# Using the Hurst Exponent and Stock Comovements for Pairs Trading

Pairs trading, or statistical arbitrage, is an effective market-neutral trading strategy. Usually fundamental or quantitative analysis is used in order to determine which pairs are suitable for trading. We have previously discussed several pairs selection methods based on quantitative measures such as stock cointegration, correlation, pair distances, etc. Reference  …

# How Options Imbalances Affect Price Dynamics

As discussed several times, markets can be loosely divided into two regimes: trending, and mean-reverting. The majority of trading literature has been devoted to exploiting these market characteristics. Less attention, however, is paid to the explanation of their existence. They are often attributed to investors’ over-, underreaction and/or market inefficiencies. …

# Predicting Firm Profit Using Machine Learning Techniques

In a previous post, we presented an article on using an econometric model for predicting the P/E ratio. In this post, we will discuss a different approach for predicting a firm’s financials. Reference utilized the Gradient boosting method for predicting a firm’s profitability. Gradient boosting is a method that …

# Long-Run Variances of Trending and Mean-Reverting Assets

Trading strategies are often loosely divided into two categories: trend-following and mean-reverting. They’re designed to exploit the mean-reverting or trending properties of asset prices. These properties are often investigated through time series techniques or Hurst exponent. Reference provided, however, a different perspective and approach for studying the mean-reverting and …

# Using the Gaussian Mixture Models to Identify Market Regimes

Characterizing the market is an important step in trading system development. Currently, there exist a couple of approaches for identifying market regimes such as using trend and/or volatility filters, machine learning techniques, etc. Reference proposed an approach that uses the Gaussian Mixture Models to identify market regimes by dividing …

# Factor Investing Through Principal Component Analysis

Factor investing is a well-known investment strategy used mostly by quant funds. Even though the factors are well published, it’s important to distinguish 2 types of factors: Explicit factors: these are for example momentum, value, size, quality, etc. Implicit factors: these are statistical features determined by using e.g. maximum likelihood, …

# Using an Autoregressive Model to Predict the Price-to-Earnings Ratio and Develop an Investment Strategy

In a previous post, we highlighted an article that showed how useful accounting numbers are. In this post, we will present a concrete example of an application of accounting numbers in portfolio management. Reference showed that the Price-to-Earnings ratio is a mean-reverting process, and it can be accurately estimated …