The Journal of Prediction Markets最新文献

Herding Behavior in Prediction Markets: Evidence from UK Financial Spread-Trading Markets 预测市场中的羊群行为：英国金融价差交易市场的证据

The Journal of Prediction Markets Pub Date : 2023-07-19 DOI: 10.5750/jpm.v17i1.2037

C. Tai, S. Gulthawatvichai, M. Sung, Johnnie E. V. Johnson, J. Cheah

引用次数: 0

Comparison of ARIMA and Exponential Smoothing Models in Prediction of Stock Prices ARIMA 与指数平滑模型在股票价格预测中的比较

The Journal of Prediction Markets Pub Date : 2023-07-19 DOI: 10.5750/jpm.v17i1.2017

Yogesh Funde, Akshay Damani

{"title":"Comparison of ARIMA and Exponential Smoothing Models in Prediction of Stock Prices","authors":"Yogesh Funde, Akshay Damani","doi":"10.5750/jpm.v17i1.2017","DOIUrl":"https://doi.org/10.5750/jpm.v17i1.2017","url":null,"abstract":"Stock prices tend to show trends or seasonality or have random walk movements. Time series statistical models developed over time aid prediction of stock prices to assist informed decision-making for investors. These models provide quantitative information to financial specialists at the time of placing their buy–sell orders. The paper compares the movement of two univariate time series using two forecasting models—exponential smoothing and autoregressive integrated moving average (ARIMA) (p; d; q). We predict stock prices of selected 15 companies across three sectors (banking, pharmaceuticals, and Information technology) from NIFTY 50 data for the period April 01, 2016 to March 31, 2021. All these 15 companies are representative constituents of the three sectors within the Nifty 50 index. Performances of models were assessed through forecasting error measures such as root mean square error and mean absolute percentage error. Performances of both models were identical for nine stocks. Prediction based on ARIMA was more accurate for six stocks, whereas exponential smoothing model was a better indicator of stock prices in the case of one stock. However, the differences in error measures of the both the models are marginal, and parsimony principle may drive the choice of model.","PeriodicalId":352536,"journal":{"name":"The Journal of Prediction Markets","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139357544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Macroeconomic Determinants of Housing Prices in Hong Kong 香港房价的宏观经济决定因素

The Journal of Prediction Markets Pub Date : 2023-07-19 DOI: 10.5750/jpm.v17i1.2055

Simon M. S. So, Frankie S. L. Wan

引用次数: 0

Crash Prediction Using Fundamental Variables: Evidence from Mainland China 利用基本面变量预测崩盘：来自中国大陆的证据

The Journal of Prediction Markets Pub Date : 2023-07-19 DOI: 10.5750/jpm.v17i1.2039

Sébastien Lleo, W. Ziemba

引用次数: 0

Bitcoin Versus Gold Prices: Correlation or Mis-specification 比特币与黄金价格：相关性还是误导

The Journal of Prediction Markets Pub Date : 2023-07-19 DOI: 10.5750/jpm.v17i1.1975

Praveen Kumar

{"title":"Bitcoin Versus Gold Prices: Correlation or Mis-specification","authors":"Praveen Kumar","doi":"10.5750/jpm.v17i1.1975","DOIUrl":"https://doi.org/10.5750/jpm.v17i1.1975","url":null,"abstract":"Bitcoin is a newly created currency, which is also considered as “Digital Gold.” Whereas, Gold is a precious yellow metal. Bitcoins are more independent of the government than gold. Both gold and bitcoins are scanty resources, and thus, prices of both these assets appreciate or deteriorate depending on the demand and supply. An attempt was made to examine the association between prices of these two currencies. For this purpose, three different models were run: independent sample t-test, correlation analysis, and regression analysis. The outcomes of the independent sample t-test revealed that there exists a significant difference between the gold and bitcoin prices. However, the findings of correlation analysis show that movements in gold prices are statistically and positively linked to bitcoin prices. These findings indicate that gold prices move in the same direction as bitcoin prices. Further, the results of regression analysis also depicted that movement of bitcoin prices depends on movement of gold prices. Since its genesis, bitcoin prices have experienced around 37,418 appreciations, which make it an extraordinary currency. However, this study argued that bitcoin is establishing itself as an investment asset for the short term only because fluctuation in prices is very abnormal and unreliable in the long run. Moreover, robustness checks further show that gold prices are increasing at a steady rate, but increments are regular and trustworthy. Finally, the study found that bitcoin provides much higher returns to investors than gold. These results are crucial for the risk-taker investors who are looking for higher returns because bitcoins are getting growing public exposure day by day and attracting investments throughout the world.","PeriodicalId":352536,"journal":{"name":"The Journal of Prediction Markets","volume":"49 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139357737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Explaining the Gamestop Short Squeeze using Ιntraday Data and Google Searches. 使用Ιntraday数据和谷歌搜索解释Gamestop Short Squeeze。

