How to estimate factor exposure, risk premia, and discount factors
The basic idea behind factor models is that a large range of assets’ returns can be explained by exposure to a small range of...
Classifying market regimes
Market regimes are clusters of persistent market conditions. They affect the relevance of investment factors and the success of trading strategies. The practical challenge...
Measuring the value-added of algorithmic trading strategies
Standard performance statistics are insufficient and potentially misleading for evaluating algorithmic trading strategies. Metrics based on prediction errors mistakenly assume that all errors matter...
Ten things investors should know about nowcasting
Nowcasting in financial markets is mainly about forecasting forthcoming data reports, particularly GDP releases. However, nowcasting models are more versatile and can be used...
Macro trends for trading models
Unlike market price trends, macroeconomic trends are hard to track in real-time. Conventional econometric models are immutable and not backtestable for algorithmic trading. That...
Machine learning for portfolio diversification
Dimension reduction methods of machine learning are suited for detecting latent factors of a broad set of asset prices. These factors can then be...
Statistical arbitrage risk premium
Any asset can use a portfolio of similar assets to hedge against its factor exposure. The factor residual risk of the hedged position is...
Classifying market states
Typically, we cannot predict a meaningful portion of daily or higher-frequency market returns. A more realistic approach is classifying the state of the market...
Real-time growth estimation with reinforcement learning
Survey data and asset prices can be combined to estimate high-frequency growth expectations. This is a specific form of nowcasting that implicitly captures all...
Nowcasting with MIDAS regressions
Nowcasting macro-financial indicators requires combining low-frequency and high-frequency time series. Mixed data sampling (MIDAS) regressions explain a low-frequency variable based on high-frequency variables and...