Consulting | Asset & Wealth Management | Services

Advanced Analytics & AI

Trading and portfolio management with AI and machine learning

Artificial Intelligence (AI) is revolutionizing asset and wealth management. We are industry leaders in implementing AI in technology in trading execution, portfolio construction, risk management and asset pricing by developing, integrating, and adapting our services to client needs.



Reinforcement learning for optimal execution

The implementation of an algorithmic trading wheel allows traders to determine the best possible trading venues, brokers and execution algorithms in the context of pre-trade (order routing) and post-trade analysis (performance and best execution).

Clustering and classification for post-trade analysis

We have extensive experience in transaction cost analysis and can build an infrastructure for evaluating execution outliers while benchmarking trader and strategy performance.

Deep learning for asset allocation

A fundamental challenge in asset allocation is to dynamically account for sophisticated constraints following investor preferences. At LPA, we address this challenge through neural networks, resulting in more robust diversification.

Hierarchical clustering for portfolio optimization

Our team has developed software and extensive knowhow on how to maximise the risk-return of an investment portfolio, while minimizing concentration risk and high turnover due to the instability problem in convex optimization.

Generative adversarial networks for tail risk estimation

The ability to accurately estimate market risk highly depends on the quality and amount of data used in the calibration of risk models. By using synthetic data generated through adversarial networks, we accomplish substantial improvements in tail risk estimation.

Support vector machines for credit risk assessments

We apply the latest techniques in supervised learning to credit risk and likelihood of default. Furthermore, we have developed a methodology to accurately aggregate different sources of risk, such as market risk, credit risk and liquidity risk.

Supervised and unsupervised learning for price forecasting

We use our background in quantitative trading to design and advice on investment strategies, where we apply advanced statistical analysis and machine learning to identify momentum and mean-reversion in the market.

Neural networks for risk neutral pricing

We combine our knowledge in financial derivatives and artificial intelligence to provide precise pricing of exotic derivatives, improving Monte Carlo estimates for pricing path-dependent options, basket options, and interest rate swaps, among others.


Sandro Schmid

Sandro Schmid

Partner, Switzerland


Software and advisory solutions for financial services.


Join our international and dynamic work culture in digitizing capital markets.


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