nep-fmk New Economics Papers
on Financial Markets
Issue of 2023‒03‒06
nine papers chosen by



  1. Seven Pitfalls of Technical Analysis By Guglielmo Maria Caporale; Alex Plastun
  2. Leverage and Interest Rates By Giovanna Nicodano; Luca Regis
  3. Zero-Leverage Puzzle By Mykola Pinchuk
  4. A Modified CTGAN-Plus-Features Based Method for Optimal Asset Allocation By Jos\'e-Manuel Pe\~na; Fernando Su\'arez; Omar Larr\'e; Domingo Ram\'irez; Arturo Cifuentes
  5. Mutual fund shareholder letters: Flows, performance, and managerial behavior By Hillert, Alexander; Niessen-Ruenzi, Alexandra; Ruenzi, Stefan
  6. Back to the 1980s or Not? The Drivers of Inflation and Real Risks in Treasury Bonds By Carolin Pflueger
  7. Where Is the Carbon Premium? Global Performance of Green and Brown Stock By Michael D. Bauer; Daniel Huber; Glenn D. Rudebusch; Ole Wilms
  8. How the PBoC´s new MLF affects the yield curve By Makram El-Shagi; Lunan Jiang
  9. Finland: Financial System Stability Assessment By International Monetary Fund

  1. By: Guglielmo Maria Caporale; Alex Plastun
    Abstract: This paper examines the main drawbacks of technical analysis. Although this is widely used by practitioners, from an academic perspective it can only be seen as a form of “voodoo finance”. In particular, it runs into the following pitfalls: Subjectivity; Doubtful assumptions; Unjustified algorithms; Low profitability; Data snooping; Statistically insignificant results; Unrealistic simplifications. The key conclusion is that it is high time that (self-fulfilling) technical analysis be replaced by more sophisticated time-series forecasting methods and models such as fractional integration, R/S analysis and autoregressive specifications .
    Keywords: technical analysis, data snooping, financial markets, price forecasting, trading
    JEL: C63 D84 E37 G12
    Date: 2023
    URL: http://d.repec.org/n?u=RePEc:ces:ceswps:_10213&r=fmk
  2. By: Giovanna Nicodano; Luca Regis
    Abstract: We study the sensitivity of optimal leverage to the level of the risk-free interest rate. Our trade-off model implies a heterogeneous response depending on the presence of a sponsor backing company debt. A highly-leveraged, backed company optimally increases debt when interest rates fall, while a company without a sponsor reduces it despite having lower initial leverage. This heterogeneity implies divergent bankruptcy probability and recovery-upondefault, in the same interest rate scenarios, for the two company types. We also show that a lower risk-free rate reduces the sponsor’s incentive to issue debt.
    Keywords: capital structure, tax-bankruptcy trade-off, default, LBO, subsidiaries, securitization, restructurings, risk transfer
    Date: 2023
    URL: http://d.repec.org/n?u=RePEc:cca:wpaper:692&r=fmk
  3. By: Mykola Pinchuk
    Abstract: In this paper, I examine why some firms have zero leverage. I fail to find evidence that firms are unlevered because of managerial entrenchment since these firms do not have weaker corporate governance. I reject the hypothesis that firms become zero-leverage after prolonged periods of high market valuation, since before levering these firms do not suffer from declining valuations and continue to issue large amounts of equity. I find strong evidence in favor of the financial constraints explanation of the zero-leverage puzzle. Zero-leverage firms appear to be financially constrained using three different measures of financial constraints. I obtain mixed evidence on the financial flexibility hypothesis since all-equity firms increase investments and acquisitions after levering, but the probability of their levering decreased during the financial crisis. My results suggest that financial constraints are the first-order the driver of zero-leverage behavior and are more important than less obvious explanations such as managerial entrenchment.
    Date: 2023–02
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2302.00761&r=fmk
  4. By: Jos\'e-Manuel Pe\~na; Fernando Su\'arez; Omar Larr\'e; Domingo Ram\'irez; Arturo Cifuentes
    Abstract: We propose a new approach to portfolio optimization that utilizes a unique combination of synthetic data generation and a CVaR-constraint. We formulate the portfolio optimization problem as an asset allocation problem in which each asset class is accessed through a passive (index) fund. The asset-class weights are determined by solving an optimization problem which includes a CVaR-constraint. The optimization is carried out by means of a Modified CTGAN algorithm which incorporates features (contextual information) and is used to generate synthetic return scenarios, which, in turn, are fed into the optimization engine. For contextual information we rely on several points along the U.S. Treasury yield curve. The merits of this approach are demonstrated with an example based on ten asset classes (covering stocks, bonds, and commodities) over a fourteen-and-half year period (January 2008-June 2022). We also show that the synthetic generation process is able to capture well the key characteristics of the original data, and the optimization scheme results in portfolios that exhibit satisfactory out-of-sample performance. We also show that this approach outperforms the conventional equal-weights (1/N) asset allocation strategy and other optimization formulations based on historical data only.
