Trading for Bailouts Staff Working Paper 2020-23 Toni Ahnert, Caio Machado, Ana Elisa Pereira In times of high uncertainty, governments often implement interventions such as bailouts to financial institutions. To use public resources efficiently and to avoid major spillovers to the rest of the economy, policy-makers try to identify which institutions should receive assistance. Content Type(s): Staff research, Staff working papers Topic(s): Financial institutions, Financial markets, Financial system regulation and policies, Lender of last resort JEL Code(s): D, D8, D83, G, G1, G12, G14, G18
Dynamic Competition in Negotiated Price Markets Staff Working Paper 2020-22 Jason Allen, Shaoteng Li Repeated interactions between borrowers and lenders create the possibility of dynamic pricing: lenders compete aggressively with low prices to attract new borrowers and then raise their prices once borrowers have made a commitment. We find such pricing patterns in the Canadian mortgage market. Content Type(s): Staff research, Staff working papers Topic(s): Financial institutions, Financial services, Market structure and pricing JEL Code(s): D, D4, G, G2, G21, L, L2
Classical Decomposition of Markowitz Portfolio Selection Staff Working Paper 2020-21 Christopher Demone, Olivia Di Matteo, Barbara Collignon In this study, we enhance Markowitz portfolio selection with graph theory for the analysis of two portfolios composed of either EU or US assets. Using a threshold-based decomposition of their respective covariance matrices, we perturb the level of risk in each portfolio and build the corresponding sets of graphs. Content Type(s): Staff research, Staff working papers Topic(s): Central bank research JEL Code(s): C, C0, C02
Trading on Long-term Information Staff Working Paper 2020-20 Corey Garriott, Ryan Riordan Investors who trade based on good research are said to be the backbone of stock markets: They conduct research to discover the value of stocks and, through their trading, guide financial prices to reflect true value. What can make their job difficult is that high-speed, short-term traders could use machine learning and other technologies to infer when informed investors are trading. Content Type(s): Staff research, Staff working papers Topic(s): Financial institutions, Financial markets, Market structure and pricing JEL Code(s): G, G1, G14, G2, G20, L, L1