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Stock‐induced Google trends and the predictability of sectoral stock returns. (2021). Salisu, Afees ; Ogbonna, Ahamuefula ; Adediran, Idris.
In: Journal of Forecasting.
RePEc:wly:jforec:v:40:y:2021:i:2:p:327-345.

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  1. Investors’ attention and network spillover for commodity market forecasting. (2024). Mattera, Raffaele ; Ficcadenti, Valerio ; Cerqueti, Roy.
    In: Socio-Economic Planning Sciences.
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  2. Google search trends and stock markets: Sentiment, attention or uncertainty?. (2024). Bwanya, Princess Rutendo ; Brzeszczyski, Janusz ; Szczygielski, Jan Jakub ; Charteris, Ailie.
    In: International Review of Financial Analysis.
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  3. Optimal hybrid framework for carbon price forecasting using time series analysis and least squares support vector machine. (2022). Wu, Zhibin ; Zhang, Wen.
    In: Journal of Forecasting.
    RePEc:wly:jforec:v:41:y:2022:i:3:p:615-632.

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  4. Bitcoin Prices and the Realized Volatility of US Sectoral Stock Returns. (2022). Salisu, Afees ; GUPTA, RANGAN ; Bouri, Elie.
    In: Working Papers.
    RePEc:pre:wpaper:202224.

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  5. Oil shocks and volatility of green investments: GARCH-MIDAS analyses. (2022). YAYA, OLAOLUWA ; Ogbonna, Ahamuefula ; Vo, Xuan Vinh.
    In: MPRA Paper.
    RePEc:pra:mprapa:113707.

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  6. Oil shocks and volatility of green investments: GARCH-MIDAS analyses. (2022). YAYA, OLAOLUWA ; Ogbonna, Ahamuefula ; Vo, Xuan Vinh.
    In: Resources Policy.
    RePEc:eee:jrpoli:v:78:y:2022:i:c:s0301420722002379.

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  7. The outbreak of COVID-19 and stock market liquidity: Evidence from emerging and developed equity markets. (2022). Tiwari, Aviral ; Gil-Alana, Luis ; Abakah, Emmanuel ; Karikari, Nana Kwasi ; Aikins, Emmanuel Joel.
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  8. An Information-Based Index of Uncertainty and the predictability of Energy Prices. (2021). YAYA, OLAOLUWA ; Olubusoye, Olusanya ; Ogbonna, Ahamuefula.
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  9. Firm-specific news and the predictability of Consumer stocks in Vietnam. (2021). Salisu, Afees ; Vo, Xuan Vinh.
    In: Finance Research Letters.
    RePEc:eee:finlet:v:41:y:2021:i:c:s1544612320316159.

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References

References cited by this document

  1. Apergis, E., & Apergis, N. (2020). Can the COVID‐19 pandemic and oil prices drive the US Partisan Conflict Index? Energy Research Letters, 1(1), 13144. https://doi.org/10.46557/001c.13144.
    Paper not yet in RePEc: Add citation now
  2. Baker, M., & Wurgler, J. (2006). Investor sentiment and the cross‐section of stock returns. The Journal of Finance LXI, 61, 1645–1680. https://doi.org/10.1111/j.1540-6261.2006.00885.x.
    Paper not yet in RePEc: Add citation now
  3. Bank, M., Larch, M., & Peter, G. (2011). Google search volume and its influence on liquidity and returns of German stocks. Financial Markets and Portfolio Management, 25(3), 239–264. https://doi.org/10.1007/s11408-011-0165-y.

  4. Bannigidadmath, D., & Narayan, P. (2015). Stock return predictability and determinants of predictability and profits. Emerging Markets Review, 26, 153–173.

  5. Barber, B. M., & Odean, T. (2008). All That Glitters: the effect of attention and news on the buying behavior of individual and institutional investors. Review of Financial Studies, 21(2), 785–818. https://doi.org/10.1093/rfs/hhm079.

  6. Bijl, L., Kringhaug, G., Molnár, P., & Sandvik, E. (2016). Google searches and stock returns. International Review of Financial Analysis, 45, 150–156. https://doi.org/10.1016/j.irfa.2016.03.015.

  7. Birz, G., & Lott, J. R. (2011). The effect of macroeconomic news on stock returns: New evidence from newspaper coverage. Journal of Banking & Finance, 35, 2791–2800. https://doi.org/10.1016/j.jbankfin.2011.03.006.

