本研究第一部份在探討實際、非預期與非預期的緊縮與寬鬆的貨幣政策對期貨報酬的影響，是否具有不對稱效果，而第二部分將進一步分析在不同類型投資人處於高情緒的情況下，貨幣政策對於報酬的影響。 研究發現，實際或非預期的貨幣政策對於期貨報酬影響性低，然而非預期寬鬆M2貨幣政策對於報酬有顯著正向影響；此外，當區分於不同景氣狀態時，在牛市中，實際與非預期的重貼現率對於報酬皆有顯著正向關聯，而非預期緊縮與寬鬆重貼現率則在熊市影響較顯著，具有不對稱效果。 此外，我們更進一步研究當各類型投資人在高情緒的情況下，貨幣政策對於報酬的影響。發現於實際、非預期與非預期的緊縮或寬鬆的貨幣政策中，幾乎在各類型投資人在高情緒的情況下，貨幣政策會顯著影響期貨報酬，且以隔夜拆款利率影響為最。區分景氣狀態後發現在實際、非預期與非預期的緊縮或寬鬆貨幣政策中，不同投資人處於高情緒時，在不同景氣狀態下貨幣政策對於報酬呈現顯著性。 / In this paper, we try to analyze the relationship between actual, unexpected and unexpected tight and easy monetary policy and TAIEX futures index returns at first and attempt to know whether there are asymmetric reactions. Moreover, we make a further effort to examine the relationship between monetary policy decisions and the returns when different types of investors sentiments are high. The results show that the coefficients of actual or unexpected monetary policies aren’t statistically significant. However, the unexpected easy M2 monetary policy has significant and positive influence on the returns. Besides, when we divide the data into different regimes, we can discover the asymmetric reactions that actual and unexpected rediscount rate has significant and positive influence in bull market, and unexpected tight and easy monetary policy rediscount rate have more effective in bear market, which means that there are asymmetric reactions in different regimes. Moreover, we make further efforts to examine that whether there are different influences of the monetary policy decisions for each of the investors in high sentiment. We find that actual, unexpected and unexpected tight and easy monetary policy decisions have large effect on the returns when investors sentiment are high, and the change of overnight rate has the most influence. Furthermore, when we divide the data into different regimes, we can examine that in actual, unexpected and unexpected tight and easy monetary policy, the relationship between monetary policies and rate of return are significant when each of the investors in high sentiment in different regimes.

I investigate the relationship between expected stock returns and trading volume. I collect together 522 estimates from 46 studies and conduct the first meta-analysis in this field. Use of Bayesian model averaging and Frequentist model averaging help me to discover the most influential factors that affect the return-volume relationship, since I control for more than 50 differences among primary articles such as midyear and type of data, length of the primary dataset, size of market, or model employed. In the end, I find out that the relation between expected stock returns and trading volume is rather negligible. On the other hand, the contemporaneous relation between returns and volume is positive. These two findings cut the mixed results from previously written studies. Moreover, the investigated relationship is influenced by the size of country of interest and the level of its development. Besides the primary studies that employ higher data frequency provide substantially larger estimates than the studies with data from longer time periods. On the contrary, there is no difference among different estimation methodologies used. Finally, I employ classical and modern techniques such as stem-based methodology for publication bias detection, and I find evidence for it in this field. 1

L’objectif des travaux présentés dans cette thèse est d’étudier la diffusion de l’information dans les marchés financiers. Considérant comme établi que les individus sont hétérogènes et à rationalité limitée, nous avons fondé nos travaux sur une catégorie de modèles computationnels dans le but de simuler les actions et les interactions des agents autonomes. Cette catégorie est communément nommée modélisation agent (ABM).Plus concrètement, cette recherche se concentre sur le rôle de l’hétérogénéité des agents dans la diffusion et l’utilisation de l’information. À cet effet, nous avons développé deux structures de marché, qui diffèrent par leur transparence. Dans les chapitres 1 et 2, nous introduisons un marché centralisé, où une partie du carnet d’ordre est accessible (information publique). Dans le chapitre 3, nous développons un marché de gré à gré dans lequel les agents négocient et échangent avec leurs relations. / The piece of work’s aim is to understand information diffusion in financial markets. Starting from the empirical evidences that agents are heterogeneous and bounded rational, we based our investigations on a class of computational models for simulating the actions and interactions of autonomous agents: the agent - based model (ABM). More precisely, this research focuses on the impacts of agents heterogeneity in diffusion and use of information. For this purpose, we developed two market structures, in which the market transparency varies. In the chapters 1 and 2, we introduce a centralised market, where a part of the order-book is available as a public information. In the chapter 3, we build an Over-The-Counter market, where agents bargains with their trading contacts.

