Ioannis Kyriakou

City, University of London · Faculty of Actuarial Science and Insurance

This study explores the effectiveness of technical and fundamental analysis in predicting and trading the returns of 12 cryptocurrencies, namely Bitcoin, Ethereum, Ripple, Dash, Cardano, Avalanche, Binance Coin, Dogecoin, Polkadot, Litecoin, Terra and Solana. A universe of 7846 technical rules, five log moving average‐based ratios and 59 fundamenta...

Dial M for Simulation For years, systems of stochastic differential equations (SDEs) were simulated by discretization, inevitably introducing a bias, which can be difficult to quantify accurately. To circumvent this, some attempts have been made to simulate exactly various models from the SDE solution. These approaches prove capable of producing ac...

In this paper, we derive constrained optimal investment strategies for long-term savers who are interested in investing their funds in stocks, but are afraid of potentially losing, for example, their retirement income. We call this probability hedging as it is determined by the probability of landing up within bounds that are agreed from interactio...

Classification models are very sensitive to data uncertainty, and finding robust classifiers that are less sensitive to data uncertainty has raised great interest in the machine learning literature. This paper aims to construct robust support vector machine classifiers under feature data uncertainty via two probabilistic arguments. The first classi...

On Modeling the Probability Distribution of Stochastic Sums In the “Technical Note—On Matrix Exponential Differentiation with Application to Weighted Sum Distributions,” Das, Tsai, Kyriakou, and Fusai propose an efficient methodology for approximating the unknown probability distribution of a weighted stochastic sum or time integral. Resulting from...

We present a new method for estimating the unobservable drift of the risk‐neutral spot freight rate process from Forward Freight Agreements (FFA) prices in the absence of a closed‐form solution and demonstrate robustness via numerical simulations. Moreover, we conduct empirical experiments involving estimation of standard parametric models and a no...

The loss function choice for any Support Vector Machine classifier has raised great interest in the literature due to the lack of robustness of the Hinge loss, which is the standard loss choice. In this paper, we plan to robustify the binary classifier by maintaining the overall advantages of the Hinge loss, rather than modifying this standard choi...

The fundamental interest of investors in econometric modeling for excess stock returns usually focuses either on short- or long-term predictions to individually reduce the investment risk. In this paper, we present a new and simple model that contemporaneously accounts for short- and long-term predictions. By combining the different horizons, we ex...

Recent advances in pension product development seem to favour alternatives to the risk free asset often used in the financial theory as a performance standard for measuring the value generated by an investment or a reference point for determining the value of a financial instrument. To this end, in this paper, we apply the simplest machine learning...

We develop a novel, workable switching option model approach to component redesign and replacement projects that are divisible into sequential phases. The component manufacturer has the option to retain the current product position and abandon the project, or switch to a redesigned product position. Additional uncertainty remains as to whether the...

In this paper, we recall actuarial and financial applications of sums of dependent random variables that follow a non-Gaussian mean-reverting process and contemplate distribution approximations. Our work complements previous related studies restricted to lognormal random variables; we revisit previous approximations and suggest new ones. We then de...

Long-term return expectations or predictions play an important role in planning purposes and guidance of long-term investors. Five-year stock returns are less volatile around their geometric mean than returns of higher frequency, such as one-year returns. One would, therefore, expect models using the latter to better reduce the noise and beat the s...

It is our pleasure to prologue the special issue on “Machine Learning in Insurance”, which represents a compilation of ten high-quality articles discussing avant-garde developments or introducing new theoretical or practical advances in this field [...]

The relationship between the prices of crude oil and its refined products is at the heart of the oil industry. Crude oil and refined products volatilities and correlations have been modelled extensively using short-memory multivariate GARCH models. This paper investigates the potential benefits from using fractionally integrated multivariate GARCH...

The aim of this paper is to analyze the performance of hedging strategies based on snow and temperature options developed by ski operators to protect their profitability under adverse changes in climatic conditions. The setup is based on a joint non-parametric model for snow and temperature aimed at providing a modelling support for the assessment...

The aim of this paper is to analyze the performance of hedging strategies based on snow and temperature options developed by ski operators to protect their profitability under adverse changes in climatic conditions. The setup is based on a joint non-parametric model for snow and temperature aimed at providing a modelling support for the assessment...

In this research, we develop a new discrete-time model approach with flexibly changeable driving dynamics for pricing Asian options, with possible early exercise, and a fixed or floating strike price. These options are ubiquitous in financial markets but can also be recast in the framework of real options. Moreover, we derive an accurate lower boun...

This paper investigates the dynamics of stock price volatility for different vessel-type segments of the U.S, water transportation industry. We measure market exposure by a portfolio of tanker, dry bulk, container, and gas stocks to examine tail behavior and tail risk dependence. The role of mixture distributions in predicting future volatility is...

The paper shows how to reform the platform of pension products so that pension savers, professional financial advisors, actuaries and investment experts intuitively understand the underlying financial risk of the optimal investment profile. It is also pointed out that an excellent optimal investment strategy can destroy the future expected utility...

