The Indian Ocean as a Memory Space

This conversation with the author Neera Kapur-Dromson took place in Nairobi, Kenya, on 9th March 2018 during filming of the documentary film ‘Afrasian Memories in East Africa’ in which Neera Kapur-Dromson features. Neera Kapur-Dromson lives in France and Kenya. She is the author of the book ‘From Jhelum to Tana’. Here, Neera-Kapur Dromson reflects upon transregional interactions across the Indian Ocean as a memory space through life histories of various generations of her ancestors, various actors within the cosmopolitanisms of the Indian Ocean and her own experiences. She discusses how specific Indian Ocean societies experienced, were shaped by and negotiated multiple transformations related but not limited to nation-state politics, transoceanic trade, citizenship politics, colonial railway projects, identity politics, religion and transculturality as migrations, colonialism, and resultant interactions occurred across time and space. Her discussion visualises and demystifies the emergence of entangled Afrasian transregional spaces within the complexity of cosmopolitan societies across the Indian Ocean. The film was part of an international research project at Goethe University, Frankfurt, Germany, titled Africa’s Asian Options (AFRASO). It was launched during an AFRASO symposium titled “Afrasian Entanglements: Current Dynamics and Future Perspectives in India-Africa Relations” at the University of Mumbai in June 2018.

Estimation of the Bid-Ask Prices for the European Discrete Geometric Average and Arithmetic Average Asian Options

Conic finance is a new and exciting development in quantitative finance, which is widely applied to several topics in finance. The theory of conic finance extends the law of one price to the law of two prices, which yields closed forms for bid-ask prices of European options. In this paper, within the framework of conic finance, we derive effective, explicit, approximate formulas to estimate the bid-ask prices for the European discrete geometric average and arithmetic average Asian options. Finally, we give two examples to demonstrate and validate that the approximate closed-form solutions are efficient and accurate.

Pricing and hedging Asian options under Levy processes and robust long-term investing with learning about stock returns

In this work we propose a parametric model using the techniques of time-changed subordination that captures the implied volatility smile. We demonstrate that the Fourier-Cosine method can be used in a semi-static way to hedge for quadratic, VaR and AVaR risk. We also observe that investors looking to hedge VaR can simply hold the amount in a portfolio of mostly cash, whereas an investor hedging AVaR will need to hold more risky assets. We also extend ES risk to a robust framework. A conditional calibration method to calibrate the bivariate model is proposed. For a robust long-term investor who maximizes their recursive utility and learns about the stock returns, as the willingness to substitute over time increases, the equity demand decreases and consumption-wealth ratio increases. As the preference for robustness increases the demand for risk decreases. For a positive correlation, we observe that learning about returns encourages the investor to short the bond at all levels of u and vice versa

Pricing and hedging Asian options under Levy processes and robust long-term investing with learning about stock returns

In this work we propose a parametric model using the techniques of time-changed subordination that captures the implied volatility smile. We demonstrate that the Fourier-Cosine method can be used in a semi-static way to hedge for quadratic, VaR and AVaR risk. We also observe that investors looking to hedge VaR can simply hold the amount in a portfolio of mostly cash, whereas an investor hedging AVaR will need to hold more risky assets. We also extend ES risk to a robust framework. A conditional calibration method to calibrate the bivariate model is proposed. For a robust long-term investor who maximizes their recursive utility and learns about the stock returns, as the willingness to substitute over time increases, the equity demand decreases and consumption-wealth ratio increases. As the preference for robustness increases the demand for risk decreases. For a positive correlation, we observe that learning about returns encourages the investor to short the bond at all levels of u and vice versa

Spanning With Binary Options: A Vector Lattice Approach

The issue of portfolio insurance is one of the prime concerns of the investors who want to insure their asset at minimum or appropriate cost. Static hedging with binary options is a popular strategy that has been explored in various option models (see e.g. (2; 3; 4; 7)). In this thesis, we propose a static hedging algorithm for discrete time models. Our algorithm is based on a vector lattice technique. In chapter 1, we give the necessary background on the theory of vector lattices and the theory of options. In chapter 2, we reveal the connection of lattice-subspaces with the minimum-cost portfolio insurance strategy. In chapter3, we outline our algorithm and give applications to binomial and trinomial option models. In chapter 4, we perform simulations and analyze the hedging errors of our algorithm for European, Barrier, Geometric Asian, Arithmetic Asian, and Lookback options. The study has revealed that static hedging could be suitable strategy for the European, Barrier, and Geometric Asian options as these options have shown less inclination to the rollover effect.