When a stock is added into the S&P 500 Index, it is automatically "cross-listed" in the index derivative markets (i.e., S&P 500 Index futures and Index options). I examined the effects of such cross-listing on the trading volume and return volatility of the underlying component stocks. Traditional finance theory asserts that futures and "cash" markets are connected by arbitrage mechanism that brings both markets to equilibrium. When arbitrage opportunities arise, arbitrageurs buy (sell) the index portfolio and take short (long) positions in the corresponding index derivative contracts until prices return to theoretical levels. Such mechanical arbitrage trading tends to create large order flows that could be difficult for the market to absorb, resulting in price changes. Utilizing a list of S&P 500 index composition changes occurring over the period September 1976 to December 2005, I investigated the market-adjusted volume turnover ratios and return variances of the stocks being added to and deleted from the S&P 500, surrounding the effective day of index membership changes. My primary finding is that, after the introduction of the S&P 500 index futures and options contracts, stocks added to the S&P 500 experience significant increase in both trading volume and return volatility. However, deleted stocks experience no significant change in either trading volume or return volatility. Both daily and monthly return variances increase following index inclusion, consistent with the hypothesis that derivative transactions "fundamentally" destabilize the underlying securities. I argue that the increase in trading volume and return volatility may be attributed to index arbitrage transactions as derivative markets provide more routes for index arbitrageurs to trade. Other index trading strategies such as portfolio insurance and program trading may also contribute to the results. On the other hand, a deleted stock is not associated with changes in trading volume and volatility since it represents an extremely small fraction of the market value-weighted index portfolio, and the influence of index trading strategies becomes slight for these shares. Furthermore, evidence is provided that trading volume and return volatility are positively related.

Sociala medier har blivit snabbt växande plattformar där människor kan diskutera, dela och inte minst erhålla information om aktuella ämnen. Framgången för sociala medier är ett tydligt tecken på människors växande intresse för åsiktsutbyte. Sociala medier har däremot sina brister, däribland menas att influencers kan orsaka överreaktioner samt leda till en ökad volatilitet på marknaden. Den stora mängdinformation som sprids på sociala medier och internet har lett till ett informationsöverskott. Vilket för privatpersoner innebär att det är svårt att hitta, filtrera och analysera all tillgänglig information om aktiebolag på marknaden för att ta välgrundade beslut som är både tids- och erfarenhetskrävande. Ett steg vidare i denna utvecklingen är sociala handelsplattformar som kan beskrivas som en nischad social media där enbart aktiehandel diskuteras och annat brus inte uppstår. Till en social handelsplattform kopplar användarna sitt aktiekonto så att deras köp och sälj av aktier blir offentliga. Huvudsyftet med denna studien är att undersöka huruvida det finns signifikanta tecken på att influencers aktiva på den sociala handelsplattformen Shareville kan påverka aktiepriser och handelsvolym på den svenska aktiemarknaden. Studien är vidare avgränsad till den svenska aktiemarknaden och undersöker endast svenska influencers på Shareville med över 10 000 följare och svensknoterade bolag av varierande storlek. Inga utländska influencers eller bolag återfinns därmed i denna studie. Studien är av kvantitativ karaktär och baseras därmed på sekundärdata från databasen Refinitiv Eikon men även primärdata från Shareville för att hjälpa oss att veta vilka influencers som har flest följare på handelsplattformen. Studiens resultat indikerar att influencers på Shareville kan påverka svenska aktiers avkastning och handelsvolym. Speciellt i bolag noterade på mindre marknadsplatser där vi ser en högre volatilitet än i till exempel Mid Cap och Large Cap noterade bolag. Utifrån studiens resultat kan vi dra slutsatsen att alla marknadsplatser utifrån den effektiva marknadshypotesen inte är effektiv i stark form utan snarare halv-stark form. / The growth of social media is a clear sign of people's interest in exchanging information. Social media, on the other hand, has its shortcomings, influencers can cause overreactions and lead to increased volatility in the stock market. A step further in the social media expansion is social trading platforms that can be described as a social media where only stock trading is discussed, and other noise does not arise. The main purpose of this study is to investigate whether there are significant signs that influencers active on the social trading platform Shareville can influence stockprices and trading volume in the Swedish stock market. The study is a quantitative study and is based on secondary data from the database Refinitiv Eikon but also primary data from Shareville. The results of the study indicate that influencers on Shareville can affect the return and trading volume of Swedish shares. Especially in companies listed on smaller markets where we see higher volatility than in, for example, Mid Cap and Large Cap companies. Based on what our results show, we can conclude that all marketplaces assumed from the effective market hypothesis are not effective in strong form, but rather semi-strong form. / <p>Betyg: Väl Godkänt (Högsta betyg)</p><p>Grade: Pass with special distinction (highest grade)</p>

