The behaviour of time series data from financial markets is influenced by a rich mixture of
quantitative information from the dynamics of the system, captured in its past behaviour, and …

We propose a DC (Difference of two Convex functions) formulation approach for sparse
optimization problems having a cardinality or rank constraint. With the largest-k norm, an …

Index tracking is a popular passive portfolio management strategy that aims at constructing a
portfolio that replicates or tracks the performance of a financial index. The tracking error can …

Mean-variance portfolios have been criticized because of unsatisfying out-of-sample
performance and the presence of extreme and unstable asset weights, especially when the …

The yield curve is the centrepiece in bond markets, a massive asset class with an overall
size of USD 100 trillion that remains relatively under-investigated using machine learning …

Index funds aim to track the performance of a financial index, such as, eg, the Standard &
Poor's 500 index. Index funds have become popular because they offer attractive risk-return …

We consider the problem of minimizing a general continuously differentiable function over
symmetric sets under sparsity constraints. These type of problems are generally hard to …

When a portfolio consists of a large number of assets, it generally incorporates too many
small and illiquid positions and needs a large amount of rebalancing, which can involve …

Index tracking is a very popular passive investment strategy. Since an index cannot be
traded directly, index tracking refers to the process of creating a portfolio that approximates …

A fast method based on coordinate-wise descent algorithms is developed to solve portfolio
optimization problems in which asset weights are constrained by lq norms for 1≤ q≤ 2. The …