Analysis of an event study using the Fama–French five‑factor model:teaching approaches including spreadsheets and the R programming language

The current financial education framework has an increasing need to introduce tools that facilitate the application of theoretical models to real-world data and contexts.However,only a limited number of free tools are available for this purpose.Given this lack of tools,the present study provides two approaches to facilitate the implementa-tion of an event study.The first approach consists of a set of MS Excel files based on the Fama–French five-factor model,which allows the application of the event study methodology in a semi-automatic manner.The second approach is an open-source R-programmed tool through which results can be obtained in the context of an event study without the need for programming knowledge.This tool widens the calculus possibilities provided by the first approach and offers the option to apply not only the Fama–French five-factor model but also other models that are common in the finan-cial literature.It is a user-friendly tool that enables reproducibility of the analysis and ensures that the calculations are free of manipulation errors.Both approaches are freely available and ready-to-use.

A Numerical Study on Forecasting the Henan Extraordinarily Heavy Rainfall Event in August 1975

This study is essentially an experiment on the control experiment in the August 1975 catastrophe which was the heaviest rainfall in China's Mainland with a maximum 24-h rainfall of 1060.3 mm, and it significantly demonstrates that the limited area model can still skillfully give reasonable results even only the conventional data are available. For such a heavy rainfall event, a grid length of 90 km is too large while 45 km seems acceptable. Under these two grid sizes, the cumulus parameterization scheme is evidently superior to the explicit scheme since it restricts instabilities such as CISK to limited extent. The high resolution scheme for the boundary treatment does not improve forecasts significantly.The experiments also revealed some interesting phenomena such as the forecast rainfall being too small while affecting synoptic system so deep as compared with observations. Another example is the severe deformation of synoptic systems both in initial conditions and forecast fields in the presence of complicated topography. Besides, the fixed boundary condition utilized in the experiments along with current domain coverage set some limitations to the model performances.

Ab Initio Study of the Dynamical Si-O Bond Breaking Event in α-Quartz

The Si-O bond breaking event in the a-quartz at the first triplet （T1） excitation state is studied by using ab initio molecular dynamics （AIMD） and nudged elastic band calculations. A meta-stable non-bridging oxygen hole center and E1 center （NBOHC-E） is observed in the AIMD which consists of a broken Si-O bond with a Si-O distance of 2.54A. By disallowing the re-bonding of the Si and 0 atoms, another defect configuration （lll- Si/V-Si） is obtained and validated to be stable at both ground and excitation states. The NBOHC-E is found to present on the minimal energy pathway of the initial to IlI-Si/V-Si transition, showing that the generating of the NBOHC-E is an important step of the excitation induced structure defect. The energy barriers to produce the NBQHC-E＇ and Ⅲ-Si/V-Si defects are calculated to be 1.19 and 1.28eV, respectively. The electronic structures of the two defects are calculated by the self-consistent GW calculations and the results show a clear electron transition from the bonding orbital to the non-bonding orbital.

Effect of blockchain technology initiatives on firms’market value

Despite blockchain’s potential to transform corporations by providing new ways of organizing business processes and handling information,extant research pays inadequate attention to how and under what conditions blockchain technology provides additional financial value for shareholders.Drawing on the efficient market hypothesis and signaling theory,we examined the relationship between firms’blockchain use,development announcements,and stock market reactions.We used the event study methodology to analyze a sample of blockchain projects initiated by US firms between 2016 and 2019.The sample contains 114 firm-event observations.The findings show that the average abnormal return over a 2 days event period(including the day of the announcement and the day after the announcement)was positive.This positive stock market reaction is even more substantial when firms announce blockchain projects that focus on saving cost or time.Our findings also indicate that blockchain announcements tend to elicit more positive market reactions from smaller firms.We analyzed 249 firm-event observations containing firms from around the world and conclude that blockchain technology has a non-significant long-term impact on operating performance.The contingency approach adopted in our research provides advice for selecting the right mix of blockchain investment initiatives that is most suitable for a given organizational context.

The impact of the COVID‑19 outbreak on Chinese‑listed tourism stocks

This research explored the effects of the coronavirus disease(COVID-19)outbreak on stock price movements of China’s tourism industry by using an event study method.The results showed that the crisis negatively impacted tourism sector stocks.Further quantile regression analyses supported the non-linear relationship between the government’s responses and stock returns.The results present that the resurgence of the virus in Beijing did bring about a short-term negative impact on the tourism industry.The empirical results can be used for future researchers to conduct a comparative study of cultural differences concerning government responses to the COVID-19.