Producing a model explaining the trading volume can be attractive for companies who’s main revenue resides on it. Previous studies have shown that factors such as stock returns, volatility and uncertainty affects the trading volume. The purpose of this work is to clarify the consensus that prevails and determine the factors that impact Avanza’s customers trading volume. Factors such as daily stock returns and economic, political and financial uncertainty are analyzed through a multiple linear regression analysis with a daily time period between 2000-2019. The work is thus designed within the framework of mathematical statistics and industrial economics. To be able to draw a conclusion, further investigation is required in the form of a time series analysis in combination with a deeper understanding of the applied area and the mathematical methods that have been used. / Att ta fram en modell som förklarar handelsvolymen kan vara eftertraktat hos företag vars huvudintäkter beror av den. Tidigare forskning visar att faktorer som prisförändringar på aktiemarknaden, volatilitet och osäkerhet påverkar handelsvolymen. Syftet med arbetet är att klargöra den konsensus som råder och fastställa de faktorer som har störst påverkan gällande handelsvolymen för Avanza’s kunders. Faktorer som dagliga förändringar inom börsmarknaden och ekonomisk, politisk och finansiell osäkerhet har genom en multipel linjär regressionsanalys analyserats med en daglig tidsperiod mellan 2000-2019. Arbetet är således utformat inom ramen för matematisk statistik och industriell ekonomi. För att kunna dra en slutsats krävs vidare undersökning i form av en tidsserieanalys och en djupare förståelse av det tillämpade området och metoderna som har an- vänds.

Bakgrund: Förutom avkastning och risk är likviditet en väsentlig faktor vid investeringsbeslut och enligt tidigare studier är småbolag mindre likvida än stora bolag. Däremot råder det ej konsensus angående hur sambandet mellan aktielikviditet och aktieavkastning ser ut. Vidare finner tidigare studier att det främst är småbolag som använder och gynnas av likviditetsgaranter. Däremot är det endast ett fåtal studier som analyserar likviditetsgaranternas påverkan på avkastning.  Syfte: Syftet med studien är att analysera sambandet mellan aktielikviditet och aktieavkastning samt huruvida användandet av likviditetsgaranter påverkar aktieavkastning.  Metod: Studien är utformad efter en kvantitativ metod och deduktiv ansats. För att uppnå studiens syfte har studien genomförts enligt två metoder; paneldata och eventstudie. Paneldata har använts för att analysera sambandet mellan aktielikviditet och aktieavkastning. Eventstudie har använts till att analysera huruvida abnormal avkastning uppstår efter att ett bolag ingått kontrakt med en likviditetsgarant.  Resultat: Studiens resultat visar att det finns ett positivt dubbelriktat samband mellan aktielikviditet och aktieavkastning. Däremot visar utfallet att avkastning påverkar likviditet i större utsträckning än vad likviditet påverkar avkastning. Vidare finner studiens resultat att kontraktering med en likviditetsgarant genererar positiv kumulativ abnormal avkastning på kort sikt. Utifrån resultatet går det att konstatera att marknaden omedelbart reagerar på ny information. / Background: In addition to risk and stock return, liquidity is an important factor for investment decisions, and according to previous studies, small corporations are less liquid than large corporations. However, there is no consensus regarding the relationship between share liquidity and share return. Furthermore, previous studies find that it is mainly small corporations that use and benefit from liquidity providers. However, there are only a few studies that analyze the impact of liquidity providers on return.  Purpose: The purpose of the study is to analyze the relationship between share liquidity and share return and whether the use of liquidity providers affect share returns.  Methodology: The study is designed using a quantitative method and a deductive approach. To achieve the purpose of the study, the study has been conducted according to two different methods, panel data and event study. The panel data has been used to analyze the relationship between share liquidity and share return. The event study has been used to analyze whether abnormal returns occur after a corporation enters into a contract with a liquidity provider.  Results: The results of this study indicate that there is a positive bidirectional relationship between share liquidity and share return. However, the outcome shows that return affects liquidity to a greater extent than liquidity affects return. Furthermore, the study finds that the use of a liquidity provider generates positive cumulative abnormal return in the short term. Based on the results, it is possible to conclude that the market immediately reacts to new information.

