\n\n\n

The answer \u2013 \u201cnot really\u201d. What a scientist like Samir reminds us of is that \u201celegant theories must\u00a0predict<\/strong>, not just\u00a0explain<\/strong>.\u201d<\/p>\n\n\n\n

In the Fed paper, 29,000 accounting ratios were brute-force data mined for statistical significance and compared to 212 peer-reviewed return predictors from academic studies. The result?\u00a0Both\u00a0<\/em><\/strong>approaches retained around 50% of their predictive power\u00a0out of sample.<\/em><\/p>\n\n\n\n

In physics, theory often leads the way. Scientists predict something should exist, then go looking for it. As Samir puts it,\u00a0\u201cTheory constrains the search space. It tells you where to look\u201d<\/strong>.<\/p>\n\n\n\n

Academic finance likes to imagine it works the same way.<\/p>\n\n\n\n

A predictor is published. Then comes the explanatory framework. Maybe it works because investors are being compensated for risk. Maybe it works because of behavioral reasons. Maybe it reflects information asymmetry, attention effects, limits to arbitrage, or some other respectable academic mechanism. The theory is supposed to help us separate genuine phenomena from statistical rubbish.<\/p>\n\n\n\n

But the Fed paper would suggest that theory does not seem to do that job very well.<\/p>\n\n\n\n

That is the uncomfortable punchline. And for traders, it matters.<\/p>\n\n\n\n

Categorizing by theoretical foundation: risk-based, mispricing-based, and agnostic, the paper found that the only category showing any real sign of outperformance is the agnostic research: the papers\u00a0that refuse to take a theoretical stance<\/strong>.<\/p>\n\n\n\n

That is a serious result. It suggests that, in markets, elegant explanations may be far less useful than people think. Worse, they may create a false sense of confidence. How many of them are created to sell a hedge fund?<\/p>\n\n\n\n

Oh, and the other theory that did actually out-perform?\u00a0Momentum!<\/strong><\/p>\n\n\n\n

\n\n\n\n

Data Mining Is Not the Villain<\/strong><\/p>\n\n\n\n

In quant circles, \u201cdata mining\u201d is often used as shorthand for bad research. Overfitting. Curve-fitting. Random pattern hunting. Statistical hallucination dressed up as alpha. Fair enough. Bad data mining exists. Plenty of it. Most of it ends badly.<\/p>\n\n\n\n

But the deeper point is this: all empirical research is, at some level, data mining. The real issue is not whether you search the data. The issue is whether you search it with rigor.<\/p>\n\n\n\n

If useful information exists in prices, accounting data, flows, or market structure, a computer can help uncover it. This shouldn\u2019t a surprise. You do not need a grand theory before you are allowed to notice that a pattern is there. The market leaves fingerprints. Some are noise. Some are not. Your job is to figure out which is which.<\/p>\n\n\n\n

In his paper Samir argues that data mining could have uncovered many of the major themes in asset pricing before they were formally published. Investment, accruals, external financing, earnings surprise\u2014many of these broad areas could have been identified by searching the data first, with theory arriving later as explanation rather than discovery.<\/p>\n\n\n\n

That should change how a trader thinks.<\/p>\n\n\n\n

It means the academic paper is not always the origin of insight. Often it is the formalisation of something the data was already trying to say. The theory may tidy it up, give it a name, and provide a narrative respectable enough for publication. But the pattern itself may have been available long before the journal article arrived wearing a tie.
That is not an argument against academia. It is an argument against passivity.<\/p>\n\n\n\n

If a trader waits for peer-reviewed permission to investigate an idea, he may already be late.<\/p>\n\n\n\n

\n\n\n\n

Academic Research Still Matters<\/strong><\/p>\n\n\n\n

Now, let us be clear. None of this means academic finance is useless. It\u2019s incredibly helpful. Samir mentioned to me he has probably read 3 papers a day for many years.<\/p>\n\n\n\n

