nep-fmk New Economics Papers
on Financial Markets
Issue of 2023‒01‒02
twelve papers chosen by
Kwang Soo Cheong
Johns Hopkins University

  1. An Early Indicator for Anomalous Stock Market Performance By Marlon Fritz; Thomas Gries; Lukas Wiechers
  2. Predictable Price Pressure By Samuel M. Hartzmark; David H. Solomon
  3. How Shocks Affect Stock Market Participation By Lorenz Meister; Karla Schulze
  4. Investor Sentiment and Firm Capital Structure By Shengfeng Li; Hafiz Hoque; Jia Liu
  5. Inflation Hedging on Main Street? Evidence from Retail TIPS Fund Flows By Stefan Nagel; Zhen Yan
  6. Bond convenience curves and funding costs By Nissinen, Juuso; Sihvonen, Markus
  7. Using crypto assets pricing methods to build technical oscillators for short-term bitcoin trading By Yang, Zixiu; Fantazzini, Dean
  8. Financial Literacy is associated with Stock Market Expectations but not with Forecast Accuracy: Evidence from Germany By Buschong, René
  9. Investor Sentiment and Multi-Scale Positive and Negative Stock Market Bubbles in a Panel of G7 Countries By Renee van Eyden; Rangan Gupta; Joshua Nielsen; Elie Bouri
  10. Bond Risk Premia, Priced Regime Shifts, and Macroeconomic Fundamentals By Constantino Hevia; Ivan Petrella; Martin Sola
  11. A Quantity-Based Approach to Constructing Climate Risk Hedge Portfolios By Georgij Alekseev; Stefano Giglio; Quinn Maingi; Julia Selgrad; Johannes Stroebel
  12. ESG compliant optimal portfolios: The impact of ESG constraints on portfolio optimization in a sample of European stocks By Costanza Torricelli; Beatrice Bertelli

  1. By: Marlon Fritz (Paderborn University); Thomas Gries (Paderborn University); Lukas Wiechers (Paderborn University)
    Abstract: We propose an indicator for detecting anomalous stock market valuation in real time such that market participants receive timely signals so as to be able to take stabilizing action. Unlike existing approaches, our anomaly indicator introduces three methodological novelties. First, we use an endogenous, purely data-driven, nonparametric trend identification method to separate long-term market movements from more short-term ones. Second, we apply SETAR models that allow for asymmetric expansions and contractions around the long-term trend and find systematic stock price cycles. Third, we implement these findings in our indicator and conduct real time market forecasts, which have so far been neglected in the literature. Simulations of our indicator using monthly S&P 500 stock data from 1970 to 2019 show that short-term anomalous market movements can be identified in real time up to one year ahead. We predict all major anomalies, including the 1987 Bubble and the initial phase of the Financial Crisis that began in 2007. In total, our anomaly indicator identifies more than 80% of all — even minor — anomalous episodes. Thus, smoothing market exaggerations through early signaling seems possible.
    Keywords: Financial Indicator, Nonparametric Trend, Stock Price Cycle, Stock Pricing, Valuation Ratio
    JEL: C14 C22 E44 G01
    Date: 2022–12
  2. By: Samuel M. Hartzmark; David H. Solomon
    Abstract: We demonstrate that predictable uninformed cash flows forecast market and individual stock returns. Buying pressure from dividend payments (announced weeks prior) predicts higher value-weighted market returns, with returns for the top quintile of payment days four times higher than the lowest. This holds internationally, and increases when reinvestment is high and market liquidity is low. High stock expense firms have lower returns from selling pressure after blackout periods, by 117 b.p. in four days. We estimate market-level price multipliers of 1.5 to 2.3. These results suggest price pressure is a widespread result of flows, not an anomaly.
    JEL: G12 G14 G4
    Date: 2022–11
  3. By: Lorenz Meister; Karla Schulze
    Abstract: While there is a broad consensus in the literature that stock ownership is associated with individual characteristics, such as wealth, income, risk preferences, and financial literacy, less is known about the dynamics of stock market participation (SMP). Major fluctuations in SMP are oftentimes related to political events, economic shocks, and technological disruptions. We discuss the literature that investigates some of these shocks, as well as personal life circumstances that determine SMP across various demographic groups. Consolidating the literature allows us to identify systematic drivers into and out of stock ownership, along with its distributional consequences. Major forces behind SMP fluctuations are changes in participation costs and benefits, risk exposure, economic policy uncertainty, income uncertainty, peer effects, and windfall gains.
