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The Influence of Renewables on Electricity Price Forecasting: A Robust Approach 可再生能源对电价预测的影响:一个稳健的方法
Econometric Modeling: Capital Markets - Forecasting eJournal Pub Date : 2018-09-21 DOI: 10.2139/ssrn.3253021
L. Grossi, F. Nan
{"title":"The Influence of Renewables on Electricity Price Forecasting: A Robust Approach","authors":"L. Grossi, F. Nan","doi":"10.2139/ssrn.3253021","DOIUrl":"https://doi.org/10.2139/ssrn.3253021","url":null,"abstract":"In this paper a robust approach to modelling electricity spot prices is introduced. Differently from what has been recently done in the literature on electricity price forecasting, where the attention has been mainly drawn by the prediction of spikes, the focus of this contribution is on the robust estimation of nonlinear SETARX models (Self-Exciting Threshold Auto Regressive models with eXogenous regressors). In this way, parameters estimates are not, or very lightly, influenced by the presence of extreme observations and the large majority of prices, which are not spikes, could be better forecasted. A Monte Carlo study is carried out in order to select the best weighting function for Generalized M-estimators of SETAR processes. A robust procedure to select and estimate nonlinear processes for electricity prices is introduced, including robust tests for stationarity and nonlinearity and robust information criteria. The application of the procedure to the Italian electricity market reveals the forecasting superiority of the robust GM-estimator based on the polynomial weighting function respect to the non-robust Least Squares estimator. Finally, the introduction of external regressors in the robust estimation of SETARX processes contributes to the improvement of the forecasting ability of the model.","PeriodicalId":11495,"journal":{"name":"Econometric Modeling: Capital Markets - Forecasting eJournal","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88395188","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: 42
MVA: Future IM for Client Trades & Dynamic Hedges MVA:客户交易和动态对冲的未来即时通讯
Econometric Modeling: Capital Markets - Forecasting eJournal Pub Date : 2018-08-21 DOI: 10.2139/ssrn.3247367
A. Antonov, Serguei Issakov, A. McClelland
{"title":"MVA: Future IM for Client Trades & Dynamic Hedges","authors":"A. Antonov, Serguei Issakov, A. McClelland","doi":"10.2139/ssrn.3247367","DOIUrl":"https://doi.org/10.2139/ssrn.3247367","url":null,"abstract":"Servicing clients can require posting Initial Margin (IM) for client trades, and for their hedges. IM should be forecast for both and reflected in MVA. For non-vanillas with dynamic hedges, forecasting hedge-trade IM is challenging as future hedge ratios are necessary, and future sensitivities are difficult to compute. However, future sensitivities are already required to forecast client-trade IM, and thus future hedges (e.g., delta and vega) can be determined. In turn, this allows IM requirements to be forecast for cleared hedges (e.g., swaps) and non-cleared hedges (e.g., swaptions).","PeriodicalId":11495,"journal":{"name":"Econometric Modeling: Capital Markets - Forecasting eJournal","volume":"177 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76872525","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
An Econometric Panel-Midas Model of Asset Returns in the Brazilian Stock Market 巴西股市资产收益的计量面板-迈达斯模型
Econometric Modeling: Capital Markets - Forecasting eJournal Pub Date : 2018-08-15 DOI: 10.2139/ssrn.3231555
Aline Moura Costa da Silva, Otavio Ribeiro de Medeiros
{"title":"An Econometric Panel-Midas Model of Asset Returns in the Brazilian Stock Market","authors":"Aline Moura Costa da Silva, Otavio Ribeiro de Medeiros","doi":"10.2139/ssrn.3231555","DOIUrl":"https://doi.org/10.2139/ssrn.3231555","url":null,"abstract":"The paper describes the specification, estimation, and testing of an unrestricted structural econometric model design to explain and forecast individual returns of securities listed on the Brazilian stock market. The model's explanatory variables include macroeconomic, fundamental and behavioural variables which are sampled at different frequencies, since they are informed within different time periods, i.e. daily, monthly or quarterly. Accordingly, the model is specified and estimated using the MIDAS (Mixed Data Sampling) regression methodology, which supports estimation of regressions with variables sampled at different frequencies. The sample includes non-financial institutions listed in the Brazilian stock exchange from 2010 to 2016. The results indicate that the model is robust in explaining and forecasting quarterly returns of individual shares listed in that market.","PeriodicalId":11495,"journal":{"name":"Econometric Modeling: Capital Markets - Forecasting eJournal","volume":"48 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75143412","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