The academic literature remains essential because it gives traders a map of what has been observed, what has been tested, and how others have tried to explain recurring effects. It gives you language, structure, categories, and a body of work to interrogate. It tells you what others think they have found. And often, that is enormously valuable.<\/p>\n\n\n\n

Now, if only you had a tool to accumulate hundreds of great academic papers into a searchable library,\u00a0summarise their trading potential, produce the strategy code even, and quickly test them before proceeding with deeper research? What if you could work collectively with others testing, sifting, letting the best ideas rise to the top? Funny, I had the same thought, and this is why I\u2019m about to drop the\u00a0Algo Vault\u00a0for Collective annual subscribers. It\u2019s exactly that.<\/em><\/p>\n\n\n\n

Samir, like any good scientists reveals the crucial shift we need to make in our approach to these theories: once you understand what the academics are saying, your job is not merely to admire it. Your job is to figure out\u00a0\u201cwhy they\u2019re wrong\u201d<\/strong>.<\/p>\n\n\n\n

That is where the trader\u2019s work begins.<\/p>\n\n\n\n

Not because academics are fools \u2013 often they are very smart. But because they are playing a different game. They are trying to explain patterns in a publishable framework. You are trying to make money going forward, after costs, after slippage, after crowding, after decay, and after your own psychology starts whispering that this time it is different.
Those are very different objectives.<\/p>\n\n\n\n

Stand on the shoulders of giants, but you better believe you need to \u2018get to work\u2019 yourself.<\/p>\n\n\n\n

An academic explanation may be directionally useful and still be wrong in the ways that matter most to a live trader. The risk framework may miss the actual driver. The behavioral story may be too neat. The statistical result may weaken after publication. The implementation assumptions may be unrealistic. Or the entire thing may only survive in sample because of specification choices no practitioner would ever use in live trading.<\/p>\n\n\n\n

That is why understanding the literature is necessary but not sufficient. You must know the \u201cwhat.\u201d Then you must attack the \u201cwhy.\u201d<\/p>\n\n\n\n

Why should this persist?<\/p>\n\n\n\n

Why did it work?<\/p>\n\n\n\n

Why did it stop working?<\/p>\n\n\n\n

Why did the paper measure it this way?<\/p>\n\n\n\n

Why would a live trader actually get paid for bearing this exposure?<\/p>\n\n\n\n

Why would this effect survive after being published, copied, and crowded?<\/p>\n\n\n\n

That line of questioning is where genuine edge begins.
Now, even by answering the \u2018why\u2019, we may not need an elegant theory, we just need to have tested it till we threw up, so that the \u2018why\u2019 is ingrained so deeply in us that we are comfortable we can trade it. The Agnostic \/ \u2018unexplainable\u2019 theories can have a \u2018why\u2019 that lives precisely in the fact that they \u2018don\u2019t fit neatly\u2019 with academic theories.<\/p>\n\n\n\n

Samir quotes Peter Brown, co-CEO of Renaissance Technologies, said in Gregory Zuckerman\u2019s\u00a0The Man Who Solved the Market<\/em><\/a>:<\/p>\n\n\n\n

\u201cIf there were signals that made a lot of sense that were very strong, they would have long-ago been traded out. There are signals that you can\u2019t understand, but they\u2019re there, and they can be relatively strong.\u201d<\/strong><\/p>\n\n\n\n

It\u2019s a quote I\u2019m happy to repeat. Samir adds \u201cThe patterns that persist are precisely the ones that resist explanation.\u201d

PS: Don\u2019t forget\u00a0we interviewed Zuckerman<\/a>\u00a0way back when!<\/em>

That is the point, isn\u2019t it?<\/p>\n\n\n\n

The signals that are easiest to explain are also the easiest to crowd. The ones that fit neatly into an academic model are the ones most vulnerable to being noticed, packaged, published, marketed, and arbitraged to death. By the time a signal becomes intellectually elegant, it may already be commercially extinct.<\/p>\n\n\n\n

