“Taps”: A trading approach based on deterministic sign patterns

We propose a new methodology for trading financial instruments based on deterministic sign patterns. These patterns are obtained from the m-dimensional elementary sample space consisting of -1,1m, the two possible signs for trading and with m varying. The collection of all possible sign combinations coming from this sample space creates a zero-cost trading strategy and we consider strategies that are selected from rotations among the possible sign sequences using several statistical criteria. Performing simulations, based on a geometric Brownian motion, we find that – on average – our strategies can outperform the buy & hold benchmark about 30% of the time in terms of total return and around 60% of the time in terms of maximum drawdown. We then illustrate the practical efficacy of the proposed strategies using daily returns from the S&P500 index, two of the largest Chinese stock market indices, the CSI300 and the SSE50, and three exchange traded funds (ETFs). Our results strongly suggest performance improvements over the corresponding buy & hold benchmarks and, furthermore, that these performance differences can be attributed to the entropy of the US and Chinese markets: we find that the two Chinese indices, which have larger entropy than the US index, provide considerable performance enhancements when traded based on our suggested methodology. © 2021 Elsevier Lt

Fathoming the Theta Method for a Unit Root Process

In this paper, building on earlier work by Assimakopoulos and Nikolopoulos ([2000. The theta model: a decomposition approach to forecasting. Int. J. Forecast., 16, 521�530], hereafter A&N) and Hyndman and Billah ([2003. Unmasking the theta method. Int. J. Forecast., 19, 287�290], hereafter H&B) on the properties and performance of the theta method, we derive new results for a unit root data generating process. In particular, (a) we investigate the theoretical underpinnings of the method when a single �theta line� is used, rather than a combination of two �theta lines� as in A&N and H&B, and we provide an optimal value for the theta parameter that coincides with the first-order autocorrelation of the innovations; (b) we demonstrate that the optimal forecast function for the model examined in A&N is identical with that of ARIMA(1,1,0) and (c) we provide formulae for optimal weights when combining two �theta lines� as in the model used by A&N in M3 competition�rather than an optimal value for the drift as in H&B. The paper concludes with a series of simulations as well as empirical investigations on the M3 yearly data

Forecasting Multivariate Time Series with the Theta Method

In this study building on earlier work on the properties and performance of the univariate Theta method for a unit root data-generating process we: (a) derive new theoretical formulations for the application of the method on multivariate time series; (b) investigate the conditions for which the multivariate Theta method is expected to forecast better than the univariate one; (c) evaluate through simulations the bivariate form of the method; and (d) evaluate this latter model in real macroeconomic and financial time series. The study provides sufficient empirical evidence to illustrate the suitability of the method for vector forecasting; furthermore it provides the motivation for further investigation of the multivariate Theta method for higher dimension

Return signal momentum

A new type of momentum based on the signs of past returns is introduced. This momentum is driven primarily by sign dependence, which is positively related to average return and negatively related to return volatility. An empirical application using a universe of commodity and financial futures offers supporting evidence for the existence of such momentum. Investment strategies based on return signal momentum result in higher returns and Sharpe ratios and lower drawdown relative to time series momentum and other benchmark strategies. Overall, return signal momentum can benefit investors as an effective strategy for speculation and hedging. © 2021 Elsevier B.V

Growth, deregulation and rent seeking in post-war British economy

There is a view that the financial sector of the post-war British economy was in need of reform that was postponed to the detriment of growth for 30 years until liberalisation started in full earnest after the election of 1979. There is another side of the story in this comparison. The first three decades of the post war period witnessed a decline in the share of wages accruing to the top percentile of earners. The trend was reversed around 1979, without any commensurate rise in output per person employed. The average growth rate of GDP in the second period was no greater than that in the first period because cyclical fluctuations were deeper. The de-regulation of the financial system allowed for recycling the wealth of the rich to contribute to housing inflation and rent seeking opportunities, creating an illusion of prosperity

On the realized volatility of the ECX CO 2 emissions 2008 futures contract: distribution, dynamics and forecasting

CO 2 price, Realized volatility, HAR-RV, Emissions markets, EU ETS, Intraday data, Forecasting, C5, G1, Q4,