financial-econometrics

- 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…

I'm trying to model GARCH volatility on electricity prices. Typically the first step is to use prices to obtain log returns to make them stationary. I have encountered a small problem however: electricity prices can go negative. So returns defined as \begin{array}{cc} r_t:=\log(P_t / P_{t-1}) \end{array} will produce some undefined values. I have gotten around it by using differences \begin{array…

More than 80% of financial services firms are adopting AI to some level and 52% are already experimenting with agentic AI, but impact to date is on efficiency gains rather than business model transformation, says a new report by the Cambridge Centre for Alternative Finance that also highlights big AI risks as reinforced by Anthropic’s new Mythos model. The post Report finds uneven AI adoption in …

Most people searching for free stock data end up in the same loop. They find Yahoo Finance. The yfinance library seems perfect — until it breaks in production, returns inconsistent data, or silently changes its response format because it's scraping an unofficial endpoint. Then they try pandas-datareader. Then Alpha Vantage with a key that throttles after 5 requests per minute. Then a random GitHu…

As people increasingly rely on AI chatbots for guidance, even on financial matters, a healthy dose of skepticism is critical.

Do you mean this? Q: Figure 1 shows binned variance versus z. Why not just do a linear regression of variance versus z2 to estimate the quadratic coefficient? A: Q-variance is a statement about the conditional expectation function E[v(T)∣z], in other words the expected variance given a value of z. Ordinary least squares regression of v on z2 does not test this claim directly; rather, it estimates…

What Do Large Factor Models Learn? Self-Induced Regularization, Cost of Overfitting, and Self-Adaptivity Xiong, Xin This paper studies the out-of-sample performance of large, overparameterized linear factor models for stochastic discount factor (SDF) estimation. Motivated by recent advances in finance and machine learning, we analyze the all-inclusive ridge estimator that incorporates all candida…

I've only looked at the SP500 parquet data that's in the github repo.  And for that data I think there's persistent quadratic behavior... Have a look at these graphs.  I use 30 bins for clarity.  I think the constant term dominates the small <z^2> bins and the linear behavior of <V> ~ <z^2> is apparent in roughly the top 25% of <z^2>.  And that's true across the 3 epochs I chose to look at and th…

To answer the binning question, the q-variance equation doesn't say that v = sigma^2 + z^2/2, it says the expected value of v follows that form. The way it is derived is by looking at cases where z is near some value, say 0. So we are testing what it says on the can. One way to look at it is to e.g. set T=5 days and look at all the periods where z is near-zero. Then paste them together so you hav…

This video provides a quantitative walkthrough for calculating the Investment Clock — using FRED data to derive Growth and Inflation Z-scores that pinpoint the current macro regime phase for optimal asset allocation. 🎥 Video Tutorial 🎥 Watch Video: https://youtu.be/Zzi1cuaPs7M Topics: quantitative finance, investment analysis, financial education, financial education video, trading tutorial

Track the US economy's position in real-time using the Merrill Lynch Investment Clock framework. Powered by FRED data and AI evaluation, this live tool maps Growth and Inflation Z-scores to identify the current phase — Reflation, Recovery, Overheat, or Stagflation — and surfaces the optimal asset allocation and sector rotation for each regime. 📊 Deep Research Topics: quantitative finance, inves…

I understand this is quite a simple question, but I'd like to make it rigorous for myself because I've seen it in a few varied contexts and haven't completely gotten it somehow. I'm starting an academic project, so I need to make it concrete. I haven't found any papers which really describe this basic detail, any links would be appreciated. How do I get the units for realized variance? I.e. after…

I want to calculate VaR and CVaR using Monte Carlo simulation and by estimating volatility with the Heston model. Do the asset log-returns have to be normally distributed? Because I haven't found any references stating that log-returns must be normally distributed.

The acquisition indicates a capability that OpenAI is building into ChatGPT: financial planning.

This video decodes ESG investing frameworks — from MSCI ratings methodology to EU taxonomy compliance — examining whether ESG scores truly guide capital toward sustainable outcomes or obscure more than they reveal. 🎥 Video Tutorial 🎥 Watch Video: https://youtu.be/UWmWNufQdLg Topics: quantitative finance, investment analysis, financial education, financial education video, trading tutorial

The financial crisis of 2008 increased the call for standard setters and financial regulators to review the effectiveness of derivative regulation in improving financial reporting quality. Prior literature defines financial reporting quality as the extent to which financial statements provide information that is useful to investors and creditors in their investment decisions (Schipper, 2003; Schi…

This video unpacks the Dark Index (DIX) and the counterintuitive 'Short is Long' hypothesis, revealing how dark pool short volume signals institutional accumulation and how smart money positioning diverges from conventional market intuition. 🎥 Video Tutorial 🎥 Watch Video: https://youtu.be/f5yZ7wdjEOY Topics: quantitative finance, investment analysis, financial education, financial education v…

A comprehensive deep dive into the Dark Index (DIX) and the counterintuitive 'Short is Long' hypothesis. Master the quantitative architecture of dark pool liquidity, market maker rebates, and how institutional accumulation manifests as short volume in off-exchange trading. 📊 Deep Research Topics: quantitative finance, investment analysis, financial education, financial research, market analysis

Abstract This study evaluates the scholarly validity of the Narrquest framework (Chen, 2026) through the lenses of financial decision-making and control theory. While Chen claims that "Invalidity Conditions (ICs)" and "self-constraints" optimize problem definitions, we contend the framework suffers from a terminal category error. By analyzing the decoupling of technical optimization from narrativ…

An independent quant platform tackling one of finance's hardest problems — isolating genuine cross-industry supply chain signals from market noise using rigorous multi-factor validation, the Bullwhip Effect, and asymmetric information pricing frameworks. 📊 Deep Research Topics: quantitative finance, investment analysis, financial education, financial research, market analysis