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Predictive Power of An Ensemble Model for Cryptocurrency Forecasting 加密货币预测集成模型的预测能力
The Journal of Prediction Markets Pub Date : 2022-08-25 DOI: 10.5750/jpm.v16i1.1877
Manas Tripathi, Bhavya Tripathi
{"title":"Predictive Power of An Ensemble Model for Cryptocurrency Forecasting","authors":"Manas Tripathi, Bhavya Tripathi","doi":"10.5750/jpm.v16i1.1877","DOIUrl":"https://doi.org/10.5750/jpm.v16i1.1877","url":null,"abstract":"Cryptocurrencies have received much attention amongst investors and policymakers due to the innovative features and simplicity. However, prices of the cryptocurrencies are nonlinear and volatile, which creates challenges for the investors to forecast the cryptocurrency prices. The present study takes the price data of two important cryptocurrencies, i.e., Bitcoin and Ripple, for 2013 to 2020. The study presents the forecasting accuracy of statistical models such as random walk (RW) and autoregressive integrated moving average (ARIMA), and machine learning models such as artificial neural network (ANN) and ensemble model. The study develops the ensemble of RW, ARIMA, and ANN. The study compares the predictive power of all the models and demonstrates that the forecasting accuracy of the ensemble model is better than all the component models, i.e., RW, ARIMA, and ANN. The results of the study have several implications for investors, traders, and policymakers.","PeriodicalId":352536,"journal":{"name":"The Journal of Prediction Markets","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116318794","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 for the 2020 United States Presidential Election Using Machine Learning Algorithm: Lasso Regression 使用机器学习算法预测2020年美国总统大选:Lasso回归
The Journal of Prediction Markets Pub Date : 2022-08-25 DOI: 10.5750/jpm.v16i1.1863
P. Sinha, Aniket Verma, P. Shah, Jahnavi Singh, Utkarsh Panwar
{"title":"Prediction for the 2020 United States Presidential Election Using Machine Learning Algorithm: Lasso Regression","authors":"P. Sinha, Aniket Verma, P. Shah, Jahnavi Singh, Utkarsh Panwar","doi":"10.5750/jpm.v16i1.1863","DOIUrl":"https://doi.org/10.5750/jpm.v16i1.1863","url":null,"abstract":"This paper aims at determining the various economic and non-economic factors that can influence the voting behaviour in the forthcoming United States Presidential Election using Lasso regression, a Machine learning algorithm. Even though contemporary discussions on the subject of the United States Presidential Election suggest that the level of unemployment in the economy will be a significant factor in determining the result of the election, in our study, it has been found that the rate of unemployment will not be the only significant factor in forecasting the election. However, various other economic factors such as the inflation rate, rate of economic growth, and exchange rates will not have a significant influence on the election result. The June Gallup Rating, is not the only significant factor for determining the result of the forthcoming presidential election. In addition to the June Gallup Rating, various other non-economic factors such as the performance of the contesting political parties in the midterm elections, Campaign spending by the contesting parties and scandals of the Incumbent President will also play a significant role in determining the result of the forthcoming United States Presidential Election. The paper explores the influence of all the aforementioned economic and non-economic factors on the voting behaviour of the voters in the forthcoming United States Presidential Election. \u0000 The proposed Lasso Regression model forecasts that the vote share for the incumbent Republican Party to be 41.63% in the 2020 US presidential election. This means that the incumbent party is most likely to lose the upcoming election.","PeriodicalId":352536,"journal":{"name":"The Journal of Prediction Markets","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121267845","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
Quantifying Stock News Relevance in Indian Markets 量化股票新闻相关性在印度市场
The Journal of Prediction Markets Pub Date : 2022-08-25 DOI: 10.5750/jpm.v16i1.1864
N. Rani, Rakshika Gupta