In this paper, we present a transform-based algorithm for pricing discretely monitored arithmetic Asian options with remarkable accuracy in a general stochastic volatility framework, including affine models and time-changed Lévy processes. The accuracy is justified both theoretically and experimentally. In addition, to speed up the valuation proces...

Communicating a pension product well is as important as optimising the financial value. In a recent study, we showed that up to 80% of the value of a pension lump sum could be lost if customer communication failed. In this paper, we extend the simple customer interaction of the earlier contribution to the more challenging lifetime annuity case. Usi...

We develop an accurate valuation setup for freight options, featuring an exponential mean-reverting model for the freight rate with distinct reversion scales for its jump and diffusion components. We calibrate to Baltic option prices and analyze the freight rate dynamics. More specifically, we observe that jumps dissipate faster than the diffusive...

This paper studies the impact of modelling time-varying variances of stock returns in terms of risk measurement and extreme risk spillover. Using a general class of regime-dependent models, we find that volatility can be disaggregated into distinct components: a persistent stable process with low sensitivity to shocks and a high volatility process...

We examine whether investors herd in their decision to order or scrap vessels in the drybulk market. We decompose herding into unintentional and intentional, and test for herd behavior under asymmetric effects with respect to freight market states, cycle phases, risk-return and valuation profiles, and ownership of the vessel. We detect unintentiona...

We develop a coherent framework for the valuation of real assets and determination of the optimal time to invest. To this end, we model the stochastic nature of income and develop methodologies for valuing traded derivatives to facilitate model calibration. A valuation paradigm for freight-linked assets is then presented and, using a real option ap...

In this paper we consider the problem of hedging an arithmetic Asian option with discrete monitoring in an exponential L´evy model by deriving backward recursive integrals for the price sensitivities of the option. The procedure is applied to the analysis of the performance of the delta and delta-gamma hedges in an incomplete market; particular att...

Stock return predictability by investor sentiment has been subject to constant updating, but reaching a decisive conclusion seems rather challenging as academic research relies heavily on US data. We provide fresh evidence on stock return predictability in an international setting and show that shipping investor sentiment is a common leading indica...

Crude oil derivatives form an important part of the global derivatives market. In this paper, we focus on Asian options which are favoured by risk managers being effective and cost-saving hedging instruments. The paper has both empirical and theoretical contributions: we conduct an empirical analysis of the crude oil price dynamics and develop an a...

We propose an accurate method for pricing arithmetic Asian options on the discrete or continuous average in a general model setting by means of a lower bound approximation. In particular, we derive analytical expressions for the lower bound in the Fourier domain. This is then recovered by a single univariate inversion and sharpened using an optimiz...

We consider a seasonal mean-reverting model for energy commodity prices with jumps and Heston-type stochastic volatility, as well as three nested models for comparison. By exploiting the affine form of the log-spot models, we develop a general valuation framework for futures and discrete arithmetic Asian options. We investigate five major petroleum...

This paper proposes an integrated pricing framework for convertible bonds, which comprises firm value evolving as an exponential jump diffusion, correlated stochastic interest rates movements and an efficient numerical pricing scheme. By construction, the proposed stochastic model fits in the framework of affine jump diffusion processes of Duffie,...

We investigate the role of sentiment and its implications for real assets. Using shipping sentiment proxies that capture market expectations, valuation, and liquidity, we construct sentiment indices for the dry bulk shipping market. Evidence suggests that sentiment affects the monthly returns of real assets. The empirical findings also show that ma...

This paper discusses an extension of the traditional lognormal representation for the risk neutral spot freight rate dynamics to a diffusion model overlaid with jumps of random magnitude and arrival. Then, we develop a valuation framework for options on the average spot freight rate, which are commonly traded in the freight derivatives market. By e...

http://onlinelibrary.wiley.com/doi/10.1002/fut.21647/abstract http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1951537 We present a joint Monte Carlo-Fourier transform sampling scheme for pricing derivative products under a CGMY model exhibiting jumps of infinite activity and finite or infinite variation. The approach relies on numerical transfor...

This paper proposes an accurate pricing algorithm for convertible bonds in a framework which comprises firm value evolving as an exponential jump diffusion, and correlated stochastic interest rates movements. This is a novel technique for the convertible bonds literature and aims at fixing dimensionality and convergence limitations previously repor...

The paper proposes a fast Fourier transform (FFT) pricing algorithm for convertible bonds in a framework which comprises rm value, evolving as an exponential jump diffusion, and correlated stochastic interest rates movements. This is a novel numerical technique for the convertible bonds literature and aims at fixing dimensionality and convergence l...

We suggest an improved FFT pricing algorithm for discretely sampled Asian options with general independently distributed returns in the underlying. Our work complements the studies of Carverhill and Clewlow [Risk, 1990, 3(4), 25-29], Benhamou [J. Comput. Finance, 2002, 6(1), 49-68], and Fusai and Meucci [J. Bank. Finance, 2008, 32(10), 2076-2088],...