Detecting and Measuring Nonlinearity 非线性检测与测量
Econometric Modeling: Capital Markets - Forecasting eJournal Pub Date : 2018-08-09 DOI: 10.3390/ECONOMETRICS6030037
Rachidi Kotchoni
{"title":"Detecting and Measuring Nonlinearity","authors":"Rachidi Kotchoni","doi":"10.3390/ECONOMETRICS6030037","DOIUrl":"https://doi.org/10.3390/ECONOMETRICS6030037","url":null,"abstract":"This paper proposes an approach to measure the extent of nonlinearity of the exposure of a financial asset to a given risk factor. The proposed measure exploits the decomposition of a conditional expectation into its linear and nonlinear components. We illustrate the method with the measurement of the degree of nonlinearity of a European style option with respect to the underlying asset. Next, we use the method to identify the empirical patterns of the return-risk trade-off on the SP500. The results are strongly supportive of a nonlinear relationship between expected return and expected volatility. The data seem to be driven by two regimes: one regime with a positive return-risk trade-off and one with a negative trade-off.","PeriodicalId":11495,"journal":{"name":"Econometric Modeling: Capital Markets - Forecasting eJournal","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76939593","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: 3
A Study of Applicability of Bankruptcy Prediction Models for Small Businesses 小企业破产预测模型的适用性研究
Econometric Modeling: Capital Markets - Forecasting eJournal Pub Date : 2018-08-01 DOI: 10.2139/ssrn.3677834
E. Kiseleva
{"title":"A Study of Applicability of Bankruptcy Prediction Models for Small Businesses","authors":"E. Kiseleva","doi":"10.2139/ssrn.3677834","DOIUrl":"https://doi.org/10.2139/ssrn.3677834","url":null,"abstract":"The paper investigates predictive ability of existing bankruptcy prediction models suitable for small business by using dates of accounting report of Russian’s firms. Combination of financial ratios analysis with bankruptcy prediction models’ testing made it possible to identify the models showing high predictive ability. Study also provides applicable model for small business. The study is based on financial statements data about one hundred enterprises of small businesses, divided two types: failed and non-failed firms. The results of the study would be useful to many users such as financial analysts, board of small enterprises, lenders, auditors, tax inspectors.","PeriodicalId":11495,"journal":{"name":"Econometric Modeling: Capital Markets - Forecasting eJournal","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87821452","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
The Impact of Disclosure Quality on Analysts’ Forecast in China 中国信息披露质量对分析师预测的影响
Econometric Modeling: Capital Markets - Forecasting eJournal Pub Date : 2018-07-01 DOI: 10.2139/ssrn.3325739
Ming Liu, B. Sohn, C. Yuen
{"title":"The Impact of Disclosure Quality on Analysts’ Forecast in China","authors":"Ming Liu, B. Sohn, C. Yuen","doi":"10.2139/ssrn.3325739","DOIUrl":"https://doi.org/10.2139/ssrn.3325739","url":null,"abstract":"Since the establishment of the Shenzhen Stock Exchange’s (SZSE) Disclosure Ranking System in 2001, listed companies’ disclosure quality has been increasing year by year in China. Better disclosure quality helps reduce the information asymmetry between the managers of those companies and external investors. This implies that analysts can access more timely, valuable, and reliable information to understand companies’ overall operating status, financial reports, and accrual components of earnings. As analysts can save time and costs when disclosure quality is higher, their earnings forecast error and optimism bias are reduced and the divergence in their opinions about the firm prospects decreases. We investigate whether disclosure quality affects analysts’ forecasting behavior in China’s securities market using the disclosure ranking data obtained from SZSE, and find that higher disclosure quality improves analysts’ forecast accuracy, alleviates forecast optimism, and reduces forecast dispersion.","PeriodicalId":11495,"journal":{"name":"Econometric Modeling: Capital Markets - Forecasting eJournal","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89554603","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
Volatility Forecasting Across Tanker Freight Rates: The Role of Oil Price Shocks 油轮运价波动预测:油价冲击的作用
Econometric Modeling: Capital Markets - Forecasting eJournal Pub Date : 2018-07-01 DOI: 10.2139/ssrn.3332262
K. Gavriilidis, Dimos S. Kambouroudis, Katerina Tsakou, Dimitris A. Tsouknidis
