CAJ | 학술논문

金融资产收益分布的非对称性不仅是投资组合选择过程中应该考虑的一个重要因子,而且与风险识别与测度也有着千丝万缕的联系.本文采用List提出的一种基于Bootstrap思想的金融资产收益分布非对称性测度方法,开展了对上证综指、深证成指、中小板指数和创业板指数等中国股票市场4种代表性股价指数收益非对称特征的全面深入检验,研究结果表明：除了中小板指数收益具有较为明显的非对称性特征外,其它3种股价指数的收益分布在较高置信水平上都可以被认为具有对称特征.论文的研究结果为金融时间序列非对称特征的考察及中国股票市场收益分布特征的研究提供了新的证据.
금융자산수익분포적비대칭성불부시투자조합선택과정중응해고필적일개중요인자,이차여풍험식별여측도야유착천사만루적련계.본문채용List제출적일충기우Bootstrap사상적금융자산수익분포비대칭성측도방법,개전료대상증종지、심증성지、중소판지수화창업판지수등중국고표시장4충대표성고개지수수익비대칭특정적전면심입검험,연구결과표명：제료중소판지수수익구유교위명현적비대칭성특정외,기타3충고개지수적수익분포재교고치신수평상도가이피인위구유대칭특정.논문적연구결과위금융시간서렬비대칭특정적고찰급중국고표시장수익분포특정적연구제공료신적증거.
The asymmetry in return distributions of financial assets is not only an important factor in optimal portfolio selection,but also highly related to risk identification and risk measurement.In recent years,a growing number of scholars have spent efforts in investigating asymmetries in price fluctuation of financial assets.This area of study still has many controversial issues.For instance,the effective approaches that should be adopted to test asymmetry in asset return distribution remain unresolved.The common approach to test asymmetry in asset return distribution is to define the coefficient of skewness of the standardized third central moment.However,when using the coefficient of skewness to test asymmetry key assumptions are that not only asset prices need to be independent of each other,but also the asset return should obey normal distribution.When the return distribution does not obey normal distribution or prices are not independent of each other,testing asymmetry based on the standardized third central moment can lead to unreliable results.Many empirical studies show that square or absolute values of returns exhibit a strong positive correlation even though the correlation of mean values of asset returns is not significant.This finding confirms that the fluctuations of asset prices in different time point are not independent.For the common frequency of selections,such as daily or weekly returns,the hypothesis for normal distribution will be rejected.In order to solve the issue,List presents a new way to test asymmetry in return distributions of financial assets based on the Bootstrap Theory.This approach is not only suitable for non-normal and non-independent data,but also based on the stability test results of Monte-Carlo simulation.For time series from different data generating process （DGP）,the result of the asymmetry test based on this approach is highly consistent with data generating process.Many empirical studies of China stock market use descriptive statistics of financial returns for asymmetry test; however,most of methods adopted by these studies are limited to the traditional asymmetry test of the sample skewness coefficient.Scholars have not adopted Bootstrap approach,which is more suitable to real financial data to study China stock market.Based on sample data of representative indices from China stock market,this paper determines autocorrelation of stock index returns and uses ARMA models as a decorrelation method..Thus,all the index return orders can satisfy the preconditions of Bootstrap approach.This paper also adopts procedures in asymmetry test of Bootstrap approach and empirical test the asymmetry of returns in China stock market.This approach can help answer whether there is a significant asymmetry in return distributions of China stock market.Our finding shows that small and medium-sized board index has a relative significant asymmetry,and the other three indices of return distributions are symmetrical even in a relative higher significant level.Based on the asymmetry test of these four kinds of stock indices,this paper uses the Bootstrap approach to reach conclusions.The conclusion could be more convincing than the traditional skewness coefficient approach.The research method and empirical results of this paper have great theoretical and practical implications.Firstly,this paper adopts the Bootstrap approach for modeling the return distribution in China stock market,asset pricing,risk management and other relating areas.Empirical results exhibit that different indices have different asymmetrical characteristics.These findings offer some help to investors for making right investment strategies and to regulators for making different policies for different markets.