不動產投資風險衡量之研究

Abstract

由於國民財富增加，對於不動產投資一事越來越熱衷，房屋不再只是供人居住使用，而成為重要的投資工具之一，但一般購屋投資者只考量投資『報酬』，卻忽略其『風險』，且由於傳統上對於投資不動產之風險只能以報酬率的標準差或變異數作計算，僅能知道其風險高或低，並不能夠確實知道其『風險值』，此外，投資者必須有分散風險之觀念，選擇適合的投資工具，以建立最佳的投資組合來分散風險。\r\n 本文以『市場風險』為主，並以『購屋者投資』角度，探討國內外衡量不動產投資風險之估計方法、模型，找出風險因子以建立一套衡量不動產投資風險因子之模式，並估計風險值，以評估投資之可行性。以1975第1季年至2003年第4季之預售屋平均房價季資料為主軸之時間範圍，並以台北市為研究的地理範圍，以預售屋住宅為研究標的，並以購屋消費者角色作分析，運用各種風險衡量方法，包括樣本變異數法、指數加權移動平均法、GRACH模型、歷史模擬方法、蒙地卡羅結構法、拔靴法、GRACH－拔靴法及VAR－拔靴法等估計風險值。\r\n\r\n 本文之實證結果顯示：\r\n\r\n一、以考量風險因子之VAR模型Ⅰ－拔靴法及VAR模型Ⅱ－拔靴法所估計之風險值最小，表示投資淨值一千萬元，有5﹪的機率可能的最大損失會大於591,218元或577,564元。\r\n\r\n二、以未考量風險因子之歷史模擬法及GARCH－拔靴法所估計風險值較大，表示投資淨值一千萬，有5﹪的機率可能的最大損失會大於2,816,827元或2,344,946元，因此，考量風險因子之VAR模型－拔靴法為較適當之模型，因有考量影響風險之因子，較能準確估計出實際之風險值。\r\n\r\n三、假設個案中估計調整後報酬率，在95﹪的信賴水準之下，未考慮風險因子模型估計之調整後報酬率為1.80﹪及2.32﹪，即持有一季後，調整後報酬約18及23萬元左右，而以考量風險因子之模型估計之調整後報酬率為2.37﹪及2.38﹪，即持有一季後報酬約24萬元左右。\r\n\r\n四、顯示投資組合於三種不同之投資工具時，當投資預售屋比例較大時，風險值是較小，而投資營建股價比例較大時，其風險值是較大。

As a result of national wealth increased, regarded real estate investment more and more desires, houses not only supply to live but also become one of investment tool, but general purchase investors only considered invest return but ignored risk at invest, as a result of traditional just estimated standard or variance of return represented risk, just to know the high or low of risk, but should not indeed to know the value at risk, investors must had concept of diversification, choose a appropriate investment tool and built the better portfolio to decrease risk.\r\n\r\n The current thesis was considered market risk and designed to examine the method or model of measure real estate risk, and looked for risk factors to build a set of model of real estate investment risk factors, and estimated value at risk to evaluate the feasible of investment. The current thesis used dates of time range are from 1975Q1 to 2003Q4, geography range is Taipei, pre-sales residential housing, and role of purchase consumer, apply many kinds of methods of measure risk, including Sample Variance, Exponentially Weighted Moving Average, Generalized Autoregressive Conditional Heteroskedasticity（GRACH）, Historical Simulation Method, Monte Carlo Simulation, Classical Bootstrap, GARCH－Bootstrap and VAR－Bootstrap, to estimate value at risk.\r\n\r\n The empirical result showed that the first, there had minimum value at risk by considering VAR－Bootstrap of risk factors, represented investitive net value are NT 10,000,000, maximum loss of 5﹪probability will greater than NT 591,218 or NT 577,564. Secondly, there are bigger value at risk by Historical Simulation Method of risk-factors free, represented investitive net value are NT 10,000,000, maximum loss of 5﹪probability will greater than NT 2,816,827 or NT 2,344,946. So used considering VAR－Bootstrap of risk factors were more appropriated model, because model of considering risk factors were able to accurate estimate reality value at risk. The third, case study estimated adjusted return, at 95﹪confidence level, risk-factors estimated rate of adjusted return were 2.37﹪and 2.38﹪, hold one quarterly period the return about two hundred and forty thousand dollars, If we have not consider risk-factors, estimated rate of adjusted return were 1.80﹪and 2.32﹪, hold one quarterly period the return about one hundred and eighty thousand dollars or two hundred and thirty thousand dollars. The last, invest portfolio three kinds of investment tool, if invest ratio of pre-sales residential housing were bigger, then value at risk were smaller, and if invest ratio of construct stock were bigger, then value at risk were bigger.