Real examples, performance summary, and python package — 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…

From portfolio construction to optimal execution — 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…

Adaptive complementary ensemble empirical mode decomposition (ACE-EMD) for non-stationary time series — Empirical studies and market observations suggest that asset prices are driven by multiscale factors, ranging from long-term market regimes to rapid fluctuations. Embedded with different timescales, many financial time series often exhibit nonstationary behaviors with trends and time-varying volatilities. …

Futures are standardized bilateral contracts of agreement to buy or sell an asset at a pre-determined price at a pre-specified time in the future. In the futures market, it is commonly observed that the futures prices may deviate from the spot price of the underlying asset. …

Full Book — Free Download — The ETF industry now consists of more than 2,000 funds with well over $4 trillion in assets. Within the ETF universe, some funds are designed to replicate a constant multiple (called leverage ratio) of the daily returns of a reference index. …

A drawdown measures the distance (in %) of the portfolio value from its peak, reflecting its downside risk. If a portfolio had previously reached a peak of $100 and subsequently dropped to $90, then the portfolio experienced a 10% drawdown. We examine the drawdown risk sector by sector through a…

Order types, price impact, and fill uncertainty — In high-frequency trading, large buy (or sell) orders may cause other traders to raise (or lower) their offered price. This additional implementation cost due to short-term liquidity demand is often called market impact. Practitioners commonly view this as a significant cost to track, avoid, or minimize. This can be done…

This new book series, Modern Trends in Financial Engineering, publishes monographs on important contemporary topics in theory and practice of Financial Engineering. The series’ objective is to provide cutting-edge mathematical tools and practical financial insights for both academics and professionals in Financial Engineering. …

How storage cost affects the futures prices — The world is experiencing the biggest supply shock to global grains markets in recent history. Prices of various crops, including wheat, soy, and corn, have skyrocketed. Take wheat as an example, the futures prices have jumped to record high in March.