  8. Buttner, D., & Hayo, B. (2010). News and correlations of CEEC‐3 financial markets. Economic Modelling, 27, 915–922. https://doi.org/10.1016/j.econmod.2010.05.014.
    Paper not yet in RePEc: Add citation now
  9. Curatola, G., Donadelli, M., & Kizys, R. And Riedel, M. (2016). Investor Sentiment and Sectoral Stock Returns: Evidence from World Cup Games. Finance Research Letters, 17, 267–274. https://doi.org/10.1016/j.frl.2016.03.023.

  10. D'Amuri, F., & Marcucci, J. (2017). The predictive power of Google searches in forecasting US unemployment. International Journal of Forecasting, 33, 801–816. https://doi.org/10.1016/j.ijforecast.2017.03.004.

  11. Da, Z., Engelberg, J., & Gao, P. (2011). In search of attention. The Journal of Finance, 66(5), 1461–1499. https://doi.org/10.1111/j.1540-6261.2011.01679.x.

  12. Devpura, N., Narayan, P. K., & Sharma, S. S. (2018). Is stock return predictability time varying? Journal of International Financial Markets Institutions and Money, 52, 152–172. https://doi.org/10.1016/j.intfin.2017.06.001.

  13. Dyck, A., & Zingales, L. (2003). The media and asset prices. Working Paper, NBER.
    Paper not yet in RePEc: Add citation now
  14. Ekinci, C., & Bulut, A. E. (2020). Google search and stock returns: A study on BIST 100 stocks. Global Finance Journal, 100518. https://doi.org/10.1016/j.gfj.2020.100518.

  15. Fang, X., Jiang, Y., & Qian, Z. (2014). The Effects of Individual Investors' Attention on Stock Returns: Evidence from the ChiNext Market. Emerging Markets Finance and Trade, 50, 158–168. https://doi.org/10.2753/REE1540-496X5003S309.

  16. Fu, M., & Shen, H. (2020). COVID‐19 and corporate performance in the energy industry. Energy Research Letters, 1(1), 12967. https://doi.org/10.46557/001c.12967.
    Paper not yet in RePEc: Add citation now
  17. Garcia, D. (2013). Sentiment during recessions. Journal of Finance, 63, 1267–1300.

  18. Gil‐Alana, L. A., & Monge, M. (2020). Crude oil prices and COVID‐19: Persistence of the shock. Energy Research Letters, 1(1), 13200. https://doi.org/10.46557/001c.13200.
    Paper not yet in RePEc: Add citation now
  19. Groseclose, T., & Milyo, J. (2005). A measure of media bias. The Quarterly Journal of Economics, 120, 1191–1237. https://doi.org/10.1162/003355305775097542.

  20. Han, L., Li, Z., & Yin, L. (2018). Investor Attention and Stock Returns: International Evidence. Emerging Markets Finance and Trade, 54, 3168–3188. https://doi.org/10.1080/1540496X.2017.1413980.

  21. Haroon, O., & Rizvi, S. A. R. (2020). COVID‐19: Media coverage and financial markets behavior—A sectoral inquiry. Journal of Behavioral and Experimental Finance, 27, 100343. https://doi.org/10.1016/j.jbef.2020.100343.
    Paper not yet in RePEc: Add citation now
  22. Hu, H., Tang, L., Zhang, S., & Wang, H. (2018). Predicting the direction of stock markets using optimized neural networks with Google Trends. Neurocomputing, 285, 188–195. https://doi.org/10.1016/j.neucom.2018.01.038.
    Paper not yet in RePEc: Add citation now
  23. Joseph, K., Wintoki, M. B., & Zhang, Z. (2011). Forecasting abnormal stock returns and trading volume using investor sentiment: Evidence from online search. International Journal of Forecasting, 27(4), 1116–1127. https://doi.org/10.1016/j.ijforecast.2010.11.001.

  24. Kim, M., & Park, K. (2015). Individual Investor Sentiment and Stock Returns: Evidence from the Korean Stock Market. Emerging Markets Finance and Trade, 51, 1–20.

  25. Kim, N., Lučivjanská, K., Molnár, P., & Villa, R. (2019). Google searches and stock market activity: Evidence from Norway. Finance Research Letters, 28, 208–220. https://doi.org/10.1016/j.frl.2018.05.003.

