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Time varying risk aversion and its connectedness: evidence from cryptocurrencies. (English) Zbl 1542.91431

Summary: Changing patterns of risk aversion may follow a non-linear counter-cyclical process. However, the evidence so far has not considered developing cryptocurrency markets. Given some unique features of cryptocurrencies, it is interesting to distinguish how these assets differ from traditional products. This paper investigates the time effects of periodicity on risk aversion for a selection of major cryptocurrencies compared to major financial assets. Significant periodic time-varying patterns are identified when analysing risk aversion. Further, bilateral and bidirectional Granger causalities are identified within cryptocurrencies, as well as between cryptocurrencies and traditional financial assets. Bitcoin is identified as a leading information transmitter of the spillover of risk aversion upon other cryptocurrencies, while estimated risk aversion of traditional financial markets plays a dominant role in the spillover processes upon the cryptocurrency cluster. The latter finding presents further evidence of developing cryptocurrency market maturity. The COVID-19 pandemic is found to have significantly influenced the connectedness of risk aversion among cryptocurrency and traditional financial markets.

MSC:

91G99 Actuarial science and mathematical finance
62P05 Applications of statistics to actuarial sciences and financial mathematics

References:

[1] Akhtaruzzaman, M.; Sensoy, A.; Corbet, S., The influence of bitcoin on portfolio diversification and design, Finance Research Letters, 37, 101344, 2020
[2] Alexander, C.; Dakos, M., A critical investigation of cryptocurrency data and analysis, Quantitative Finance, 20, 2, 173-188, 2020
[3] Ammous, S., Can cryptocurrencies fulfil the functions of money?, The Quarterly Review of Economics and Finance, 70, 38-51, 2018
[4] Antoniou, A.; Koutmos, G.; Pericli, A., Index futures and positive feedback trading: Evidence from major stock exchanges, Journal of Empirical Finance, 12, 2, 219-238, 2005
[5] Baker, M.; Wurgler, J., Investor sentiment in the stock market, Journal of Economic Perspectives, 21, 2, 129-152, 2007
[6] Bassi, A.; Colacito, R.; Fulghieri, P., ’O sole mio: An experimental analysis of weather and risk attitudes in financial decisions, The Review of Financial Studies, 26, 7, 1824-1852, 2013
[7] Baur, DG; Hong, K.; Lee, AD, Bitcoin: Medium of exchange or speculative assets?, Journal of International Financial Markets, Institutions and Money, 54, 177-189, 2018
[8] Baur, DG; McDermott, TK, Is gold a safe haven? International evidence, Journal of Banking & Finance, 34, 8, 1886-1898, 2010
[9] Baur, DG; McDermott, TK, Why is gold a safe haven?, Journal of Behavioral and Experimental Finance, 10, 63-71, 2016
[10] Bordalo, P.; Gennaioli, N.; Shleifer, A., Salience theory of choice under risk, The Quarterly Journal of Economics, 127, 3, 1243-1285, 2012 · Zbl 1400.91128
[11] Brandt, MW; Wang, KQ, Time-varying risk aversion and unexpected inflation, Journal of Monetary Economics, 50, 7, 1457-1498, 2003
[12] Bredin, D.; Conlon, T.; Potì, V., Does gold glitter in the long-run? Gold as a hedge and safe haven across time and investment horizon, International Review of Financial Analysis, 41, 320-328, 2015
[13] Briere, M.; Oosterlinck, K.; Szafarz, A., Virtual currency, tangible return: Portfolio diversification with bitcoin, Journal of Asset Management, 16, 6, 365-373, 2015
[14] Campbell, JY; Cochrane, JH, By force of habit: A consumption-based explanation of aggregate stock market behavior, Journal of Political Economy, 107, 2, 205-251, 1999
[15] Cho, D.; Han, H., The tail behavior of safe haven currencies: A cross-quantilogram analysis, Journal of International Financial Markets, Institutions and Money, 70, 2021
[16] Chou, R.; Engle, RF; Kane, A., Measuring risk aversion from excess returns on a stock index, Journal of Econometrics, 52, 1-2, 201-224, 1992
[17] Cohn, A.; Engelmann, J.; Fehr, E.; Maréchal, MA, Evidence for countercyclical risk aversion: An experiment with financial professionals, American Economic Review, 105, 2, 860-885, 2015
[18] Conlon, T.; Corbet, S.; McGee, RJ, Are cryptocurrencies a safe haven for equity markets? An international perspective from the COVID-19 pandemic, Research in International Business and Finance, 54, 101248, 2020
[19] Corbet, S.; Hou, Y.; Hu, Y.; Oxley, L., The influence of the COVID-19 pandemic on asset-price discovery: Testing the case of Chinese informational asymmetry, International Review of Financial Analysis, 72, 101560, 2020
[20] Corbet, S.; Lucey, B.; Urquhart, A.; Yarovaya, L., Cryptocurrencies as a financial asset: A systematic analysis, International Review of Financial Analysis, 62, 182-199, 2019
[21] Cretarola, A.; Figà-Talamanca, G., Detecting bubbles in Bitcoin price dynamics via market exuberance, Annals of Operations Research, 299, 1-21, 2019
[22] David, S.; Inácio, C. Jr; Machado, JAT, The recovery of global stock markets indices after impacts due to pandemics, Research in International Business and Finance, 55, 101335, 2021
[23] Diebold, FX; Yilmaz, K., Measuring financial asset return and volatility spillovers, with application to global equity markets, The Economic Journal, 119, 534, 158-171, 2009
