Micro-level transmission of monetary policy shocks: The trading book channel

Abstract

We open the black box of the monetary policy transmission mechanism with a granular model that considers the balance-sheet composition and network relationships of each economic agent. Though there are several well-documented channels through which monetary policy operates, we focus on the overlooked trading book channel, which arises because of adjustments in the accounting value of trading book exposures on banks’ balance sheets that have to be marked to market when interest rates change. Variations in banks’ net worth due these adjustments are used as input to a network model that incorporates the financial and corporate sectors. The framework permits us to determine the effects of interest rate changes on every bank and firm in the economy and any second-round (contagion) effects in the short run. We apply the model to a comprehensive database of Brazilian banks and firms from 2015 to 2020. We find that interest rate shocks affect more strongly financial stability in periods of monetary policy tightening. We also find notable asymmetric effects of positive and negative interest rate shocks in the Brazilian economy, with positive interest rate shocks affecting more financial stability. Finally, our results also suggest a non-linear relationship between interest rate changes and financial stability, reinforcing the need to mitigate monetary policy shocks through interest rate smoothing and adequate communication and transparency to society.

Interconnectivity disrupted by fading globalization: a network approach to recent international trade developments

“…There is substantial research in the literature employing complex networks to investigate subjects within the field of economics and finance. These studies encompass diverse topics such as stock returns during the Global Financial Crisis [12], volatility of stock prices [20], the interplay between COVID-19 and the stock market [21], the prediction of financial crises through machine learning techniques [22], the effects of monetary policy shocks [23], investment strategies in the global context [24], the connectedness of the global bank network [25], trust within banking networks [26], financial networks and banking efficiency [27], the relationship between firm network structure and innovation [28], the impact of migrant networks on FDI [29], and the estimation of vulnerability and the diffusion of impact [30].…”

The financial network channel of monetary policy transmission: an agent-based model

“…In Georg (2013) and Bluhm et al (2014), for instance, the central bank provides liquidity in the interbank market. Meanwhile, Silva et al (2020) estimate both direct and indirect impacts of monetary policy shocks (as measured by changes in the policy interest rate) on the economy by applying a multi-layer network model to a unique Brazilian data set.…”

Using Entropy to Evaluate the Impact of Monetary Policy Shocks on Financial Networks

“…In a different framework, using agent-based modeling, Riccetti et al [20] found a significant role for a financial accelerator that was founded on three dimensions: a leverage one, a stock market one, and a network one. We can also mention the study by Silva et al [21], who consider a granular approach that takes into consideration the network relationships between agents, along with the balance sheets compositions. The inclusion of network data allowed them to study contagion effects as well.…”