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This write-up breaks down one of the most misunderstood areas in trading: market impact. We’ve just released a clean, structured write-up on Market Impact and Optimal Execution - covering how large orders move markets, why impact dominates trading costs, and how TWAP/VWAP, order-book dynamics, and Almgren–Chriss style liquidation models fit together. If you're serious about understanding execution quality and microstructure, especially how your own orders affect the book  -- Kickstart your Quant Interview Prep ↗ ‘Interview Byte’ contains 500+ Interview questions (https://lnkd.in/gkqcrrKf) ↗ Check out Quant Insider Stack - https://lnkd.in/gcfdUEfg A Bundle of Interview Byte and Project Handbook ↗ Turn math from your biggest fear into your greatest edge — with the ABCD Maths Course(Primer for quant finance, machine learning, and data science) 50+ hours of Video lectures with lecture notes - https://lnkd.in/gQeWjMRV Machine Learning for Finance course- Designed by Industry Veterans Hariom Tatsat, CQF, FRM with years of working on Wall Street - https://lnkd.in/gtJDWcus Use Coupon code - "EARLYBIRD20" for 20% off on the ML for Finance course ↗ATC - Algorithmic Trading Certificate (ATC): A Practitioner’s Guide, taught by Ex-Citadel Director - https://lnkd.in/gkMfXVP2 Join our Quant Insider community - https://lnkd.in/g7TaxyPA Follow us on Twitter - https://lnkd.in/ggsyM4sr Subscribe to Quant Insider's YouTube channel -https://lnkd.in/gT4vGZAh -- Are you a Broking House, FinTech Startup, RA/RIA or trading with a custom algo trading requirement? Let’s connect and explore how this groundbreaking solution can help your business thrive in today’s dynamic market. visit https://lnkd.in/gh-zVvcN Email - qitech@quantinsider.io

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When you're trying to unwind a large position, every trade you make pushes the price around. Some of that move stays in the price permanently, some of it bounces back right after you trade, and on top of that the market is always noisy. So the real question is: how do you pick a trading path that deals with all three? What this note does is walk through that logic step by step. First, it breaks down price movements into permanent impact, temporary impact, and randomness. Then it shows how each piece contributes to the total execution cost. Once that’s clear, we look at two extreme cases: selling evenly to minimise cost, or dumping everything instantly to kill all the risk. Neither one is fully satisfying, so we combine both ideas in a mean–variance objective. From there, you get a clean differential equation whose solution is a smooth liquidation curve. And depending on how much you care about risk, the path bends in different ways, aggressive at the start, perfectly linear, or slow and passive. It’s all laid out clearly in the PDF, with diagrams and the exact equations you need. Kickstart your Quant Interview Prep ↗ ‘Interview Byte’ contains 500+ Interview questions (https://lnkd.in/gkqcrrKf) ↗ Check out Quant Insider Stack - https://lnkd.in/gcfdUEfg A Bundle of Interview Byte and Project Handbook ↗ Turn math from your biggest fear into your greatest edge — with the ABCD Maths Course(Primer for quant finance, machine learning, and data science) 50+ hours of Video lectures with lecture notes - https://lnkd.in/gQeWjMRV Machine Learning for Finance course- Designed by Industry Veterans Hariom Tatsat, CQF, FRM with years of working on Wall Street - https://lnkd.in/gtJDWcus Use Coupon code - "EARLYBIRD20" for 20% off on the ML for Finance course ↗ATC - Algorithmic Trading Certificate (ATC): A Practitioner’s Guide, taught by Ex-Citadel Director - https://lnkd.in/gkMfXVP2 Join our Quant Insider community - https://lnkd.in/g7TaxyPA Follow us on Twitter - https://lnkd.in/ggsyM4sr Subscribe to Quant Insider's YouTube channel -https://lnkd.in/gT4vGZAh -- Are you a Broking House, FinTech Startup, RA/RIA or trading with a custom algo trading requirement? Let’s connect and explore how this groundbreaking solution can help your business thrive in today’s dynamic market. visit https://lnkd.in/gh-zVvcN Email - qitech@quantinsider.io

