需要fama French三因子模型计算行业不确定性，时间是1998-2018年，急求，有偿，联系方式：QQ-3024816487
具体计算方法参考文献描述如下：We perform the following procedures to generate the uncertainty measure. We first compute the monthly value-weighted market returns for each industry using information from COMPUSTAT and CRSP. We then specify the following model to forecast monthly industry returns recursively from 1950–2007:
Rt−RFt = a + b*MKTRFt + s*SMBt + h*HMLt + et
Rt is the return on the stock portfolio in an industry. RFt is the risk-free return rate. Rt−RFt is the excess return on the stock
portfolio. MKTRFt is the excess market return over the risk-free return rate where the market return is the value-weighted return
on all stocks. SMBt is the difference between small-firm return and big-firm return. HMLt is the difference between high book-tomarket equity return and low book-to-market equity return. The average adjusted R-square for all the regressions based on Eq. (1)is 0.58, suggesting that the forecasting model indeed captures a significant fraction of the variation in stock returns (Fama and French, 1993).
Last, we take the standard error of the regression as the uncertainty measure (market volatility — standard error). The
forecasting equation filters out the systematic component and the standard error of the regression represents what is volatile and unpredictable. This volatility measure is consistent with suggestions from the theoretical real options work and with previous empirical real options work