nep-fmk New Economics Papers
on Financial Markets
Issue of 2024‒02‒19
ten papers chosen by



  1. How the information content of integrated reporting flows into the stock market By Dimos Andronoudis; Diogenis Baboukardos; Fanis Tsoligkas
  2. Market structure of cryptoasset exchanges: Introduction, challenges and emerging trends By Vladimir Skavysh; Jacob Sharples; Sofia Priazhkina; Salman H. Hasham
  3. Sector Rotation by Factor Model and Fundamental Analysis By Runjia Yang; Beining Shi
  4. Relationship discounts in corporate bond trading By Jurkatis, Simon; Schrimpf, Andreas; Todorov, Karamfil; Vause, Nicholas
  5. Effects of Monetary Policy Frameworks on Stock Market Volatilities: An Empirical Study of Global Economies By Lee, King Fuei
  6. Realized Stochastic Volatility Model with Skew-t Distributions for Improved Volatility and Quantile Forecasting By Makoto Takahashi; Yuta Yamauchi; Toshiaki Watanabe; Yasuhiro Omori
  7. A Runs Test for Stock-Market Prices with an Unobserved Trend By Nils Herger
  8. Leverage ratio and risk-taking: theory and practice By Fatouh, Mahmoud; Giansante, Simone; Ongena, Steven
  9. The role of uncertainty and sentiment for intraday volatility connectedness between oil and financial markets By Karol Szafranek; Michał Rubaszek; Gazi Salah Uddin
  10. The nexus between the volatility of Bitcoin, gold, and American stock markets during the COVID-19 pandemic: evidence from VAR-DCC-EGARCH and ANN models By Virginie Terraza; Aslı Boru İpek; Mohammad Mahdi Rounaghi

  1. By: Dimos Andronoudis (no affiliation - no affiliation); Diogenis Baboukardos (Audencia Business School); Fanis Tsoligkas (University of Bath [Bath])
    Abstract: According to its advocates, integrated reporting (IR) aims to enhance firms' information environment by placing financial reporting into a much broader perspective in which interrelated non‐financial information of firms' activities are taken into consideration. We examine whether this intended outcome of IR embeds into the stock pricing process using a sample of South African listed firms that mandatorily adopted IR in 2011. Unlike previous studies that explore market valuation implications of IR, we examine the channel through which the IR‐related information flows into firm value. Specifically, we quantify the effects of revisions of expectation about future cash flows (prompted by financial reporting information), revisions of expectation about discount rates (prompted by non‐financial reporting information) and their interconnectedness. We hypothesize and empirically show that the adoption of an IR approach prompted greater market revisions of expectations about future discount rates and a stronger interconnectedness between market revisions of expectations about future cash flows and discount rates. Thus, the change in the stock pricing process after the adoption of IR is determined by non‐financial reporting information and its strong interconnectedness with financial reporting information. We also show that our results are stronger for firms with greater earnings opacity, suggesting that investors find IR more useful when firms' financial reporting is opaque. Results indicate to researchers, practitioners and regulators that IR enhances the firm‐level information environment by providing informative non‐financial reporting which is also well integrated with financial reporting.
    Keywords: Integrated Reporting, Discount Rate News, Pricing Process, South Africa
    Date: 2024–01–11
    URL: http://d.repec.org/n?u=RePEc:hal:journl:hal-04389552&r=fmk
  2. By: Vladimir Skavysh; Jacob Sharples; Sofia Priazhkina; Salman H. Hasham
    Abstract: Centralized trading platforms, or exchanges, are playing an increasingly important role in expanding the global crypto ecosystem. In contrast with their counterparts in traditional financial markets, these exchanges are vertically integrated and solely responsible for the execution, clearing and settlement of transactions. Moreover, exchanges often act as the custodian of users’ assets, which exacerbates the risk borne by its users. In this note, we provide an introduction to the functions that cryptoasset exchanges typically perform and contrast their design with infrastructure used in traditional financial markets. We also discuss several emerging trends in regulation and financial innovation that help address the problems cryptoasset exchanges face.
    Keywords: Digital currencies and fintech; Payment clearing and settlement systems
    JEL: G15 L1
    Date: 2024–01
    URL: http://d.repec.org/n?u=RePEc:bca:bocsan:24-2&r=fmk
  3. By: Runjia Yang; Beining Shi
    Abstract: This study presents an analytical approach to sector rotation, leveraging both factor models and fundamental metrics. We initiate with a systematic classification of sectors, followed by an empirical investigation into their returns. Through factor analysis, the paper underscores the significance of momentum and short-term reversion in dictating sectoral shifts. A subsequent in-depth fundamental analysis evaluates metrics such as PE, PB, EV-to-EBITDA, Dividend Yield, among others. Our primary contribution lies in developing a predictive framework based on these fundamental indicators. The constructed models, post rigorous training, exhibit noteworthy predictive capabilities. The findings furnish a nuanced understanding of sector rotation strategies, with implications for asset management and portfolio construction in the financial domain.