  26. Liu, L., Wang, E. Z., & Lee, C. C. (2020). Impact of the COVID‐19 pandemic on the crude oil and stock markets in the US: A time‐varying analysis. Energy Research Letters, 1(1), 13154. https://doi.org/10.46557/001c.13154.
    Paper not yet in RePEc: Add citation now
  27. Makin, A. J., Narayan, P. K., & Narayan, S. (2014). What expenditure does Anglosphere foreign borrowing fund? Journal of International Money and Finance, 40, 63–78. https://doi.org/10.1016/j.jimonfin.2013.08.020.

  28. Merton, R. C. (1987). A simple model of capital market equilibrium with incomplete information. The Journal of Finance, 42(3), 483–510. https://doi.org/10.1111/j.1540-6261.1987.tb04565.x.

  29. Mishra, V., & Smyth, R. (2014). Is monthly US natural gas consumption stationary? New evidence from a GARCH unit root test with structural breaks. Energy Policy, 69, 258–262. https://doi.org/10.1016/j.enpol.2014.03.033.

  30. Narayan, P. K. (2019). Can stale oil price news predict stock returns? Energy Economics, 83(C), 430–444. https://doi.org/10.1016/j.eneco.2019.07.022.

  31. Narayan, P. K. (2020). Oil price news and COVID‐19—Is there any connection? Energy Research Letters, 1(1), 13176. https://doi.org/10.46557/001c.13176.
    Paper not yet in RePEc: Add citation now
  32. Narayan, P. K., & Bannigidadmath, D. (2015). Are Indian stock returns predictable? Journal of Banking & Finance, 58, 506–531. https://doi.org/10.1016/j.jbankfin.2015.05.001.

  33. Narayan, P. K., & Bannigidadmath, D. (2017). Does Financial News Predict Stock Returns? New Evidence from Islamic and Non‐Islamic Stocks. Pacific‐Basin Finance Journal, 42, 24–45. https://doi.org/10.1016/j.pacfin.2015.12.009.

  34. Narayan, P. K., & Gupta, R. (2015). Has oil price predicted stock returns for over a century? Energy Economics, 48, 18–23. https://doi.org/10.1016/j.eneco.2014.11.018.

  35. Narayan, P. K., & Liu, R. (2015). A unit root model for trending time‐series energy variables. Energy Economics, 50, 391–402. https://doi.org/10.1016/j.eneco.2014.11.021.

  36. Narayan, P. K., & Phan, D. (2019). A survey of Islamic banking and finance literature: Issues, challenges and future directions. Pacific‐Basin Finance Journal, 53, 484–496. https://doi.org/10.1016/j.pacfin.2017.06.006.

  37. Narayan, P. K., & Phan, D. H. B. (2017). Momentum strategies for Islamic stocks. Pacific‐Basin Finance Journal, 42, 96–112. https://doi.org/10.1016/j.pacfin.2016.05.015.

  38. Narayan, P. K., & Popp, S. (2010). A new unit root test with two structural breaks in level and slope at unknown time. Journal of Applied Statistics, 37(9), 1425–1438. https://doi.org/10.1080/02664760903039883.

  39. Narayan, P. K., Liu, R., & Westerlund, J. (2016). A GARCH model for testing market efficiency. Journal of International Financial Markets Institutions and Money, 41, 121–138. https://doi.org/10.1016/j.intfin.2015.12.008.

  40. Narayan, P. K., Phan, D. H. B., & Sharma, S. S. (2019). Does Islamic stock sensitivity to oil prices have economic significance? Pacific‐Basin Finance Journal, 53, 497–512. https://doi.org/10.1016/j.pacfin.2018.04.003.

  41. Narayan, P. K., Phan, D. H. B., Sharma, S. S., & Westerlund, J. (2016). Are Islamic stock returns predictable? A global perspective. Pacific‐Basin Finance Journal, 40(A), 210–223. https://doi.org/10.1016/j.pacfin.2016.08.008.

  42. Nguyen, P. C., Schinckus, C., & Nguyen, T. V. H. (2019). Google search and stock returns in emerging markets. Borsa Istanbul Review, 19, 288–296. https://doi.org/10.1016/j.bir.2019.07.001.
    Paper not yet in RePEc: Add citation now
  43. Ni, Z.‐X., Wang, D.‐W., & Xue, W.‐J. (2015). Investor sentiment and its nonlinear effect on stock returns ‐ New evidence from the Chinese stock market based on panel quantile regression model. Economic Modelling, 50, 266–274. https://doi.org/10.1016/j.econmod.2015.07.007.

