Portfolio Risk Management Strategies : Hedging and Quantitative Approaches with Python

The current global pandemic situation highly affected the stability of the economic environment and the financial markets. The volatility increase represented both opportunities and threats for investors, allowing speculators to largely increase their profits. On the other hand, the possibility of incurring large losses largely raised: it is then necessary to purchase insurances to reduce the exposure to price fluctuations. This insurance is represented by a practice known as “hedging”. The objective of the thesis is to analyze some of the different aspects of financial risk, and how it can be evaluated and measured through some indicators. After the risk has been recognized, it can be hedged through the performance of transactions that can partially or totally cover the possible losses. The instruments that can be used are several, and, in particular, the analysis will be focused on the use of financial derivatives, such as forward, futures, options, and swaps. Their function is to state the condition of the trades before they occur, trying to reduce the negative impact of the assets’ performance on investors’ portfolios. The results of the research are summed up in some strategies put in action in the last chapter: the first one shows that a strategic asset picking, and respective weight allocation, may help in reducing total portfolio sensitiveness to financial risk, while the second one will be an example on how derivatives can be used to hedge a real situation. Some strategies have been built with a quantitative approach, using Python programming language as a supportive tool.