Bitcoin and gold price returns: A quantile regression and NARDL analysis
This research analyses the sensitivity of Bitcoin returns to changes in gold price returns and some other international risk factors such as US stock market returns, interest rates, crude oil prices, the volatility index of the American stock market (VIX) and the Saint Louis financial stress index (...
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description | This research analyses the sensitivity of Bitcoin returns to changes in gold price returns and some other international risk factors such as US stock market returns, interest rates, crude oil prices, the volatility index of the American stock market (VIX) and the Saint Louis financial stress index (STLFSI). This study applies the quantile regression approach for the 2010–2018 period. For robustness, this paper splits the whole sample period into two different subsamples: a more volatile and a less volatile sub-period. Moreover, to capture both long- and short-run asymmetries between Bitcoin and gold price returns, an asymmetric nonlinear cointegration approach (NARDL) is applied. The results evidence that the most relevant risk factor is the VIX index, followed by changes in the STLFSI stress index, and both show negative and statistically significant effects on Bitcoin returns in most periods and quantiles. The US stock market returns have statistically significant effects (with positive sign) on Bitcoin returns in all periods and specifically in high quantiles. Bitcoin returns show negative statistically significant sensitivity to changes in nominal interest rates in the highest quantile and the full period. Moreover, Bitcoin returns show negative and statistically significant sensitivity to oil returns at low quantiles, by serving as a safe-haven asset during economic turmoil. Therefore, in general, the sensitivity of Bitcoin returns to movements in international risk factors tends to be more pronounced in extreme market conditions (bullish and bearish scenarios), showing the highest explanatory power in the lowest quantile. Finally, we have applied the non-linear ARDL approach to analyse the long- and short-run relations between Bitcoin and gold price returns and have found a positive and statistically significant connectedness between them.
•Sensitivity of Bitcoin returns to changes in gold price returns and other international risk factors.•Changes in VIX and STLFSI stress index may have negative and statistically significant effects on Bitcoin returns.•Sensitivity of Bitcoin returns more pronounced in extreme market conditions (bullish and bearish scenarios).•Non-linear ARDL approach analyses the long- and short-run relations between Bitcoin and gold price returns.•Positive and statistically significant connectedness between Bitcoin and gold price returns. |
doi_str_mv | 10.1016/j.resourpol.2020.101666 |
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•Sensitivity of Bitcoin returns to changes in gold price returns and other international risk factors.•Changes in VIX and STLFSI stress index may have negative and statistically significant effects on Bitcoin returns.•Sensitivity of Bitcoin returns more pronounced in extreme market conditions (bullish and bearish scenarios).•Non-linear ARDL approach analyses the long- and short-run relations between Bitcoin and gold price returns.•Positive and statistically significant connectedness between Bitcoin and gold price returns.</description><identifier>ISSN: 0301-4207</identifier><identifier>EISSN: 1873-7641</identifier><identifier>DOI: 10.1016/j.resourpol.2020.101666</identifier><language>eng</language><publisher>Kidlington: Elsevier Ltd</publisher><subject>Asymmetry ; Bitcoin ; Change agents ; Crude oil ; Crude oil prices ; Digital currencies ; Economic conditions ; Economic stress ; Gold ; Indexes ; Interest rates ; International factors ; NARDL ; Nonlinear analysis ; Petroleum ; Prices ; Pricing ; Quantile regression ; Quantiles ; Regression analysis ; Risk analysis ; Risk factors ; Robustness ; Robustness (mathematics) ; Securities markets ; Sensitivity analysis ; Statistical significance ; Stock exchanges ; Stock market ; Volatility</subject><ispartof>Resources policy, 2020-08, Vol.67, p.101666, Article 101666</ispartof><rights>2020 Elsevier Ltd</rights><rights>Copyright Elsevier Science Ltd. Aug 2020</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c442t-b305cfd36e5477d6c928cad26b2003e5a1ae05cc8d53f10ca0d523572917f6063</citedby><cites>FETCH-LOGICAL-c442t-b305cfd36e5477d6c928cad26b2003e5a1ae05cc8d53f10ca0d523572917f6063</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0301420719309985$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27843,27901,27902,65306</link.rule.ids></links><search><creatorcontrib>Jareño, Francisco</creatorcontrib><creatorcontrib>González, María de la O</creatorcontrib><creatorcontrib>Tolentino, Marta</creatorcontrib><creatorcontrib>Sierra, Karen</creatorcontrib><title>Bitcoin and gold price returns: A quantile regression