  44. Ozatay, F., Ozmen, E., & Sahinbeyoglu, G. (2009). Emerging market sovereign spreads, global financial considerations and U.S. macroeconomic news. Economic Modelling, 26, 526–531. https://doi.org/10.1016/j.econmod.2008.10.008.

  45. Phan, D. H. B., Sharma, S. S., & Narayan, P. K. (2015). Stock return forecasting: some new evidence. International Review of Financial Analysis, 40, 38–51.

  46. Preis, T., Moat, H. S., & Stanley, H. E. (2013). Quantifying trading behavior in financial markets using Google Trends. Scientific Reports, 3, 1684. https://doi.org/10.1038/srep01684.
    Paper not yet in RePEc: Add citation now
  47. Qin, M., Zhang, Y. C., & Su, C. W. (2020). The Essential Role of Pandemics: A Fresh Insight into the Oil Market. Energy Research Letters, 1(1), 13166. https://doi.org/10.46557/001c.13166.
    Paper not yet in RePEc: Add citation now
  48. Salisu, A. A., & Adeleke, A. I. (2016). Further application of Narayan and Liu (2015) unit root model for trending time series. Economic Modelling, 55, 305–314. https://doi.org/10.1016/j.econmod.2016.02.026.

  49. Salisu, A. A., & Fasanya, I. O. (2013). Modelling oil price volatility with structural breaks. Energy Policy, 53, 554–562.

  50. Salisu, A. A., & Isah, K. O. (2018). Predicting US inflation: Evidence from a new approach. Economic Modelling, 71, 134–158. https://doi.org/10.1016/j.econmod.2017.12.008.

  51. Salisu, A. A., & Mobolaji, H. (2013). Modeling returns and volatility transmission between oil price and US–Nigeria exchange rate. Energy Economics, 39, 169–176. https://doi.org/10.1016/j.eneco.2013.05.003.

  52. Salisu, A. A., Ademuyiwa, I., & Isah, K. (2018). Revisiting the forecasting accuracy of Phillips curve: the role of oil price. Energy Economics, 70, 334–356. https://doi.org/10.1016/j.eneco.2018.01.018.

  53. Salisu, A. A., Ndako, U. B., Oloko, T. F., & Akanni, L. O. (2016). Unit root modeling for trending stock market series. Borsa Istanbul Review, 16(2), 82–91. https://doi.org/10.1016/j.bir.2016.05.001.

  54. Salisu, A. A., Ogbonna, A. E., & Adewuyi, A. (2020). Google trends and the predictability of precious metals. Resources Policy, 65, 101542. https://doi.org/10.1016/j.resourpol.2019.101542.

  55. Salisu, A. A., Swaray, R., & Oloko, T. F. (2019). Improving the predictability of the oil–US stock nexus: The role of macroeconomic variables. Economic Modelling, 76, 153–171. https://doi.org/10.1016/j.econmod.2018.07.029.

  56. Shin, Y., Yu, B., & Greenwood‐Nimmo, M. (2014). Modelling Asymmetric Cointegration and Dynamic Multipliers in a Nonlinear ARDL Framework. In Festschrift in honor of Peter Schmidt (pp. 281–314). New York, NY: Springer.
    Paper not yet in RePEc: Add citation now
  57. Takeda, F., & Wakao, T. (2014). Google search intensity and its relationship with returns and trading volume of Japanese stocks. Pacific‐Basin Finance Journal, 27, 1–18. https://doi.org/10.1016/j.pacfin.2014.01.003.

  58. Tang, W., & Zhu, L. (2017). How security prices respond to a surge in investor attention: Evidence from Google Search of ADRs. Global Finance Journal, 33, 38–50. https://doi.org/10.1016/j.gfj.2016.09.001.

  59. Westerlund, J., & Narayan, P. K. (2012). Does the choice of estimator matter when forecasting returns? Journal of Banking & Finance, 36, 2632–2640. https://doi.org/10.1016/j.jbankfin.2012.06.005.

  60. Westerlund, J., & Narayan, P. K. (2015). Testing for predictability in conditionally hetoroscedastic stock returns. Journal of Financial Economics, 13, 342–375. https://doi.org/10.1093/jjfinec/nbu001.

