The effects of derivative use on equity fund performance

Investing in mutual funds has become more popular than ever and the amount of money invested in mutual funds registered in Finland has hit its all-time high. Mutual funds provide a relatively low-cost method for private investors to invest in stock market and achieve diversified portfolios. In finance there is always a tradeoff between risk and return, where higher expected returns can usually be achieved only by taking higher risks. Diversifying the portfolio gets rid some of the risk but systematic risk cannot be diversified away. These risks can be managed by hedging the investments with derivatives. The use of derivatives should improve the performance of the portfolios using them compared to the funds that don’t. However, previous studies have shown that the risk exposure and return performance of derivative users does not considerably differ from nonusers. The purpose of this study is to examine how the use of derivatives affects the performance of equity funds. The funds studied were 155 equity funds registered in Finland in 2013. Empirical research was done by studying the derivative use of the funds during a 6-year period between 2008–2013. The performance of the funds was studied quantitatively by using several different performance measures used in mutual fund industry; Sharpe Ratio, Treynor Ratio, Jensen's alpha, Sortino Ratio, M2 and Omega Ratio. The effect of derivative use on funds' performance was studied by using a dummy variable and comparing performance measures of derivative-users and nonusers. The differences in performance measures between the two groups were analyzed with statistical tests. The hypothesis was that funds' derivative use should improve their performance relative to the funds that don't use them. The results of this study are in line with previous studies that state that the use of derivatives does not improve mutual funds' performance. When performance was measured with Jensen's alpha, funds that did not use derivatives performed better than the ones that used them. When measured with other performance measures, the results didn’t differ between two groups.

Derivative hedging strategies for bitumen price risk

The objective of the study is to extend the existing hedging literature of the commodity price risks by investigating what kind of hedging strategies can be used in companies using bitumen as raw material in their production. Five different alternative swap hedging strategies in bitumen markets are empirically tested. Strategies tested are full hedge strategy, simple, conservative, and aggressive term structure strategies, and implied volatility strategy. The effectiveness of the alternative strategies is measured by excess returns compared to no hedge strategy. In addition, the downside risk of each strategy is measured with target absolute semi-deviation. Results indicate that any of the tested strategies does not outperform the no hedge strategy in terms of excess returns in all maturities. The best-performing aggressive term structure strategy succeeds to create positive excess returns only in short maturities. However, risk seems to increase hand-in-hand with the excess returns so that the best-performing strategies get the highest risk metrics as well. This implicates that the company willing to gain from favorable price movements must be ready to bear a greater risk. Thus, no superior hedging strategy over the others is found.

Does friendship give us non-derivative partial reasons ?

Une des façons d’approcher la question de l’existence de raisons partiales non-dérivatives d’une quelconque sorte consiste à expliquer ce que sont les raisons partiales et ensuite à chercher à savoir s’il y a des raisons de cette sorte. Si de telles raisons existent, alors il est au moins possible qu’il y ait des raisons partiales d’amitié. C’est cette approche que j’adopterai ici, et elle produit des résultats intéressants. Le premier a trait à la structure des raisons partiales. C’est au moins une condition nécessaire pour qu’une raison soit partiale qu’elle aie une composante relationnelle explicite. Cette composante, techniquement parlant, est un relatum dans la relation d’être une raison qui elle-même est une relation entre la personne à qui la raison s’applique et la personne concernée par l’action pour laquelle il y a une raison. La deuxième conclusion de ce texte est que cette composante relationnelle est aussi requise dans de nombreuses sortes de raisons admises comme impartiales. Afin d’éviter de banaliser la distinction entre raisons partiales et impartiales nous devons appliquer une condition suffisante additionnelle. Finalement, bien qu’il pourrait s’avérer possible de distinguer les raisons impartiales ayant une composante relationnelle des raisons partiales, cette approche suggère que la question de savoir si l’éthique est partiale ou impartiale devra se régler au niveau de l’éthique normative, ou à tout le moins, qu’elle ne pourra se régler au niveau du discours sur la nature des raisons d’agir.

A PVC Plasticized Sensor for Ni(II) Ion Based on a Simple Ethylenediamine Derivative

new PVC membrane ion selective electrode which is highly selective towards Ni(II) ions was constructed using a Schiff base containing a binaphthyl moiety as the ionophore. The sensor exhibited a good Nernstian response for nickel ions over the concentration range 1.0 × 10–1 – 5.0 × 10–6 M with a lower limit of detection of 1.3 × 10–6 M. It has a fast response time and can be used for a period of 4 months with a good reproducibility. The sensor is suitable for use in aqueous solutions in a wide pH range of 3.6 – 7.4 and works satisfactorily in the presence of 25% (v/v) methanol or ethanol. The sensor shows high selectivity to nickel ions over a wide variety of cations. It has been successfully used as an indicator electrode in the potentiometric titration of nickel ions against EDTA and also for the direct determination of nickel content in real samples: effluent samples, chocolates and hydrogenated oils.

A Nonparametric Approach to Pricing and Hedging Derivative Securities via Learning Networks

We propose a nonparametric method for estimating derivative financial asset pricing formulae using learning networks. To demonstrate feasibility, we first simulate Black-Scholes option prices and show that learning networks can recover the Black-Scholes formula from a two-year training set of daily options prices, and that the resulting network formula can be used successfully to both price and delta-hedge options out-of-sample. For comparison, we estimate models using four popular methods: ordinary least squares, radial basis functions, multilayer perceptrons, and projection pursuit. To illustrate practical relevance, we also apply our approach to S&P 500 futures options data from 1987 to 1991.