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本文以 GJR-GARCH 為分析模型，針對所選八家台灣上市公司股價所計算之每日對數報酬率(daily log returns)，對於各種不斷到達的新增訊息所引起的波動反應。所納入條件變異數方程式的訊息到達(解釋變數)分別為：(1)同日成交數量(2)成交量變動率(3)星期一與星期五之日曆效應(4)不同權值規模(size-based)投資組合間的波動外溢效果。研究結果發現(1)同日成交量對於台股權值較低的小公司，有能力捕捉其波動性，但是對於權值偏高的大公司，其解釋能力顯有不足(2)成交量變化普遍會導致公司報酬率的波動(3)臺灣股市波動性並不具有星期五效應，至於星期一效應也只出現在部分的小公司(4)不同規模的投資組合間雖然互有波動外溢現象，但其不對稱性非常明顯， 亦即訊息到達後，先造成大公司股價的波動，此波動再進而影響到小公司，引起小公司股價的波動。 / Applying the GJR-GARCH model to the daily returns of eight selected firms from Taiwan stock market, this paper examines response of variance volatility to various information arrivals which separately include (1) concurrent trading volume (2) change in trading volume (3) calendar effects, especially Modnay and Friday effects, and (4) asymmetric volatility spillover between two sized-based portfolios. The results find that concurrent trading volume as a proxy of information arrival dramatically reduces volatility persistence of the small firm's conditional variance, but has little influence on large firm's, and change in trading volume cause significant change in conditional variance. Although there is a conjecture that the volatility in stock markets may be higher on Monday and Friday, it can't be found in this study. The results also strongly support that the volatility spillover effect from larger to small portfolio is more significant than that from smaller to large portfolio.

過去研究指出，公司管理當局可藉由即時揭露更多攸關資訊以降低市場之資訊不對稱，而管理當局所發布之財務預測亦為揭露資訊之一種。我國證管會於民國八十年五月起正式實施強制性財務預測制度，影響資本市場甚鉅。本研究旨在探討管理當局所發布之財務預測對資本市場資訊不對稱之影響，進而推論我國強制性財務預測制度對於降低資本市場之資訊不對稱是否有其功效。 本研究採用股票交易量、股價變異性及市場深度作為資訊不對稱之代理變數，實證結果顯示： 1.在強制性財務預測制度實施前，自願發布財務預測之公司於預測發布後，其資訊不對稱顯著較預測發布前降低；然與未發布財務預測公司相較之結果卻顯示，以股票交易量為資訊不對稱之代理變數時，發布財測公司於預測發布後之資訊不對稱反而顯著較未發布財測者為高。 2.在強制性財務預測制度實施後，強制或自願發布財務預測之公司於預測發布後，其資訊不對稱程度仍顯著較其發布前降低；而以股價變異性為資訊不對稱代理變數之結果亦顯示，發布財測公司於預測發布後之資訊不對稱顯著較未發布公司為低。 3.以市場深度為資訊不對稱代理變數之結果顯示，在強制性財務預測制度實施後，發布強制性財務預測之公司，其資訊不對稱於預測發布後顯著降低；此外，與發布自願性財務預測公司相較之結果顯示，發布強制性財測公司於預測發布後，其資訊不對稱程度不顯著高於發布自願性財務預測者。 / A firm can increase levels of disclosure to lower the information asymmetry. Financial forecast released by managers is also one of information about corporation. Our country began to implement the mandatory financial forecast regulations since May, 1991. This study mainly investigates the association between financial forecast released by companies and the mandatory financial forecast regulations. Furthermore , it also investigates that if the regulations effectively mitigate information asymmetry. This study uses trading volume, price volatility, and market depth as proxies for the information asymmetry. The empirical results show that: 1.Before May, 1991, corporations with voluntary forecast significantly mitigated the information asymmetry after the forecast released. But the information asymmetry (use trading volume as a proxy) of corporations after forecast released was not significantly lower than corporations without forecast. 2.After May, 1991, corporations with mandatory or voluntary forecast also significantly mitigated the information asymmetry after the forecast released. And the information asymmetry (use price volatility as a proxy) of corporations after forecast released was significantly lower than corporations without forecast. 3.After May, 1991, corporations with mandatory forecast significantly mitigated the information asymmetry (use market depth as a proxy) after the forecast released. And the information asymmetry of corporations after mandatory forecast released was not significantly higher than corporations with voluntary forecast.