financial-econometrics

Financial institutions have spent years building AI: fraud models, credit models, recommendation engines and risk systems. While this sprawl of task-specific models has been effective, it’s also constrained by siloed systems.  Siloed systems prevent institutions from developing a unified understanding of consumers’ financial behavior. As enterprise datasets keep growing, so does the gap between w…

A comprehensive guide to Agent-to-Agent (A2A) protocols, solving fragmentation, and orchestrating autonomous AI in modern finance. Explore capability advertising, stateful collaboration, opacity architecture, and the broader protocol stack (MCP, ACP, AGP) powering the next generation of financial infrastructure. 📊 Deep Research Topics: quantitative finance, investment analysis, financial educat…

PurposeThis study investigates the impact of financial development on CO2 emissions in BRICS-T countries within the framework of the Environmental Kuznets Curve (EKC) hypothesis over the period 1990–2021.MethodsThe study employs panel quantile regression to examine heterogeneous effects across different emission levels. Robustness analyses were conducted using CUP-FM and CUP-BC estimators. In add…

This is a summary of links recently featured on Quantocracy as of Wednesday, 05/27/2026. To see our most recent links, visit the Quant Mashup. Read on readers! Quantpedia Awards 2026 Winners Announcement [Quantpedia] Welcome to the Quantpedia Awards 2026 winners announcement. For the third time, we are proud to celebrate excellence in quantitative research and […] The post Recent Quant Links from…

I've been modelling the relationship between government debt auction calendars and implied volatility surfaces in emerging market contexts — specifically whether φ (sovereign refinancing pressure) and λ (liquidity stress) create predictable, calendar-driven dislocations that standard models like Heston and Bates don't capture. The intuition: retail-dominated EM options markets systematically unde…

Using the following Python code I am setting USD LIBOR Swap quotes. I found that by default settlementdays uses whatever is associated with the Index (in C++: if (settlementDays_==Null<Natural>()) settlementDays_ = iborIndex->fixingDays(); ). If I wanted to explicitly set settlementDays = 0 , how can I do that? I tried just use settlementDays = 0 , but the code does not seem to like named argumen…

I was able to obtain some tick data on a particular asset and I wanted to calculate the daily realized variance of the asset. After browsing through a few threads here, it seems the formula to calculate daily realized variance is simply (assuming you have constant time intervals): Where R^2 is the squared log returns from the constant time interval t , with a total of m time intervals during the …

Intercontinental Exchange, Inc., one of the world’s leading providers of financial market technology and data powering global capital markets, and Ornn, a market leading compute company building financial markets for AI, announced plans to launch a suite of GPU compute futures contracts based on Ornn’s Compute Price Index (OCPI), which tracks live-traded spot prices for GPU compute across major h…

_Financial Retrieval and Risk Governance Forum_. 2026Financial retrieval-augmented generation (RAG) systems are increasingly used to summarize market events, explain portfolio exposures, answer policy questions, and support regulated advisory workflows. Standard retrieval pipelines optimize semantic relevance and latency, but financial decisions are shaped by asymmetric losses, tail events, priva…

Learn how financial data APIs power quant research pipelines, from data ingestion to scalable analysis using structured financial datasets.

A comprehensive deep research analysis of correlation as the most mathematically complex parameter in quantitative finance. Explores statistical foundations, portfolio diversification failures, realized vs. implied correlation, the Correlation Risk Premium, dispersion trading mechanics, correlation-sensitive derivatives, and advanced copula modeling frameworks. 📊 Deep Research Topics: quantitat…

A comprehensive quantitative analysis of Credit Default Swaps from bilateral insurance mechanics to advanced Greeks. Master hazard rates, the Credit Triangle, Big Bang standardization, CS01 risk sensitivities, and professional stress testing frameworks used by institutional credit desks. 📊 Deep Research Topics: quantitative finance, investment analysis, financial education, financial research, …

I am trying to implement a local volatility pricer using Monte Carlo and Dupire's equation in function of implied volatilities and I was told that first of all I have to check Dupire is well implemented so I was reccommended to prove it like this: -The first step, to check Dupire's function, was to get the local volatility surface from a flat implied volatility surface. As it is flat and we know …

The investment giant is seeking regulatory approval for two new tokenized funds.

A comprehensive guide to the Model Context Protocol (MCP) — the open standard transforming how LLMs integrate with quantitative finance systems. From algorithmic backtesting automation and massive dataset handling to stateful session memory, zero-trust security, and UX engineering for autonomous AI agents. 📊 Deep Research Topics: quantitative finance, investment analysis, financial education, f…

Explainable AI (XAI) in finance addresses a fundamental governance challenge: financial institutions deploy AI models that approve loans, flag fraud, price insurance, and recommend portfolios. However, many of those models cannot explain how they reach a decision. When models lack that capacity, they create risk exposure that cascades from model validation teams to the C-suite ... Read more » The…

I've been following an asset wherein a "R-squared predictive forecast (close, 14)" is posted online each day. On some days, this figure is extremely high, like .92. Exactly what is the significance of the "14?" Does it refer to the past 14 days? The next 14 days? Something else? How do I interpret the R-squared predictive forecast? For example, does it mean that 92% of the variance in the next da…

The Dubai-based platform's WES League gives 400-plus participants 45 days to trade on demo accounts, with the top five competing in a live final round. SageMaster's WES League competition scores participants on discipline and risk management over 45 days of simulated forex trading. SageMaster has opened a simulated forex trading competition with $25,000 in combined prize money, targeting people l…

I am reading the book "Trades, Quotes and Prices" by JEAN-PHILIPPE BOUCHAUD and have stuck in the very beginning with understanding the formula of variance of MM's gain per trade (see picture). How is this formula derived since it is not like a standard variance formula with expected value and mean in it? It is also strange to me that we literally calculate variance for a single variable. Would b…

- Bullish has entered into a definitive agreement to acquire Equiniti, a leading global transfer agent serving nearly 3,000 issuer clients, 15,000 total corporate clients, 20 million shareholders, and processing $500 billion in annual payments. - The combination creates the first fully integrated blockchain-enabled, blue-chip issuer services provider — unifying a regulated transfer agent with end…