  61. Xu, Q., Bo, Z., Jiang, C., & Liu, Y. (2019). Does Google search index really help predicting stock market volatility? Evidence from a modified mixed data sampling model on volatility. Knowledge‐Based Systems, 166, 170–185. https://doi.org/10.1016/j.knosys.2018.12.025.
    Paper not yet in RePEc: Add citation now
  62. Ying, Q., Kong, D., & Luo, D. (2015). Investor Attention, Institutional Ownership, and Stock Return: Empirical Evidence from China. Emerging Markets Finance and Trade, 51(3), 672–685. https://doi.org/10.1080/1540496X.2015.1046339.

  63. Zhang, B., & Wang, Y. (2015). Limited attention of individual investors and stock performance: Evidence from the ChiNext market. Economic Modelling, 50, 94–104. https://doi.org/10.1016/j.econmod.2015.06.009.

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    RePEc:eee:intfor:v:34:y:2018:i:4:p:665-677.

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  22. Effects of investor attention on commodity futures markets. (2018). Kou, YI ; Wang, Xiaolin ; Ye, Qiang ; Zhao, Feng.
    In: Finance Research Letters.
    RePEc:eee:finlet:v:25:y:2018:i:c:p:190-195.

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  23. Can Google econometrics predict unemployment? Evidence from Spain. (2018). González-Fernández, Marcos ; Gonzalez-Fernandez, Marcos ; Gonzalez-Velasco, Carmen.
    In: Economics Letters.
    RePEc:eee:ecolet:v:170:y:2018:i:c:p:42-45.

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  24. Information demand and stock market liquidity: International evidence. (2018). Roubaud, David ; AROURI, Mohamed ; Aouadi, Amal.
    In: Economic Modelling.
    RePEc:eee:ecmode:v:70:y:2018:i:c:p:194-202.

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  25. Forecasting Financial Market Volatility Using a Dynamic Topic Model. (2017). Kawasaki, Yoshinori ; Morimoto, Takayuki.
    In: Asia-Pacific Financial Markets.
    RePEc:kap:apfinm:v:24:y:2017:i:3:d:10.1007_s10690-017-9228-z.

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  26. The use of open source internet to analysis and predict stock market trading volume. (2017). ben Ouda, Olfa ; Moussa, Faten ; Delhoumi, Ezzeddine.
    In: Research in International Business and Finance.
    RePEc:eee:riibaf:v:41:y:2017:i:c:p:399-411.

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  27. Stock return and volatility reactions to information demand and supply. (2017). ben Ouda, Olfa ; Moussa, Faten ; Delhoumi, Ezzeddine.
    In: Research in International Business and Finance.
    RePEc:eee:riibaf:v:39:y:2017:i:pa:p:54-67.

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  28. Google search intensity and its relationship to the returns and liquidity of Japanese startup stocks. (2017). Takeda, Fumiko ; Adachi, Yuta ; Masuda, Motoki.
    In: Pacific-Basin Finance Journal.
    RePEc:eee:pacfin:v:46:y:2017:i:pb:p:243-257.

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  29. How security prices respond to a surge in investor attention: Evidence from Google Search of ADRs. (2017). Tang, Wenbin ; Zhu, Lili.
    In: Global Finance Journal.
    RePEc:eee:glofin:v:33:y:2017:i:c:p:38-50.

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  30. Modeling and predicting oil VIX: Internet search volume versus traditional mariables. (2017). Reyes, T ; Campos, I ; Cortazar, G.
    In: Energy Economics.
    RePEc:eee:eneeco:v:66:y:2017:i:c:p:194-204.

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  31. Investor attention and Portuguese stock market volatility: We’ll google it for you!. (2016). Brochado, Ana.
    In: EcoMod2016.
    RePEc:ekd:009007:9345.

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  32. Googling gold and mining bad news. (2016). Dimpfl, Thomas ; Baur, Dirk G.
    In: Resources Policy.
    RePEc:eee:jrpoli:v:50:y:2016:i:c:p:306-311.

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  33. In Search of Concepts: The Effects of Speculative Demand on Stock Returns. (2016). Wang, Qingwei ; HASAN, IFTEKHAR ; ap Gwilym, Owain ; Xie, RU.
    In: European Financial Management.
    RePEc:bla:eufman:v:22:y:2016:i:3:p:427-449.

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  34. Can Internet Search Queries Help to Predict Stock Market Volatility?. (2016). Dimpfl, Thomas ; Jank, Stephan.
    In: European Financial Management.
    RePEc:bla:eufman:v:22:y:2016:i:2:p:171-192.