    Date: 2022
  4. By: Shengfeng Li (University of Portsmouth); Hafiz Hoque (Swansea University); Jia Liu (University of Portsmouth)
    Abstract: We provide novel evidence of the role of investor sentiment in determining firms’ capital structure decisions from three perspectives: leverage ratio, debt maturity and leverage target adjustment. We find that when investor sentiment is high, firms increase their leverage ratios, supporting our contention that high investor sentiment increases firms’ debt capacity and facilitates the use of an aggressive leverage policy. Debt maturity is shorter in high sentiment periods, implying that firms are confident about future earnings and use shorter debt maturity to signal their financial solvency. Leverage target adjustment is faster in high sentiment periods, indicating a lower cost of external finance. Furthermore, the sentiment-leverage relationship sensitivity is greater for financially constrained firms. Our extended analysis determines that leverage-increasing firms generate lower stock returns subsequent to a period of high sentiment, offering practical insights into the economic consequences of increasing leverage in high sentiment periods on corporate value for investors. Our research advances the understanding of the impact of investor sentiment on firms’ financing decisions and stock returns.
    Keywords: Investor sentiment; capital structure; leverage; debt maturity; debt capacity; speed of adjustment; stock returns
    JEL: G31 G32
    Date: 2022–12–05
  5. By: Stefan Nagel; Zhen Yan
    Abstract: Households participating in financial markets pay attention to inflation news when making their investment decisions, even in an environment of mostly low and stable inflation. ETFs and open-ended mutual funds holding Treasury Inflation-Protected Securities (TIPS) receive inflows from retail investors, and nominal Treasury ETF experience outflows, when long-horizon market-based inflation expectations measures increase. Changes in household survey expectations or in measures of inflation uncertainty do not contribute much in explaining retail TIPS fund flows. Retail flows into TIPS funds are asymmetric, with strong reactions only to positive inflation news, and sticky, with flow responses to news gradually playing out over several months. Retail investors appear to pay some attention to regular Federal Reserve announcements, but major events such as the ``taper tantrum'' in May 2013, the presidential election in November 2016, and the COVID-19 crisis in March 2020 are associated with particularly large retail TIPS fund flows.
    JEL: E31 G23 G5
    Date: 2022–11
  6. By: Nissinen, Juuso; Sihvonen, Markus
    Abstract: A convenience yield represents a difference between yield on a safe bond and yield on a synthetic safe bond, constructed by combining a risky bond with a CDS contract. We explain the shapes of eurozone sovereign convenience curves using a model in which arbitrageurs face higher funding costs on bonds with credit risk and bond demand shocks induce funding risk. We provide novel causal evidence for our mechanism using variation in funding costs generated through exogenous haircut category changes. Changes in convenience yields represent a key transmission channel of unconventional monetary policy to bond yields.
    Keywords: Sovereign bond convenience yields,money markets,asset pricing with frictions,monetary policy
    JEL: G12 G15
    Date: 2022
  7. By: Yang, Zixiu; Fantazzini, Dean
    Abstract: This paper examines the trading performances of several technical oscillators created using crypto assets pricing methods for short-term bitcoin trading. Seven pricing models proposed in the professional and academic literature were transformed into oscillators, and two thresholds were introduced to create buy and sell signals. The empirical back testing analysis showed that some of these methods proved to be profitable with good Sharpe ratios and limited max drawdowns. However, the trading performances of almost all methods significantly worsened after 2017, thus indirectly confirming an increasing financial literature that showed that the introduction of bitcoin futures in 2017 improved the efficiency of bitcoin markets.
    Keywords: C32, C51; C53; C58; G11; G12; G17;
    JEL: C32 C51 C53 C58 G11 G12 G17
    Date: 2022
  8. By: Buschong, René
    Abstract: Using a representative panel dataset, this study focuses on stock market expectations as well as the accuracy of forecasts made by private households in Germany. First, I find evidence that higher financial literacy is associated with lower stock market expectations. However, there is no evidence that financial literacy is associated with the accuracy of forecasts. Second, the findings suggest that individuals form their expectations based on past performance: The three-month stock market return prior to being surveyed is associated with stated expectations and this association is heterogenous by financial literacy levels.
    Keywords: financial literacy,stock market expectations,forecast error,stock market participation
    JEL: G53 G41 G51
    Date: 2022
  9. By: Renee van Eyden (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa); Rangan Gupta (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa); Joshua Nielsen (Boulder Investment Technologies, LLC, 1942 Broadway Suite 314C, Boulder, CO, 80302, USA); Elie Bouri (School of Business, Lebanese American University, Beirut, Lebanon)
    Abstract: In this paper, firstly, we use the Log-Periodic Power Law Singularity Multi-Scale Confidence Indicator (LPPLS-CI) approach to detect both positive and negative bubbles in the short-, medium- and long-term of the stock market indices of the G7 countries. After detecting major crashes and booms in the seven stock markets over the monthly period of 1973:02 to 2020:09, we observe similar timing of strong (positive and negative) LPPLS-CIs across the G7 countries, suggesting synchronized extreme movements in these stock markets. Given this, secondly, we apply heterogeneous coefficients panel data-based regressions to analyze the impact of investor sentiment, proxied by business and consumer confidence indicators, on the indicators of bubbles of the G7. After controlling for the impacts of output growth, inflation, monetary policy, stock market volatility, and growth in trading volumes, we find that investor sentiment increases the positive and reduces the negative LPPLS-CIs, primarily at the medium- and long-term scales for the G7 considered all together, with the result being driven by at least five of the seven countries. Our results have important implications for both investors and policymakers, as the collapse (improvement) of investor sentiment can lead to a crash (recovery) in a bull (bear) market.
