This paper presents a backtesting framework for a probability of default (PD) model, assuming that the latter is calibrated to both point-in-time (PIT) and through-the-cycle (TTC) levels. We claim ...

Abstract: In portfolio theory, the investment portfolio optimization problem is one of those problems whose complexity grows exponentially with the number of assets. By backtesting classical and ...

This framework is designed for developing high-frequency trading and market-making strategies. It focuses on accounting for both feed and order latencies, as well as the order queue position for order ...

The Basel Accords require financial institutions to regularly validate their loss given default (LGD) models. This is crucial so banks are not misestimating the minimum required capital to protect ...

About A high frequency trading and market making backtesting and trading bot in Python and Rust, which accounts for limit orders, queue positions, and latencies, utilizing full tick data for trades ...

Portfolio Backtesting is a strategy used by investors and traders to backtest how a portfolio would have performed if they have invested in a few specific assets during a defined time frame. The ...

Backtesting is an essential part of the trading and investment process as it reveals how a strategy would perform under real-market conditions. It enables traders and analysts to assess, through ...