Research · Blog

The blog.

Research summaries and the first notes on AI agents in finance — 29 posts from the people behind OpenEXA and the researchers they work with.

02Financial markets research16 posts · 2020–2022

Financial markets research.

Summaries of peer-reviewed research in computational finance: ETF price dynamics and drawdown risk, optimal execution, futures portfolios, sparse mean-reverting portfolios and multiscale signal processing.

More on financial markets research
Sep 1, 2022Tim Leung, Ph.D.

Multiscale Analysis & Volatility Asymmetry of Cryptocurrency Prices

Adaptive complementary ensemble empirical mode decomposition (ACE-EMD) for non-stationary time series

3 min read
Jun 11, 2022Tim Leung, Ph.D.

Leveraged ETFs - Price Dynamics and Options Valuation

The ETF industry now consists of more than 2,000 funds with well over $4 trillion in assets.

3 min read
May 17, 2022Tim Leung, Ph.D.

Modern Trends in Financial Engineering

Modern Trends in Financial Engineering, publishes monographs on important contemporary topics in theory and practice of Financial Engineering.

3 min read
Apr 24, 2022Tim Leung, Ph.D.

Examining the Drawdown Risk of Sector ETFs - 2022

A drawdown measures the distance (in %) of the portfolio value from its peak, reflecting its downside risk.

3 min read
Apr 22, 2022Tim Leung, Ph.D.

Optimal Execution for High Frequency Trading

In high-frequency trading, large buy (or sell) orders may cause other traders to raise (or lower) their offered price.

4 min read
Mar 13, 2022Tim Leung, Ph.D.

Stochastic Storage Cost Model for Grains Futures

The world is experiencing the biggest supply shock to global grains markets in recent history. Prices of various crops have skyrocketed.

6 min read
Feb 9, 2022Tim Leung, Ph.D.

Dynamic Estimation of Stochastic Gold Exposure

Gold is often viewed as a safe haven asset or a hedge against market turmoil, currency depreciation, and other economic or political events.

4 min read
Nov 3, 2021Tim Leung, Ph.D.

Encoding Market View via a Randomized Brownian Bridge

Trading decisions often depend on the trader's subjective belief of the distribution of the asset price on a given future date.

1 min read
Oct 19, 2021Tim Leung, Ph.D.

Multiscale Decomposition and Analysis of Sector ETF Price Dynamics

Asset prices are driven by factors of different timescales, ranging from long-term market regimes to short-term fluctuations.

5 min read
Aug 24, 2021Tim Leung, Ph.D.

Dynamic Futures Portfolio in a Regime-Switching Market

Asset prices are often seen as being dependent on market conditions. Market regimes may change suddenly and persist for a period of time.

3 min read
Aug 16, 2021Tim Leung, Ph.D.

Dynamic Futures Portfolio Under a Multifactor Gaussian Framework

Futures are standardized exchange-traded bilateral contracts of agreement to buy or sell an asset at a pre-determined price at a time in future.

2 min read
May 8, 2021Tim Leung, Ph.D.

Multiscale Financial Signal Processing

Market observations and empirical studies have shown that asset prices are often driven by multiscale factors in the short term.

5 min read
Feb 7, 2021Tim Leung, Ph.D.

Cardinality-Constrained Portfolios: Optimization Approach & Algorithm

Every portfolio can be partitioned into multiple asset groups defined by asset classes, sectors, styles, and other features.

4 min read
Nov 14, 2020Tim Leung, Ph.D.

Employee Stock Options - Exercise Timing, Hedging, and Valuation

Book Title: Employee Stock Options Exercise Timing, Hedging, and Valuation

2 min read
Oct 21, 2020Tim Leung, Ph.D.

An Optimization Algorithm for Sparse Mean-Reverting Portfolio Selection

We study an approach that combines statistical learning and optimization to construct portfolios.

5 min read
Oct 8, 2020Tim Leung, Ph.D.

The Drawdown Risk and Portfolio Concentration of Sector ETFs

A drawdown measures the distance (in %) of the portfolio value from its peak, reflecting its downside risk.

3 min read
03Market structure & economics8 posts · 2008–2023

Market structure & economics.

Summaries of academic research on how financial markets shape real decisions — information, contracting, credit, automation and the labour share.

Research

The thinking behind the swarm.

Two research notes and an eight-part series on why high-stakes work should be run by thousands of narrow agents behind one deterministic boundary.