Monetary Policy Shocks and Stock Market Liquidity#
Assessing the Impact of Monetary Policy Shocks on Stock Market Liquidity
Study Rationale and Objective#
In recent times, several countries, including South Korea, have started adjusting their monetary policy to deal with the mounting inflationary pressures in spite of concerns regarding economic downturns induced by supply chain disruptions and geopolitical challenges. The changes are mostly due to factors on the supply side, mandating a meticulous calibration of policies by the respective authorities. This measure ensures the effects of the monetary policy are as intended, and potential side effects are minimized.
Stock market liquidity can be viewed as a mirror of the economy, reflecting the anticipations of economic agents about real-world events. In turn, these expectations may influence the economy itself. Indeed, historical data supports this notion, indicating that stock market liquidity can predict real economy fluctuations [Naes et al., 2011, 강장구 and 장지원, 2015]. Furthermore, a liquidity crunch in the financial market, like the one during the 2008 financial crisis, could lead to a severe drop in asset prices and exacerbate economic shocks.
Monetary policy alterations can lead to shocks in the system. These changes could be a result of changes in the base interest rate or a change in the communication style. The effects of these shocks can be estimated by evaluating the response of liquidity.
Therefore, this study aims to create a stock market liquidity judgment indicator using real transaction data, investigating whether a refined calibration of monetary policy is possible based on this indicator’s response to monetary policy shocks.
Research Methodology#
1. Constructing the Stock Market Liquidity Judgment Indicator#
The elasticity of standardized stock prices for stock trading units or trading volume will be measured using the following model:
where \(\lambda_t\): stock price elasticity, \(P\): stock price, \(Q\): Trading volume, \(D_t\): [0,1] trading direction (Buy:1, Sell:0).
Based on prior research [강장구 and 심명화, 2014], liquidity varies between buy-led and sell-led trades. Therefore, we’ll separate them into buy-led liquidity (\(\lambda_{t,buy}\)) and sell-led liquidity (\(\lambda_{t,sell}\)). The disparity in buy-sell liquidity (\(\lambda_{t,gap}=|\lambda_{t,sell}|-|\lambda_{t,buy}|\)) is sensitive to external shocks and also mirrors the illiquidity premium.
2. Estimating the Impact of Monetary Policy Shocks#
Monetary policy shocks are categorized into changes in the base interest rate and changes in the tone of press conferences. We’ll measure the shock response by analyzing the change in the size of the liquidity judgment indicator before and after the Monetary Policy Committee (MPC).
The tone of the press conference is gauged using a sentiment dictionary [Lee et al., 2019], and the correlation between the linguistic features of the conference transcript and Q&A and the shock response of the liquidity judgment indicator is identified. To control the sensitivity of the liquidity judgment indicator to the monetary policy stance, we use the tone index of the MPC minutes as a control variable.
The study will then analyze the response of the liquidity judgment indicator to monetary policy shocks by dividing it into market trends (bull market, bear market).
Policy Implications#
This study carries significant policy implications. As stock market liquidity reflects investors’ expectations about the real economy, changes in the liquidity judgment indicator reflect changes in real economic expectations. Understanding these changes will help policymakers verify the effects of their decisions.
Identifying the causal relationship between the language used in major communications as part of monetary policy and the liquidity judgment indicator could offer a new tool for fine-tuning monetary policy through communication.
References#
Young Joon Lee, Soohyon Kim, and Ki Young Park. Deciphering monetary policy board minutes with text mining: the case of south korea. Korean Economic Review, 35(2):471–511, 2019.
Randi Naes, Johannes A Skjeltorp, and Bernt Arne ødegaard. Stock market liquidity and the business cycle. The Journal of Finance, 66(1):139–176, 2011.
강장구 and 심명화. 한국 주식시장의 매도, 매수 유동성 비대칭에 대한 연구. 한국증권학회지, 43(2):327–358, 2014.
강장구 and 장지원. 주식시장 유동성의 실물경기변동 예측력에 관한 연구. 재무연구, 28(1):71–108, 2015.