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on Financial Markets |
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Issue of 2024‒04‒01
nine papers chosen by |
| By: | Hayden Brown |
| Abstract: | Over the past 60 years, there has been a gradual increase in the volatility of daily returns for the S&P 500 Index. Hypothetically, suppose that market forces determine daily volatility such that a daily leveraged S&P 500 fund cannot outperform a standard S&P 500 fund in the long run. Then this hypothetical volatility happens to support the increase in volatility seen in the S&P 500 index. On this basis, it appears that the classic argument of the market portfolio being unbeatable in the long run is determining the volatility of S&P 500 daily returns. Moreover, it follows that the long-term volatility of the daily returns for the S&P 500 Index should continue to increase until passing a particular threshold. If, on the other hand, this hypothesis about market forces increasing volatility is invalid, then there is room for daily leveraged S&P 500 funds to outperform their unleveraged counterparts in the long run. |
| Date: | 2024–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2403.01088&r=fmk |
| By: | Pala, Melissa |
| Abstract: | This paper provides evidence of a highly fragmented European interbank market that is tightened during the COVID-19 pandemic, when the interbank market was under stress. Using a unique dataset of unsecured, overnight interbank loans at the transactional level allows me to apply advanced panel methods. Furthermore, this paper shows liquidity hoarding during the pandemic and relationship lending as a German phenomenon. In addition, there is evidence that borrowers who have to pay higher rates in the market are more likely to participate in tender auctions and that the COVID-19 pandemic had the greatest impact on smaller interbank borrowers. |
| Keywords: | nterbank Market, Relationship Lending, Liquidity, COVID-19, Monetary Policy |
| JEL: | G01 G15 G18 G21 D85 |
| Date: | 2024 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:bubdps:284408&r=fmk |
| By: | Serge Darolles (DRM - Dauphine Recherches en Management - Université Paris Dauphine-PSL - PSL - Université Paris sciences et lettres - CNRS - Centre National de la Recherche Scientifique); Gaëlle Le Fol (DRM - Dauphine Recherches en Management - Université Paris Dauphine-PSL - PSL - Université Paris sciences et lettres - CNRS - Centre National de la Recherche Scientifique); Yuyi He (CUHK - The Chinese University of Hong Kong [Hong Kong]) |
| Abstract: | We examine how the information contained in corporate social performance isincorporated into stock prices. Pastor et al. (2021) propose an equilibrium modelfocusing exclusively on the demand part coming from investors (discount rate story).They show that brown assets should have higher expected returns than green assetsbecause investors have green tastes. In line with theoretical model of Pedersen etal. (2021), Derrien et al. (2022) analyze how the impact of negative ESG news onfirms' future value, focusing exclusively on the expectations of futures sales (cashflows story). To understand the net effect of ESG on stocks returns, we must reconcilethe two stories and analyze the perception of customers and investors' green realinvestment of firms and the effects of their actions and interactions. Neither theory, nor empirical studies give a clear conclusion on the sign of the effect because they onlylook at one channel at a time. We decompose here the effect of "S" scores on expectedreturns via changes in institutional ownership, and show that the negative effect candisappear when allowing for both the cash flows and the discount rate parts in theempirical model. Finally, we show that "E", "S", and "G" qualities are not perceivedthe same by customers and investors changing the overall effect on stocks returns. |
| Date: | 2023–06–05 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-04462749&r=fmk |
| By: | Ziyuan Ma; Conor Ryan; Jim Buckley; Muslim Chochlov |
| Abstract: | Sentiment analysis can be used for stock market prediction. However, existing research has not studied the impact of a user's financial background on sentiment-based forecasting of the stock market using artificial neural networks. In this work, a novel combination of neural networks is used for the assessment of sentiment-based stock market prediction, based on the financial background of the population that generated the sentiment. The state-of-the-art language processing model Bidirectional Encoder Representations from Transformers (BERT) is used to classify the sentiment and a Long-Short Term Memory (LSTM) model is used for time-series based stock market prediction. For evaluation, the Weibo social networking platform is used as a sentiment data collection source. Weibo users (and their comments respectively) are divided into Authorized Financial Advisor (AFA) and Unauthorized Financial Advisor (UFA) groups according to their background information, as collected by Weibo. The Hong Kong Hang Seng index is used to extract historical stock market change data. The results indicate that stock market prediction learned from the AFA group users is 39.67% more precise than that learned from the UFA group users and shows the highest accuracy (87%) when compared to existing approaches. |
| Date: | 2024–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2403.00772&r=fmk |
| By: | Jiajian Zheng; Duan Xin; Qishuo Cheng; Miao Tian; Le Yang |
| Abstract: | The stock market is a crucial component of the financial market, playing a vital role in wealth accumulation for investors, financing costs for listed companies, and the stable development of the national macroeconomy. Significant fluctuations in the stock market can damage the interests of stock investors and cause an imbalance in the industrial structure, which can interfere with the macro level development of the national economy. The prediction of stock price trends is a popular research topic in academia. Predicting the three trends of stock pricesrising, sideways, and falling can assist investors in making informed decisions about buying, holding, or selling stocks. Establishing an effective forecasting model for predicting these trends is of substantial practical importance. This paper evaluates the predictive performance of random forest models combined with artificial intelligence on a test set of four stocks using optimal parameters. The evaluation considers both predictive accuracy and time efficiency. |