Meanwhile, perhaps the weird stuff survives longer precisely because it resists neat explanation. The pattern looks uncomfortable. The rationale is murky. The narrative is weak. Which means fewer people pile in with conviction, fewer funds leverage it aggressively, and fewer allocators convince themselves it is a durable gift from the heavens.<\/p>\n\n\n\n

Ugly signals may live longer because they do not flatter the human need for coherence.<\/p>\n\n\n\n

But hey, this is just my theory, you should test it. It probably doesn\u2019t hold up.<\/p>\n\n\n\n

\n\n\n\n

Theory Does Not Trade for A Living. Process Does.<\/strong><\/p>\n\n\n\n

The real lesson here is not that theory is worthless. It is that theory is not a substitute for research discipline.<\/p>\n\n\n\n

What actually seems to predict persistence is not theoretical elegance but statistical strength. The stronger the in-sample evidence, the better the odds that something real is there.<\/p>\n\n\n\n

That is why the serious quant has to be maniacal about process.<\/p>\n\n\n\n

In fact, one advantage of looking at older papers, is that there is more out of sample time for you to check them against. This is a common issue with the peer review process; it doesn\u2019t generally do robustness testing out of sample.<\/p>\n\n\n\n

You need to test ideas hard. Across time. Across markets. Across parameter ranges. Across regimes.<\/strong>\u00a0Before publication and after publication if possible. Before costs and after costs. Under realistic assumptions, not fantasy ones.\u00a0You need to know what breaks the idea, what strengthens it, what dilutes it, and what its true behavioural profile looks like when the equity curve gets ugly.<\/strong><\/p>\n\n\n\n

That is where conviction comes from.<\/strong><\/p>\n\n\n\n

Papers are full of great ideas, plausible explanations for phenomena are important, but conviction comes from doing the work yourself and understanding what the work is actually telling you.<\/p>\n\n\n\n

This is especially important because many traders do not really understand the ideas they trade. They understand the headline. They understand the sales pitch. They may even understand the backtest summary. But they do not understand the mechanism well enough to survive the periods when the strategy inevitably disappoints.<\/p>\n\n\n\n

That is fatal.<\/p>\n\n\n\n

If you do not understand the strategy deeply, you will not trust it when you most need to. And if you do not trust it, you will override it, reduce it, abandon it, or morph it into something else at exactly the wrong moment.<\/p>\n\n\n\n

\n\n\n\n

Your Edge Must Fit You<\/strong><\/p>\n\n\n\n

The final filter is not just whether a signal is statistically valid. It is whether it is congruent with the person trading it.<\/p>\n\n\n\n

Samir says\u00a0\u201cthat durable competitive advantage needs to be 100% congruent with your own personality\u201d<\/strong>.<\/p>\n\n\n\n

That line is more important than most people realise.<\/p>\n\n\n\n

A strategy is not just a return stream. It is an experience. It has a rhythm, a temperament, a pattern of pain. Some strategies win infrequently but explosively. Some grind steadily then suffer sharp reversals. Some require patience bordering on monasticism. Others demand speed, decisiveness, and emotional resilience in the face of constant noise.<\/p>\n\n\n\n

If the strategy clashes with your nature, it will eventually beat you, even if the backtest is valid.<\/p>\n\n\n\n

A risk-averse person may not be able to hold a sharp momentum system through its inevitable drawdowns. A slow, patient thinker may sabotage a short-term strategy by second-guessing constant signals. A trader who craves narrative certainty may abandon a robust but ugly model simply because he cannot explain it elegantly enough to himself.<\/p>\n\n\n\n

That is why your edge cannot be borrowed. It cannot just be copied from a paper, a fund manager, or a clever person on the internet. Samir says it so well,\u00a0\u201cYour edge must be yours. Not borrowed. Not copied. Not theoretically optimal for some abstract investor. Yours\u201d<\/strong>.<\/p>\n\n\n\n

That does not mean inventing something from nothing. It means making it your own through understanding, research, and repeated testing until the logic and the pain profile are both something you can actually live with.<\/p>\n\n\n\n

