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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
321

Essays on corporate risk, U.S. business cycles, international spillovers of stock returns, and dual listing

Ivaschenko, Iryna January 2003 (has links)
This thesis consists of four self-contained essays on the various topics in finance.  The first essay, The Information Content of The Systematic Risk Structure of Corporate Yields for Future Real Activity: An Exploratory Empirical Investigation, constructs a proxy for the systematic component of the risk structure of corporate yields (or systematic risk structure), and tests how well it predicts real economic activity in the United States. It finds that the systematic risk structure predicts the growth rate of industrial production 3 to 18 months into the future even when other leading indicators are controlled for, outperforming other models. A regime-switching estimation also shows that the systematic risk structure is very successful in identifying and capturing different growth regimes of industrial production.  The second essay, How Much Leverage is Too Much, or Does Corporate Risk Determine the Severity of a Recession? investigates whether financial conditions of the U.S. corporate sector  can explain the probability and severity of recessions. It proposes a measure of corporate vulnerability, the Corporate Vulnerability Index (CVI) constructed as the default probability for the entire corporate sector. It finds that the CVI is a significant predictor of the probability of a recession 4 to 6 quarters ahead, even controlling for other leading indicators, and that an increase in the CVI is also associated with a rise in the probability of a more severe and lengthy recession 3 to 6 quarters ahead.  The third essay, Asian Flu or Wall Street Virus? Tech and Non-Tech Spillovers in the United States and Asia (with Jorge A. Chan-Lau), using TGARCH models, finds that U.S. stock markets have been the major source of price and volatility spillovers to stock markets in the Asia-Pacific region during three different periods: the pre-LTCM crisis period, the “tech bubble” period, and the “stock market correction” period. Hong Kong SAR, Japan, and Singapore were sources of spillovers within the region and affected the United States during the latter period. There is also evidence of structural breaks in the stock price and volatility dynamics induced during the “tech bubble” period.  The fourth essay, Coping with Financial Spillovers from the United States: The Effect of U. S. Corporate Scandals on Canadian Stock Prices, investigates the effect of U.S. corporate scandals on stock prices of Canadian firms interlisted  in the United States. It finds that firms interlisted during the pre-Enron period enjoyed increases in post-listing equilibrium prices, while firms interlisted during the post-Enron period experienced declines in post-listing equilibrium prices, relative to a model-based benchmark. Analyzing the entire universe of Canadian firms, it finds that interlisted firms, regardless of their listing time, were perceived as increasingly risky by Canadian investors after the Enron’s bankruptcy. / Diss. Stockholm : Handelshögskolan, 2003
322

Trois contributions sur l'effet informatif des cours boursiers dans les décisions d'entreprise / Three essays on informational feedback from stock prices to corporate decisions

Xu, Liang 27 June 2017 (has links)
Ce travail doctoral étudie l’effet « retour » de l’information financière liée aux prix des actions sur les décisions des dirigeants d’entreprise. Plus précisément, j'étudie si et comment les gestionnaires apprennent effectivement les nouvelles informations contenues dans les prix des actions pour guider leurs décisions d'entreprise. Ma thèse de doctorat est composée de trois essais, chacun abordant un aspect différent de ce même sujet. Le premier essai étudie le lien entre l'efficacité informationnelle du marché d'actions et le niveau d’efficacité économique réelle de l'entreprise. Dans le premier essai, je constate que lorsque les prix de l'action agrègent une plus quantité d'informations utile plus grande, les décisions des entreprises prises par les gestionnaires devraient être encore plus optimales efficaces. Le deuxième essai étudie si les gestionnaires cherchent à apprendre les informations utilisées par les vendeurs à découvert. L’étude des prix des actions en présence de vendeurs à découvert est-il utile pour les décisions de l'entreprise ? Dans le deuxième essai, j'ai surmonté les difficultés empiriques en exploitant une caractéristique institutionnelle unique sur le marché des actions de Hong Kong. Je constate que les gestionnaires des entreprises « non-shortable » peuvent tirer profit des informations des vendeurs à découvert sur les conditions économiques sectorielles par l'intermédiaire des prix des actions d'autres entreprises « shortable » dans la même industrie et les utilisent dans leurs décisions d'entreprise. Le troisième essai étudie les effets réels de la négociation d'options à long terme. Dans le troisième essai, je constate que l’introduction d’une catégorie spécifique d'options à long terme stimule la production d'informations privées à long terme et donc entraîne une augmentation de l'informativité des prix sur les fondamentaux à long terme des entreprises. Par conséquent, les dirigeants peuvent extraire davantage d'informations du prix de l’action pour guider leurs décisions d'investissement à long terme. / In my doctoral thesis, I investigate the information feedback from stock prices to managers’ decisions. More specifically, I study whether and how managers learn new information from stock prices to guide their corporate decisions. My doctoral thesis includes three essays focusing on this topic. The first essay studies the relationship between stock market informational efficiency and real economy efficiency at firm-level. In the first essay, I find that when stock prices reflect greater amount of information that managers care about, corporate decisions made by managers become more efficient. The second essay studies whether managers seek to learn short sellers’ information from stock prices and use it in corporate decisions. In the second essay, I overcome the empirical difficulties by exploiting a unique institutional feature in Hong Kong stock market that only stocks included in an official list are allowed for short sales. I find that that non-shortable firms’ managers can learn short sellers’ information on external conditions from shortable peers’ stock prices and use it in their corporate decisions. The third essay studies the real effects of long-term option trading. I find that long-term option trading stimulates the production of long-term information, which managers can use to guide their long-term investment decisions.
323