and NARDL analysis</title><title>Resources policy</title><description>This research analyses the sensitivity of Bitcoin returns to changes in gold price returns and some other international risk factors such as US stock market returns, interest rates, crude oil prices, the volatility index of the American stock market (VIX) and the Saint Louis financial stress index (STLFSI). This study applies the quantile regression approach for the 2010–2018 period. For robustness, this paper splits the whole sample period into two different subsamples: a more volatile and a less volatile sub-period. Moreover, to capture both long- and short-run asymmetries between Bitcoin and gold price returns, an asymmetric nonlinear cointegration approach (NARDL) is applied. The results evidence that the most relevant risk factor is the VIX index, followed by changes in the STLFSI stress index, and both show negative and statistically significant effects on Bitcoin returns in most periods and quantiles. The US stock market returns have statistically significant effects (with positive sign) on Bitcoin returns in all periods and specifically in high quantiles. Bitcoin returns show negative statistically significant sensitivity to changes in nominal interest rates in the highest quantile and the full period. Moreover, Bitcoin returns show negative and statistically significant sensitivity to oil returns at low quantiles, by serving as a safe-haven asset during economic turmoil. Therefore, in general, the sensitivity of Bitcoin returns to movements in international risk factors tends to be more pronounced in extreme market conditions (bullish and bearish scenarios), showing the highest explanatory power in the lowest quantile. Finally, we have applied the non-linear ARDL approach to analyse the long- and short-run relations between Bitcoin and gold price returns and have found a positive and statistically significant connectedness between them.
•Sensitivity of Bitcoin returns to changes in gold price returns and other international risk factors.•Changes in VIX and STLFSI stress index may have negative and statistically significant effects on Bitcoin returns.•Sensitivity of Bitcoin returns more pronounced in extreme market conditions (bullish and bearish scenarios).•Non-linear ARDL approach analyses the long- and short-run relations between Bitcoin and gold price returns.•Positive and statistically significant connectedness between Bitcoin and gold price returns.</description><subject>Asymmetry</subject><subject>Bitcoin</subject><subject>Change agents</subject><subject>Crude oil</subject><subject>Crude oil prices</subject><subject>Digital currencies</subject><subject>Economic conditions</subject><subject>Economic stress</subject><subject>Gold</subject><subject>Indexes</subject><subject>Interest rates</subject><subject>International factors</subject><subject>NARDL</subject><subject>Nonlinear analysis</subject><subject>Petroleum</subject><subject>Prices</subject><subject>Pricing</subject><subject>Quantile regression</subject><subject>Quantiles</subject><subject>Regression analysis</subject><subject>Risk analysis</subject><subject>Risk factors</subject><subject>Robustness</subject><subject>Robustness (mathematics)</subject><subject>Securities markets</subject><subject>Sensitivity analysis</subject><subject>Statistical significance</subject><subject>Stock exchanges</subject><subject>Stock market</subject><subject>Volatility</subject><issn>0301-4207</issn><issn>1873-7641</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>7TQ</sourceid><recordid>eNqFUF1LwzAUDaLgnP4GCz533nw06Xyr82NCURB9DlmSjpTabEkr7N-bUfHVp3s5nHPuPQehawwLDJjftotgox_DzncLAmRCOT9BM1wKmgvO8CmaAQWcMwLiHF3E2AJAIUo-Q-t7N2jv-kz1Jtv6zmS74LTNgh3G0Me7rMr2o-oH1x2xbToVnZ_Yr9X7Q5021R2ii5forFFdtFe_c44-nx4_Vuu8fnt-WVV1rhkjQ76hUOjGUG4LJoTheklKrQzhGwJAbaGwsomhS1PQBoNWYApCC0GWWDQcOJ2jm8l3F_x-tHGQbQqfnoiSMAYYaMmWiSUmlg4-xmAbmWJ9qXCQGOSxINnKv9rksTY51ZaU1aS0KcS3s0FG7WyvrXHB6kEa7_71-AHIe3l7</recordid><startdate>202008</startdate><enddate>202008</enddate><creator>Jareño, Francisco</creator><creator>González, María de la O</creator><creator>Tolentino, Marta</creator><creator>Sierra, Karen</creator><general>Elsevier Ltd</general><general>Elsevier Science Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TA</scope><scope>7TQ</scope><scope>8BJ</scope><scope>8FD</scope><scope>DHY</scope><scope>DON</scope><scope>FQK</scope><scope>JBE</scope><scope>JG9</scope></search><sort><creationdate>202008</creationdate><title>Bitcoin and gold price returns: A quantile regression and NARDL analysis</title><author>Jareño, Francisco ; González, María de la O ; Tolentino, Marta ; Sierra, Karen</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c442t-b305cfd36e5477d6c928cad26b2003e5a1ae05cc8d53f10ca0d523572917f6063</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Asymmetry</topic><topic>Bitcoin</topic><topic>Change agents</topic><topic>Crude oil</topic><topic>Crude oil prices</topic><topic>Digital currencies</topic><topic>Economic conditions</topic><topic>Economic