{"title":"Quantifying Stock News Relevance in Indian Markets","authors":"N. Rani, Rakshika Gupta","doi":"10.5750/jpm.v16i1.1864","DOIUrl":"https://doi.org/10.5750/jpm.v16i1.1864","url":null,"abstract":"Researchers have extensively tried machine learning algorithms in news classification and related quantitative finance domains in the past. Stock market investors look forward to being able to predict stock prices successfully not only to get the best returns but also to minimize the risk of losses with a forecast of stock prices and movement of the stock exchange depending upon the type of news. In this paper, we hypothesize that any news that comes to the market can broadly be classified into two types: Class A- News that has an effect such that it leads to a rise in the stock prices of the reference stock and a fall in the stock prices of its competitor stocks, or vice versa, and Class B- News that results in a simultaneous surge or decline in the stock prices of the reference stocks and its competitor stocks alike. This study is an effort to mathematically validate this hypothesis. \u0000This domain hasn’t been explored, and through our work, we try to demonstrate the capability of the existence of a pattern in the market, which could then be used for building automated trading strategies. We also adopt a unique approach to model the data as a supervised machine learning problem and by solving, on obtaining an accuracy of 66.5% we prove that such patterns exist and further suggest research inputs on ideas derived from this. \u0000 ","PeriodicalId":352536,"journal":{"name":"The Journal of Prediction Markets","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126076376","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
Normality Tests and its Power against Alternative Distributions: An Empirical Analysis on Emerging Asian Stock Index Returns. 正态性检验及其对另类分布的影响:新兴亚洲股票指数收益的实证分析。
The Journal of Prediction Markets Pub Date : 2022-08-25 DOI: 10.5750/jpm.v16i1.1852
Muneer Shaik
{"title":"Normality Tests and its Power against Alternative Distributions: An Empirical Analysis on Emerging Asian Stock Index Returns.","authors":"Muneer Shaik","doi":"10.5750/jpm.v16i1.1852","DOIUrl":"https://doi.org/10.5750/jpm.v16i1.1852","url":null,"abstract":"In this paper, we investigate the power of various normality tests against alternative distributions using Monte Carlo simulation experiments. We use seven different normality tests classified as moments tests, correlation and regression tests, and empirical distribution functional tests against six symmetric and four asymmetric alternative distributions. We also perform the rank analysis for the power of the normality tests. Furthermore, we conduct an empirical analysis of five emerging Asian stock indices (India, Indonesia, Malaysia, Singapore, and Taiwan) to understand whether the returns follow a normal distribution or not during the period from January 2000 to January 2020. We find that emerging Asian stock index returns do not follow normal distribution irrespective of the different frequencies of the data.","PeriodicalId":352536,"journal":{"name":"The Journal of Prediction Markets","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126978991","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
Predicting In-Play Match Decisions 预测游戏中的比赛决策
The Journal of Prediction Markets Pub Date : 2021-11-16 DOI: 10.5750/jpm.v15i3.1987
L. Williams, J. Kennedy
{"title":"Predicting In-Play Match Decisions","authors":"L. Williams, J. Kennedy","doi":"10.5750/jpm.v15i3.1987","DOIUrl":"https://doi.org/10.5750/jpm.v15i3.1987","url":null,"abstract":"We investigate the effect of the crowd on the decisions of match officials within a professional sports environment. We do this using data from 9,835 football (soccer) matches, comparing matches played behind closed doors because of the COVID-19 pandemic with those played before a crowd. We find that home advantage in terms of in-play decisions by match officials is significantly reduced in the absence of crowds. Examining the decisions of football referees, we find that away teams receive fewer yellow and red cards when playing in an empty stadium compared to matches with a crowd. This suggests the decisions of officials are influenced by the social pressure on match officials of a crowd, and that forecasts of match-related events and outcomes should be adjusted accordingly.","PeriodicalId":352536,"journal":{"name":"The Journal of Prediction Markets","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123971631","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
Holiday Effects in the US Equity Futures Markets 美国股票期货市场的假日效应
The Journal of Prediction Markets Pub Date : 2021-11-16 DOI: 10.5750/jpm.v15i3.1964
W. Ziemba, Constantine Dzhabarov
{"title":"Holiday Effects in the US Equity Futures Markets","authors":"W. Ziemba, Constantine Dzhabarov","doi":"10.5750/jpm.v15i3.1964","DOIUrl":"https://doi.org/10.5750/jpm.v15i3.1964","url":null,"abstract":"\u0000 \u0000 \u0000We investigate the holiday effect in US equity futures markets during three sub-periods 1993-2011, 1993-2020, and during the 2020 covid-19 year for small cap stocks measured by the Russell2000 and large cap stocks measured by the S&P500. All the days from -3 before the holiday to -1 had gains and for the large caps there were gains on +1 and +2. The effect is stronger for the small caps. The year 2020 had results similar to the longer series with positive gains. We show the various holidays by holiday day and observe that the -3 day had gains on all the holidays whereas the other days did not. The effect has diminished in the 1990s and 2000s and only the -3 day is statistically significant. The -3 day in the futures anticipates the cash move on -1 day. \u0000 \u0000 \u0000","PeriodicalId":352536,"journal":{"name":"The Journal of Prediction Markets","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127397718","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
