nep-fmk New Economics Papers
on Financial Markets
Issue of 2023‒03‒20
five papers chosen by

  1. Stock market correlation and geographical distance: does the degree of economic integration matter? By Bonga-Bonga, Lumengo; Manguzvane, Mathias Mandla
  2. Forecasting realized volatility in turbulent times using temporal fusion transformers By Frank, Johannes
  3. Crypto Trading and Bitcoin Prices: Evidence from a New Database of Retail Adoption By Raphael Auer; Giulio Cornelli; Sebastian Doerr; Jon Frost; Leonardo Gambacorta; Raphael A. Auer
  4. The impact of bank loan announcements on stock liquidity By Pham, Thu Phuong; Singh, Harminder; Vu, Van Hoang
  5. Carbon Policy Surprises and Stock Returns: Signals from Financial Markets By Ugo Panizza; Martina Hengge; Mr. Richard Varghese

  1. By: Bonga-Bonga, Lumengo; Manguzvane, Mathias Mandla
    Abstract: This paper investigates the effects of geographical distance on stock market correlations between countries within economic blocs. Specifically, this paper examines whether the degree of economic integration influences the nexus between geographical distance and stock market correlation. As the study compares two economic blocs, the European Union (EU) and the North Atlantic Free Trade Area (NAFTA), it finds that geographical distance negatively affects stock market correlations in the two economic blocs, but that effect is less significant for economic blocs with advanced economic integration. Contrary to past studies, this paper postulates that the negative impact of geographical distance on stock market correlation is a result of portfolio reallocation by foreign investors seeking high yields and safe havens in the local stock market when taking advantage of possible capital market liberalization.
    Keywords: stock market correlation; geographical distance; gravity model; economic integration.
    JEL: C13 F38 G1
    Date: 2023
  2. By: Frank, Johannes
    Abstract: This paper analyzes the performance of temporal fusion transformers in forecasting realized volatilities of stocks listed in the S&P 500 in volatile periods by comparing the predictions with those of state-of-the-art machine learning methods as well as GARCH models. The models are trained on weekly and monthly data based on three different feature sets using varying training approaches including pooling methods. I find that temporal fusion transformers show very good results in predicting financial volatility and outperform long short-term memory networks and random forests when using pooling methods. The use of sectoral pooling substantially improves the predictive performance of all machine learning approaches used. The results are robust to different ways of training the models.
    Keywords: Realized volatility, temporal fusion transformer, long short-term memory network, random forest
    JEL: C45 C53 C58 E44
    Date: 2023
  3. By: Raphael Auer; Giulio Cornelli; Sebastian Doerr; Jon Frost; Leonardo Gambacorta; Raphael A. Auer
    Abstract: Prices for cryptocurrencies have undergone multiple boom-bust cycles, together with ongoing entry by retail investors. To investigate the drivers of crypto adoption, we assemble a novel database (made available with this paper) on retail use of crypto exchange apps at daily frequency for 95 countries over 2015–22. We show that a rising Bitcoin price is followed by the entry of new users. About 40% of these new users are men under 35, commonly identified as the most “risk-seeking” segment of the population. We confirm these findings by exploiting two exogenous price shocks: the crackdown of Chinese authorities on crypto mining in mid-2021 and the social unrest in Kazakhstan in early 2022. Moreover, we find that when prices rise retail investors buy, while the largest holders sell — making a return at the smaller users’ expense. Overall, back of the envelope calculations suggest that around three-quarters of users have lost money on their Bitcoin investments.
    Keywords: Bitcoin, cryptocurrencies, cryptoassets, regulation, decentralised finance, DeFi, retail investment
    JEL: E42 E51 E58 F31 G28 L50 O32
    Date: 2023
  4. By: Pham, Thu Phuong; Singh, Harminder; Vu, Van Hoang
    Abstract: We examine the impact of bank loan announcements on stock liquidity. Using a comprehensive loan announcement sample over 14 years in Australia, we find that effective spreads and realised spreads of borrowers' stocks fall after the announcements. The findings suggest these announcements send positive signals about borrowers to the market that increases liquidity provision, and reduce transaction costs, leading to improved liquidity for borrowers’ stocks. This liquidity improvement is more pronounced following announcements of new loans than loan renewals. Overall, our findings provide practical implications for firm managers in the financing decision-making process and market participants in trading strategy adjustment.
    Keywords: Loans announcements; Stock liquidity; Transaction costs, Corporate decisions
    JEL: G10 G14 G20 G24
    Date: 2023–02–13
  5. By: Ugo Panizza; Martina Hengge; Mr. Richard Varghese
    Abstract: Understanding the impact of climate mitigation policies is key to designing effective carbon pricing tools. We use institutional features of the EU Emissions Trading System (ETS) and high-frequency data on more than 2, 000 publicly listed European firms over 2011-21 to study the impact of carbon policies on stock returns. After extracting the surprise component of regulatory actions, we show that events resulting in higher carbon prices lead to negative abnormal returns which increase with a firm's carbon intensity. This negative relationship is even stronger for firms in sectors which do not participate in the EU ETS suggesting that investors price in transition risk stemming from the shift towards a low-carbon economy. We conclude that policies which increase carbon prices are effective in raising the cost of capital for emission-intensive firms.
    Keywords: Carbon Emissions; Carbon Prices: Climate Change; Transition Risk; Stock Returns; carbon Policy surprise; investors price; carbon intensity; climate mitigation policy; EU ETS; Greenhouse gas emissions; Stocks; Asset prices; Climate change; Europe; Global
    Date: 2023–01–27

General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.