
Jul 26, 2026 - Quant Insider
Is Quant Insider Legit? A Transparent Look at What We Offer
Wondering if Quant Insider is legit? Get a transparent breakdown of our courses, team credentials, student outcomes, and policies — no hype, just facts.

Jul 26, 2026 - Quant Insider
Wondering if Quant Insider is legit? Get a transparent breakdown of our courses, team credentials, student outcomes, and policies — no hype, just facts.

Jun 09, 2026 - Tribhuven Bisen
A low skew percentile is not a buy signal. In efficient markets, low implied skew often reflects expectations for low realized skew, and the missing context is usually flow, carry, and why the surface is shaped that way.

May 02, 2026 - Tribhuven Bisen
A practical accounting of what we give up when we cap, threshold, or smooth momentum signals: skewness is the tax we pay for trend insurance.

Apr 22, 2026 - Tribhuven Bisen
From Signal to Simulation to Deployment

Apr 22, 2026 - Tribhuven Bisen
Vector-based backtesting is fast but simplified, while event-based backtesting is slower but more realistic, with the choice depending on strategy complexity and time horizon.

Apr 22, 2026 - Tribhuven Bisen
From Signal to Simulation to Deployment

Apr 22, 2026 - Tribhuven Bisen
A Comprehensive Framework for Alpha Aggregation

Apr 22, 2026 - Tribhuven Bisen
The blog explains how to compute and use Gamma and higher-order Greeks to manage hedging, volatility sensitivity, and risk dynamically in options trading.

Apr 22, 2026 - Tribhuven Bisen
Volatility skew and the smile reflect the market pricing in asymmetric, fat-tailed risks—capturing crash fears and rare upside events rather than a simple lognormal distribution.

Apr 22, 2026 - Tribhuven Bisen
B-Booking, Last-Look Delays, and the Trust Problem in Crypto Venues

Apr 21, 2026 - Tribhuven Bisen
Dispersion trading only generates real P&L when you move beyond the clean academic framework and account for the execution costs, funding drag, gamma mismatches, and flow asymmetries that define the dirty, real-world version of the trade.

Apr 21, 2026 - Tribhuven Bisen
In high-frequency trading, the biggest performance gains come from optimizing how software interacts with hardware (CPU, memory, networking) rather than improving trading models.

Apr 20, 2026 - Tribhuven Bisen
Most desks talk about “PnL attribution”, But very few stop to ask: what kind of attribution are we really doing?

Apr 20, 2026 - Tribhuven Bisen and Shubham Pandey
We analyze causal relationships among major cryptocurrencies using the Toda–Yamamoto method and show that once multiple-testing corrections (FDR) are applied, apparent strong and persistent market leadership—especially by Bitcoin—largely disappears, revealing only weak and intermittent connections.

Apr 20, 2026 - Tribhuven Bisen
A random walk drifts without a restoring force, while a mean-reverting process pulls back toward a central level, making stationarity crucial for applying standard statistical models.

Apr 17, 2026 - Tribhuven Bisen
This article explains that hyperparameters in trading systems are actually risk decisions that define how a strategy reacts to market changes and failures.