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2. Let denote the weight of the -th variable. The total score of stock at time ,
, , can be defined as:
, ,,
,
(2)
where is the vector of the weights of the input features. Given the scores for all
stocks, the ranking of a stock can be defined as:
, , ,
(3)
where is a ranking function so that , ∈N is the ranking of stock at time ,
and , , if , , .
3. Use rankings from step 2 to select the top-ranked stocks as components of a
portfolio. The performance of a portfolio can be evaluated by averaging the actual
returns of the stocks in the portfolio, which is defined as:
,
(4)
,
where , is the -th ranked stock at time ; is the actual return for a stock at
time and
is the average return over all the stocks in the portfolio at time .
4. Use the following two objectives to evaluate the performance of a stock selection
model.
The cumulative total (compounded) return:
,
(5)
, of the stocks in a
where is defined as the product of the average yearly return,
portfolio over consecutive years.
as the measure of risk:
The standard deviation of
,
(6)
σ
,
(7)
;
is the average return of all the stocks
where is defined as the mean of
in the portfolio at time .
5. With return and risk, use the non-dominated sorting and crowding distance [4] to
calculate the scores for all portfolios, in which the ranking of a portfolio can be de-
fined as:
if or ,
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