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Deep learning for asset bubble...
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Aktienmarkt
Theorie
730,902
Theory
715,992
Börsenkurs
55,085
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53,589
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42,013
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40,982
USA
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26,486
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24,743
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22,844
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22,077
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21,170
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Gupta, Rangan
122
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119
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70
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59
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44
Sum, Vichet
40
Plastun, Alex
36
Hammoudeh, Shawkat
35
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35
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33
Ma, Feng
33
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31
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31
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31
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30
Mensi, Walid
30
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29
Chiang, Thomas C.
28
Narayan, Paresh Kumar
28
Spagnolo, Nicola
28
Vo Xuan Vinh
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26
Demirer, Rıza
26
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26
Arouri, Mohamed
24
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24
Grobys, Klaus
24
Hautsch, Nikolaus
24
Yoon, Seong-min
24
Balcilar, Mehmet
23
Kočenda, Evžen
23
Nartea, Gilbert V.
23
Salisu, Afees A.
23
Hanousek, Jan
22
Nguyen, Duc Khuong
22
Weber, Michael
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Jawadi, Fredj
21
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Finance research letters
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NBER working paper series
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Applied economics letters
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Pacific-Basin finance journal
168
International review of economics & finance : IREF
155
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International journal of economics and financial issues : IJEFI
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Cogent economics & finance
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The European journal of finance
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The quarterly review of economics and finance : journal of the Midwest Economics Association ; journal of the Midwest Finance Association
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Emerging markets finance & trade : a journal of the Society for the Study of Emerging Markets
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Investment management and financial innovations
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CESifo working papers
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Discussion paper / Centre for Economic Policy Research
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Finance India : the quarterly journal of Indian Institute of Finance
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Global finance journal
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ECONIS (ZBW)
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EconStor
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USB Cologne (EcoSocSci)
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USB Cologne (business full texts)
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date (oldest first)
1
Learning from the past : the role of personal experiences in artificial stock markets
Lenhard, Gregor
-
2024
Recent survey evidence suggests that investors form beliefs about future stock returns by predominantly extrapolating their own experience: They overweight returns they have personally experienced while underweighting returns from earlier years and consequently expect high (low) stock market...
Persistent link: https://www.econbiz.de/10014490050
Saved in:
2
An investigation into multivariate variance ratio statistics and their application to stock market predictability
Hong, Seok Young
;
Linton, Oliver
;
Zhang, Hui Jun
-
2015
We propose several multivariate variance ratio statistics. We derive the asymptotic distribution of the statistics and scalar functions thereof under the null hypothesis that returns are unpredictable after a constant mean adjustment (i.e., under the weak form Efficient Market Hypothesis). We do...
Persistent link: https://www.econbiz.de/10010496122
Saved in:
3
Stock Market
Bubbles
and Anti-
Bubbles
Tarlie, Martin
-
2018
Using a simple model of equity valuation, we de fine stock market
bubbles
and anti-
bubbles
as periods in which the … dynamics of valuation is temporarily explosive. We identify a mechanism for the creation and destruction of
bubbles
and anti-
bubbles
…
Persistent link: https://www.econbiz.de/10012935334
Saved in:
4
An application of asymmetric GARCH models on volatility of banks equity in Nigeria’s stock market
Asemota, Omorogbe J.
;
Ekejiuba, Ucheoma C.
- In:
CBN journal of applied statistics
8
(
2017
)
1
,
pp. 73-99
This paper examines the volatility of banks equity weekly returns for six banks (coded B1 to B6) using GARCH models. Results reveal the presence of ARCH effect in B2 and B3 equity returns. In addition, the estimated models could not find evidence of leverage effect. On evaluating the estimated...
Persistent link: https://www.econbiz.de/10011843494
Saved in:
5
Weak-form market efficiency and corruption : a cross-country comparative analysis
İcan, Özgür
;
Çelik, Taha Buğra
- In:
Journal of capital markets studies
7
(
2023
)
1
,
pp. 72-90
Purpose - The economic and administrative conditions of countries normatively have an effect on the economy and level of market development. Moreover, it is of great importance for a healthy economy whether the public institutions and organizations are transparent and functioning in accordance...
Persistent link: https://www.econbiz.de/10014318195
Saved in:
6
PREDICTING STOCK RETURN AND VOLATILITY WITH MACHINE LEARNING AND ECONOMETRIC MODELS : A COMPARATIVE CASE STUDY OF THE BALTIC STOCK MARKET
Nõu, Anders
;
Lapitskaya, Darya
;
Eratalay, Mustafa Hakan
; …
-
2022
For stock market predictions, the essence of the problem is usually predicting the magnitude and direction of the stock price movement as accurately as possible. There are different approaches (e.g., econometrics and machine learning) for predicting stock returns. However, it is non-trivial to...
Persistent link: https://www.econbiz.de/10013305881
Saved in:
7
Nonlinear asset pricing in Chinese stock market : a deep learning approach
Pan, Shuiyang
;
Long, Suwan
;
Wang, Yiming
;
Xie, Ying
- In:
International review of financial analysis
87
(
2023
),
pp. 1-9
Persistent link: https://www.econbiz.de/10014460620
Saved in:
8
Sup-ADF-style bubble-detection methods under test
Monschang, Verena
;
Wilfling, Bernd
-
2019
and date-stamping financial
bubbles
. In Monte Carlo simulations, we show that the SADF and GSADF tests may reveal …). Simulating stock-price trajectories that contain these parametric
bubbles
, we demonstrate that the SADF and GSADF tests can have …
Persistent link: https://www.econbiz.de/10012287533
Saved in:
9
Sector Level Equity Returns Predictability with Machine Learning and Market Contagion Measure
Peng, Weijia
;
Yao, Chun
-
2023
In this paper, we develop new latent risk measures that are designed as a prior synthesis of key forecasting information associated with financial market contagion. These measures are based on the decomposition (using high-frequency financial data) of the quadratic covariation between two assets...
Persistent link: https://www.econbiz.de/10014256827
Saved in:
10
Bubbles
and Trading Volume
Bidian, Florin
-
2015
Rational
bubbles
in stocks can cause increases in trading volume, even after accounting for their expansionary effect ….
Bubbles
, on the contrary, do not produce dividends and require more rebalancing after a bad shock …
Persistent link: https://www.econbiz.de/10013033019
Saved in:
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