portfolio-theory

A new study presents a neural-network method for building efficient portfolios while keeping the allocation process interpretable. Instead of treating asset correlations as a black box, the model learns how to clean noisy collective market patterns and respects the symmetries of covariance matrices.

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The first step in the Black-Litterman method is to find the "implied market returns" (the prior). Usually this is calculated as: $\Pi = \lambda \Sigma w$ , where $\Pi$ is the vector of returns "implied by the market", $w$ is the vector of market weights (each element = security market cap / total market cap), $\Sigma$ is the covariance matrix, $\lambda$ is the market risk aversion (a constant). I…

Cover's universal portfolio maximizes the wealth growth rate Markowitz's mean-variance model minimizes portfolio variance Both allocate assets based on historical returns. How do these two models perform against one another (assuming for Markowitz we use the global minimum variance portfolio by default). How does the universal portfolio compare against the equally-weighted portfolio that is known…

i'm facing a new and interesting task: We are calculating a time series of (hypothetical) behavioral portfolios, for which i need a few parameters to calculate the portfolio's weights in each asset. I'm using an observed portfolio as starting point, from which i need to extract the implied utility parameters (in the case at hand the CPT utility as seen in my screeenshot). My idea is to find the p…

Abstract The paper re-examines the principle of the bird-in-hand under the dynamic situation in the emerging spots market in Pakistan. Our sample consisted of 100 KSE—100 companies dating 2009–2024. The abnormal returns are separated out using an event study model and a rolling window version of the CAPM, and we have constructed a new Dividend Announcement Factor (DAF) to capture systematic varia…

Our study explores a weekly-rebalanced dual-momentum-based Global Tactical Asset Allocation (GTAA) strategy applied to a diversified set of ETFs. The strategy selects assets based on relative momentum and applies an absolute momentum filter to avoid declining investments. Ultimately, a single combined strategy was created by merging two sub-strategies, incorporating both shorter- and longer-term …

This study examines and analyzes the effect of the capital adequacy ratio and loan-to-deposit ratio on return on assets in the context of green banking, specifically for banking companies listed on the Indonesia Stock Exchange (IDX) during the 2022-2024 period. This study aims to provide empirical evidence on how financial performance indicators, particularly the capital adequacy ratio and liquid…

A pair of stock that I have been trading has a negative cointegration coefficient (Beta) that is statistically significant. When i want to long a spread, according to the spread equation below, I should long both stockA and stockB (vice versa for short spread). This pair has strong positive correlations that is statistically significant as well. The spread is stationary and hurst exponent is < 0.…

From your first backtest to a real trading system, here are GitHub repos that can seriously level up your quant trading skills fast.

For U.S. equities, fixed income, and commodities, reconstructing long-term historical datasets is relatively straightforward, and we have already explored these challenges in several previous studies, including 100 Years of Multi-Asset Trend Following, Extending Historical Daily Bond Data to 100 Years, and Extending Historical Daily Commodities Data to 100 Years. Moreover, the broader methodology…

I am a mathematician. What's the go-to reference for a proper math-based introduction to martingale theory and arbitrage pricing? The books I am being referred to deal mostly either with the discrete case, or, if its continuous, then it does not contain all the proofs and there's a lot of hand-waving (for example, Bjork's Arbitrage theory in Continuous time, which does not even contain proper pro…

I would like to model different type of investors, hence I need to find some kind of utility functions to optimize. Apart from very abstract exponential utility function, I couldn't find any proper one. Frankly speaking, I would like to find some kind of more realistic criteria rather than type of abstract utility function. For example, for risk-neutral investor I have two questions: 1)Is it poss…

August Marčan has joined Citadel as a long/short equity associate. Based in London, he specialises in international financials equities. Hedge fund Citadel reported US$65 billion in assets under management in [&#8230;]

Elgin Chau has joined CIBC as an associate quantitative portfolio manager. CIBC reported CAD 3.1 billion in net income over Q1 2026, up 43% year-on-year (YoY). Its capital markets division [&#8230;]

Paul Adams has been promoted to head of portfolio management in Downing’s liquid alternatives business. He is based in London. Downing’s liquid alternatives group, led by Russell Catley, is a [&#8230;]

Jonathan Mortenson has joined Clear Street as director of outsourced trading, based in New Jersey. Clear Street, a mid sized agency broker that offers outsourced trading services, reported US$1 billion [&#8230;]