Calibration to FX triangles of the 4/2 model under the benchmark approach

We calibrate a novel multifactor stochastic volatility model that includes as special cases the Heston-based model of De Col et al. (J Bank Finance 37(10):3799–3818, 2013) and the 3/2-based model of Baldeaux et al. (J Bank Finance 53:34–48, 2015). Using a dataset on vanilla option quotes in a triangle of currencies, we find that the risk neutral approach typically fails for the calibrated model, in line with the results of Baldeaux et al. (2015).

Deep Compressed Sensing for Learning Submodular Functions

The AI community has been paying attention to submodular functions due to their various applications (e.g., target search and 3D mapping). Learning submodular functions is a challenge since the number of a function’s outcomes of N sets is 2 N . The state-of-the-art approach is based on compressed sensing techniques, which are to learn submodular functions in the Fourier domain and then recover the submodular functions in the spatial domain. However, the number of Fourier bases is relevant to the number of sets’ sensing overlapping. To overcome this issue, this research proposed a submodular deep compressed sensing (SDCS) approach to learning submodular functions. The algorithm consists of learning autoencoder networks and Fourier coefficients. The learned networks can be applied to predict 2 N values of submodular functions. Experiments conducted with this approach demonstrate that the algorithm is more efficient than the benchmark approach.

LESS-EXPENSIVE VALUATION AND RESERVING OF LONG-DATED VARIABLE ANNUITIES WHEN INTEREST RATES AND MORTALITY RATES ARE STOCHASTIC

Variable annuities are products offered by pension funds and life offices that provide periodic future payments to the investor and often have ancillary benefits that guarantee survival benefits or sums insured on death. This paper extends the benchmark approach to value and hedge long-dated variable annuities using a combination of cash, bonds and equities under a variety of market models, allowing for dependence between financial and insurance markets. Under a simplified case of independence, the results show that when the discounted index is modelled as a time-transformed squared Bessel process, less-expensive valuation and reserving is achieved regardless of the short rate model or the mortality model.

Pengaruh Audit Tenure, Komite Audit Dan Audit Capacity Stress Terhadap Kualitas Audit

This study aims to determine the effect of the audit tenure, audit committee, and audit capacity stress on audit quality as measured by earnings surprise benchmark approach. The research used secondary data. The population was all manufacturing companies listed in Indonesia Stock Exchange in the period of 2015-2017. The data collection technique used is purposive sampling and 303 samples obtained data. The independent variables were audit tenure, audit committee, and audit capacity stress at the significance level of 5%. This study using logistic regression analysis techniques. The result of the research showed that audit tenure had no significant influence on audit quality with a significance level that is equal to 0.145, audit committee had no significant influence on audit quality a significance level that is equal to 0.652, and audit capacity stress had no significant influence on audit quality a significance level that is equal to 0.522 of the manufacturing companies listed in Indonesia Stock Exchange

Cartographic Visualization for Indoor Semantic Wayfinding

In recent years, pedestrian navigation assistance has been used by an increasing number of people to support wayfinding tasks. Especially in unfamiliar and complex indoor environments such as universities and hospitals, the importance of an effective navigation assistance becomes apparent. This paper investigates the feasibility of the indoor landmark navigation model (ILNM) [1], a method for generating landmark-based routing instructions, by combining it with indoor route maps and conducting a wayfinding experiment with human participants. Within this context, three different cartographic visualization scenarios were designed and evaluated. Two of these scenarios were based on the implementation of the ILNM algorithm, with the concurrent effort to overcome the challenge of representing the semantic navigation instructions in two different ways. In the first scenario, the selected landmarks were visualized as pictograms, while in the second scenario, an axonometric-based design philosophy for the depiction of landmarks was followed. The third scenario was based on the benchmark approach (metric-based routing instructions) for conveying routing instructions to the users. The experiment showed that the implementation of the ILNM was feasible, and, more importantly, it was beneficial in terms of participants’ navigation performance during the wayfinding experiment, compared to the metric-based instructions scenario (benchmark for indoor navigation). Valuable results were also obtained, concerning the most suitable cartographic approach for visualizing the selected landmarks, while implementing this specific algorithm (ILNM). Finally, our findings confirm that the existence of landmarks, not only within the routing instructions, but also as cartographic representations on the route map itself, can significantly help users to position themselves correctly within an unfamiliar environment and to improve their navigation performance.