Similar to the cross-sectional momentum crashes, the time series momentum experiences deep and persistent drawdowns in the stressed time of slumps in the upward momentum, rebounds in the downward momentum, and long time sideways market. We measure the upside and downside risk using the upper and...

In comparison to developed securities markets, it is intriguing to observe that the Chinese stock market's momentum or reversal effect is inconsistent. We address this controversy using a novel paradigm based on functional data analysis (FDA) with the goal of reconciling previous inconsistency....

We study forward curves formed from commodity futures prices listed on the Standard and Poor's-Goldman Sachs Commodities Index (S&P GSCI) using recently developed tools in functional time series analysis. Functional tests for stationarity and serial correlation suggest that log-differenced...

We propose a Multivariate Volatility Regulated Kelly strategy, which has extra penalization on variance compared to the Kelly criterion. The objective function is constructed and solved. We show the superiority of our method in relative low correlated portfolios, relatively to fractional Kelly...

In this paper, we employ a three-state hidden semi-Markov model (HSMM) to explain the time-varying distribution of the Chinese stock market returns since 2005. Our results indicate that the time-varying distribution depends on the hidden states, which are represented by three market conditions,...

We develop and study sequential testing procedures á la Chu et al. (1996) for on-line detection of changes in a time series from stationarity to mild forms of non-stationarity. The proposed tests are based on sequential CUSUM and KPSS-type detector processes, and are shown to provide consistent...

We propose a sequential monitoring scheme to find structural breaks in real estate markets. The changes in the real estate prices are modeled by a combination of linear and autoregressive terms. The monitoring scheme is based on a detector and a suitably chosen boundary function. If the...

The estimation of risk at extreme levels of significance (such as 0.1%) can be crucial to capture the losses during market downturns, such as the global financial crisis and the COVID-19 market crash. For many existing models, it is challenging to estimate risk at extreme levels of significance....

We employ the indicator saturation approach on electricity price series from the National Electricity Market (NEM) in Australia to simultaneously model the stylised facts of electricity prices, including extreme spikes, seasonality, level-shifts, and autocorrelation. Standard modelling methods...