Spectral Portfolio Optimisation with LSTM Stock Price Prediction / Spektralportföljsoptimering med LSTM aktieprispredikering

Wang, Nancy January 2020 (has links)
Nobel Prize-winning modern portfolio theory (MPT) has been considered to be one of the most important and influential economic theories within finance and investment management. MPT assumes investors to be riskaverse and uses the variance of asset returns as a proxy of risk to maximise the performance of a portfolio. Successful portfolio management reply, thus on accurate risk estimate and asset return prediction. Risk estimates are commonly obtained through traditional asset pricing factor models, which allow the systematic risk to vary over time domain but not in the frequency space. This approach can impose limitations in, for instance, risk estimation. To tackle this shortcoming, interest in applications of spectral analysis to financial time series has increased lately. Among others, the novel spectral portfolio theory and the spectral factor model which demonstrate enhancement in portfolio performance through spectral risk estimation [1][11]. Moreover, stock price prediction has always been a challenging task due to its non-linearity and non-stationarity. Meanwhile, Machine learning has been successfully implemented in a wide range of applications where it is infeasible to accomplish the needed tasks traditionally. Recent research has demonstrated significant results in single stock price prediction by artificial LSTM neural network [6][34]. This study aims to evaluate the combined effect of these two advancements in a portfolio optimisation problem and optimise a spectral portfolio with stock prices predicted by LSTM neural networks. To do so, we began with mathematical derivation and theoretical presentation and then evaluated the portfolio performance generated by the spectral risk estimates and the LSTM stock price predictions, as well as the combination of the two. The result demonstrates that the LSTM predictions alone performed better than the combination, which in term performed better than the spectral risk alone. / Den nobelprisvinnande moderna portföjlteorin (MPT) är utan tvekan en av de mest framgångsrika investeringsmodellerna inom finansvärlden och investeringsstrategier. MPT antar att investerarna är mindre benägna till risktagande och approximerar riskexponering med variansen av tillgångarnasränteavkastningar. Nyckeln till en lyckad portföljförvaltning är därmed goda riskestimat och goda förutsägelser av tillgångspris. Riskestimering görs vanligtvis genom traditionella prissättningsmodellerna som tillåter risken att variera i tiden, dock inte i frekvensrummet. Denna begränsning utgör bland annat ett större fel i riskestimering. För att tackla med detta har intresset för tillämpningar av spektraanalys på finansiella tidsserier ökat de senast åren. Bland annat är ett nytt tillvägagångssätt för att behandla detta den nyintroducerade spektralportföljteorin och spektralfak- tormodellen som påvisade ökad portföljenprestanda genom spektralriskskattning [1][11]. Samtidigt har prediktering av aktierpriser länge varit en stor utmaning på grund av dess icke-linjära och icke-stationära egenskaper medan maskininlärning har kunnat använts för att lösa annars omöjliga uppgifter. Färska studier har påvisat signifikant resultat i aktieprisprediktering med hjälp av artificiella LSTM neurala nätverk [6][34]. Detta arbete undersöker kombinerade effekten av dessa två framsteg i ett portföljoptimeringsproblem genom att optimera en spektral portfölj med framtida avkastningar predikterade av ett LSTM neuralt nätverk. Arbetet börjar med matematisk härledningar och teoretisk introduktion och sedan studera portföljprestation som genereras av spektra risk, LSTM aktieprispredikteringen samt en kombination av dessa två. Resultaten visar på att LSTM-predikteringen ensam presterade bättre än kombinationen, vilket i sin tur presterade bättre än enbart spektralriskskattningen.
324

上限型股權連結保本票券之評價、避險和風險控管 / Valuation, Hedge and Risk Management of Capped, Equity-linked and Principal-protected Notes