\n\n\n\n

The Trader\u2019s Real Job \u2013 Practical Take-Aways<\/strong><\/p>\n\n\n\n

I\u2019ve said it before \u2013 Trading is a business. Writing academic papers is not. Academic insight remains essential because it tells you what has been seen and how people have framed it.<\/p>\n\n\n\n

But your real job is to test it yourself, understand it deeply, and figure out where the academic story is incomplete, fragile, or simply wrong.<\/p>\n\n\n\n

That is where edge lives.<\/p>\n\n\n\n

Not in theory alone.<\/p>\n\n\n\n

Not in data alone.<\/p>\n\n\n\n

In the disciplined confrontation between the two.<\/p>\n\n\n\n

And then, one level deeper still, in building something you can actually trade.<\/p>\n\n\n\n

Because in the end, the best strategy in the world is useless if you do not understand it, do not trust it, or cannot execute it.<\/p>\n\n\n\n

That is why the work matters. Test it. Break it. Rebuild it. Strip it back. Understand it until it is no longer just an idea from a paper, but a method you could hold through stress.\u00a0Empirical evidence is your only friend.\u00a0<\/strong>Here\u2019s the only \u2018process\u2019 you really need:\u00a0test until you throw up, then test some more.<\/em><\/p>\n\n\n\n

One last quote from Samir. \u201cThe data mining result in this paper is liberating in this sense. It means you don\u2019t need to genuflect before academic authority. You need to understand the academics, yes. But then you need to find what works\u00a0for you<\/em>, validated by data, congruent with your psychology.<\/p>\n\n\n\n

That\u2019s a much harder problem than reading papers. It\u2019s also the only problem that matters.\u201d<\/p>\n\n\n\n

Research widely, always be skeptical, don\u2019t assume complexity makes more money, mine the data vigorously, and,\u00a0if<\/em>\u00a0it holds statistical significance out of sample,\u00a0then<\/em>\u00a0devise the theory.<\/p>\n","protected":false},"excerpt":{"rendered":"

