該篇文章中提出一個新的交易方式：條件機率交易模型conditional probability trading model。 這個模型應用了三個主要的基本假設： （1）總體經濟因子和股價指數間有相關性。因此可以透過總經指標來衡量股市應有的合理價位。 （2）股價具有回歸均數的特質。亦即股價一旦過度偏離基本價值，理論上會傾向回復到基本價值之上。 （3）股價指數相對於基本價值線的距離，將會影響偏態係數的大小。 根據以上三個性質，試圖建構出一個能夠捕捉股價指數變動的模型，並用以進行交易模擬，觀察其是否能獲取正報酬。 / The trading strategy, conditional probability trading model(CPTM), is presented in this article. We’ve tried to develop a new trading strategy which is built up by the combination of the properties which includes 1)the relationship between macroeconomic factors and stock market. 2) mean reversion and 3) conditional skewness. The conclusion implies that we may successfully find out a method to combine fundamental and technical analysis, if this method is proved effective. The former hypothesis is assumed that the different level of stock market index may stand for a specific condition of macroeconomic environment. Meanwhile, a better fundamental economic condition could reasonably create a higher stock market index, vice versa. By observing the fundamental value, we can figure out the market ,currently, is over-priced or under-priced. Next, we construct a trading model which is graphed like Bollinger bands. According to specific rules, it provides buying or selling signals. In some special situations, it can also forecast the turning points of the stock market precisely. 3) Skewness also plays a very important role in CPTM, because one of the hypothesis assumes that overpriced /underpriced stock market probably accompanies with left-skewed / right-skewed distribution of daily stock return. The hypothesis of dynamically adjusted skewness implies the concept that over-priced/under-priced stock market has higher propensity to decline/rise. To judge the trading timing is the core value in this model.