Boeing Professor of Applied Math & Director of the Computational Finance & Risk Management (CFRM) Program at UW; Senior Research Advisor.

Empirical mode decomposition and Hilbert spectral analysis

“Everything is Energy” — Photo by Darius Bashar on Unsplash

Market observations and empirical studies have shown that asset prices are often driven by multiscale factors, ranging from long-term economic cycles to rapid fluctuations in the short term. This suggests that financial time series are potentially embedded with different timescales.

On the other hand, nonstationary and behaviors and nonlinear dynamics…

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Asset prices are driven by factors of different timescales, ranging from long-term market regimes to short-term fluctuations, and they often exhibit nonstationary behaviors, such as time-varying volatility and trends.

The empirical mode decomposition (EMD) is designed for analyzing nonstationary time series. This adaptive data-driven method decomposes any time series into…

Algo Trading

Real examples, performance summary, and python package

A powerful pair, ready to pounce. Photo by Geran de Klerk on Unsplash.

Pairs trading is among the most popular trading strategies in many markets, ranging from equities and ETFs to currencies and futures markets. It involves taking simultaneous positions in two correlated assets. The idea is that while typically it is difficult to accurately capture the price evolution of a single asset…

Algo Trading

From portfolio construction to optimal execution

A Deep Dive into Pairs Trading. Photo by NOAA on Unsplash

In this new python package called Machine Learning Financial Laboratory (mlfinlab) developed by Hudson & Thames, there is a module that automatically solves for the optimal trading strategies (entry & exit price thresholds) when the underlying assets/portfolios have mean-reverting price dynamics.

It covers a few mean-reverting models, including the Ornstein-Uhlenbeck…

Stochastic model, simulation, and trading strategy

Roosevelt Lake Bridge, AZ. Photo by Tom Gainor on Unsplash

Trading decisions often depend on the trader’s subjective belief of the distribution of the asset price on a given future date. For example, if a trader anticipates a big price movement for a company stock after its earnings announcement, then perhaps a long straddle position makes sense. …

Playa de la Misericordia, Spain. Photo by Quino Al on Unsplash

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. The unpredictability of the timing of regime changes also means that associated risks are almost impossible to hedge.

In order to capture these crucial properties of market…

Mt. Rainier glowing on a summer evening. Photo by Caleb Riston on Unsplash

Futures are standardized exchange-traded bilateral contracts of agreement to buy or sell an asset at a pre-determined price at a pre-specified time in the future. At the Chicago Mercantile Exchange (CME), futures trading volume averages over 15 million contracts per day.

Managed futures portfolios play an integral role in hedge…

Useful information & links

Space needle and Mt. Rainier in Seattle, Washington.

The Master of Science in Computational Finance and Risk Management (MS-CFRM), housed within the Applied Math Department at University of Washington — Seattle, addresses the demand in the financial services profession for advanced quantitative and computational finance skills, and next generation risk management competencies.

For students and current professionals with…

Tim Leung, Ph.D.

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