quant-finance

Building a Polymarket TWAP-Aware Trading Engine A trading engine can predict the underlying asset correctly and still lose the trade. That sounds obvious in traditional markets. It is less obvious in short-duration prediction markets, where traders often treat the latest external price as if it were the same thing as the market's settlement value. It isn't—when the settlement mechanism depends on…

Instead of maintaining separate endpoints for each data type, use /api/v1/universal-query to access all our financial data from one place. Query parameters give you direct control over the response payload. You can select the dataset, request specific fields, and apply multiple filters – keeping payload sizes small and your integration clean. eq, gt, in) per query.https://financialdata.net/api/v1…

Hi, Which indicator actually tells you what bitcoin does next month? I tested 17 of them. On the last day of every month since September 2015 I read one indicator. If it said trend was up, my test held bitcoin for that month. If it said down, my test held cash. Then I measured what happened. That is 132 months, run 17 times over. The best rule turned $10,000 into $4,742,074. The worst turned the …

Edward O. Thorp is one of those people who really should be better known. His Wikipedia entry describes him as ‘an American mathematics professor, author, hedge fund manager, and blackjack researcher’ before elaborating that he ‘… pioneered the modern applications of probability theory, including the harnessing of very small correlations for reliable financial gain.’ In fact Thorp’s life has been…

Five years ago this month, a quantum company rang the opening bell on a US exchange for the first time. That company was Arqit, a British quantum encryption firm briefly valued at close to $3 billion, now valued considerably less. Seven pure-play quantum computing companies have followed it onto American markets since, and between them they have produced a five-year record that deserves closer in…

Quant strategies group instruments for portfolio construction, risk aggregation, statistical arbitrage, and trade surveillance, but incorrect groupings can obscure risk and fail under stress. AdaptGrow, a GPU-accelerated matrix factorization algorithm, turns correlation and tail-dependence matrices into clusters and factor loadings at single-GPU and multi-node scale.

Risk management advisors are playing an increasingly important role in helping organisations establish and manage captive insurance structures that provide greater control over risk financing, improve resilience and support strategic risk management objectives. The evolving role of captive advisors goes Read More ... The post Risk Management Advisors: Driving Innovation and Impact in Captive Mana…

I've often seen 2-3 different ways factor models are constructed, but I don't understand when do you use one approach, the benefits. I do have some intuition but really looking for some industry context here Long-Short portfolio based on some ranking : Eg. Take P/B ratio sort all stocks and then create a ranking, go long the top quantile and short the bottom. You've a value factor portfolio. Do s…

QuFi Network anticipates a shift toward new verification infrastructure for blockchains, institutions, and tokenized assets—critical for a secure digital asset economy.

The integration of artificial intelligence into algorithmic trading has ignited a race to transform generative text into systematic alpha. A new paper written by Steven Edwards empirically investigates whether constructing a synthetic consensus using large language models can simulate information aggregation dynamics or if it merely acts as a sophisticated echo chamber. By utilizing an expansive …

Given a series of closed trade profits and loses, a quality measure that could be applied is Sortino Ratio multiplied by the square root of N (N being the number of trades). However, according to an online AI chatbot, the N value should be adjusted to account for the trade returns not being i.i.d, i.e. autocorrelated. Is this actually true, and if so, what is the formula for making this adjustmen…

Most BFSI institutions run risk training every year, yet many struggle to answer a simple question, is this training actually closing the capability gaps that matter most to the institution right now. Training calendars are often built around what was Read More ... The post How BFSI Institutions Can Conduct a Risk Training Needs Assessment first appeared on Risk Management Association of India .

Inside the $1 trillion repo market: SOFR transition, 56-to-1 Treasury basis trades, Fed standing facilities, and the 2019 and 2020 liquidity crises. 📊 Deep Research 🎥 Watch Video: https://youtu.be/D28mk_bOO4c Topics: quantitative finance, investment analysis, financial education, financial research, market analysis

This paper focuses on developing and analyzing two novel implicit temporal discretization methods for the stochastic semilinear wave equations with multiplicative noise. The proposed methods are natural extensions of well-known time discrete schemes for deterministic wave equations; hence, they are easy to implement. It is proven that both methods are energy-stable. Moreover, the first method is …

I'm working with Kraken historical ETH-USD trade data from 2017 onward, which includes: Timestamp (Datetime) Trade ID Trade price Trade volume Taker side (buy/sell) Order type (market or marketable limit) My goal is to derive a fair (efficient) price series that's minimally affected by bid-ask bounce with the goal being to use it for execution backtesting and modeling/analysis. I am okay with dow…

From my reading I understand that: The Bitcoin Pi Cycle top indicator signals a top when: 111 day Simple Moving average > 350 day Simple Moving Average * 2 The Bitcoin Pi Cycle bottom indicator signals a bottom when: 150 day Exponential Moving Average <= .745 * 471 day Simple Moving Average The Bitcoin Pi Cycle bottom indicator then indicates the end of the bottoming zone when: 150 day Exponentia…

Every backtest has to answer a boring question: when the strategy says "buy," what price does it actually get? Most backtesting frameworks answer this question badly by default, and the badness is almost always in the strategy's favor. Here are the four assumptions that do the most damage, roughly in order of how often they show up. Mid-price fills If your backtest fills orders at the midpoint of…