In quant circles, \u201cdata mining\u201d is often used as shorthand for bad research. <\/p>\n","protected":false},"author":1726,"featured_media":241926,"comment_status":"open","ping_status":"closed","sticky":true,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":"","jetpack_post_was_ever_published":false},"categories":[339,338,341],"tags":[851,494],"contributors-categories":[21000],"class_list":{"0":"post-241677","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-algo-trading","11":"tag-quant","12":"contributors-categories-algo-advantage"},"pp_statuses_selecting_workflow":false,"pp_workflow_action":"current","pp_status_selection":"publish","acf":[],"yoast_head":"\nAlgo Advantage 050 – Samir Varma – The Pre-Trading Show (on Quantum Physics)<\/title>\n<meta name=\"description\" content=\"In quant circles, \u201cdata mining\u201d is often used as shorthand for bad research.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.interactivebrokers.com\/campus\/wp-json\/wp\/v2\/posts\/241677\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Algo Advantage 050 \u2013 Samir Varma \u2013 The Pre-Trading Show (on Quantum Physics)\" \/>\n<meta property=\"og:description\" content=\"In quant circles, \u201cdata mining\u201d is often used as shorthand for bad research.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.interactivebrokers.com\/campus\/ibkr-quant-news\/algo-advantage-050-samir-varma-the-pre-trading-show-on-quantum-physics\/\" \/>\n<meta property=\"og:site_name\" content=\"IBKR Campus US\" \/>\n<meta property=\"article:published_time\" content=\"2026-04-17T15:40:48+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-04-23T13:45:18+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2026\/04\/swirl-numbers-green-background.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1000\" \/>\n\t<meta property=\"og:image:height\" content=\"563\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Simon\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Simon\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"10 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\n\t \"@context\": \"https:\\\/\\\/schema.org\",\n\t \"@graph\": [\n\t {\n\t \"@type\": \"NewsArticle\",\n\t \"@id\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/ibkr-quant-news\\\/algo-advantage-050-samir-varma-the-pre-trading-show-on-quantum-physics\\\/#article\",\n\t \"isPartOf\": {\n\t \"@id\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/ibkr-quant-news\\\/algo-advantage-050-samir-varma-the-pre-trading-show-on-quantum-physics\\\/\"\n\t },\n\t \"author\": {\n\t \"name\": \"Simon\",\n\t \"@id\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/#\\\/schema\\\/person\\\/42b3fa40f53ead4ca41c50acd804d1df\"\n\t },\n\t \"headline\": \"Algo Advantage 050 – Samir Varma – The Pre-Trading Show (on Quantum Physics)\",\n\t \"datePublished\": \"2026-04-17T15:40:48+00:00\",\n\t \"dateModified\": \"2026-04-23T13:45:18+00:00\",\n\t \"mainEntityOfPage\": {\n\t \"@id\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/ibkr-quant-news\\\/algo-advantage-050-samir-varma-the-pre-trading-show-on-quantum-physics\\\/\"\n\t },\n\t \"wordCount\": 2268,\n\t \"commentCount\": 1,\n\t \"publisher\": {\n\t \"@id\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/#organization\"\n\t },\n\t \"image\": {\n\t \"@id\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/ibkr-quant-news\\\/algo-advantage-050-samir-varma-the-pre-trading-show-on-quantum-physics\\\/#primaryimage\"\n\t },\n\t \"thumbnailUrl\": \"https:\\\/\\\/www.interactivebrokers.com\\\/campus\\\/wp-content\\\/uploads\\\/sites\\\/2\\\/2026\\\/04\\\/swirl-numbers-green-background.jpg\",\n\t \"keywords\": [\n\t \"Algo Trading\",\n\t \"Quant\"\n\t ],\n\t \"articleSection\": [\n\t \"Data Science\",\n\t \"Quant\",\n\t \"Quant Development\"\n\t ],\n\t \"inLanguage\": \"en-US\",\n\t \"potentialAction\": [\n\t {\n\t \"@type\": \"CommentAction\",\n\t \"name\": \"Comment\",\n\t \"target\": [\n\t \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/ibkr-quant-news\\\/algo-advantage-050-samir-varma-the-pre-trading-show-on-quantum-physics\\\/#respond\"\n\t ]\n\t }\n\t ]\n\t },\n\t {\n\t \"@type\": \"WebPage\",\n\t \"@id\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/ibkr-quant-news\\\/algo-advantage-050-samir-varma-the-pre-trading-show-on-quantum-physics\\\/\",\n\t \"url\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/ibkr-quant-news\\\/algo-advantage-050-samir-varma-the-pre-trading-show-on-quantum-physics\\\/\",\n\t \"name\": \"Algo Advantage 050 - Samir Varma - The Pre-Trading Show (on Quantum Physics) | IBKR Campus US\",\n\t \"isPartOf\": {\n\t \"@id\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/#website\"\n\t },\n\t \"primaryImageOfPage\": {\n\t \"@id\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/ibkr-quant-news\\\/algo-advantage-050-samir-varma-the-pre-trading-show-on-quantum-physics\\\/#primaryimage\"\n\t },\n\t \"image\": {\n\t \"@id\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/ibkr-quant-news\\\/algo-advantage-050-samir-varma-the-pre-trading-show-on-quantum-physics\\\/#primaryimage\"\n\t },\n\t \"thumbnailUrl\": \"https:\\\/\\\/www.interactivebrokers.com\\\/campus\\\/wp-content\\\/uploads\\\/sites\\\/2\\\/2026\\\/04\\\/swirl-numbers-green-background.jpg\",\n\t \"datePublished\": \"2026-04-17T15:40:48+00:00\",\n\t \"dateModified\": \"2026-04-23T13:45:18+00:00\",\n\t \"description\": \"In quant circles, \u201cdata mining\u201d is often used as shorthand for bad research.\",\n\t \"inLanguage\": \"en-US\",\n\t \"potentialAction\": [\n\t {\n\t \"@type\": \"ReadAction\",\n\t \"target\": [\n\t \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/ibkr-quant-news\\\/algo-advantage-050-samir-varma-the-pre-trading-show-on-quantum-physics\\\/\"\n\t ]\n\t }\n\t ]\n\t },\n\t {\n\t \"@type\": \"ImageObject\",\n\t \"inLanguage\": \"en-US\",\n\t \"@id\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/ibkr-quant-news\\\/algo-advantage-050-samir-varma-the-pre-trading-show-on-quantum-physics\\\/#primaryimage\",\n\t \"url\": \"https:\\\/\\\/www.interactivebrokers.com\\\/campus\\\/wp-content\\\/uploads\\\/sites\\\/2\\\/2026\\\/04\\\/swirl-numbers-green-background.jpg\",\n\t \"contentUrl\": \"https:\\\/\\\/www.interactivebrokers.com\\\/campus\\\/wp-content\\\/uploads\\\/sites\\\/2\\\/2026\\\/04\\\/swirl-numbers-green-background.jpg\",\n\t \"width\": 1000,\n\t \"height\": 563,\n\t \"caption\": \"Quant\"\n\t },\n\t {\n\t \"@type\": \"WebSite\",\n\t \"@id\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/#website\",\n\t \"url\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/\",\n\t \"name\": \"IBKR Campus US\",\n\t \"description\": \"Financial Education from Interactive Brokers\",\n\t \"publisher\": {\n\t \"@id\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/#organization\"\n\t },\n\t \"potentialAction\": [\n\t {\n\t \"@type\": \"SearchAction\",\n\t \"target\": {\n\t \"@type\": \"EntryPoint\",\n\t \"urlTemplate\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/?s={search_term_string}\"\n\t },\n\t \"query-input\": {\n\t \"@type\": \"PropertyValueSpecification\",\n\t \"valueRequired\": true,\n\t \"valueName\": \"search_term_string\"\n\t }\n\t }\n\t ],\n\t \"inLanguage\": \"en-US\"\n\t },\n\t {\n\t \"@type\": \"Organization\",\n\t \"@id\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/#organization\",\n\t \"name\": \"Interactive Brokers\",\n\t \"alternateName\": \"IBKR\",\n\t \"url\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/\",\n\t \"logo\": {\n\t \"@type\": \"ImageObject\",\n\t \"inLanguage\": \"en-US\",\n\t \"@id\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/#\\\/schema\\\/logo\\\/image\\\/\",\n\t \"url\": \"https:\\\/\\\/www.interactivebrokers.com\\\/campus\\\/wp-content\\\/uploads\\\/sites\\\/2\\\/2024\\\/05\\\/ibkr-campus-logo.jpg\",\n\t \"contentUrl\": \"https:\\\/\\\/www.interactivebrokers.com\\\/campus\\\/wp-content\\\/uploads\\\/sites\\\/2\\\/2024\\\/05\\\/ibkr-campus-logo.jpg\",\n\t \"width\": 669,\n\t \"height\": 669,\n\t \"caption\": \"Interactive Brokers\"\n\t },\n\t \"image\": {\n\t \"@id\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/#\\\/schema\\\/logo\\\/image\\\/\"\n\t },\n\t \"publishingPrinciples\": \"https:\\\/\\\/www.interactivebrokers.com\\\/campus\\\/about-ibkr-campus\\\/\",\n\t \"ethicsPolicy\": \"https:\\\/\\\/www.interactivebrokers.com\\\/campus\\\/cyber-security-notice\\\/\"\n\t },\n\t {\n\t \"@type\": \"Person\",\n\t \"@id\": \"https:\\\/\\\/ibkrcampus.com\\\/campus\\\/#\\\/schema\\\/person\\\/42b3fa40f53ead4ca41c50acd804d1df\",\n\t \"name\": \"Simon\",\n\t \"url\": \"https:\\\/\\\/www.interactivebrokers.com\\\/campus\\\/author\\\/simon\\\/\"\n\t }\n\t ]\n\t}<\/script>\n<!-- \/ Yoast SEO Premium plugin. -->","yoast_head_json":{"title":"Algo Advantage 050 – Samir Varma – The Pre-Trading Show (on Quantum Physics)","description":"In quant circles, \u201cdata mining\u201d is often used as shorthand for bad research.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/www.interactivebrokers.com\/campus\/wp-json\/wp\/v2\/posts\/241677\/","og_locale":"en_US","og_type":"article","og_title":"Algo Advantage 050 \u2013 Samir Varma \u2013 The Pre-Trading Show (on Quantum Physics)","og_description":"In quant circles, \u201cdata mining\u201d is often used as shorthand for bad research.","og_url":"https:\/\/www.interactivebrokers.com\/campus\/ibkr-quant-news\/algo-advantage-050-samir-varma-the-pre-trading-show-on-quantum-physics\/","og_site_name":"IBKR Campus US","article_published_time":"2026-04-17T15:40:48+00:00","article_modified_time":"2026-04-23T13:45:18+00:00","og_image":[{"width":1000,"height":563,"url":"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2026\/04\/swirl-numbers-green-background.jpg","type":"image\/jpeg"}],"author":"Simon","twitter_card":"summary_large_image","twitter_misc":{"Written by":"Simon","Est. reading time":"10 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"NewsArticle","@id":"https:\/\/ibkrcampus.com\/campus\/ibkr-quant-news\/algo-advantage-050-samir-varma-the-pre-trading-show-on-quantum-physics\/#article","isPartOf":{"@id":"https:\/\/ibkrcampus.com\/campus\/ibkr-quant-news\/algo-advantage-050-samir-varma-the-pre-trading-show-on-quantum-physics\/"},"author":{"name":"Simon","@id":"https:\/\/ibkrcampus.com\/campus\/#\/schema\/person\/42b3fa40f53ead4ca41c50acd804d1df"},"headline":"Algo Advantage 050 – Samir Varma – The Pre-Trading Show (on Quantum Physics)","datePublished":"2026-04-17T15:40:48+00:00","dateModified":"2026-04-23T13:45:18+00:00","mainEntityOfPage":{"@id":"https:\/\/ibkrcampus.com\/campus\/ibkr-quant-news\/algo-advantage-050-samir-varma-the-pre-trading-show-on-quantum-physics\/"},"wordCount":2268,"commentCount":1,"publisher":{"@id":"https:\/\/ibkrcampus.com\/campus\/#organization"},"image":{"@id":"https:\/\/ibkrcampus.com\/campus\/ibkr-quant-news\/algo-advantage-050-samir-varma-the-pre-trading-show-on-quantum-physics\/#primaryimage"},"thumbnailUrl":"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2026\/04\/swirl-numbers-green-background.jpg","keywords":["Algo Trading","Quant"],"articleSection":["Data Science","Quant","Quant Development"],"inLanguage":"en-US","potentialAction":[{"@type":"CommentAction","name":"Comment","target":["https:\/\/ibkrcampus.com\/campus\/ibkr-quant-news\/algo-advantage-050-samir-varma-the-pre-trading-show-on-quantum-physics\/#respond"]}]},{"@type":"WebPage","@id":"https:\/\/ibkrcampus.com\/campus\/ibkr-quant-news\/algo-advantage-050-samir-varma-the-pre-trading-show-on-quantum-physics\/","url":"https:\/\/ibkrcampus.com\/campus\/ibkr-quant-news\/algo-advantage-050-samir-varma-the-pre-trading-show-on-quantum-physics\/","name":"Algo Advantage 050 - Samir Varma - The Pre-Trading Show (on Quantum Physics) | IBKR Campus