New Entry and Strategic Group Emergence in the Soccer Betting Market 足球博彩市场的新进入者和战略集团的出现
The Journal of Prediction Markets Pub Date : 2021-11-16 DOI: 10.5750/jpm.v15i3.1988
A. Bruce, Anastasios Oikonomidis, M. Sung, Johnnie E. V. Johnson
{"title":"New Entry and Strategic Group Emergence in the Soccer Betting Market","authors":"A. Bruce, Anastasios Oikonomidis, M. Sung, Johnnie E. V. Johnson","doi":"10.5750/jpm.v15i3.1988","DOIUrl":"https://doi.org/10.5750/jpm.v15i3.1988","url":null,"abstract":"","PeriodicalId":352536,"journal":{"name":"The Journal of Prediction Markets","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123863245","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
Who are the most important players in team sports 谁是团队运动中最重要的运动员
The Journal of Prediction Markets Pub Date : 2021-11-16 DOI: 10.5750/jpm.v15i3.1963
W. Ziemba, L. MacLean
{"title":"Who are the most important players in team sports","authors":"W. Ziemba, L. MacLean","doi":"10.5750/jpm.v15i3.1963","DOIUrl":"https://doi.org/10.5750/jpm.v15i3.1963","url":null,"abstract":"We present a statistical model using box scores from games as data to develop a theory to determine which players are the most important to success in team sports. We apply this to NBA basketball, NFL football and NHL hockey. The results show that the most important players for team success are not necessarily the most outstanding players. Moreover, its generally much more successful to have several good players rather than a single outstanding player. In NBA basketball, NFL football, and NHL hockey defensive players often stand out. The results are useful for good team construction, game strategy and recruiting of players.","PeriodicalId":352536,"journal":{"name":"The Journal of Prediction Markets","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121484091","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
Revisiting the Balanced Book Hypothesis – Bettor Preferences and Results in the NFL 重新审视平衡账面假说- NFL的投注者偏好和结果
The Journal of Prediction Markets Pub Date : 2021-11-16 DOI: 10.5750/jpm.v15i3.1961
R. Paul, A. Weinbach
{"title":"Revisiting the Balanced Book Hypothesis – Bettor Preferences and Results in the NFL","authors":"R. Paul, A. Weinbach","doi":"10.5750/jpm.v15i3.1961","DOIUrl":"https://doi.org/10.5750/jpm.v15i3.1961","url":null,"abstract":"Data on betting percentages, both in terms of number of bets and actual money wagered, is still difficult to find.  Sports Action Network, in their premium access service, does provide this data in terms of both number of bets and money bet.  For the2020 NFL season, it was found that the balanced book could be rejected as bettors were shown to prefer road favorites, big favorites, and the over at the highest totals.  Allowing this imbalance in the sides market appeared profitable for the book as the underdog won more often than implied by efficiency, while totals were evenly split.","PeriodicalId":352536,"journal":{"name":"The Journal of Prediction Markets","volume":"185 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126776455","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
Does the impact of the COVID-19 pandemic influence the FX? A note. COVID-19大流行是否会影响外汇?一份报告中指出。
The Journal of Prediction Markets Pub Date : 2021-08-27 DOI: 10.5750/jpm.v15i2.1865
Evangelos Vasileiou
{"title":"Does the impact of the COVID-19 pandemic influence the FX? A note.","authors":"Evangelos Vasileiou","doi":"10.5750/jpm.v15i2.1865","DOIUrl":"https://doi.org/10.5750/jpm.v15i2.1865","url":null,"abstract":"This note shows that the effective response of a country in its battle against COVID-19 influences the exchange rate of its currency. Particularly, we examine the GBPUSD, AUDUSD and AUDGBP pairs of currency during the COVID-19 outbreak and the results show that the domestic currency of the country which documents more COVID-19 cases in each pair is depreciated against the foreign one. Therefore, a country which cannot effectively mitigate the impact of COVID-19 and whose currency is depreciated may present further economic consequences in the future. Such consequences extend beyond economic recession and may include sovereign and interest rate risk. These findings may be useful for policy makers in order to estimate the cost of the pandemic.","PeriodicalId":352536,"journal":{"name":"The Journal of Prediction Markets","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124582310","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
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