This paper investigates how to improve prediction accuracy of stock realized volatility using a large set of predictors. Exploiting normalized positive adjusted R-square and significant t statistic of predictor obtained from the in-sample result as weight, we develop two simple and effective...

By using a unique data set of single-family house transactions, we examine the accuracy of the cost and sales comparison approach over different forecast horizons. We find that sales comparison values provide better long-term forecasts than cost values if the economic loss function is symmetric....

We show that house prices from Aberdeen in the UK improve in- and out-of-sample oil price forecasts. The improvements are of a similar magnitude to those attained using macroeconomic indicators. We explain these forecast improvements with the dominant role of the oil industry in Aberdeen. House...

Market value predictions for residential properties are important for investment decisions and the risk management of households, banks, and real estate developers. The increased access to market data has spurred the development and application of Automated Valuation Models (AVMs), which can...