This paper presents a network index system for assessing investor sentiment. The proposed comprehensive investor sentiment index is based on intuitionistic fuzzy analytic network process (IFANP) and regression model, and is compared with a sentiment index constructed on the basis of principal component analysis (PCA). The long-term relationship and dynamic relationship between the yields of these investor sentiment indexes and the Shanghai Composite Index (SHCI) are explored. Based on autoregressive moving average models and cointegration models, short-term and medium-term forecasts of the yields of investor sentiment index and SHCI are derived. The results of cointegration test, short-term forecasting and medium-term forecasting all show that the investor sentiment index based on IFANP is superior to that based on PCA.
ZweigM.E., An investor expectations stock price predictive model using closedend fund premiums, The Journal of Finance28(1) (1973), 67–78.
2.
LeeC.M.C., ShleiferA. and ThalerR.H., Investor Sentiment and the Closed-End Fund Puzzle, Journal of Finance46(1) (1991), 75–109.
3.
BrownG.W. and CliffM.T., Investor sentiment and the near-term stock market, Journal of Empirical Finance11(1) (2004), 1–27.
4.
BakerM. and WurglerJ., Investor Sentiment and the Cross-Section of Stock Returns, The Journal of Finance61(4) (2006), 1645–1680.
5.
WurglerJ., Introduction: A special issue on investor sentiment, Journal of Financial Economics104(2) (2012), 227–227.
6.
BormannS.K., Sentiment indices on financial markets: What do they measure?Economics Discussion Papers58 (2013), 1–41.
7.
GalariotisE.C., HolmesP., KallinterakisV. and MaX.S., Market states, expectations, sentiment and momentum: how naive are investors?, International Review of Financial Analysis32(3) (2014), 1–12.
8.
KhanM.S.Ali., AbdullahS. and AliA., Multiattribute group decision-making based on Pythagorean fuzzy Einstein prioritized aggregation operators, International Journal of Entelligent Systems34(5) (2019), 1001–1033.
9.
ShakeelM., AbduulahS., ShahzadM., MahmoodT. and SiddiquiN., Averaging aggregation operators with pythagorean trapezoidal fuzzy numbers and their application to group decision making, Journal of Intelligent & Fuzzy Systems36(2) (2019), 1899–1915.
10.
KhanA.A., AbdullahS., ShakeelM., KhanF. and LuoJ., A New Ranking Methodology for Pythagorean Trapezoidal Uncertain Linguistic Fuzzy Sets Based on Einstein Operations, Symmetry11(3) (2019a), 440–469.
11.
AshrafS., AbdullahS., MahmoodT., GhaniF. and MahmoodT., Spherical Fuzzy Sets and Their Applications in Multi-Attribute Decision Making Problems, Journal of Intelligent & Fuzzy Systems36(3) (2019), 2829–2844.
12.
KhanF., KhanM.S.A., ShahzadM. and AbdullahS., Pythagorean cubic fuzzy aggregation operators and their application to multicriteria decision making problems, Journal of Intelligent & Fuzzy Systems36(1) (2019b), 595–607.
13.
ListonD.P., Sin stock returns and investor sentiment, Quarterly Review of Economics & Finance59 (2016), 63–70.
14.
SunL., NajandM. and ShenJ., Stock return predictability and investor sentiment: A high-frequency perspective, Journal of Banking & Finance73 (2016), 147–164.
15.
JitmaneerojB., Does investor sentiment affect priceearnings ratios?Studies in Economics & Finance34(2) (2017), 229–237.
16.
RuanQ., YangH., LvD. and ZhangS., Cross correlations between individual investor sentiment and Chinese stock market return: New perspective based on MFDCCA, Physica A: Statistical Mechanics and Its Applications503 (2018), 243–256.
17.
CaoM. and WeiJ., Stock market returns: A note on temperature anomaly, Journal of Banking & Finance29(6) (2005), 1559–1573.
18.
EdmansA., GarciaD. and NorliØ., Sports Sentiment and Stock Returns, The Journal of Finance62(4) (2007), 1967–1998.
19.
AissiaD.B., Home and foreign investor sentiment and the stock returns, The Quarterly Review of Economics and Finance59 (2016), 71–77.
20.
FangL., YuH. and HuangY., The role of investor sentiment in the long-term correlation between U.S. stock and bond markets, International Review of Economics & Finance58 (2018), 127–139.
21.
LiaoT.L., HuangC.J. and WuC.Y., Do fund managers herd to counter investor sentiment, Journal of Business Research64(2) (2011), 207–212.
22.
FinterP., Niessen-RuenziJ.P.D.A. and RuenziS., The impact of investor sentiment on the German stock market, Zeitschrift Für Betriebswirtschaft82(2) (2012), 133–163.
23.