General derivative relations for anharmonic force fields

The brace notation, introduced by Allen and Csaszar (1993, J. chem. Phys., 98, 2983), provides a simple and compact way to deal with derivatives of arbitrary non-tensorial quantities. One of its main advantages is that it builds the permutational symmetry of the derivatives directly into the formalism. The brace notation is applied to formulate the general nth-order Cartesian derivatives of internal coordinates, and to provide closed forms for general, nth-order transformation equations of anharmonic force fields, expressed as Taylor series, from internal to Cartesian or normal coordinate spaces.

X-ray crystallographic study of DNA duplex cross-linking: simultaneous binding to two d(CGTACG)(2) molecules by a bis(9-aminoacridine-4-carboxamide) derivative

Acridine-4-carboxamides form a class of known DNA mono-intercalating agents that exhibit cytotoxic activity against tumour cell lines due to their ability to inhibit topoisomerases. Previous studies of bis-acridine derivatives have yielded equivocal results regarding the minimum length of linker necessary between the two acridine chromophores to allow bis-intercalation of duplex DNA. We report here the 1.7 angstrom resolution X-ray crystal structure of a six-carbon-linked bis(acridine-4-carboxamide) ligand bound to d(CGTACG)(2) molecules by non-covalent duplex cross-linking. The asymmetric unit consists of one DNA duplex containing an intercalated acridine-4-carboxamide chromophore at each of the two CG steps. The other half of each ligand is bound to another DNA molecule in a symmetry-related manner, with the alkyl linker threading through the minor grooves. The two crystallographically independent ligand molecules adopt distinct side chain interactions, forming hydrogen bonds to either O6 or N7 on the major groove face of guanine, in contrast to the semi-disordered state of mono-intercalators bound to the same DNA molecule. The complex described here provides the first structural evidence for the non-covalent cross-linking of DNA by a small molecule ligand and suggests a possible explanation for the inconsistent behaviour of six-carbon linked bis-acridines in previous assays of DNA bis-intercalation.

Design of a minimum variance multiple input-multiple output neuro self-tuning proportional-integral-derivative controller for non-linear dynamic systems

In this study a minimum variance neuro self-tuning proportional-integral-derivative (PID) controller is designed for complex multiple input-multiple output (MIMO) dynamic systems. An approximation model is constructed, which consists of two functional blocks. The first block uses a linear submodel to approximate dominant system dynamics around a selected number of operating points. The second block is used as an error agent, implemented by a neural network, to accommodate the inaccuracy possibly introduced by the linear submodel approximation, various complexities/uncertainties, and complicated coupling effects frequently exhibited in non-linear MIMO dynamic systems. With the proposed model structure, controller design of an MIMO plant with n inputs and n outputs could be, for example, decomposed into n independent single input-single output (SISO) subsystem designs. The effectiveness of the controller design procedure is initially verified through simulations of industrial examples.

Electronic energy transfer in a dinuclear Ru/Os complex containing a photoresponsive dithienylethene derivative as bridging ligand

In order to build up a multicomponent system able to perform useful light-induced functions, a dithienylethene-bridged heterodinuclear metal complex (Ru/Os) has been prepared. The compound was characterized and its photophysical properties studied in detail.

A neural network enhanced generalized minimum variance self-tuning proportional, integral and derivative control algorithm for complex dynamic systems

A neural network enhanced proportional, integral and derivative (PID) controller is presented that combines the attributes of neural network learning with a generalized minimum-variance self-tuning control (STC) strategy. The neuro PID controller is structured with plant model identification and PID parameter tuning. The plants to be controlled are approximated by an equivalent model composed of a simple linear submodel to approximate plant dynamics around operating points, plus an error agent to accommodate the errors induced by linear submodel inaccuracy due to non-linearities and other complexities. A generalized recursive least-squares algorithm is used to identify the linear submodel, and a layered neural network is used to detect the error agent in which the weights are updated on the basis of the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model, and therefore the error agent is naturally functioned within the control law. In this way the controller can deal not only with a wide range of linear dynamic plants but also with those complex plants characterized by severe non-linearity, uncertainties and non-minimum phase behaviours. Two simulation studies are provided to demonstrate the effectiveness of the controller design procedure.

Self-tuning proportional, integral and derivative controller based on genetic algorithm least squares

A self-tuning proportional, integral and derivative control scheme based on genetic algorithms (GAs) is proposed and applied to the control of a real industrial plant. This paper explores the improvement in the parameter estimator, which is an essential part of an adaptive controller, through the hybridization of recursive least-squares algorithms by making use of GAs and the possibility of the application of GAs to the control of industrial processes. Both the simulation results and the experiments on a real plant show that the proposed scheme can be applied effectively.

Eliminativism about derivative prima facie duties

Ross divides prima facie duties into derivative and foundational ones, but seems to understand the notion of a derivative prima facie duty in two very different ways. Sometimes he understands them in a non-eliminativist way. According to this understanding, basic prima facie duties ground distinct derivative ones. According to the eliminativist understanding, basic duties do not ground distinct derivative duties, but replace (eliminate) them. On the eliminativist view, discovering that a prima facie duty is derivative is discovering that it is not genuine. The genuine one is the basic one. I argue that Ross is best understood as an eliminativist.

The synthesis of dicobalt and dinickel complexes of trimethylsilylethynyl-1, 2-dihydrofullerene; characterisation by n.m.r. and structure of the first acyclic metal fullerene derivative: molecular structure of [η2-{2-H-1-(Me3SiC ≡ C)-C60}Ni2(η-C5H5)2]

The synthesis and characterisation of the complexes [η2-{2-H-1-(Me3SiC ≡ C)-C60}Co2(CO)6] (2)} and [η-2-{2-H-1-(Me3SiC ≡ C)-C60}Ni2η-C5H5)2] (3)} is reported, together with a single-crystal molecular structure for (3). This provides the first structural data for an acyclic metal derivative of [60]-fullerene.