In this article, we show how to take into account skewness risk in portfolio allocation. Until recently, this issue has been seen as a purely statistical problem, since skewness corresponds to the third statistical moment of a probability distribution. However, in finance, the concept of...

In the last few years, the financial advisory industry has been impacted by the emergence of digitalization and robo-advisors. This phenomenon affects major financial services, including wealth management, employee savings plans, asset managers, private banks, pension funds, banking services,...

In this short note, we consider mean-variance optimized portfolios with transaction costs. We show that introducing quadratic transaction costs makes the optimization problem more difficult than using linear transaction costs. The reason lies in the specification of the budget constraint, which...

In this article, we consider a multi-period portfolio optimization problem, which is an extension of the single-period mean-variance model. We discuss several formulations of the objective function, constraints and coupling relationships. We then derive three numerical algorithms that can be...

It is impossible to analyze an asset taken in isolation, without taking into account the wider picture of the market. This fact is behind the extensive use of copulas or vector autoregressive models in finance, which allow to model dependencies between assets. In this paper, we look at the...

Since the last decade, financial technology (Fintech) has made a lot progresses in many angles of the finance industry from the novel concepts of the transaction to the systematic/intelligent management of financial products. Back to the 80s, the first attempts to combine applied mathematics,...

The objectives of this report are two-fold. We first studied some novel techniques in statistics and signal processing fields such as trend filtering, daily and high frequency volatility estimator or support vector machine. We employed these techniques to extract interesting financial signals....

In this article, we discuss various implementation of L1 filtering in order to detect some properties of noisy signals. This filter consists of using a L1 penalty condition in order to obtain the filtered signal composed by a set of straight trends or steps. This penalty condition, which...