A basic pairs trading strategy involves three main steps: (i) identification of assets, (ii) formation of spreads, and (iii) design of trading rules. Existing studies only analyze the performance of trading a single pair, rather than the aggregate performance of multiple pairs. There are several practical benefits of trading multiple…

Empirical mode decomposition and Hilbert spectral analysis — 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…

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…

Many individual and institutional investors are wary of large market drawdowns as they not only lead to portfolio losses and liquidity shocks but also indicate potential imminent recessions. As is well known, fund managers are typically compensated based on the fund’s outperformance over the last record maximum, or the high-water…

The standard no-arbitrage pricing model assumes that all option positions can be hedged perfectly by continuously trading the underlying asset. However, in many financial applications, the underlying is not liquidly traded; instead, the investor (option holder or writer) trades a correlated asset as a proxy to minimize risk exposure. Examples…

The popularity of ETFs has led to increased trading of options written on ETFs and leveraged ETFs (LETFs). Traded options have different strikes and expiration dates. For each expiration date, we can compare returns of LETF calls and puts with different strikes and leverage ratios. Option prices can be considered…

Empirical Analysis & Free Book — Leveraged ETFs (LETFs) are typically designed to replicate multiples of the daily returns of some underlying index or benchmark. For example, the ProShares Ultra S&P 500 (SSO) is supposed to approximately generate twice the daily returns of the S&P 500 index. Moreover, investors can take a bearish position on the…

One of the most common strategies in commodity trading is inter-commodity futures spread trading. Generally speaking, it is a class of strategies that takes advantage of the price differential between two (or more) related commodities. Here, we illustrate three examples of futures spread trading in three different sectors, namely, Energy…