| Date: | 2024–02 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2402.17194&r=fmk |
| By: | Mehmet Selman Colak; Sumeyra Korkmaz; Huseyin Ozturk; Muhammed Hasan Yilmaz |
| Abstract: | [EN] This paper studies the peer effects on emerging markets credit default swap (CDS) premia. Unlike various other spillover models, spatial econometrics is used to distinguish between direct (countryspecific) and indirect (non-country specific) effects on the CDS premia. This strategy enables us to investigate non-country specific channels driving the shifts in sovereign credit risk. On top of documenting statistically significant spatial interactions, the paper finds that indirect effects are nearly as important as the direct ones in explaining the CDS movements. The findings are robust to a set of additional analyses. This study emphasizes that caution is warranted in using CDS premium as a sovereign risk indicator. [TR] Bu calismada, gelismekte olan ulkelerin kredi temerrut takasi (CDS) primlerindeki akran etkileri incelenmektedir. Diger cesitli yayilim modellerinin aksine, CDS primleri uzerindeki dogrudan (ulkeye ozgu olan) ve dolayli (ulkeye ozgu olmayan) etkilerin ayristirilmasinda mekânsal ekonometrik yontemlerden faydalanilmaktadir. Bu strateji, ulke kredi riskinde degisimlere yol acan ulke-disi belirli kanallarin incelenmesine olanak saglamaktadir. Ýstatistiki olarak anlamli mekânsal etkilesimleri belgelemesinin yani sira, calisma CDS hareketlerini aciklamada dolayli etkilerin neredeyse dogrudan etkiler kadar onemli oldugunu ortaya koymaktadir. Bulgular bir dizi ek analize karsi saglamdir. Bu calisma CDS priminin ulke kredi riskini temsilen gosterge olarak kullaniminda dikkatli olunmasi gerektigine vurgu yapmaktadir. |
| Date: | 2024 |
| URL: | http://d.repec.org/n?u=RePEc:tcb:econot:2406&r=fmk |
| By: | Dr. Lukas Voellmy |
| Abstract: | In various banking models, banks are viewed as arrangements that insure households against uncertain liquidity needs. However, the exact nature of the liquidity risk faced by households – and hence the insurance function of banks – differs across models. This paper attempts to disentangle the different meanings of the term ‘liquidity insurance’ in the literature and to clarify what kind of insurance banks provide in which models. The paper also shows under which conditions banking is equivalent to eliminating uncertainty about liquidity needs or letting households trade with each other in an asset market. Special attention is given to the comparison of banking models in the tradition of Diamond and Dybvig (1983) with those based on monetary (notably New Monetarist) frameworks. |
| Keywords: | Liquidity insurance, Banking theory |
| JEL: | G21 G52 |
| Date: | 2024 |
| URL: | http://d.repec.org/n?u=RePEc:snb:snbwpa:2024-03&r=fmk |
| By: | Shutter Zor |
| Abstract: | The contrast between companies' "fleshy" promises and the "skeletal" performance in digital transformation may lead to a higher risk of stock price crash. This paper selects a sample of Shanghai and Shenzhen A-share listed companies from 2010 to 2021, empirically analyses the specific impact of the gap between words and deeds in digital transformation (GDT) on the stock price crash risk, and explores the possible causes of GDT. We found that GDT significantly increases the stock price crash risk, and this finding is still valid after a series of robustness tests. In a further study, a deeper examination of the causes of GDT reveals that firms' perceptions of economic policy uncertainty significantly increase GDT, and the effect is more pronounced in the sample of loss-making firms. At the same time, the results of the heterogeneity test suggest that investors are more tolerant of state-owned enterprises when they are in the GDT situation. Taken together, we provide a concrete bridge between the two measures of digital transformation - digital text frequency and digital technology share - and offer new insights to enhance capital market stability. |
| Date: | 2024–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2403.01360&r=fmk |
| By: | Selcuk Gul |
| Abstract: | [EN] This study aims to identify the role played by the sovereign risk in determining the local currency lending rates to the non-financial sector. In this context, lending rate equations for five emerging countries that are members of the Organisation for Economic Cooperation and Development (OECD) are estimated by the Autoregressive Distributed Lag (ARDL) model. The findings indicate that the impact of sovereign risk on lending rates varies among countries. While an increase in the sovereign risk premium leads to a significant rise in the local currency lending rates in Türkiye, its impacts on the lending rates are relatively low in Poland and Mexico and almost negligible in Hungary and Chile. Results imply that, in the case of Türkiye, as the decline in the risk premium, accompanying the monetary tightening policy initiated in June 2023, become permanent, it may have a reducing effect on the financing costs of the non-financial sector in the medium-to-long term. [TR] Bu calisma, finansal olmayan sektore verilen yerli para cinsiden kredi faizlerinin belirlenmesinde ulke riskinin oynadigi rolu ortaya koymayi amaclamaktadir. Bu cercevede, Ekonomik Kalkinma ve Isbirligi Teskilati (OECD) uyeleri arasindan secilmis bes gelismekte olan ulke icin kredi faizi denklemleri Otoregresif Gecikmesi Dagitilmis (ARDL) modeli ile tahmin edilmektedir. Bulgular, ulke riskinin kredi faizleri uzerindeki etkisinin ulkeler arasinda degiskenlik gosterdigine isaret etmektedir. Ulke risk primindeki artis finansal olmayan sektore verilen yerli para cinsinden kredi faizlerini Turkiye ekonomisinde onemli oranda artirirken, Polonya ve Meksika'da soz konusu artisin kredi faizleri uzerindeki etkisinin daha zayif, Macaristan ve Sili’de ise neredeyse ihmal edilebilir duzeyde oldugu gorulmektedir. Sonuclar, Turkiye ozelinde, 2023 yilinin haziran ayinda uygulanmaya baslanan parasal sikilastirma politikasina eslik eden risk primindeki dususun kalici hale gelmesiyle, orta ve uzun vadede finansal olmayan sektorun finansman maliyetlerini azaltici etkide bulunabilecegini ima etmektedir. |
| Date: | 2024 |
| URL: | http://d.repec.org/n?u=RePEc:tcb:econot:2403&r=fmk |