Matches in SemOpenAlex for { <https://semopenalex.org/work/W2890329545> ?p ?o ?g. }
Showing items 1 to 90 of
90
with 100 items per page.
- W2890329545 abstract "This paper explores a common machine learning tool, the kernel ridge regression, as applied to financial volatility forecasting. It is shown that kernel ridge provides reliable forecast improvements to both a linear specification, and a fitted nonlinear specification which represents well known empirical features from volatility modeling. Therefore, the kernel ridge specification is still finding some nonlinear improvements that are not part of the usual volatility modeling toolkit. Various diagnostics show it to be a reliable and useful tool. Finally, the results are applied in a dynamic volatility control trading strategy. The kernel ridge results again show improvements over linear modeling tools when applied to building a dynamic strategy." @default.
- W2890329545 created "2018-09-27" @default.
- W2890329545 creator A5003388525 @default.
- W2890329545 date "2018-01-01" @default.
- W2890329545 modified "2023-09-27" @default.
- W2890329545 title "Forecasting Realized Volatility With Kernel Ridge Regression" @default.
- W2890329545 cites W1493879008 @default.
- W2890329545 cites W1503398984 @default.
- W2890329545 cites W1543574586 @default.
- W2890329545 cites W1823577794 @default.
- W2890329545 cites W1965402578 @default.
- W2890329545 cites W1965635191 @default.
- W2890329545 cites W1973959218 @default.
- W2890329545 cites W1999814123 @default.
- W2890329545 cites W2000412613 @default.
- W2890329545 cites W2021824814 @default.
- W2890329545 cites W2024197312 @default.
- W2890329545 cites W2061160212 @default.
- W2890329545 cites W2070516830 @default.
- W2890329545 cites W2078718287 @default.
- W2890329545 cites W2146134639 @default.
- W2890329545 cites W2158595111 @default.
- W2890329545 cites W2161117089 @default.
- W2890329545 cites W2281985070 @default.
- W2890329545 cites W2298264596 @default.
- W2890329545 cites W2774564222 @default.
- W2890329545 cites W2964142097 @default.
- W2890329545 cites W3090813300 @default.
- W2890329545 cites W3121757665 @default.
- W2890329545 cites W3123351111 @default.
- W2890329545 cites W3143394208 @default.
- W2890329545 cites W63255284 @default.
- W2890329545 doi "https://doi.org/10.2139/ssrn.3229272" @default.
- W2890329545 hasPublicationYear "2018" @default.
- W2890329545 type Work @default.
- W2890329545 sameAs 2890329545 @default.
- W2890329545 citedByCount "0" @default.
- W2890329545 crossrefType "journal-article" @default.
- W2890329545 hasAuthorship W2890329545A5003388525 @default.
- W2890329545 hasConcept C114614502 @default.
- W2890329545 hasConcept C127313418 @default.
- W2890329545 hasConcept C149782125 @default.
- W2890329545 hasConcept C151730666 @default.
- W2890329545 hasConcept C162324750 @default.
- W2890329545 hasConcept C24189920 @default.
- W2890329545 hasConcept C32277403 @default.
- W2890329545 hasConcept C33923547 @default.
- W2890329545 hasConcept C41008148 @default.
- W2890329545 hasConcept C74193536 @default.
- W2890329545 hasConcept C85393063 @default.
- W2890329545 hasConcept C91602232 @default.
- W2890329545 hasConceptScore W2890329545C114614502 @default.
- W2890329545 hasConceptScore W2890329545C127313418 @default.
- W2890329545 hasConceptScore W2890329545C149782125 @default.
- W2890329545 hasConceptScore W2890329545C151730666 @default.
- W2890329545 hasConceptScore W2890329545C162324750 @default.
- W2890329545 hasConceptScore W2890329545C24189920 @default.
- W2890329545 hasConceptScore W2890329545C32277403 @default.
- W2890329545 hasConceptScore W2890329545C33923547 @default.
- W2890329545 hasConceptScore W2890329545C41008148 @default.
- W2890329545 hasConceptScore W2890329545C74193536 @default.
- W2890329545 hasConceptScore W2890329545C85393063 @default.
- W2890329545 hasConceptScore W2890329545C91602232 @default.
- W2890329545 hasLocation W28903295451 @default.
- W2890329545 hasOpenAccess W2890329545 @default.
- W2890329545 hasPrimaryLocation W28903295451 @default.
- W2890329545 hasRelatedWork W1902964007 @default.
- W2890329545 hasRelatedWork W2017715655 @default.
- W2890329545 hasRelatedWork W2025983492 @default.
- W2890329545 hasRelatedWork W2031770044 @default.
- W2890329545 hasRelatedWork W2145805781 @default.
- W2890329545 hasRelatedWork W2269808627 @default.
- W2890329545 hasRelatedWork W2366487028 @default.
- W2890329545 hasRelatedWork W2384689389 @default.
- W2890329545 hasRelatedWork W2612344772 @default.
- W2890329545 hasRelatedWork W2614754869 @default.
- W2890329545 hasRelatedWork W2912319196 @default.
- W2890329545 hasRelatedWork W2974308494 @default.
- W2890329545 hasRelatedWork W2974926361 @default.
- W2890329545 hasRelatedWork W3121421590 @default.
- W2890329545 hasRelatedWork W3134772730 @default.
- W2890329545 hasRelatedWork W3139665642 @default.
- W2890329545 hasRelatedWork W3148050929 @default.
- W2890329545 hasRelatedWork W3166281041 @default.
- W2890329545 hasRelatedWork W3177819893 @default.
- W2890329545 hasRelatedWork W2184736014 @default.
- W2890329545 isParatext "false" @default.
- W2890329545 isRetracted "false" @default.
- W2890329545 magId "2890329545" @default.
- W2890329545 workType "article" @default.