陳芬英, Chen, Fen-ying Unknown Date (has links)
本論文含蓋三篇文章,分別從評價、避險和風險控管三方面,分析上限型股權連結保本票券。 第一篇文章為上限型股權連結保本票券之設計、評價和比較。本文考量投資人保守的投資行為與設限型股權連結票券所存在的delta跳躍(delta jump)現象,延伸Brennan and Schwartz (1976)模型,提出一個能在股價波動之際,使發行的避險部位delta呈現平滑變動且兼具保本(protected principal)功用的一般化模型(general form)。相較於一般的設限型股權連結保本模型,本模型具有以下特色。第一,加入股價成長率的調整因子(adjustable factor),當景氣低靡,股價不停下跌時,正的調整因子可減緩股價下滑之勢,進而增加投資人在票券到期日時獲取更多資本利得(capital gain)的機會。同時,調整因子縮小了當期股價成長率與股價上限成長率(capped stock growth rate)之間的差距,繼而減緩delta 跳躍的幅度,降低發行者的避險成本。並且在HJM利率模型下,delta隨股價與股價波動度的變化更顯平滑(smooth)。第二,在保本率(protection rate)和參與率 (participation rate)不變之下,本模型的期初合理價格(fair price)較低,投資人能以較低的成本取得同等的投資保障。第三,若將本票券的名目面額(notional principal)視作共同基金(mutual fund)的淨值(net value),而該淨值與股價連動,則本模型即成為股權連結的保本型基金(principal-protected fund)。 第二篇文章是路徑依賴之上限型股權連結保本模型之評價和風險測量。該文是擴展Brennan and Schwartz (1976)模型發展一個路徑依賴之上限型股權連結保本模型,並且提出一個比二元數模型更精確的封閉解。此外,也對七個時間序列進行股價波動度之精確檢定,得知AR-ARCH(1)模型對上限型股權連結保本票券而言,較其它時間序列模型,更能有效估計股價之波動度。 第二篇文章是外國資產的風險管理。目前在國內金融市場上,國外金融商品很多,大都以外幣計價,因此匯率風險是投資人不可忽視的因子。本文拓展Kupiec(1999)模型,將匯率風險加入模型中,使投資人更有效進行風險管理。 / This thesis studies valuation, hedge and risk management of capped equity-linked and principal-protected notes by means of the following essays: (1) Design, Valuation and Comparison of Capped Equity-linked and Principal-protected Notes (2) Valuation and Risk Measurement of Capped Equity-linked and Principal-protected Notes with Path Dependence (3) Risk Management of Foreign Assets Capped equity-linked and principal-protected notes are similar with barrier options. There exists delta jump as stock price or growth rate reaches the barrier. But previous studies about equity-linked and principal-protected notes with a restricted growth rate of stock price never explicitly discussed how the delta jump could be solved. In my first essay, I present a new design for capped equity-linked and principal-protected notes and add an adjustable factor to growth rate of stock price in such a way that the adjustable factor narrows the gap between the current stock growth rate and the capped stock growth rate and thus really reduces the magnitude of the delta jump and hence lowers the hedging cost for brokers. Recently, the focus of previous studies about principal-protected notes has been on either the restriction on the rate of stock return or the path dependence on the underlying asset, but not both in the same context. In my second essay, I develop a model on the capped, equity-linked and principal-protected notes with path dependence. There are two issues in this article. The first issue is valuation on the capped, equity-linked and principal-protected notes with path dependence. I find a closed-form approximation using the 2nd-order Taylor approximation and the method of Vorst (1992) that has higher accuracy than binomial tree model as maturity time or volatility becomes large. The second issue is risk measurement. I use VaR model to evaluate market risk of the principal-protected notes, and employ seven univariate time series models to forecast volatility and examine the accuracy. Additionally, investors may well encounter potential loss as the prices of financial products are reduced in the secondary market. The VaR is mainly concerned with the downside risk and becomes a standard measure of financial market risk that is increasingly used by investors. But if we want to apply 〝textbook〞formulation to risk management of foreign assets, there leaves exchange rate risk out of consideration. Therefore, I extend the work by Kupiec (1999) to present VaR formula with exchange rate risk for foreign assets and then to manage market risk usefully.
325

An Empirical Analysis of Herd Behavior in Sweden's First North Growth Market on NASDAQ Nordic

Singh, Bavneet, Maslarov, Boris January 2024 (has links)
In this paper, market participants’ tendency to form investor herds in the stocks listed on Nasdaq First North Growth Market of Sweden is examined for the period from 2018 to 2023. The models used in this study to detect herd behavior in stocks consist of two measures of dispersions, Cross-Sectional Standard Deviation of returns (CSSD) and Cross-Sectional Absolute Deviation of returns (CSAD), which were proposed by Christie and Huang (1995) and Chang, et al. (2000), respectively. An equally-weighted index consisting of all of the stocks that have traded on this market during the period is created and a quantitative analysis is conducted. Evidence showed absence of herd behavior when using both models, as well as when accounting for robustness tests consisting of small, mid-and large cap portfolios. Our results also support the prediction of rational asset pricing models, which suggest that stock return dispersions around the market returns increase during periods of market stress.

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