Just published a short note on decoding CTA flow in oil using a tiny, interpretable neural network. We compress prices into 25 moving-average momentum signals, feed them into a 3-neuron network with a custom risk-aware reaction function, and recover ~56% of CTA position variation using price-only data. This lets us decompose flows into systematic (mechanical CTA) vs discretionary (macro / OPEC / event-driven) and visualize how each leg contributes to cumulative P&L and risk regimes. --- Kickstart your Quant Interview Prep ↗ ‘Interview Byte’ contains 500+ Interview questions (https://lnkd.in/gkqcrrKf) ↗ Check out Quant Insider Stack - https://lnkd.in/gcfdUEfg A Bundle of Interview Byte and Project Handbook ↗ Turn math from your biggest fear into your greatest edge — with the ABCD Maths Course(Primer for quant finance, machine learning, and data science) 50+ hours of Video lectures with lecture notes - https://lnkd.in/gQeWjMRV Machine Learning for Finance course- Designed by Industry Veterans Hariom Tatsat, CQF, FRM with years of working on Wall Street - https://lnkd.in/gtJDWcus Use Coupon code - "EARLYBIRD20" for 20% off on the ML for Finance course ↗ATC - Algorithmic Trading Certificate (ATC): A Practitioner’s Guide, taught by Ex-Citadel Director - https://lnkd.in/gkMfXVP2 Join our Quant Insider community - https://lnkd.in/g7TaxyPA Follow us on Twitter - https://lnkd.in/ggsyM4sr Subscribe to Quant Insider's YouTube channel -https://lnkd.in/gT4vGZAh -- Are you a Broking House, FinTech Startup, RA/RIA or trading with a custom algo trading requirement? Let’s connect and explore how this groundbreaking solution can help your business thrive in today’s dynamic market. visit https://lnkd.in/gh-zVvcN Email - qitech@quantinsider.io

How to Make a Market on an Item in an Interview for HFT or Market-Making Roles, a step-by-step guide combining theoretical concepts and practical considerations. Making a market involves quoting both buy (bid) and sell (ask) prices for an asset, thereby providing liquidity and facilitating trading. Demonstrating a structured and analytical approach is crucial in an interview setting for high-frequency trading (HFT) or market-making roles. Kickstart your Quant Interview Prep ↗ ‘Interview Byte’ contains 500+ Interview questions (https://lnkd.in/gkqcrrKf) ↗ Check out Quant Insider Stack - https://lnkd.in/gcfdUEfg A Bundle of Interview Byte and Project Handbook ↗ Turn math from your biggest fear into your greatest edge — with the ABCD Maths Course(Primer for quant finance, machine learning, and data science) 50+ hours of Video lectures with lecture notes - https://lnkd.in/gQeWjMRV Machine Learning for Finance course- Designed by Industry Veterans Hariom Tatsat, CQF, FRM with years of working on Wall Street - https://lnkd.in/gtJDWcus Use Coupon code - "EARLYBIRD20" for 20% off on the ML for Finance course ↗ATC - Algorithmic Trading Certificate (ATC): A Practitioner’s Guide, taught by Ex-Citadel Director - https://lnkd.in/gkMfXVP2 Join our Quant Insider community - https://lnkd.in/g7TaxyPA Follow us on Twitter - https://lnkd.in/ggsyM4sr Subscribe to Quant Insider's YouTube channel -https://lnkd.in/gT4vGZAh -- Are you a Broking House, FinTech Startup, RA/RIA or trading with a custom algo trading requirement? Let’s connect and explore how this groundbreaking solution can help your business thrive in today’s dynamic market. visit https://lnkd.in/gh-zVvcN Email - qitech@quantinsider.io

