Emerging Needs and Tailored Products for Untapped Markets by Luisa Anderloni, Maria Debora Braga and Emanuele Maria Carluccio 13 doc
Emerging Needs and Tailored Products for Untapped Markets by Luisa Anderloni, Maria Debora Braga and Emanuele Maria Carluccio_1 docx
... parametric and semi-parametric models, and models
that have and do not have closed-form solutions. The typology appears in
Table 2.1.
Both linear and polynomial models have closed-form solutions for ... β>0.
3
GARCH stands for generalized autoregresssive conditional heteroskedasticity, and
was introduced by Bollerslev (1986, 1987) and Engle (1982). Engle received the Nobe...
Emerging Needs and Tailored Products for Untapped Markets by Luisa Anderloni, Maria Debora Braga and Emanuele Maria Carluccio_3 pot
... particular point forecasts. Granger and
Jeon (2002) have suggested “thick modeling” as a strategy for neural net-
works, particularly for forecasting. The idea is simple and straightforward.
We should ... two real numbers r
1
and r
2
from the [0, 1]
interval and one random number s from a standard normal distribution.
The mutated coefficient
Ω
i,p
is given by the following formu...
Emerging Needs and Tailored Products for Untapped Markets by Luisa Anderloni, Maria Debora Braga and Emanuele Maria Carluccio_5 pdf
... network
approximation by Lai and Wong (2001). The model has the following form:
y
t
= x
2
t−1
x
t
(5.12)
x
t
= .99x
t−1
+
t
(5 .13)
∼ N (0,σ
2
) (5.14)
Following Lai and Wong, we specify σ = .5 and x
0
= ... model
chaos model), forecast
onevar svjdmodel new1.m (for the stochastic volatil-
ity jump diffusion model), forecast
onevar markovmodel new1.m (for the
Markov regime switch...
Emerging Needs and Tailored Products for Untapped Markets by Luisa Anderloni, Maria Debora Braga and Emanuele Maria Carluccio_7 pptx
... process.
We specify four lags for the dependent variable. For quarterly data, this
is equivalent to a 12-month lag for monthly data, used by Stock and Watson
(1999) for forecasting inflation.
To make ... draw upon the standard Phillips curve framework used by Stock and
Watson (1999) for forecasting inflation in the United States. They define
the inflation as an h-period ahead fo...
Emerging Needs and Tailored Products for Untapped Markets by Luisa Anderloni, Maria Debora Braga and Emanuele Maria Carluccio_8 ppt
... an Application to
Forecasting Inflation,” IEEE Transactions in Neural Networks 12:
674–683.
Chow, Gregory (1960), “Statistical Demand Functions for Automobiles and
Their Use for Forecasting,” in ... (ed.), The Demand
for Durable Goods. Chicago: University of Chicago Press, 149–178.
Clark, Todd E., and Michael W. McCracken (2001), “Tests of Fore-
cast Accuracy and Encompassing for...
Emerging Needs and Tailored Products for Untapped Markets by Luisa Anderloni, Maria Debora Braga and Emanuele Maria Carluccio_9 doc
... Economics and Statistics:
212–218.
Mandic, Danilo, and Jonathan Chambers (2001), Recurrent Neural
Networks for Prediction: Learning Algorithms, Architectures, and
Stability. New York: John Wiley and ... Poloni, and G. Winter (eds.), Genetic
Algorithms and Evolution Strategy in Engineering and Computer
Science: Recent Advances and Industrial Applications. West Sussex,
England...
Emerging Needs and Tailored Products for Untapped Markets by Luisa Anderloni, Maria Debora Braga and Emanuele Maria Carluccio_10 pptx
... bond market for confirmation. A bullish technical forecast for bonds is also
a bullish technical forecast for stocks. Conversely, a bearish analysis for bonds is a
bearish forecast for stocks. ... market and falling commodity markets, the spring and early summer saw
surging commodity markets and a weak bond market. This surge in the CRB Index
was caused mainly by strong g...
Emerging Needs and Tailored Products for Untapped Markets by Luisa Anderloni, Maria Debora Braga and Emanuele Maria Carluccio_13 doc
... 1955, before computers were so common,
the RAND Corporation published a book entitled A Million Random Digits.
It was used in selecting random trials for experimental designs and simulations
(and ... prices
that can be forecast based on a given information set.
The only possible changes in price are random,
driven by unforecastable external information.
Profits occur only by chance....
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