US","isPartOf":{"@id":"https:\/\/ibkrcampus.com\/campus\/#website"},"primaryImageOfPage":{"@id":"https:\/\/ibkrcampus.com\/campus\/ibkr-quant-news\/algo-advantage-050-samir-varma-the-pre-trading-show-on-quantum-physics\/#primaryimage"},"image":{"@id":"https:\/\/ibkrcampus.com\/campus\/ibkr-quant-news\/algo-advantage-050-samir-varma-the-pre-trading-show-on-quantum-physics\/#primaryimage"},"thumbnailUrl":"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2026\/04\/swirl-numbers-green-background.jpg","datePublished":"2026-04-17T15:40:48+00:00","dateModified":"2026-04-23T13:45:18+00:00","description":"In quant circles, \u201cdata mining\u201d is often used as shorthand for bad research.","inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/ibkrcampus.com\/campus\/ibkr-quant-news\/algo-advantage-050-samir-varma-the-pre-trading-show-on-quantum-physics\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/ibkrcampus.com\/campus\/ibkr-quant-news\/algo-advantage-050-samir-varma-the-pre-trading-show-on-quantum-physics\/#primaryimage","url":"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2026\/04\/swirl-numbers-green-background.jpg","contentUrl":"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2026\/04\/swirl-numbers-green-background.jpg","width":1000,"height":563,"caption":"Quant"},{"@type":"WebSite","@id":"https:\/\/ibkrcampus.com\/campus\/#website","url":"https:\/\/ibkrcampus.com\/campus\/","name":"IBKR Campus US","description":"Financial Education from Interactive Brokers","publisher":{"@id":"https:\/\/ibkrcampus.com\/campus\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/ibkrcampus.com\/campus\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Organization","@id":"https:\/\/ibkrcampus.com\/campus\/#organization","name":"Interactive Brokers","alternateName":"IBKR","url":"https:\/\/ibkrcampus.com\/campus\/","logo":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/ibkrcampus.com\/campus\/#\/schema\/logo\/image\/","url":"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2024\/05\/ibkr-campus-logo.jpg","contentUrl":"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2024\/05\/ibkr-campus-logo.jpg","width":669,"height":669,"caption":"Interactive Brokers"},"image":{"@id":"https:\/\/ibkrcampus.com\/campus\/#\/schema\/logo\/image\/"},"publishingPrinciples":"https:\/\/www.interactivebrokers.com\/campus\/about-ibkr-campus\/","ethicsPolicy":"https:\/\/www.interactivebrokers.com\/campus\/cyber-security-notice\/"},{"@type":"Person","@id":"https:\/\/ibkrcampus.com\/campus\/#\/schema\/person\/42b3fa40f53ead4ca41c50acd804d1df","name":"Simon","url":"https:\/\/www.interactivebrokers.com\/campus\/author\/simon\/"}]}},"jetpack_featured_media_url":"https:\/\/www.interactivebrokers.com\/campus\/wp-content\/uploads\/sites\/2\/2026\/04\/swirl-numbers-green-background.jpg","_links":{"self":[{"href":"https:\/\/ibkrcampus.com\/campus\/wp-json\/wp\/v2\/posts\/241677","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ibkrcampus.com\/campus\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ibkrcampus.com\/campus\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ibkrcampus.com\/campus\/wp-json\/wp\/v2\/users\/1726"}],"replies":[{"embeddable":true,"href":"https:\/\/ibkrcampus.com\/campus\/wp-json\/wp\/v2\/comments?post=241677"}],"version-history":[{"count":0,"href":"https:\/\/ibkrcampus.com\/campus\/wp-json\/wp\/v2\/posts\/241677\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/ibkrcampus.com\/campus\/wp-json\/wp\/v2\/media\/241926"}],"wp:attachment":[{"href":"https:\/\/ibkrcampus.com\/campus\/wp-json\/wp\/v2\/media?parent=241677"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ibkrcampus.com\/campus\/wp-json\/wp\/v2\/categories?post=241677"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ibkrcampus.com\/campus\/wp-json\/wp\/v2\/tags?post=241677"},{"taxonomy":"contributors-categories","embeddable":true,"href":"https:\/\/ibkrcampus.com\/campus\/wp-json\/wp\/v2\/contributors-categories?post=241677"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}