Business & Economics
Neural Networks
100%
Value at Risk
45%
Finance
41%
Job Matching
40%
Cointegration
36%
Hill Estimator
35%
Stock Market Index
34%
Matching Model
34%
Prediction
34%
Estimator
33%
Error Correction Model
33%
Bayesian Analysis
32%
Safety-first
31%
Model Selection
31%
Subsampling
31%
Network Model
31%
Feedforward Neural Networks
30%
Order Statistics
30%
Bayesian Model
29%
Moving Average
29%
Wage Rigidity
28%
Trading Strategies
26%
Capital Markets
26%
Jump
24%
Econometrics
23%
Turbulence
22%
Job Creation
21%
GARCH Model
21%
Granger Causality
21%
Portfolio Selection
21%
Market Risk
20%
Market Segments
20%
Workers
20%
Deregulation
19%
Product Market
19%
Investors
18%
Feedforward Networks
16%
Cross-validation
16%
Financial Markets
15%
Wages
14%
Akaike Information Criterion
13%
Density Forecasts
11%
Mean-variance
10%
European Unemployment
10%
Empirical Research
10%
Market Development
10%
Mathematics
Forecasting
47%
Finance
43%
Forecast
39%
Error Correction Model
34%
Hill Estimator
30%
Extreme Order Statistics
30%
Portfolio Selection
28%
Value at Risk
28%
Subsampling
27%
Strong Mixing
26%
Financial Markets
26%
t-distribution
24%
Dependent Data
24%
Safety
23%
Neural Networks
19%
Estimator
18%
Time series
18%
Prediction
16%
Trading Strategies
16%
Strictly
15%
Granger Causality
15%
Network Architecture
15%
Cointegration
14%
Statistics
14%
Feedforward Neural Networks
14%
Stock Market
13%
Unknown
13%
Alternatives
12%
Information Criterion
12%
Moving Average
12%
Option Pricing
9%
Estimate
9%
Econometrics
9%
Relationships
6%
Antiderivative
6%
Density Functional
6%
Engineering & Materials Science
Financial markets
87%
Error correction
54%
Neural networks
50%
Finance
48%
Linear networks
40%
Statistics
15%
Liquids
13%
Time series
9%