초고빈도 환율의 불연속 점프 변동성과 주기성에 대한 비모수적 추정

The parametric approaches such as the ARCH class of the models andstochastic volatility models, however, rely on explicit functional forms whichcan be misspecified and mainly low frequency financial data. Furthermore,the parametric approaches are very difficult to capture the properties ofmicrostructure of financial markets and announcement effects of importantfinancial and economic information. To overcome this drawback of theparametric approach, in recent years a few studies adopt nonparametricapproaches which are free from specific functional forms using ultra highfrequency financial data. Thus this paper uses a new nonparametric realized volatility modelby summing intraday returns to analyze the discrete jumps as well ascontinuous volatility in returns of the exchange rate of Korean won. Firstof all, this paper introduces and analyzes the realized volatility, bipowervolatility, tripower quarticity, quadpower quarticity and relative jump modelsand then estimate whether the jumps are significant or not according toseveral derived jump statistics. Then this paper estimates whether the jumpsare significant or not according to derived jump statistics which are derivedfrom the realized volatility variables. Then this paper compares the discrete jump volatility of the exchangerate returns of Korean won versus US dollar using the ultra-high frequencyfive minute returns spanning the period from year 2003 through 2010. Thispaper also includes the Realized Outlyingness Weighted Variance (ROWV)and Realized Outlying Weighted Quarticity (ROWQ) to obtain more efficientand robust jump estimates. Furthermore, this paper includes the periodicityfilters of volatility such as median absolute deviation (MAD), Short HalfScale estimator and Weighted Standard deviation (WSD) to analyze and toidentify whether the jumps are significant or not according to derived jumpstatistics. These estimators have the advantage that they are little affectedby jumps affecting two contiguous returns and periodicity. The proposed robust estimation and jump detection depend on ROWVand ROWQ, and the several periodicity filters such as MAD, Short Half Scale,and WSD. Thus this paper compares the results of jumps detection usingnon filtered return tests and the filtered return tests with max outlyingness.This paper finds that if we include periodicity filters such as MAD, ShortHalf Scale and WSD, jumps occurred less frequently and the proportionof days with significant jumps of the exchange rate returns of Korean wonversus US dollar appeared smaller during years 2003 through 2010. Firstly, when we did not use any periodicity filters, jump probabilitiesin the exchange rate returns of Korean won versus US dollar appeared higherthan 82% at the common critical levels. Secondly, we use Short Half Scalefilters, we have the approximate 66% of jump probabilities in the exchangerate returns of Korean won versus US dollar at the common critical levels. Thirdly, when we use WSD filters, we have the approximate 49% ofjump probability so that five minute returns in the exchange rate returnsof Korean won versus US dollar have the discrete frequent jumps inapproximately two days during years 2003 through 2010. Then we consider the max outlyingness as well as the periodicity filterssuch as MAD, Short Half Scale and WSD in jump statitics. First of all, weuse intraday observations. While when we do not consider any periodicityfilter, the jump probabilities of the realized returns of Korean won versusUS dollar appeared approximately 77%, when we do consider periodicityfilters such as MAD, Short Half Scale and WSD, the jump probabilities ofthe realized returns of Korean won appeared 77%, 62% and 47% at =0.999,respectively. Then we use intraday periods. While when we do not consider anyperiodicity filter, the jump probabilities of the realized returns of Koreanwon versus US dollar appeared approximately 81%, when we do considerperiodicity filters such as MAD, Short Half Scale and WSD, the jumpprobabilities of the realized returns of Korean won appeared approximately80%, 65% and 48%, respectively. Thus we found that when we consider periodicity filters such as MAD,Short Half Scale and WSD in jump statistics, jumps in the exchange ratereturns of Korean won versus US dollar occurred also less frequently andthe proportion of days with significant jumps in the exchange rate returnsof Korean won are also smaller. Thus the jump probabilities for five minute returns of the exchangerate of Korean won versus US dollar spanning the period from year 2003through 2010 can be different according to which jump statistic we use.When we use the robust periodicity estimation such as MAD, Short HalfScale and WSD in jump probabilities, five minute returns in the exchangerate returns of Korean won versus US dollar have shown less frequent jumps.