    Date: 2023–11
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2401.00001&r=fmk
  4. By: Jurkatis, Simon (Bank of England); Schrimpf, Andreas (BIS and CEPR); Todorov, Karamfil (BIS); Vause, Nicholas (Bank of England)
    Abstract: We find that clients with stronger past trading relationships with a dealer receive consistently better prices in corporate bond trading. The top 1% of relationship clients enjoy transaction costs that are 51% lower than those of the median client – an effect which was particularly beneficial when transaction costs spiked during the Covid-19 turmoil. We find clients’ liquidity provision to be a key motive why dealers grant relationship discounts: clients to whom balance-sheet constrained dealers can turn as a source of liquidity are rewarded with relationship discounts. Another important motive for dealers to give discounts to relationship clients is because these clients generate the bulk of dealers’ profits. Finally, we find no evidence that extraction of information from clients’ order flow is related to relationship discounts.
    Keywords: : Corporate bonds; Covid-19; dealers; over-the-counter markets; trading relationships
    JEL: G12 G14 G23 G24
    Date: 2023–11–03
    URL: http://d.repec.org/n?u=RePEc:boe:boeewp:1049&r=fmk
  5. By: Lee, King Fuei
    Abstract: This study investigates the relationship between monetary policy frameworks and stock market volatilities across countries. Using a novel classification framework by Cobham (2021), we study 84 countries across the world over the period of 1984 to 2017. We find that countries that maintain a fixed exchange rate peg tend to experience higher levels of stock market volatility, while countries adopting flexible inflation-targeting policies tend to exhibit lower levels of stock market volatilities. Additionally, the stock markets of countries operating under monetary policies characterized by unstructured discretion tend to be more volatile, while those operating with well-structured discretion tend to be more stable. Our results also suggest that while the choice of monetary policy framework is an important determinant of stock market volatility, it is not the only factor driving it. As such, policymakers should carefully consider the implications of different monetary policy frameworks when designing monetary policy, and take a holistic approach to financial stability that incorporates a range of factors beyond just monetary policy frameworks.
    Keywords: Monetary Policy Frameworks, Stock Market Volatility, Exchange Regimes, Inflation-Targeting
    JEL: E42 G10
    Date: 2023–12
    URL: http://d.repec.org/n?u=RePEc:pra:mprapa:119755&r=fmk
  6. By: Makoto Takahashi; Yuta Yamauchi; Toshiaki Watanabe; Yasuhiro Omori
    Abstract: Forecasting volatility and quantiles of financial returns is essential for accurately measuring financial tail risks, such as value-at-risk and expected shortfall. The critical elements in these forecasts involve understanding the distribution of financial returns and accurately estimating volatility. This paper introduces an advancement to the traditional stochastic volatility model, termed the realized stochastic volatility model, which integrates realized volatility as a precise estimator of volatility. To capture the well-known characteristics of return distribution, namely skewness and heavy tails, we incorporate three types of skew-t distributions. Among these, two distributions include the skew-normal feature, offering enhanced flexibility in modeling the return distribution. We employ a Bayesian estimation approach using the Markov chain Monte Carlo method and apply it to major stock indices. Our empirical analysis, utilizing data from US and Japanese stock indices, indicates that the inclusion of both skewness and heavy tails in daily returns significantly improves the accuracy of volatility and quantile forecasts.
    Date: 2024–01
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2401.13179&r=fmk
  7. By: Nils Herger (Study Center Gerzensee)
    Abstract: To analyze whether stock-market prices follow a random walk, the algebraic sign of their returns has been compared with a coin toss, which is a prominent example for a Bernoulli trial with equiprobable outcomes. Like coin tosses, signed returns lend themselves for a simple runs test for randomness. However, they typically comprise an unobserved trend, and therefore represent Bernoulli trials whose theoretical outcome probability is not easily known. Fortunately, the Von Neumann algorithm can trans- form Bernoulli trials with unknown outcome probabilities into equiprobable outcomes. Thus, a runs test on correspondingly transformed returns can handle an unobserved stock-market trend.