[24] Diebold, FX; Yilmaz, K., Better to give than to receive: Predictive directional measurement of volatility spillovers, International Journal of Forecasting, 28, 1, 57-66, 2012
[25] Greenwood-Nimmo, M.; Nguyen, VH; Rafferty, B., Risk and return spillovers among the G10 currencies, Journal of Financial Markets, 31, 43-62, 2016
[26] Guiso, L.; Paiella, M., Risk aversion, wealth, and background risk, Journal of the European Economic Association, 6, 6, 1109-1150, 2008
[27] Guiso, L.; Sapienza, P.; Zingales, L., Time varying risk aversion, Journal of Financial Economics, 128, 3, 403-421, 2018
[28] Hackethal, A.; Hanspal, T.; Lammer, DM; Rink, K., The characteristics and portfolio behavior of bitcoin investors: Evidence from indirect cryptocurrency investments, Review of Finance, 26, 4, 855-898, 2022
[29] Hamao, Y.; Masulis, RW; Ng, V., Correlations in price changes and volatility across international stock markets, The Review of Financial Studies, 3, 2, 281-307, 1990
[30] Heaton, J.; Lucas, D., Portfolio choice in the presence of background risk, The Economic Journal, 110, 460, 1-26, 2000
[31] Hou, Y.; Li, S., The impact of the CSI 300 stock index futures: Positive feedback trading and autocorrelation of stock returns, International Review of Economics & Finance, 33, 319-337, 2014
[32] Jin, F.; Li, J.; Xue, Y., Preferring stablecoin over dollar: Evidence from a survey of ethereum platform traders, Journal of International Money and Finance, 131, 102796, 2023
[33] Joo, YC; Park, SY, Oil prices and stock markets: Does the effect of uncertainty change over time?, Energy Economics, 61, 42-51, 2017
[34] Katsiampa, P.; Corbet, S.; Lucey, B., High frequency volatility co-movements in cryptocurrency markets, Journal of International Financial Markets, Institutions and Money, 62, 35-52, 2019
[35] Kaul, A.; Sapp, S., Y2k fears and safe haven trading of the us dollar, Journal of international money and finance, 25, 5, 760-779, 2006
[36] Koutmos, G., Feedback trading and the autocorrelation pattern of stock returns: Further empirical evidence, Journal of International Money and Finance, 16, 4, 625-636, 1997
[37] Koutmos, G.; Pericli, A.; Trigeorgis, L., Short-term dynamics in the Cyprus stock exchange, European Journal of Finance, 12, 3, 205-216, 2006
[38] Loewenstein, G., Emotions in economic theory and economic behavior, American Economic Review, 90, 2, 426-432, 2000
[39] Mensi, W.; Rehman, MU; Shafiullah, M.; Al-Yahyaee, KH; Sensoy, A., High frequency multiscale relationships among major cryptocurrencies: Portfolio management implications, Financial Innovation, 7, 1-21, 2021
[40] Merton, RC, An intertemporal capital asset pricing model, Econometrica: Journal of the Econometric Society, 41, 867-887, 1973 · Zbl 0283.90003
[41] Mills, DJ; Nower, L., Preliminary findings on cryptocurrency trading among regular gamblers: A new risk for problem gambling?, Addictive Behaviors, 92, 136-140, 2019
[42] Nelson, DB, Conditional heteroskedasticity in asset returns: A new approach, Econometrica: Journal of the Econometric Society, 59, 347-370, 1991 · Zbl 0722.62069
[43] Ozdamar, M.; Akdeniz, L.; Sensoy, A., Lottery-like preferences and the max effect in the cryptocurrency market, Financial Innovation, 7, 1, 1-27, 2021
[44] Pålsson, A-M, Does the degree of relative risk aversion vary with household characteristics?, Journal of Economic Psychology, 17, 6, 771-787, 1996
[45] Park, JY; Hahn, SB, Cointegrating regressions with time varying coefficients, Econometric Theory, 15, 664-703, 1999 · Zbl 0963.62080
[46] Park, SY; Zhao, G., An estimation of US gasoline demand: A smooth time-varying cointegration approach, Energy Economics, 32, 1, 110-120, 2010
[47] Ranaldo, A.; Söderlind, P., Safe haven currencies, Review of Finance, 14, 3, 385-407, 2010
[48] Safra, Z.; Segal, U., Constant risk aversion, Journal of Economic Theory, 83, 1, 19-42, 1998 · Zbl 0913.90068
[49] Sensoy, A.; Silva, TC; Corbet, S.; Tabak, BM, High-frequency return and volatility spillovers among cryptocurrencies, Applied Economics, 53, 37, 4310-4328, 2021
[50] Sentana, E.; Wadhwani, S., Feedback traders and stock return autocorrelations: Evidence from a century of daily data, The Economic Journal, 102, 411, 415-425, 1992
[51] Seven, Ü.; Yılmaz, F., World equity markets and COVID-19: Immediate response and recovery prospects, Research in International Business and Finance, 56, 101349, 2021
[52] Shaw, KL, An empirical analysis of risk aversion and income growth, Journal of Labor Economics, 14, 4, 626-653, 1996
[53] Shiller, RJ; Fischer, S.; Friedman, BM, Stock prices and social dynamics, Brookings Papers on Economic Activity, 1984, 2, 457-510, 1984
[54] Wang, Y.; Wang, C.; Sensoy, A.; Yao, S.; Cheng, F., Can investors’ informed trading predict cryptocurrency returns? Evidence from machine learning, Research in International Business and Finance, 62, 2022
[55] Wei, WC, Liquidity and market efficiency in cryptocurrencies, Economics Letters, 168, 21-24, 2018
[56] Yao, S., Kong, X., Sensoy, A., Akyildirim, E., & Cheng, F. (2021). Investor attention and idiosyncratic risk in cryptocurrency markets. The European Journal of Finance, 1-19.
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