ERN: Time-Series Models (Single) (Topic)最新文献

Better the Devil You Know: Improved Forecasts from Imperfect Models 更好的魔鬼你知道:改进预测从不完美的模型

ERN: Time-Series Models (Single) (Topic) Pub Date : 2021-08-31 DOI: 10.2139/ssrn.3925545

D. Oh, Andrew J. Patton

引用次数: 4

Reducing the Risk in Tail Risk Forecasting Models 降低尾部风险预测模型中的风险

ERN: Time-Series Models (Single) (Topic) Pub Date : 2020-12-17 DOI: 10.2139/ssrn.3750440

A. Clements, C. Drovandi, Dan Li

引用次数: 1

Time-Series Heston Model Calibration Using a Trinomial Tree 基于三叉树的时间序列赫斯顿模型校正

ERN: Time-Series Models (Single) (Topic) Pub Date : 2020-10-25 DOI: 10.2139/ssrn.3718697

Michael A. Clayton

{"title":"Time-Series Heston Model Calibration Using a Trinomial Tree","authors":"Michael A. Clayton","doi":"10.2139/ssrn.3718697","DOIUrl":"https://doi.org/10.2139/ssrn.3718697","url":null,"abstract":"In this work a trinomial tree representing the Heston model variance process is used to estimate the parameters for the Heston stochastic volatility model using historical daily observations of the asset. The results include estimates for all Heston model parameters as well as an estimated most likely path for the latent variance process. The variance tree is constructed using a somewhat novel approach that uses a non-uniform, recombining grid, and some analysis is included to justify the approach. The probability of the observed asset path is computed as an average over all variance paths using this tree, with the asset return observations approximated as normal conditional on the values of the variance at the start and end of each observation. Calibration is achieved using a reasonably generic multidimensional optimization algorithm, with the negative of the logarithm of the asset path probability computed using the trinomial tree as the objective function. Bounds are imposed on all parameters based on the ability of the tree to estimate the parameters accurately, in particular noting that with increasing the volatility of variance the grid becomes coarser, and there is therefore a limit to how large this parameter can be in order for the tree to accurately resolve the variance distribution. Reasonable convergence with increasing number of asset return observations is demonstrated for all parameters as well as the latent variance estimation, using paths simulated from the Heston model. Results from the calibration to four foreign exchange processes are also provided, showing that the results are reasonably stable.","PeriodicalId":418701,"journal":{"name":"ERN: Time-Series Models (Single) (Topic)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133484129","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

Estimation of a Time-Varying Parameter from Long Range Dependent Data 基于长距相关数据的时变参数估计

ERN: Time-Series Models (Single) (Topic) Pub Date : 2020-10-04 DOI: 10.2139/ssrn.3653458

M. Tseng

引用次数: 0

Time Series Momentum in the US Stock Market: Empirical Evidence and Theoretical Implications 美国股票市场的时间序列动量:经验证据和理论意义

ERN: Time-Series Models (Single) (Topic) Pub Date : 2020-04-26 DOI: 10.2139/ssrn.3585714

Valeriy Zakamulin, Javier Giner

{"title":"Time Series Momentum in the US Stock Market: Empirical Evidence and Theoretical Implications","authors":"Valeriy Zakamulin, Javier Giner","doi":"10.2139/ssrn.3585714","DOIUrl":"https://doi.org/10.2139/ssrn.3585714","url":null,"abstract":"We start this paper by presenting compelling evidence of short-term momentum in the excess returns on the S&P Composite stock price index. For the first time ever, we assume that the excess returns follow an autoregressive process of order p, AR(p), and evaluate the parameters of this process. Armed with a fairly accurate knowledge of the momentum generating process, we continue this paper by providing a number of important theoretical implications. First, we present analytical results on the profitability of long-only and long-short time-series momentum (TSMOM) strategies. Our results suggest that the long-only TSMOM strategy is profitable, while the long-short one is not. We find that over multiple periods the risk profile of the long-only TSMOM strategy resembles the risk profile of a portfolio insurance strategy. We estimate the power of the statistical test for superiority of the TSMOM strategy and find that the power is much below the acceptable level. Consequently, any empirical study tends not to reject the null hypothesis of no profitability of TSMOM strategy. Finally, we evaluate the precision of identification of the optimal number of lags in the TSMOM rule using a standard back-testing methodology and find that this precision is extremely poor. However, we demonstrate that the performance of the TSMOM rule is robust to the choice of the number of lags.","PeriodicalId":418701,"journal":{"name":"ERN: Time-Series Models (Single) (Topic)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129173361","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: 2

Housing Price Dynamics within the U.S.: Evidence from Zip Codes with Different Demographics 美国房价动态:来自不同人口统计的邮政编码的证据

ERN: Time-Series Models (Single) (Topic) Pub Date : 2020-04-11 DOI: 10.2139/ssrn.3575021

Shahrzad Ghourchian, H. Yilmazkuday

{"title":"Housing Price Dynamics within the U.S.: Evidence from Zip Codes with Different Demographics","authors":"Shahrzad Ghourchian, H. Yilmazkuday","doi":"10.2139/ssrn.3575021","DOIUrl":"https://doi.org/10.2139/ssrn.3575021","url":null,"abstract":"We study time-series fluctuations in the United States housing market from 2010 to 2019 using the Gordon growth model. We apply a vector autoregressive model (VAR) with fixed coefficients to measure expectations at each point in time. Our results show that, using zip code level data, we are able to explain the broad movements in housing volatility with higher prediction power compared to previous studies. Using variance decomposition analysis, we find that the housing premium is the main driver of housing market fluctuations. Motivated by previous studies and using impulse response functions, we show how different components of the housing market respond over time to a shock in the interest rate in regions with different levels of income or demographics. Our findings suggest that the impact of monetary policy is bigger in the U.S. housing market when households have less income, more female members, more African Americans, or less well-educated members; a combination of these demographics and lower income in households results in a bigger impact of monetary policy in housing market, due to the necessity of housing for these families.","PeriodicalId":418701,"journal":{"name":"ERN: Time-Series Models (Single) (Topic)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124078471","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

Nowcasting Rwanda’s Quarterly GDP Using Mixed-Frequency Methods 使用混合频率方法预测卢旺达季度GDP

ERN: Time-Series Models (Single) (Topic) Pub Date : 2020-04-01 DOI: 10.2139/ssrn.3653136

O. Habimana, Didier Tabaro, Thierry Kalisa

引用次数: 0

Online Drift Estimation for Jump-Diffusion Processes 跃变扩散过程的在线漂移估计

ERN: Time-Series Models (Single) (Topic) Pub Date : 2020-02-18 DOI: 10.2139/ssrn.3540252

Theerawat Bhudisaksang, Á. Cartea

引用次数: 11

Tail Risk Monotonicity Under Temporal Aggregation in GARCH(1,1) Models GARCH(1,1)模型时间聚集下的尾部风险单调性

ERN: Time-Series Models (Single) (Topic) Pub Date : 2019-12-11 DOI: 10.2139/ssrn.3502425

P. Glasserman, D. Pirjol, Qi Wu

引用次数: 0

Nonlinear Economic Time Series as a Testbed for Dynamic Macro Models Including Finance 非线性经济时间序列作为包括金融在内的动态宏观模型的检验平台

ERN: Time-Series Models (Single) (Topic) Pub Date : 2019-06-13 DOI: 10.2139/ssrn.3453306

Michael Wood

引用次数: 0