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This paper breaks down how to statically replicate dispersion options using only vanilla basket calls. It gives exact replication formulas, handles both calls and puts, and extends the classic Carr–Madan framework to multi-asset payoffs. If you work with correlation, covariance, or multi-asset volatility products, this gives you a model-free pricing method instead of relying on complex stochastic-correlation assumptions Key Takeaways Dispersion options on ∣x∣ (Euclidean norm of asset performances) can be statically replicated using a continuous portfolio of vanilla basket calls. This gives model-free prices for a wide class of multi-asset volatility, correlation, and variance-based payoffs. The paper extends Carr–Madan / Breeden–Litzenberger ideas to multi-dimensional settings using Radon-transform and fractional-calculus machinery. Closed-form replicating kernels are provided for dispersion calls, puts, zero-strike cases, and general payoff functions F(∣x∣). Replication sometimes involves binary basket calls and higher-order payoff derivatives, highlighting hedging challenges in practice. Even complex payoffs like the Mexican hat dispersion straddle admit tractable numerical replication formulas. Overall: dispersion products don’t need exotic stochastic correlation models; their fair prices are implied by vanilla basket call surfaces ---- Kickstart your Quant Interview Prep ↗ ‘Interview Byte’ contains 500+ Interview questions (https://lnkd.in/gkqcrrKf) ↗ Check out Quant Insider Stack - https://lnkd.in/gcfdUEfg A Bundle of Interview Byte and Project Handbook ↗ Turn math from your biggest fear into your greatest edge — with the ABCD Maths Course(Primer for quant finance, machine learning, and data science) 50+ hours of Video lectures with lecture notes - https://lnkd.in/gQeWjMRV Machine Learning for Finance course- Designed by Industry Veterans Hariom Tatsat, CQF, FRM with years of working on Wall Street - https://lnkd.in/gtJDWcus Use Coupon code - "EARLYBIRD20" for 20% off on the ML for Finance course ↗ATC - Algorithmic Trading Certificate (ATC): A Practitioner’s Guide, taught by Ex-Citadel Director - https://lnkd.in/gkMfXVP2 Join our Quant Insider community - https://lnkd.in/g7TaxyPA Follow us on Twitter - https://lnkd.in/ggsyM4sr Subscribe to Quant Insider's YouTube channel -https://lnkd.in/gT4vGZAh -- Are you a Broking House, FinTech Startup, RA/RIA or trading with a custom algo trading requirement? Let’s connect and explore how this groundbreaking solution can help your business thrive in today’s dynamic market. visit https://lnkd.in/gh-zVvcN Email - qitech@quantinsider.io

Why Binary Prediction Accuracy Fails in Real-World Forecasting? Most discussions around forecasting, prediction markets, and “superforecasters” still rely on binary metrics. Brier scores, calibration curves, and yes/no event probabilities. Taleb’s paper “On the Statistical Differences Between Binary Forecasts and Real-World Payoffs” shows why this entire framework collapses once you step outside toy environments. The core issue is mathematical, not philosophical: Binary forecasts live in probability space. Real-world decisions live in payoff space. Binary predictions measure whether an event occurs (the zeroth moment). Real exposures depend on all moments- magnitude, variance, skew, kurtosis, and, in fat-tailed domains, extreme outcomes that dominate the distribution. Under thin tails, the difference is small. Under fat tails - which govern markets, macro variables, conflicts, and most socio-economic phenomena - the gap explodes. This leads to several hard conclusions: Binary accuracy does not map to economic performance. A forecaster can be “calibrated” and still blow up if the payoff function is nonlinear. Prediction markets can price occurrences but cannot hedge real exposures. Continuous payoffs cannot be replicated by binary contracts, especially when tails dominate. Common behavioral-economics claims (e.g., “people overestimate small