    Date: 2023–02
    URL: http://d.repec.org/n?u=RePEc:arx:papers:2302.02269&r=fmk
  5. By: Hillert, Alexander; Niessen-Ruenzi, Alexandra; Ruenzi, Stefan
    Abstract: Fund companies regularly send shareholder letters to their investors. We use textual analysis to investigate whether these letters' writing style influences fund flows and whether it predicts performance and investment styles. Fund investors react to the tone and content of shareholder letters: A less negative tone leads to higher netflows. Thus, fund companies can use shareholder letters as a tactical instrument to influence flows. However, at the same time, a dishonest communication that is not consistent with the fund's actual performance decreases flows. A positive writing style predicts higher idiosyncratic risk as well as more style bets, while there is no consistent predictive power for future performance.
    Keywords: Fund Flows, Textual Analysis, Shareholder Letters, Investment Styles
    JEL: G23 G11
    Date: 2023
    URL: http://d.repec.org/n?u=RePEc:zbw:safewp:380&r=fmk
  6. By: Carolin Pflueger
    Abstract: I use nominal and real bond risks as new moments to discipline a New Keynesian asset pricing model, where supply shocks, demand shocks, and monetary policy are the fundamental drivers of inflation. Endogenously time-varying risk premia imply that nominal bond risks—as measured by their stock market beta—are a forward-looking indicator of stagflation risks. Calibrating the model separately for the 1980s and the 2000s, I show that positive nominal bond betas in the 1980s resulted from a “perfect storm” of supply shocks and a reactive monetary policy rule, but not from either supply shocks or monetary policy in isolation.
    JEL: E0 E31 E40 G10 G12
    Date: 2023–02
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:30921&r=fmk
  7. By: Michael D. Bauer; Daniel Huber; Glenn D. Rudebusch; Ole Wilms
    Abstract: The relative equity pricing of more climate-friendly (“green”) versus less climate-friendly (“brown”) companies is an open question in climate finance. Previous research comes to conflicting conclusions, documenting either a “carbon premium” with brown stocks yielding higher returns, or the opposite, with green stocks outperforming brown. This paper provides new international evidence on this issue for a range of methodologies. Using carbon dioxide (CO2) emissions as reported by companies to measure their greenness, we document that green stocks across the G7 have generally provided higher returns than brown stocks for much of the past decade. We also try to reconcile our findings with previous work, and we provide some results for early 2022 that show that brown stocks outperformed green ones during the energy crisis.
    Keywords: climate risk, transition risk, carbon emissions, green stocks, brown stocks
    JEL: G11 G12 Q54
    Date: 2023
    URL: http://d.repec.org/n?u=RePEc:ces:ceswps:_10246&r=fmk
  8. By: Makram El-Shagi (Center for Financial Development and Stability at Henan University, and School of Economics at Henan University, Kaifeng, Henan); Lunan Jiang (Center for Financial Development and Stability at Henan University, and School of Economics at Henan University, Kaifeng, Henan)
    Abstract: In this paper, we assess the impact of the Medium-term Lending Facility (MLF), an instrument recently introduced by the People's Bank of China (PBoC), on treasury and corporate bond yields. This instrument and, more specifically, the transmission of its use through treasury bond yields to corporate bond yields plays a major role in the more market-based policy the PBoC envisions for the future. Using a semi-parametric local projection framework, we show that the mechanism is already fairly effective, allowing the PBoC to manipulate the entire yield curve.
    Keywords: Monetary policy; yield curves; MLF; Chinese bond market
    JEL: E52 G12 E44
    Date: 2023–02
    URL: http://d.repec.org/n?u=RePEc:fds:dpaper:202301&r=fmk
  9. By: International Monetary Fund
    Abstract: Finland has further improved the regulation and supervision of its financial sector since the 2016 FSAP, in part driven by European legislation and institutions. The size of the banking sector increased significantly in 2018 with the redomicilation of Nordea. Finland weathered the COVID-19 pandemic well relative to other economies, with fiscal support and interventions from the authorities. However, Finland is now navigating a weaker economic outlook given the war in Ukraine and ensuing energy crisis, despite limited direct financial exposures to Russia.
    Date: 2023–01–23
    URL: http://d.repec.org/n?u=RePEc:imf:imfscr:2023/039&r=fmk

General information on the NEP project can be found at https://nep.repec.org. For comments please write to the director of NEP, Marco Novarese at <director@nep.repec.org>. 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.