本研究以Ederington and Guan (2005)所提出之限制最小平方估計模型(RLS),針對三個不同市場(股價指數、利率及個股股價)共十二種金融資產報酬率作波動性之評估,並以平方根預測誤差來評估、比較其與另外三種常用波動性預測模型(歷史標準差、指數加權移動平均、GARCH(1,1)模型)之波動性預測能力。實證研究指出限制最小平方模型其平方根預測誤差爲在十二項金融資產中均小於其他三個預測模型之平方根預測誤差,因此限制最小平方(RLS)模型之樣本內波動性預測能力優於其它三種實證模型。然而,模型之樣本外預測能力則無一致性之結果。
In this paper, we apply the RLS model, proposed by Ederington and Guan (2005), to perform the volatility valuations of the returns of twelve financial assets in three different financial markets (stock index, interest rate and individual stock markets) and use the root mean square forecast error (RMSFE) as the loss function to compare the in-sample forecasting ability of the RLS model with the other three competing models (STD, EWMA and GARCH (1,1)). Empirical results indicate that the root mean square forecast error of the RLS model is less than those generated by the other three models. Consequently, the RLS model delivers superior forecasting ability to alternative models. However, there is no consistent result for out-of-sample predictive analysis.