The value of tail risk hedging in defined contribution plans: What does history tell us

Hedging against tail events in equity markets has been forcefully advocated in the aftermath of recent global financial crisis. Whether this is beneficial to long horizon investors like employees enrolled in defined contribution (DC) plans, however, has been subject to criticism. We conduct historical simulation since 1928 to examine the effectiveness of active and passive tail risk hedging using out of money put options for hypothetical equity portfolios of DC plan participants with 20 years to retirement. Our findings show that the cost of tail hedging exceeds the benefits for a majority of the plan participants during the sample period. However, for a significant number of simulations, hedging result in superior outcomes relative to an unhedged position. Active tail hedging is more effective when employees confront several panic-driven periods characterized by short and sharp market swings in the equity markets over the investment horizon. Passive hedging, on the other hand, proves beneficial when they encounter an extremely rare event like the Great Depression as equity markets go into deep and prolonged decline.

Teaching persuasive texts : building a language of evaluation through hedging and moderated intensification

We identify two persuasive writing techniques – hedging and intensification – that pose difficulty for students in the middle years. We use examples of student writing from 3000 work samples collected as part of a larger Australian Research Council Linkage Project, URLearning (2009–2013). To realise the effective power of rhetorical persuasion, students need to be explicitly taught a range of hedging techniques to use to their advantage, and an expanded lexicon that does not rely on intensifiers. Practical teaching tips are provided for teachers.

Analysing children’s persuasive texts : the use of hedging and intensification

Research Quality This is a dialogue between two Australian literacy scholars about two persuasive writing techniques that posed difficulty for the students in our research. This dialogue flows from the analysis of Year 6 writing samples from an ARC Linkage Project, URLearning (2009-2013) - the focus of the symposium. We use vivid examples of writing from students’ handwritten persuasive texts on topics that were chosen by teachers. The persuasive structure in the texts followed the Toulmin (2003) model: a thesis statement, three arguments with evidence, and a conclusion. The findings show that to realise the effective power of rhetorical persuasion, students need an expanded lexicon that does not rely on intensifiers, and which employs a greater range of advanced hedging techniques to use to their advantage. National & International Importance The study is potentially of national and international relevance, given that argumentation or persuasion is a key life skill in many professional, personal, and discourses. It is also a requirement in the International English Language Testing Systems (IELTS) tests, which are a critical gateway for tertiary studies in many English-speaking countries (Coffin, 2004). Timeliness The research is timely given the Australian Curriculum English, in which persuasive texts figure prominently from Preparatory to Year 10 (ACARA, 2014). The recommendations are also timely in the context of educational policies in other parts of the world. For example, in the United States, the Common Core Standards: English Language Arts, mandates the teaching of persuasive texts (Council of Chief State School Officers & National Governors Association, 2013) Implications for practice/policy The findings of the study have specific practical implications for teachers, who can address the persuasive writing techniques of hedging and intensification with which children need targeted support and explicit instruction. The presentation is positioned at the nexus of teacher practice to better address the national priorities of the Australian Curriculum: English (ACARA, 2014), while having implications for applied linguistics research by identifying common problems in students' persuasive writing.

Hedging Options with Different Time Units in the Pricing Models

This study examined the effects of the Greeks of the options and the trading results of delta hedging strategies, with three different time units or option-pricing models. These time units were calendar time, trading time and continuous time using discrete approximation (CTDA) time. The CTDA time model is a pricing model, that among others accounts for intraday and weekend, patterns in volatility. For the CTDA time model some additional theta measures, which were believed to be usable in trading, were developed. The study appears to verify that there were differences in the Greeks with different time units. It also revealed that these differences influence the delta hedging of options or portfolios. Although it is difficult to say anything about which is the most usable of the different time models, as this much depends on the traders view of the passing of time, different market conditions and different portfolios, the CTDA time model can be viewed as an attractive alternative.

A new proposition on the martingale representation theorem and on the approximate hedging of contingent claim in mean-variance criterion

In this work we revisit the problem of the hedging of contingent claim using mean-square criterion. We prove that in incomplete market, some probability measure can be identified so that becomes -martingale under .This is in fact a new proposition on the martingale representation theorem. The new results also identify a weight function that serves to be an approximation to the Radon-Nikodým derivative of the unique neutral martingale measure.

The Baltic Dry Index: cyclicalities, forecasting and hedging strategies

The cyclical properties of the Baltic Dry Index (BDI) and their implications for forecasting performance are investigated. We find that changes in the BDI can lead to permanent shocks to trade of major exporting economies. In our forecasting exercise, we show that commodities and trigonometric regression can lead to improved predictions and then use our forecasting results to perform an investment exercise and to show how they can be used for improved risk management in the freight sector.

A decision-support system based on particle swarm optimization for multiperiod hedging in electricity markets

This paper proposes a particle swarm optimization (PSO) approach to support electricity producers for multiperiod optimal contract allocation. The producer risk preference is stated by a utility function (U) expressing the tradeoff between the expectation and variance of the return. Variance estimation and expected return are based on a forecasted scenario interval determined by a price range forecasting model developed by the authors. A certain confidence level is associated to each forecasted scenario interval. The proposed model makes use of contracts with physical (spot and forward) and financial (options) settlement. PSO performance was evaluated by comparing it with a genetic algorithm-based approach. This model can be used by producers in deregulated electricity markets but can easily be adapted to load serving entities and retailers. Moreover, it can easily be adapted to the use of other type of contracts.

Dynamic delta hedging of autocallables under a discrete rebalancing context

This work tests different delta hedging strategies for two products issued by Banco de Investimento Global in 2012. The work studies the behaviour of the delta and gamma of autocallables and their impact on the results when delta hedging with different rebalancing periods. Given its discontinuous payoff and path dependency, it is suggested the hedging portfolio is rebalanced on a daily basis to better follow market changes. Moreover, a mixed strategy is analysed where time to maturity is used as a criterion to change the rebalancing frequency.

Impact of Black-Scholes assumptions on Delta Hedging

In this work we are going to evaluate the different assumptions used in the Black- Scholes-Merton pricing model, namely log-normality of returns, continuous interest rates, inexistence of dividends and transaction costs, and the consequences of using them to hedge different options in real markets, where they often fail to verify. We are going to conduct a series of tests in simulated underlying price series, where alternatively each assumption will be violated and every option delta hedging profit and loss analysed. Ultimately we will monitor how the aggressiveness of an option payoff causes its hedging to be more vulnerable to profit and loss variations, caused by the referred assumptions.

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.

Dynamic programming for stochastic target problems, Viscosity solutions and hedging in markets with Portfolio constraints and large investors

The purpose of this expository arti le is to present a self- ontained overview of some results on the hara terization of the optimal value fun tion of a sto hasti target problem as (dis ontinuous) vis osity solution of a ertain dynami programming PDE and its appli ation to the problem of hedging ontingent laims in the presen e of portfolio onstraints and large investors