Financial engineering in the context of "Princeton University School of Engineering and Applied Science"

The Lebanese liquidity crisis is an ongoing financial crisis affecting Lebanon, that became fully apparent in August 2019, and was further exacerbated by the COVID-19 pandemic in Lebanon (which began in February 2020), the 2020 Beirut port explosion and the Russian invasion of Ukraine. The country experienced liquidity shortages in the years prior to 2019 but the full extent of the fragility of the economy was concealed through financial engineering by the governor of the central bank. Lebanon's crisis was worsened by sanctions targeting Syria's former government and Iran-backed Hezbollah, which intensified under Donald Trump.

The currency was devalued by over 98% between January 2023 and March 2024, with an annual inflation rate of 221.3% in 2023. Public services have collapsed; without using a private generator, households can expect only an hour or so of power a day. Shortages of drinking water have contributed to disease outbreaks, including the first cholera cases in decades. Parents are sending their children to orphanages because they cannot feed them. A growing number of citizens have resorted to armed robbery as the only way to extract their own deposits (now vastly reduced in real terms) from banks when they desperately need to pay for basic services such as healthcare. The collapse of Lebanon, formerly known as the "Paris of the Middle East", has been described by Western media as one of the most devastating and worst financial recessions since at least the 19th century.

Mathematical finance, also known as quantitative finance and financial mathematics, is a field of applied mathematics, concerned with mathematical modeling in the financial field.

In general, there exist two separate branches of finance that require advanced quantitative techniques: derivatives pricing on the one hand, and risk and portfolio management on the other.Mathematical finance overlaps heavily with the fields of computational finance and financial engineering. The latter focuses on applications and modeling, often with the help of stochastic asset models, while the former focuses, in addition to analysis, on building tools of implementation for the models. Also related is quantitative investing, which relies on statistical and numerical models (and lately machine learning) as opposed to traditional fundamental analysis when managing portfolios.