portfolio-optimization

Background I am trying to calculate the returns on a sequence of trades performed by an entity, where I do not know the starting capital. Therefore I assume a starting capital of zero. From these returns I want to calculate the Sharpe ratio of a portfolio on which these trades are performed. The initial idea of simply comparing successive portfolio values to calculate returns falls apart in this …

This video traces the evolution of portfolio construction from Markowitz's mean-variance framework to modern information-theoretic paradigms, exploring how entropy methods and the Entropy Pooling framework have transformed the way institutional investors build optimal portfolios. 🎥 Video Tutorial 🎥 Watch Video: https://youtu.be/gr4Z7fOsVk0 Topics: quantitative finance, investment analysis, fin…

The historical evolution from rigid mean-variance frameworks to flexible information-theoretic paradigms. Explore the deep intuition of the Entropy Pooling framework and its mapping to the classical Black-Litterman model. 📊 Deep Research Topics: quantitative finance, investment analysis, financial education, financial research, market analysis

I am currently developping/finalizing a multi-platform quantitative trading dashboard designed for real-time performance monitoring and risk management across MetaTrader, Interactive Brokers (TWS), and NinjaTrader. The system aggregates live trading data and computes: Real-time and rolling Sharpe ratio Dynamic risk/reward and expectancy metrics Risk of ruin estimation based on live equity curves …

This is a summary of links recently featured on Quantocracy as of Saturday, 06/06/2026. To see our most recent links, visit the Quant Mashup. Read on readers! The crossword puzzle of fitting – why across and then down? [Investment Idiocy] This will be the first in a series of posts about portfolio optimisation. Main reason […] The post Recent Quant Links from Quantocracy as of 06/06/2026 appeared…

Published on June 6, 2026 6:37 PM GMT I used an LLM to help review this post and it likely contains some AI-generated re-formulations. The ideas are not fundametally new and inspired by Nassim Taleb and trading lore. In effective giving, it makes sense to be close to risk-neutral and focus on high expected utility per dollar. However, in practice, organisations and people are risk-averse for good…

This video breaks down the architecture of quantitative factor models — from the mathematical bridge between risk management and alpha generation to the distinction between systematic beta exposure and true alpha in ML-driven trading. 🎥 Video Tutorial 🎥 Watch Video: https://youtu.be/3FS6Yqd-zDU Topics: quantitative finance, investment analysis, financial education, financial education video, t…

I am trying to prepare to exit academia and transition into quantitative finance from a statistical physics background (after spending 6 years as a postdoctoral researcher). My experience covers heavy ...

I am currently working on a couple of finance research papers at master’s level, based on my thesis work. I have already uploaded similar work on SSRN, and I am now trying to publish and share my work more broadly. I am also exploring arXiv as a potential platform, but I am currently facing difficulties with the endorsement process and finding an endorser within the network. Would anyone here be …

Quantitative investors usually start their research by analyzing individual trading strategies. They compare performance, risk, implementation complexity, market exposure, and the economic intuition behind each anomaly. However, once historical equity curves of individual strategies are available, a different research question becomes possible. Instead of asking only which individual strategy loo…

The firm is launching a suite of equity index futures based on Bloomberg equity indices.

In our previous article, we peeled back the curtain on how we built VTrade’s high-fidelity market execution engine to simulate real-world slippage and order-book friction. But calculating a precise execution price is only half the battle. Once those orders clear, you hit the ultimate state-tracking nightmare: Portfolio Intelligence . On VecTrade.io , users expect to see their Total Portfolio Valu…

In This Article YMYL Classification and What It Means Building E-E-A-T Signals Structured Data Schema Implementation Core Web Vitals for Financial Sites Topic Cluster Architecture Internal Linking and Canonical Tags YMYL Classification and What It Means Google classifies content in financial services as YMYL — "Your Money or Your Life" — a category that receives heightened scrutiny from quality r…

Hi all, As the title says, as prospective students should be making their decisions, I would like to use this platform to interact with students who might be interested in the career path. Who Am I: I’m a senior quantitative researcher working in systematic equities. I’m what some might call a “full-stack” quant leading a team on the entire pipeline from data exploration to generating the trades …

First, there are a few things I'm not clear about, like what the 'risk free' return is.. is there even such a thing in trading? or how to handle inactive days, etc. Let's assume I have a period of 30 days. During these 30 days, I have 5 trades with their duration: +5%, 2 days -3%, 5 days +1%, 3 days +2%, 1 day -2%, 3 days I have 16 days where there is no activity. How would I calculate the Sharpe…

Classic balanced investing has long centered on the 60/40 portfolio: 60% stocks for growth and 40% bonds for stability. That […]

ETFGI, reported that assets invested in the actively managed ETFs listed globally reached a new record of US$2.33 trillion at the end of April. During April the actively managed ETFs industry globally gathered net inflows of US$67.02 billion, bringing year-to-date net inflows to a record US$311.66 billion, according to ETFGI’s April 2026 Active ETF and ETP industry landscape insights report, an a…

Goldman lost US$960 million on three days during the first quarter, followed by Bank of America with $376 million and JP Morgan with US$182 million on two days apiece, and […]

There is a well known approach to annualize volatility of log-returns for a given frequency. Let $P(t)$ a price process and define a log return $r_l(t)$ as $$r_l(t) = \ln \left( \frac{P(t)}{P(t-1)} \right).$$ An aggregate return over $n$ periods is $$ \begin{equation} \begin{aligned} r_l^A(t) &= \ln \left( \frac{P(t)}{P(t-n)} \right) \\ &= \sum_{t-n+1}^t r_l(i). \end{aligned} \end{equati…

It is my understanding that one can use both excess returns and price returns to compute a beta coefficient. In the former way, beta would be interpreted in the standard way (a 1 unit change in market excess returns is associated with a beta unit change in share excess returns). In the latter way, you have the same interpretation but only considering the actual returns of the market and the share…