    Keywords: Multi-Scale Bubbles and Crashes, Investor Sentiment, Business and consumer confidence, Panel Regressions, G7 Stock Markets
    JEL: C22 C32 G41
    Date: 2022–11
  10. By: Constantino Hevia (Universidad Torcuato Di Tella); Ivan Petrella (Warwick Business School and CEPR); Martin Sola (Universidad Torcuato Di Tella)
    Abstract: In this paper, we develop and estimate an arbitrage-free model of bond prices in which the evolution of the risk factors and the parameters of the stochastic discountfactor are subject to occasional discrete changes in regimes. We show that the component of risk premia associated with regime shifts is related to the macroeconomic environment. In particular, the explicit pricing of regime shifts and the nonlinearities associated with the Markov switching model generates a strong connection betweenbond risk premia and the macroeconomy as summarized by variables such as inflation, industrial production, and unemployment.
    Keywords: Yield Curve; Term structure of interest rates; Markov regime switching; Priced switching risk prem
    JEL: C13 C22 E43
    Date: 2022–12
  11. By: Georgij Alekseev; Stefano Giglio; Quinn Maingi; Julia Selgrad; Johannes Stroebel
    Abstract: We propose a new methodology to build portfolios that hedge the economic and financial risks from climate change. Our quantity-based approach exploits information on how mutual fund managers trade in response to idiosyncratic changes in their climate risk beliefs. We exploit two types of idiosyncratic belief shocks: (i) instances when fund advisers experience local extreme heat events that are known to shift climate change beliefs, and (ii) instances when fund managers change the language in shareholder disclosures to express concerns about climate risks. We use the funds’ observed portfolio changes around such idiosyncratic belief shocks to predict how investors will reallocate their capital in response to aggregate climate news shocks that shift the beliefs and asset demands of many investors and thus move equilibrium prices. We show that a portfolio that is long stocks that investors tend to buy after experiencing negative idiosyncratic climate belief shocks, and short stocks that investors tend to sell, appreciates in value in periods with negative aggregate climate news shocks. Our quantity-based portfolios have superior out-of-sample hedge performance compared to portfolios constructed using existing alternative methods. The key advantage of the quantity-based approach is that it learns from rich cross-sectional trading responses rather than time-series price information, which is particularly limited in the case of newly emerging risks such as those from climate change. We also demonstrate the versatility of the quantity-based approach by constructing successful hedge portfolios for aggregate unemployment and house price risk.
    JEL: G10 G11 G12 G14 Q50 Q54
    Date: 2022–12
  12. By: Costanza Torricelli; Beatrice Bertelli
    Abstract: The introduction of the Environmental, Social, Governance (ESG) dimensions in setting up optimal portfolios has been becoming of uttermost importance for the financial industry. Given the absence of consensus in empirical literature and the limited number of studies providing performance comparison of ESG strategies, the aim of this paper is to assess the impact of ESG on optimal portfolios and to compare different approaches to the construction of ESG compliant portfolios. Following Varmaz et al. (2022) optimization model, we minimize portfolio residual risk by imposing a desired level of portfolio average systemic risk and ESG (measured by Bloomberg ESG score) over both an unscreened and a screened sample based on the 586 stocks of the EURO STOXX Index in the period January 2007 – August 2022. Three are the main results. First, regardless of the level of portfolio systemic risk, the Sharpe ratio of the optimal portfolios worsens as the target ESG level increases. Second, the Sharpe ratio dynamics of portfolios with the highest average ESG scores follows market phases: it is very close to/higher than other portfolios in bull markets, whereas it underperforms in stable or bear markets suggesting that ESG portfolios do not seem to represent a safe haven. Third, negative screenings with medium-low threshold reduce the performance of optimal portfolios with respect to optimization over an unscreened sample. However, when adopting a very severe screening we obtain a superior performance implying that very virtuous companies allows investors to do well by doing good.
    Keywords: sustainable portfolio, portfolio optimization, investor preferences, ESG score, negative screening, portfolio performance
    JEL: C61 G11 M14 Q01
    Date: 2022–10

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