    Date: 2024–01
    URL: http://d.repec.org/n?u=RePEc:szg:worpap:2401&r=fmk
  8. By: Fatouh, Mahmoud (Bank of England); Giansante, Simone (Department of Economics, Business and Statistics, University of Palermo); Ongena, Steven (University of Zurich, Swiss Finance Institute, KU Leuven, NTNU Business School and CEPR)
    Abstract: We assess the impact of the leverage ratio capital requirements on the risk‑taking behaviour of banks both theoretically and empirically. We use a difference‑in‑differences (DiD) setup to compare the behaviour of UK banks subject to the leverage ratio requirements (LR banks) to otherwise similar banks (non‑LR banks). Conceptually, introducing binding leverage ratio requirements into a regulatory framework with risk-based capital requirements induces banks to reoptimise, shifting from safer to riskier assets (higher asset risk). Yet, this shift would not be one‑for‑one due to risk‑weight differences, meaning the shift would be associated with a lower level of leverage (lower insolvency risk). The interaction of these two changes determines the impact on the aggregate level of risk. Empirically, we show that LR banks did not increase asset risk, and slightly reduced leverage levels, compared to the control group after the introduction of leverage ratio in the UK. As expected, these two changes lead to a lower aggregate level of risk. Our results show that credit default swap spreads on the five‑year subordinated debt of LR banks dropped relative to non‑LR banks post leverage ratio introduction.
    Keywords: Finance; capital regulation; risk-taking; leverage ratio; risk‑based requirements
    JEL: G01 G21 G28
    Date: 2023–10–01
    URL: http://d.repec.org/n?u=RePEc:boe:boeewp:1048&r=fmk
  9. By: Karol Szafranek; Michał Rubaszek; Gazi Salah Uddin
    Abstract: We quantify intraday volatility connectedness between oil and key financial assets and assess how it is related to uncertainty and sentiment measures. For that purpose, we integrate the well-known spillover methodology with a TVP VAR model estimated on a unique, vast dataset of roughly 300 thousand 5 minute quotations for crude oil, the US dollar, S&P 500 index, gold and US treasury prices. This distinguishes our investigation from previous studies, which usually employ relatively short samples of daily or weekly data and focus on connectedness between two asset classes. We contribute to the literature across three margins. First, we document that market connectedness at intraday frequency presents new picture on markets co-movement compared to the estimates obtained using daily data. Second, we show that at 5 minute frequency volatility is mostly transmitted from the stock market and absorbed by the bond and dollar markets, with oil and gold markets being occasionally important for volatility transmission. Third, we present evidence that daily averages of intraday connectedness measures respond to changes in sentiment and market-specific uncertainty. Interestingly, our results contrast with earlier findings, as they show that connectedness among markets decreases in periods of high volatility owing to market-specific factors. Our study points to the importance of using high-frequency data in order to better understand market dynamics.
    Keywords: volatility connectedness, uncertainty and sentiment, oil market, intraday data, TVP-VAR model
    JEL: C32 C58 D80 Q31
    Date: 2023–11
    URL: http://d.repec.org/n?u=RePEc:sgh:kaewps:2023095&r=fmk
  10. By: Virginie Terraza (MRE - Montpellier Recherche en Economie - UM - Université de Montpellier); Aslı Boru İpek; Mohammad Mahdi Rounaghi
    Abstract: The spread of the coronavirus has reduced the value of stock indexes, depressed energy and metals commodities prices including oil, and caused instability in financial markets around the world. Due to this situation, investors should consider investing in more secure assets, such as real estate property, cash, gold, and crypto assets. In recent years, among secure assets, cryptoassets are gaining more attention than traditional investments. This study compares the Bitcoin market, the gold market, and American stock indexes (S&P500, Nasdaq, and Dow Jones) before and during the COVID-19 pandemic. For this purpose, the dynamic conditional correlation exponential generalized autoregressive conditional heteroskedasticity model was used to estimate the DCC coefficient and compare this model with the artificial neural network approach to predict volatility of these markets. Our empirical findings showed a substantial dynamic conditional correlation between Bitcoin, gold, and stock markets. In particular, we observed that Bitcoin offered better diversification opportunities to reduce risks in key stock markets during the COVID-19 period. This paper provides practical impacts on risk management and portfolio diversification.
    Keywords: JEL Classification: C22 C58 G17 Bitcoin market Gold market American stock markets COVID-19 pandemic VAR-DCC-EGARCH model ANN model, JEL Classification: C22, C58, G17 Bitcoin market, Gold market, American stock markets, COVID-19 pandemic, VAR-DCC-EGARCH model, ANN model
    Date: 2024–01–15
    URL: http://d.repec.org/n?u=RePEc:hal:journl:hal-04395168&r=fmk

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