probabilities”) collapse under fat-tailed math. The experiments conflated expected payoff with probability × threshold payoff - a category error. Forecasting tournaments and Brier scores are thin-tailed metrics applied to fat-tailed domains. They reward surface-level accuracy, not robustness or survival. ---- Kickstart your Quant Interview Prep ↗ ‘Interview Byte’ contains 500+ Interview questions (https://lnkd.in/gkqcrrKf) ↗ Check out Quant Insider Stack - https://lnkd.in/gcfdUEfg A Bundle of Interview Byte and Project Handbook ↗ Turn math from your biggest fear into your greatest edge — with the ABCD Maths Course(Primer for quant finance, machine learning, and data science) 50+ hours of Video lectures with lecture notes - https://lnkd.in/gQeWjMRV Machine Learning for Finance course- Designed by Industry Veterans Hariom Tatsat, CQF, FRM with years of working on Wall Street - https://lnkd.in/gtJDWcus Use Coupon code - "EARLYBIRD20" for 20% off on the ML for Finance course ↗ATC - Algorithmic Trading Certificate (ATC): A Practitioner’s Guide, taught by Ex-Citadel Director - https://lnkd.in/gkMfXVP2 Join our Quant Insider community - https://lnkd.in/g7TaxyPA Follow us on Twitter - https://lnkd.in/ggsyM4sr Subscribe to Quant Insider's YouTube channel -https://lnkd.in/gT4vGZAh -- Are you a Broking House, FinTech Startup, RA/RIA or trading with a custom algo trading requirement? Let’s connect and explore how this groundbreaking solution can help your business thrive in today’s dynamic market. visit https://lnkd.in/gh-zVvcN Email - qitech@quantinsider.io

Most people talk about “trading oil” as if it’s one big directional bet. It isn’t. Oil is one of the cleanest markets for systematic trading, if you know where the real edges sit. The published article provides a breakdown of the core quantitative edges in crude oil futures: -Momentum from inventory-driven trends -Carry from the slope of the futures curve -Term-structure momentum (carry-momentum) -Volatility normalization + nonlinear reaction sizing -Positioning signals using CFTC data (MM-SLOW / MM-FAST) -An empirically-validated volatility risk premium tilt If you want to understand why CTAs and commodity quants consistently extract returns from energy markets, this will give you a clear and practical view without the usual hand-waving. ---- Kickstart your Quant Interview Prep ↗ ‘Interview Byte’ contains 500+ Interview questions (https://lnkd.in/gkqcrrKf) ↗ Check out Quant Insider Stack - https://lnkd.in/gcfdUEfg A Bundle of Interview Byte and Project Handbook ↗ Turn math from your biggest fear into your greatest edge — with the ABCD Maths Course(Primer for quant finance, machine learning, and data science) 50+ hours of Video lectures with lecture notes - https://lnkd.in/gQeWjMRV Machine Learning for Finance course- Designed by Industry Veterans Hariom Tatsat, CQF, FRM with years of working on Wall Street - https://lnkd.in/gtJDWcus Use Coupon code - "EARLYBIRD20" for 20% off on the ML for Finance course ↗ATC - Algorithmic Trading Certificate (ATC): A Practitioner’s Guide, taught by Ex-Citadel Director - https://lnkd.in/gkMfXVP2 Join our Quant Insider community - https://lnkd.in/g7TaxyPA Follow us on Twitter - https://lnkd.in/ggsyM4sr Subscribe to Quant Insider's new YouTube channel -https://lnkd.in/gT4vGZAh For more quant finance memes, follow us on Instagram - Quant Insider (https://lnkd.in/gfjc4hBu) --- Are you a Broking House, FinTech Startup, or RA/RIA with a custom algo trading requirement? Let’s connect and explore how this groundbreaking solution can help your business thrive in today’s dynamic market. Drop us a message or visit https://lnkd.in/gh-zVvcN Alternatively, you can also fill in this Google Form, https://lnkd.in/gb9gbXuS so we can learn more about you, your business, and your requirements. This will help us have better clarity while connecting with you. Email - qitech@quantinsider.io