Analysing the behavioural finance impact of ‘fake news’phenomena on financial markets:a representative agent model and empirical validation

This paper proposes an original behavioural finance representative agent model,to explain how fake news’empirical price impacts can persist in finance despite contradicting the efficient-market hypothesis.The model reconciles empirically-observed price overreactions to fake news with empirically-observed price underreactions to real news,and predicts a novel secondary impact of fake news:that fake news in a security amplifies underreactions to subsequent real news for the security.Evaluating the model against a large-sample event study of the 2019 Chinese ADR Delisting Threat fake news and debunking event,this paper finds strong qualitative validation for its model’s dynamics and predictions.

The Analysis of Asda-Sainsbury’s Merger/Acquisition

The merger of Sainsbury’s and Asda caused huge impacts on Britain retail industry.Since the announcement that J Sainsbury plc would acquire Asda for £7.5 billion was published in April,2018,the changes in the UK grocery market have been discussed and questioned.And the grocery market in UK will be reordered without doubt.This essay firstly introduces Sainsbury by using Pestle model,then aims to figure out the type and the benefits of this M&A,analyze the market response and how investors react to this event in the first two parts.In the third and the last part,we aim to explain why the CMA blocked the merge.

Does the Shanghai-Hong Kong Stock Connect Program Enhance the Abnormal Rate of Return and Transaction Volatility of the Underlying Stocks:A Quasi-Natural Experimental Design

Shanghai-Hong Kong Stock Connect Program,which is a new starting point for the opening up of the mainland capital market,still has many uncertainties.Research on the benefits and market volatility of such policies can provide investors with time to invest in such policies,fluctuations in the underlying stocks of the Chinese stock market,and decision support for the formulation and revision of relevant policies.This paper studies whether there is significant abnormal rate of return in the selected stocks which are in the Shanghai Stock Connect Program within the specified period,the excess return gap between the stocks which are in the program and which are not in the program,and the impact of the Shanghai Stock Connect Program on the volatility of the relevant stocks.Based on the CAPM model and the Fama-French 3-factor model,this paper uses t test to study the significance of the abnormal rate of return.By establishing a difference-in-difference(DID)model,the regression of the abnormal rate of return is tested,and the sample volatility is analyzed according to the influence of the fund transaction.The study found that the stocks in the program have significant abnormal rate of returns during the window period.The Shanghai Stock Connect has brought about a huge change in transaction amount,and policy makers need to improve related and similar policies.

The Capital Market Reaction and the Influencing Mechanism of the Establishment of the Data Basic Institutional System

This study uses a sample of A-share listed companies to investigate the impact of China's Data Basic Institutional System on capital market reactions and the mechanism by which it exerts influence.The findings reveal that within a 5-day period before and after the policy announcement,listed companies with high data resources experience a significantly higher abnormal return compared to those with low data resources.Moreover,this difference becomes more pronounced as enterprise technology intensity increases.Furthermore,the policy enhances the capital market's perception of the value of data resources and its potential for generating multiplier effects.Additional tests confirm that post-implementation of the policy,the capital market reevaluates the long-term value of enterprises associated with data resources.This comprehensive examination contributes empirical evidence to support academic research,inform policy formulation,and guide strategic planning in relevantindustries.

STUDY ON MECHANISM OF EL NINO EVENT OCCURRENCE

A possible mechanism is put forward in this paper for El Nino events from the viewpoint of plate tec- tonics and oceanic geology.A number of the data are cited to illustrate the views that sea-bottom volcanic ac- tivities and hot springs may cause El Nino events.

Impacts of CME Changing Mechanism for Allowing Negative Oil Prices on Prices and Trading Activities in the Crude Oil Futures Market

This study investigates and compares the effects of the Coronavirus disease 2019(COVID-19)pandemic,the Chicago mercantile exchange(CME)'s negative price suggestion on prices and trading activities in the crude oil futures market to discuss the cause of negative crude oil futures prices.Through event studies,the empirical results show that the COVID-19 pandemic no longer impacts crude oil futures prices in April,2020 after controlled market risk,while the CME's negative prices suggestion can explain the crude oil futures price changes around and even after April 8,2020 to some degree.Moreover,this study uncovers anomalies in prices and trading activities by analyzing returns,trading volume,open interest,and illiquidity measures using vector autoregressive(VAR)models.The results imply that CME's allowing negative prices strengthens the price impact on trading volume and makes illiquidity risk matter.This study's results coincide with the following lawsuit evidence of market manipulation.