stress</topic><topic>Gold</topic><topic>Indexes</topic><topic>Interest rates</topic><topic>International factors</topic><topic>NARDL</topic><topic>Nonlinear analysis</topic><topic>Petroleum</topic><topic>Prices</topic><topic>Pricing</topic><topic>Quantile regression</topic><topic>Quantiles</topic><topic>Regression analysis</topic><topic>Risk analysis</topic><topic>Risk factors</topic><topic>Robustness</topic><topic>Robustness (mathematics)</topic><topic>Securities markets</topic><topic>Sensitivity analysis</topic><topic>Statistical significance</topic><topic>Stock exchanges</topic><topic>Stock market</topic><topic>Volatility</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jareño, Francisco</creatorcontrib><creatorcontrib>González, María de la O</creatorcontrib><creatorcontrib>Tolentino, Marta</creatorcontrib><creatorcontrib>Sierra, Karen</creatorcontrib><collection>CrossRef</collection><collection>Materials Business File</collection><collection>PAIS Index</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>Technology Research Database</collection><collection>PAIS International</collection><collection>PAIS International (Ovid)</collection><collection>International Bibliography of the Social Sciences</collection><collection>International Bibliography of the Social Sciences</collection><collection>Materials Research Database</collection><jtitle>Resources policy</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Jareño, Francisco</au><au>González, María de la O</au><au>Tolentino, Marta</au><au>Sierra, Karen</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Bitcoin and gold price returns: A quantile regression and NARDL analysis</atitle><jtitle>Resources policy</jtitle><date>2020-08</date><risdate>2020</risdate><volume>67</volume><spage>101666</spage><pages>101666-</pages><artnum>101666</artnum><issn>0301-4207</issn><eissn>1873-7641</eissn><abstract>This research analyses the sensitivity of Bitcoin returns to changes in gold price returns and some other international risk factors such as US stock market returns, interest rates, crude oil prices, the volatility index of the American stock market (VIX) and the Saint Louis financial stress index (STLFSI). This study applies the quantile regression approach for the 2010–2018 period. For robustness, this paper splits the whole sample period into two different subsamples: a more volatile and a less volatile sub-period. Moreover, to capture both long- and short-run asymmetries between Bitcoin and gold price returns, an asymmetric nonlinear cointegration approach (NARDL) is applied. The results evidence that the most relevant risk factor is the VIX index, followed by changes in the STLFSI stress index, and both show negative and statistically significant effects on Bitcoin returns in most periods and quantiles. The US stock market returns have statistically significant effects (with positive sign) on Bitcoin returns in all periods and specifically in high quantiles. Bitcoin returns show negative statistically significant sensitivity to changes in nominal interest rates in the highest quantile and the full period. Moreover, Bitcoin returns show negative and statistically significant sensitivity to oil returns at low quantiles, by serving as a safe-haven asset during economic turmoil. Therefore, in general, the sensitivity of Bitcoin returns to movements in international risk factors tends to be more pronounced in extreme market conditions (bullish and bearish scenarios), showing the highest explanatory power in the lowest quantile. Finally, we have applied the non-linear ARDL approach to analyse the long- and short-run relations between Bitcoin and gold price returns and have found a positive and statistically significant connectedness between them.
•Sensitivity of Bitcoin returns to changes in gold price returns and other international risk factors.•Changes in VIX and STLFSI stress index may have negative and statistically significant effects on Bitcoin returns.•Sensitivity of Bitcoin returns more pronounced in extreme market conditions (bullish and bearish scenarios).•Non-linear ARDL approach analyses the long- and short-run relations between Bitcoin and gold price returns.•Positive and statistically significant connectedness between Bitcoin and gold price returns.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.resourpol.2020.101666</doi></addata></record> |
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subjects | Asymmetry Bitcoin Change agents Crude oil Crude oil prices Digital currencies Economic conditions Economic stress Gold Indexes Interest rates International factors NARDL Nonlinear analysis Petroleum Prices Pricing Quantile regression Quantiles Regression analysis Risk analysis Risk factors Robustness Robustness (mathematics) Securities markets Sensitivity analysis Statistical significance Stock exchanges Stock market Volatility |
title | Bitcoin and gold price returns: A quantile regression and NARDL analysis |
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