The Journal of Prediction Markets Pub Date : 2023-02-17 DOI: 10.5750/jpm.v16i3.1967

Evangelos Vasileiou

引用次数: 0

Empirical Analysis of Bitcoin and Major Cryptocurrencies Prices 比特币和主要加密货币价格的实证分析

The Journal of Prediction Markets Pub Date : 2023-02-17 DOI: 10.5750/jpm.v16i3.1949

Isik Akin, H. Şatıroğlu

引用次数: 0

Interaction of Onshore and Offshore Rupee Markets 在岸和离岸卢比市场的相互作用

The Journal of Prediction Markets Pub Date : 2023-02-17 DOI: 10.5750/jpm.v16i3.1950

Gaurav Raizada, S. N. Rao

引用次数: 0

Predicting the Supply chain impacts on investment behaviour due to the COVID-19 outbreak - Evidence from Indian Stock Market 预测2019冠状病毒病疫情对投资行为的供应链影响——来自印度股市的证据

The Journal of Prediction Markets Pub Date : 2023-02-17 DOI: 10.5750/jpm.v16i3.1951

J. Seal, A. Paul

{"title":"Predicting the Supply chain impacts on investment behaviour due to the COVID-19 outbreak - Evidence from Indian Stock Market","authors":"J. Seal, A. Paul","doi":"10.5750/jpm.v16i3.1951","DOIUrl":"https://doi.org/10.5750/jpm.v16i3.1951","url":null,"abstract":"Purpose: As the Covid-19 virus originated from China, there was an anti-China sentiment all over the world. The purpose of our study is to find out whether this anti-China sentiment affected the stock return of the companies dependent on Chinese supply chain vis-à-vis the companies those do not have a Chinese supply chain link. \u0000Methodology: To analyze the impact of announcements on lockdown and relief measures by the government on stock market data, we use the dummy variable approach in the event methodology suggested by Karafiath (1988). We observe the stock market reaction to lockdown and relief measure announcements on consecutive seven days after the announcement. \u0000Findings: Overall findings show us that investors did not have a negative outlook on firms with Chinese suppliers. The investors are either not aware of the companies' Chinese supply link or do not consider these at the time of investing. The potential problems associated with supply chain disruptions are overlooked if we do not consider the supply chain information when investing. \u0000Originality: Our paper is unique because there is no study on the supply chain glitches of Indian companies’ dependent on the Chinese supply chain due to the Covid-19 breakout.","PeriodicalId":352536,"journal":{"name":"The Journal of Prediction Markets","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115086758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Prediction, Risk Assessment and Comparison of Selected Emerging Markets' Stock Indices During COVID-19 Pandemic Using the Coherent Measure 基于相干测度的新冠肺炎大流行期间新兴市场股票指数预测、风险评估及比较

The Journal of Prediction Markets Pub Date : 2023-02-17 DOI: 10.5750/jpm.v16i3.1974

P. Das, Anarghya Das

{"title":"Prediction, Risk Assessment and Comparison of Selected Emerging Markets' Stock Indices During COVID-19 Pandemic Using the Coherent Measure","authors":"P. Das, Anarghya Das","doi":"10.5750/jpm.v16i3.1974","DOIUrl":"https://doi.org/10.5750/jpm.v16i3.1974","url":null,"abstract":"In this study, we modeled the log-return of three emerging markets' stock indices, namely, Shanghai SSE, Russia MOEX, and Bombay Stock Exchange Sensex using the generalized hyperbolic family of distributions. We found the generalized hyperbolic family of distributions as the best fit for describing the probability density based on AIC and likelihood ratio test. The coherent risk measure, i.e., the expected shortfall, predicted using the best fit probability distribution, was used as a market risk quantification metric. During the COVID-19 period, the Indian stock market showed maximum market risk, followed by the Russian. The Chinese market showed the least market risk. Our experiment demonstrated a significant (p = 0.000) difference in the three markets concerning the coherent risk at different probability levels from 0.001 to 0.05 in the COVID-19 period using the Jonckheere-Terpstra test. The coherent market risk increased substantially in the Indian and Russian markets during the COVID-19 pandemic compared to the pre-COVID-19 period. However, in the Chinese market, we found that the coherent risk decreased during the COVID-19 period compared to the pre-COVID-19 period. We carried out the empirical study using the adjusted daily closing values of SSE, MOEX, and Sensex from July 2018 to July 2021 and dividing the data sets into pre-COVID-19 and COVID-19 periods based on the first emergence of the COVID-19 case.","PeriodicalId":352536,"journal":{"name":"The Journal of Prediction Markets","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129180625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1