BakerM. and SteinJ.C., Market liquidity as a sentiment indicator, Journal of Financial Markets7(3) (2004), 271–299.
24.
BrownG.W. and CliffM.T., Investor Sentiment and Asset Valuation, Journal of Business78(2) (2005), 405–440.
25.
SchmelingM., Investor sentiment and stock returns: Some international evidence, Journal of Empirical Finance16(3) (2009), 394–408.
26.
HuangD., JiangF., TuJ. and ZhouG., Investor Sentiment Aligned: A Powerful Predictor of Stock Returns, The Review of Financial Studies28(3) (2015), 791–837.
27.
SibleyS.E., WangY., XingY. and ZhangX., The information content of the sentiment index, Social Science Electronic Publishing62 (2016), 164–179.
28.
BekaertG. and HoerovaM., What Do Asset Prices Have to Say About Risk Appetite and Uncertainty?Journal of Banking & Finance67 (2016), 103–118.
29.
XuH.C. and ZhouW.X., A weekly sentiment index and the cross-section of stock returns, Finance Research Letters27 (2018), 135–139.
30.
HoC. and HungC.H., Investor sentiment as conditioning information in asset pricing, Journal of Banking & Finance33(5) (2009), 892–903.
31.
BisserierA., BoukezzoulaR. and GalichetS., A revisited approach to linear fuzzy regression using trapezoidal fuzzy intervals, Information Sciences180(19) (2010), 3653–3673.
32.
JiangH., KwongC.K., ChanC.Y. and YungK.L., A multi-objective evolutionary approach for fuzzy regression analysis, Expert Systems with Application130 (2019), 225–235.
33.
ChukhrovaN. and JohannssenA., Fuzzy regression analysis: Systematic review and bibliography, Applied Soft Computing84 (2019), 1–29.
34.
SaatyT.L. and SaatyT.L., Decision Making with Dependence and Feedback: The Analytic Network Process, International95(2) (1996), 129–157.
DimitrovD., The Paretian liberal with intuitionistic fuzzy preferences: A result, Social Choice and Welfare23(1) (2004), 149–156.
37.
LiaoH., MiX., XuZ., XuJ. and HerreraF., Intuitionistic Fuzzy Analytic Network Process, IEEE Transactions on Fuzzy Systems26(5) (2018), 2578–2590.
38.
XuZ. and LiaoH., Intuitionistic Fuzzy Analytic Hierarchy Process, IEEE Transactions on Fuzzy Systems22(4) (2014), 749–761.
39.
MikhailovL. and SinghM.G., Fuzzy analytic network process and its application to the development of decision support systems, Systems Man & Cybernetics Part C Applications & Reviews IEEE Transactions on33(1) (2003), 33–41.
40.
BueyuekoezkanG., ErtayT., KahramanC. and DaR., Determining the Importance Weights for the Design Requirements in the House of Quality Using the Fuzzy Analytic Network Approach, International Journal of Intelligent Systems19(5) (2004), 443–461.
41.
ChangC.W., HorngD.J. and LinH.L., A measurement model for experts knowledge-based systems algorithm using fuzzy analytic network process, Expert Systems with Applications38(10) (2011), 12009–12017.
42.
LinR., An integrated model for supplier selection under a fuzzy situation, International Journal of Production Economics138(1) (2012), 55–61.
43.
SadiqR. and TesfamariamS., Environmental decision-making under uncertainty using intuitionistic fuzzy analytic hierarchy process (IF-AHP), Stochastic Environmental Research & Risk Assessment23(1) (2009), 75–91.
44.
AbdullahL. and NajibL., A new preference scale of intuitionistic fuzzy analytic hierarchy process in multi-criteria decision making problems, Journal of Intelligent & Fuzzy Systems26(2) (2014), 1039–1049.
45.
KahramanC., ÖztayşiB. and OnarS.Ç., An integrated intuitionistic fuzzy ahp and topsis approach to evaluation of outsource manufacturers, Journal of Intelligent Systems29(1) (2020), 283–297.
46.
BuyukozkanG., GuleryuzS. and KarpakB., A new combined IF-DEMATEL and IF-ANP approach for CRM partner evaluation, International Journal of Production Economics191 (2017), 194–206.
47.
ChenH., ChongT.T. and DuanX., A principal-component approach to measuring investor sentiment, Quantitative Finance10(4) (2010), 339–347.
48.
SakaO., FuertesA.M. and KalotychouE., ECB Policy and Eurozone Fragility: Was De Grauwe Right?Journal of International Money and Finance54 (2015), 168–185.
49.
DingZ., LiuZ., ZhangY. and LongR., The contagion effect of international crude oil price fluctuations on Chinese stock market investor sentiment, Applied Energy187 (2017), 27–36.
