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We developed a nicking endonuclease
dependent DNA amplification (NDA), using Nt.BstNBI
to catalyze single-stranded nick on double-stranded DNA, and Bst DNA polymerase
to make extension while sealing the nick and displacing the downstream strand. The
displaced single-stranded DNA thereby serves as template for primers hybridization
and extension, resulting in exponential synthesis of target DNA under isothermal
condition. Over 105 folds target DNA amplification can be achieved
in 30 minutes, generating DNA product suitable for both diagnosis and DNA cloning.
This NDA strategy does not require thermal cycling or prerequisite nucleotides
modification, making it suitable for application in the field and at the point-of-care.
Due to the illiquidity of inventories pledged, the essential of price risk management of supply chain finance is to long-term price risk measure. Long memory in volatility, which attests a slower than exponential decay in the autocorrelation function of standard proxies of volatility, yields an additional improvement in specification of multi-period volatility models and further impact on the term structure of risk. Thus, long memory is indispensable to model and measure long-term risk. This paper sheds new light on the impact of the existence and persistence of long memory in volatility on inventory portfolio optimization. Firstly, we investigate the existence of long memory in volatility of the inventory returns, and examine the impact of long memory on the modeling and forecasting of multi-period volatility, the dependence structure between inventory returns and portfolio optimization. Secondly, we further explore the impact of the persistence of long memory in volatility on the efficient frontier of inventory portfolio via a data generation process with different long memory parameter in the FIGARCH model. The extensive Monte Carlo evidence reveals that both GARCH and IGARCH models without accounting for long memory will misestimate the actual long-term risk of the inventory portfolio and further bias the efficient frontier; besides, through A sensitive analysis of long memory parameter d, it is proved that the portfolio with higher long memory parameter possesses higher expected return and lower risk level. In conclusion, banks and other participants will benefit from the long memory taken into the long-term price risk measure and portfolio optimization in supply chain finance.