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  35. Underpricing, underperformance and overreaction in initial pubic offerings: Evidence from investor attention using online searches. (2015). Krištoufek, Ladislav ; Vakrman, Tomas .
    In: FinMaP-Working Papers.
    RePEc:zbw:fmpwps:35.

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  36. Online Information Search, Market Fundamentals and Apartment Real Estate. (2015). Das, Prashant ; Coulson, N ; Ziobrowski, Alan.
    In: The Journal of Real Estate Finance and Economics.
    RePEc:kap:jrefec:v:51:y:2015:i:4:p:480-502.

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  37. Intercity Information Diffusion and Price Discovery in Housing Markets: Evidence from Google Searches. (2015). Wu, Jing ; Deng, Yongheng.
    In: The Journal of Real Estate Finance and Economics.
    RePEc:kap:jrefec:v:50:y:2015:i:3:p:289-306.

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  38. Power-law correlations in finance-related Google searches, and their cross-correlations with volatility and traded volume: Evidence from the Dow Jones Industrial components. (2015). Krištoufek, Ladislav.
    In: Physica A: Statistical Mechanics and its Applications.
    RePEc:eee:phsmap:v:428:y:2015:i:c:p:194-205.

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  39. Investor attention and FX market volatility. (2015). Goddard, John ; Wang, Qingwei ; Kita, Arben.
    In: Journal of International Financial Markets, Institutions and Money.
    RePEc:eee:intfin:v:38:y:2015:i:c:p:79-96.

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  40. How does Google search affect trader positions and crude oil prices?. (2015). Zhang, Xun ; Li, Xin ; Wang, Shouyang ; Ma, Jian.
    In: Economic Modelling.
    RePEc:eee:ecmode:v:49:y:2015:i:c:p:162-171.

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  41. Investor attention and stock market activity: Evidence from France. (2014). Arouri, Mohamed ; Aouadi, Amal.
    In: Working Papers.
    RePEc:ipg:wpaper:2014-405.

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  42. Internet, noise trading and commodity futures prices. (2014). Peri, Massimo ; Baldi, Lucia ; Vandone, Daniela.
    In: International Review of Economics & Finance.
    RePEc:eee:reveco:v:33:y:2014:i:c:p:82-89.

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  43. Google search intensity and its relationship with returns and trading volume of Japanese stocks. (2014). Takeda, Fumiko ; Wakao, Takumi .
    In: Pacific-Basin Finance Journal.
    RePEc:eee:pacfin:v:27:y:2014:i:c:p:1-18.

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  44. Speculate against speculative demand. (2014). Wang, Qingwei ; ap Gwilym, Owain ; Kita, A..
    In: International Review of Financial Analysis.
    RePEc:eee:finana:v:34:y:2014:i:c:p:212-221.

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  45. Do individual investors’ stock recommendations in online communities contain investment value?. (2013). Nitzsch, Rudiger ; Stephan, Philipp .
    In: Financial Markets and Portfolio Management.
    RePEc:kap:fmktpm:v:27:y:2013:i:2:p:149-186.

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  46. Investor attention and abnormal performance of timberland investments in the United States. (2013). Gao, Lei ; Mei, Bin.
    In: Forest Policy and Economics.
    RePEc:eee:forpol:v:28:y:2013:i:c:p:60-65.

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  47. Google attention and target price run ups. (2013). Siganos, Antonios.
    In: International Review of Financial Analysis.
    RePEc:eee:finana:v:29:y:2013:i:c:p:219-226.

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  48. Investor attention and stock market activity: Evidence from France. (2013). AROURI, Mohamed ; AOUADI, AMAL ; Teulon, Frederic.
    In: Economic Modelling.
    RePEc:eee:ecmode:v:35:y:2013:i:c:p:674-681.

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  49. Open source information, investor attention, and asset pricing. (2013). Shen, Dehua ; Zhang, Yongjie ; Xiong, Xiong.
    In: Economic Modelling.
    RePEc:eee:ecmode:v:33:y:2013:i:c:p:613-619.

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  50. In search of concepts : The effects of speculative demand on returns and volume. (2013). HASAN, IFTEKHAR ; ap Gwilym, Owain ; Xie, RU ; Wang, Qvigwei.
    In: Research Discussion Papers.
    RePEc:bof:bofrdp:2013_010.

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