{"title":"Volatility Forecasting Across Tanker Freight Rates: The Role of Oil Price Shocks","authors":"K. Gavriilidis, Dimos S. Kambouroudis, Katerina Tsakou, Dimitris A. Tsouknidis","doi":"10.2139/ssrn.3332262","DOIUrl":"https://doi.org/10.2139/ssrn.3332262","url":null,"abstract":"This paper examines whether the inclusion of oil price shocks of different origin as exogenous variables in a wide set of GARCH-X models improves the accuracy of their volatility forecasts for spot and 1-year time-charter tanker freight rates. Kilian's (2009) oil price shocks of different origin enter GARCH-X models which, among other stylized facts of the freight rates examined, take into account the presence of asymmetric and long-memory effects in tanker freight rates. The results reveal that the inclusion of aggregate oil demand shocks and precautionary oil-specific demand shocks (price) significantly improves the accuracy of the volatility forecasts drawn.","PeriodicalId":11495,"journal":{"name":"Econometric Modeling: Capital Markets - Forecasting eJournal","volume":"45 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89100291","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: 51
Is the Cycle the Trend? Evidence from the Views of International Forecasters 周期是趋势吗?来自国际预测者观点的证据
Econometric Modeling: Capital Markets - Forecasting eJournal Pub Date : 2018-07-01 DOI: 10.5089/9781484363980.001
John C. Bluedorn, D. Leigh
{"title":"Is the Cycle the Trend? Evidence from the Views of International Forecasters","authors":"John C. Bluedorn, D. Leigh","doi":"10.5089/9781484363980.001","DOIUrl":"https://doi.org/10.5089/9781484363980.001","url":null,"abstract":"We revisit the conventional view that output fluctuates around a stable trend by analyzing professional long-term forecasts for 38 advanced and emerging market economies. If transitory deviations around a trend dominate output fluctuations, then forecasters should not change their long-term output level forecasts following an unexpected change in current period output. By contrast, an analysis of Consensus Economics forecasts since 1989 suggest that output forecasts are super-persistent—an unexpected 1 percent upward revision in current period output typically translates into a revision of ten year-ahead forecasted output by about 2 percent in both advanced and emerging markets. Drawing upon evidence from the behavior of forecast errors, the persistence of actual output is typically weaker than forecasters expect, but still consistent with output shocks normally having large and permanent level effects.","PeriodicalId":11495,"journal":{"name":"Econometric Modeling: Capital Markets - Forecasting eJournal","volume":"113 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84213586","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: 12
Forecasting Cryptocurrencies: A Comparison of GARCH Models 预测加密货币:GARCH模型的比较
Econometric Modeling: Capital Markets - Forecasting eJournal Pub Date : 2018-06-07 DOI: 10.2139/ssrn.3195704
Giovanni Angelini, S. Emili
{"title":"Forecasting Cryptocurrencies: A Comparison of GARCH Models","authors":"Giovanni Angelini, S. Emili","doi":"10.2139/ssrn.3195704","DOIUrl":"https://doi.org/10.2139/ssrn.3195704","url":null,"abstract":"In this paper we enhance the literature exploring the forecasting capability of six alternatives GARCH-type models to predict volatility of four of the most traded cryptocurrencies: Bitcoin, Ethereum, Ripple and Litecoin. The analysis is performed on daily data from 1st March 2016 to 28th February 2018.","PeriodicalId":11495,"journal":{"name":"Econometric Modeling: Capital Markets - Forecasting eJournal","volume":"81 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76099749","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: 3
Determinants and Forecasting of Jackpot Stock Returns 头奖股票收益的决定因素与预测
Econometric Modeling: Capital Markets - Forecasting eJournal Pub Date : 2018-05-23 DOI: 10.2139/ssrn.3183821
David Miersch, Soenke Sievers, C. Homburg
{"title":"Determinants and Forecasting of Jackpot Stock Returns","authors":"David Miersch, Soenke Sievers, C. Homburg","doi":"10.2139/ssrn.3183821","DOIUrl":"https://doi.org/10.2139/ssrn.3183821","url":null,"abstract":"This paper investigates the determinants of six different lottery-like stock return definitions that have been analyzed separately in prior literature. While we focus on information uncertainty as captured by accounting information, mispricing, institutional ownership and default risk as main determinants, our comprehensive framework investigates 47 independent variables as drivers of these particular stocks. Using state-of-the-art variable selection techniques, namely, stepwise regressions and the LASSO approach, we identify key drivers that differ based on the lottery stock definition used. Based on these insights, we present improved forecasting models for predicting jackpot returns.","PeriodicalId":11495,"journal":{"name":"Econometric Modeling: Capital Markets - Forecasting eJournal","volume":"27 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83343457","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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