A Dynamic Fuzzy Money Management Approach for Controlling the Intraday Risk-Adjusted Performance of AI Trading Algorithms

The majority of existing artificial intelligence (AI) studies in computational finance literature are devoted solely to predicting market movements. In this paper we shift the attention to how AI can be applied to control risk-based money management decisions. We propose an innovative fuzzy logic approach which identifies and categorizes technical rules performance across different regions in the trend and volatility space. The model dynamically prioritizes higher performing regions at an intraday level and adapts money management policies with the objective to maximize global risk-adjusted performance. By adopting a hybrid method in conjunction with a popular neural network (NN) trend prediction model, our results show significant performance improvements compared with both standard NN and buy-and-hold approaches. Copyright © 2014 John Wiley & Sons, Ltd.     

Volatility and Market Risk of Rubber Price in Malaysia: Pre- and Post-Global Financial Crisis

The volatility in rubber price is a significant risk to producers, traders, consumers and others who are involved in the production and marketing of natural rubber. Such being the case, forecasting the rubber price volatility is desired to assist in decision-making in this uncertain situation. The 2008 Global Financial Crisis caused some disruptions and uncertainties in the future supply or demand for natural rubber and thus leading to higher rubber price volatility. Using ARCH-type models, this paper intends to model the dynamics of the price volatility of Standard Malaysia Rubber Grade 20 (SMR 20) in the Malaysian market before and after the Global Financial Crisis. Additionally, Value-at-Risk (VaR) approach is implemented to evaluate the market risk of SMR 20. Our empirical result denotes the existence of volatility clustering and long memory volatility in the SMR 20 market for both crisis periods. Leverage effect is also detected in the SMR 20 market where negative innovations (bad news) have a larger impact on the volatility than positive innovations (good news) for post-crisis period. When tested with Superior Predictive Ability (SPA) test, FIGARCH model is the best model across five loss functions for short- and long-term forecasts for pre-crisis period. Meanwhile, over post-crisis period, FIGARCH and GJR GARCH indicate the superior out-of-sample-forecast results and better forecasting accuracy over short- and long-term horizons, respectively. In terms of market risk, the short trading position encounters higher risk or greater losses than the long trading position at both 1 and 5 % VaR quantile for pre-crisis period. In contrast, over post-crisis period, long traders of rubber SMR 20 tend to face limited gains but unlimited losses.

     

Does board gender diversity improve the informativeness of stock prices?

We show that stock prices of firms with gender-diverse boards reflect more firm-specific information after controlling for corporate governance, earnings quality, institutional ownership and acquisition activity. Further, we show that the relationship is stronger for firms with weak corporate governance suggesting that gender-diverse boards could act as a substitute mechanism for corporate governance that would be otherwise weak. The results are robust to alternative specifications of informativeness and gender diversity and to sensitivity tests controlling for time-invariant firm characteristics and alternative measures of stock price informativeness. We also find that gender diversity improves stock price informativeness through the mechanism of increased public disclosure in large firms and by encouraging private information collection in small firms.     

A tale of two yield curves: Modeling the joint term structure of dollar and euro interest rates

Modeling the joint term structure of interest rates in the United States and the European Union, the two largest economies in the world, is extremely important in international finance. In this article, we provide both theoretical and empirical analysis of multi-factor joint affine term structure models (ATSM) for dollar and euro interest rates. In particular, we provide a systematic classification of multi-factor joint ATSM similar to that of Dai and Singleton (2000). A principal component analysis of daily dollar and euro interest rates reveals four factors in the data. We estimate four-factor joint ATSM using the approximate maximum likelihood method of [A?t-Sahalia, 2002] and [A?t-Sahalia, forthcoming] and compare the in-sample and out-of-sample performances of these models using some of the latest nonparametric methods. We find that a new four-factor model with two common and two local factors captures the joint term structure dynamics in the US and the EU reasonably well.     

Population growth and the benefits from optimally priced externalities

"In this article we show that, considering only economic effects, even if population growth, by natural increase or immigration, increases congestion, pollution, and other forms of external costs, that provided pre-existing citizens own the resources giving rise to the externalities, and provided they efficiently price usage of such, that existing citizens must, in net average terms, be better off with population growth than without it. In simple terms the increased revenues they gain from efficient pricing at increased demand levels will be strictly greater than the monetary value of the increased external costs together with the higher tax costs they incur as consumers of the resources."     

Effects of Employee Support on Junior Accountants' Job Attitudes and Intention to Quit

This study examines the effects of four types of employee support on a sample of 231 junior accountants' organisational commitment, job involvement and intention to quit. The four types of support include organisational, supervisory, psycho-social and career development support. Results of path analysis suggest that only organisational support and psycho-social support influence organisational commitment which, in turn, increases job involvement and reduces intention to quit.     

A feasibility study of stateful automaton packet inspection for streaming application detection systems

The rapid development of the internet has brought huge benefits and social impacts; however, internet security has also become a great problem for users, since traditional approaches to packet classification cannot achieve satisfactory detection performance due to their low accuracy and efficiency. In this paper, a new stateful packet inspection method is introduced, which can be embedded in the network gateway and used by a streaming application detection system. This new detection method leverages the inexact automaton approach, using part of the header field and part of the application layer data of a packet. Based on this approach, an advanced detection system is proposed for streaming applications. The workflow of the system involves two stages: the training stage and the detection stage. In the training stage, the system initially captures characteristic patterns from a set of application packet flows. After this training is completed, the detection stage allows the user to detect the target application by capturing new application flows. This new detection approach is also evaluated using experimental analysis; the results of this analysis show that this new approach not only simplifies the management of the state detection system, but also improves the accuracy of data flow detection, making it feasible for real-world network applications.     

Antecedents and outcomes of managing diversity in a UK context: test of a mediation model

Abstract

Extant research on diversity management (DM) has primarily examined the main effects of diversity management practices (DMP) on outcomes from an organizational perspective. Meta-analysis in this field corroborates the conclusion that this approach is unable to account for the outcomes of DM effectively. The current study extends the literature by examining micro-level antecedents of DMP. This study also examines the mediating influences of perception of overall justice (POJ) and social exchange with organization (SEWO) on the relationships between DMP and work outcomes of career satisfaction (CS) and turnover intention (TI). Results of data obtained from a cross section of 191 minority employees in UK revealed: (i) the reasons why organizations adopted and implemented DMP influenced employees’ outcomes of TI and CS; (ii) the relationship between DM and SEWO is mediated by POJ; (iii) SEWO relates to increased CS; and (iv) DMP related positively to CS through POJ and SEWO.