Market reactions to trade friction between China and the United States:Evidence from the soybean futures market

In March 2018,the US used an immense trade deficit as an excuse to provoke trade friction with China.This study uses the EGARCH model and event study methods to study the impact of the major risk event of Sino-US trade friction on soybean futures markets in China and the United States.Results indicate that the Sino-US trade friction weakened the return spillover effect between the soybean futures markets in China and the US,and significantly increased market volatilities.As the scale of additional tariffs increased,the volatility of the Chinese soybean futures market declined;however,the volatility of the US soybean futures market did not weaken.In addition,expanding the sources of soybean imports helped ease the impact of tariffs on China's soybean futures market,while the decline in US soybean exports to China intensified the volatility of the US soybean futures market.In addition,while the release of multiple tariff increases has had a short-termimpact on the returns of soybean futures markets,the impact of trade friction has grad-ually decreased.

Liquidity Dynamics Around Intraday Price Jumps in Chinese Stock Market

Using 4128 single jumps detected from high frequency data of 220 individual stocks in SZ300 P index, this paper investigates the liquidity dynamics around price jumps in Chinese market.Some interesting empirical results are obtained and the corresponding explanations are given. The frequency of positive jumps is quite higher than that of negative jumps. The trading volumes and average trade sizes are all in a high level around positive jumps. The relatively low liquidities around negative jumps show that negative jumps may be generated and enlarged by poor liquidity provision.The price reversal after price jumps is significant, and price reversal lasts longer after positive jumps.Moreover, the size and direction of jumps are significantly correlated with the returns and trades in the post-jump trading time. These findings are believed to be associated with the high proportion of retail investors and their herding behavior for price trend chasing.

Analysis of the Relation between Interest Rate Policy and the Stock Market in China

Based on the modern monetary theory, this paper analyze the relation between interest rate policy and Shanghai and Shenzhen Stock Exchange by using event study and co\|integration model method. We point out that the interest rate policy have some abnormal effects on the stock market in short time and have negative effects on the stock market in long run. The influence of the interest rate is different on Shanghai Stock Exchange and Shenzhen Stock Exchange.

Effect of economic policies on the stock and bond market under the impact of COVID-19

The global epidemic of COVID-19 has made a huge impact on global health and financial markets.And the spread of the virus has stalled economic development in many parts of the world.As stocks and bonds are two important financial assets,how to take appropriate economic policies to restore the stock and bond markets is the focus of governments as they are seeking for quick recovery.Based on the Event Study method and the GARCH model,data from 1 October 2019 to 1 April 2020 were collected from 26 countries or regions as analytic samples.The results show:1)COVID-19 has made greater impacts on the stock market than the bond market;2)the economic policy responses after the COVID-19 has brought impacts on both of the stock and the bond markets;3)the monetary policy responses has brought greater volatility to the stock market than the fiscal policy responses,while the fiscal policy responses has brought greater volatility to the bond market than the monetary policy;4)the fiscal policy has brought more positive effects on the stock market,and monetary policy has brought more positive effects on the bond market.This research is helpful to understand the mechanism of COVID-19’s impacts on the stock and bond market.And it is of great practical significance to the governments’decisions to make economic policy responses after an epidemic.

A great disturbance in the crypto:Understanding cryptocurrency returns under attacks

A non-traditional type of financial asset,cryptocurrencies based on public blockchains are still little understood in their real-world behavior.Exogenous events such as cyber-attacks and their media coverage can strongly affect their supply and demand,adoption and usage,efficiency,and infrastructural development,thus influencing their price stability and market valuation.Given the great technical complexity of blockchains,we believe that a pure economic analysis of risks associated with cryptocurrencies is simply not sufficient to convey the relationships between attacks and the disruptive effects that these can bring on the operation of cryptocurrencies.On these grounds,we survey the most common types of attacks for Proof-of-Work(PoW)cryptocurrencies and evaluate their impact on the returns of a number of real-world cryptocurrencies for which market data are available.Due to data availability,our event study analysis focuses on instances of 51% attacks,hard forks,and wallet attacks.The main goal of our analysis is to understand the relationship between technical events(cyber-attacks and coordinated user/miner behavior)and the economic impacts surrounding them.We aim to develop a deeper understanding of these systems that are objects of great research interest in separate disciplines,supporting policymakers in their regulatory decisions concerning crypto-assets and associated cyber-related financial risks.