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Forecasting for the generation of trading signals in financial markets
Author(s) -
Lam Kin,
Chung Lam King
Publication year - 2000
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/(sici)1099-131x(200001)19:1<39::aid-for743>3.0.co;2-b
Subject(s) - statistic , position (finance) , trading strategy , futures contract , key (lock) , transaction cost , investment (military) , hang , index (typography) , database transaction , computer science , financial market , economics , investment strategy , pairs trade , econometrics , finance , algorithmic trading , mathematics , statistics , market liquidity , alternative trading system , politics , world wide web , political science , computer security , law , programming language , operating system
In this paper we show that optimal trading results can be achieved if we can forecast a key summary statistic of future prices. Consider the following optimization problem. Let the return r i (over time i =1, 2, ..., n ) for the i th day be given and the investor has to make investment decision d i on the i th day with d i =1 representing a ‘long' position and d i =0 a ‘neutral' position. The investment return is given by r =Σ n i =1 r i d i − c Σ n +1 i =1 ∣ d i − d i −1 ∣, where c is the transaction cost. The mathematical programming problem of choosing d 1 , ..., d n to maximize r under a given transaction cost c is shown to have an analytic solution, which is a function of a key summary statistic called the largest change before reversal. The largest change before reversal is recommended to be used as an output in a neural network for the generation of trading signals. When neural network forecasting is applied to a dataset of Hang Seng Index Futures Contract traded in Hong Kong, it is shown that forecasting the largest change before reversal outperforms the k ‐step‐ahead forecast in achieving higher trading profits. Copyright © 2000 John Wiley & Sons, Ltd.