Developing Mortality Improvement Formulas

Abstract

Longevity improvements have contributed to widespread underfunding of pension plans and losses in insured annuity portfolios. Insurers might reasonably expect some upside from the effect of lower mortality on their life business. Although mortality improvement scales, such as the Society of Actuaries Scale AA, are widely employed in pension and annuity valuation, the derivation of these scales appears heuristic, leading to problems in deriving meaningful measures of uncertainty. We explore the evidence on mortality trends for the Canadian life insurance companies, data, using stochastic models. We use the more credible population data to benchmark the insured lives data. Finally, we derive a practical, model-based formula for actuaries to incorporate mortality improvement and the associated uncertainty into their calculations.     

Necessary but not sufficient: Beyond novelty in advertising creativity

Novelty has been considered the bedrock of creative advertising. However, Ang, Lee, and Leong (2007, Journal of the Academy of Marketing Science 35: 220–232) proposed in their ad creativity cube that, to be effective, novel ads need to be both meaningful and connect to their audience as well. This study empirically tests whether the effects of novelty can be enhanced by meaningfulness and connectedness. Results generally showed that novelty, coupled with meaningfulness and connectedness, enhances consumer ad response. Such ads were evaluated as being more creative and were recalled and liked better than novel ads which lack either meaningfulness or connectedness, or both, as well as less novel ads of a similar nature. Implications are discussed and directions for future research suggested.     

Applications of randomized low discrepancy sequences to the valuation of complex securities

This paper deals with a recent modification of the Monte Carlo method known as quasi-random Monte Carlo. Under this approach, one uses specially selected deterministic sequences rather than random sequences as in Monte Carlo. These special sequences are known as low discrepancy sequences and have the property that they tend to be evenly dispersed throughout the unit cube. For many applications in finance, the use of low discrepancy sequences seems to provide more accurate answers than random sequences. One of the main drawbacks of the use of low discrepancy sequences is that there is no obvious method of computing the standard error of the estimate. This means that in performing the calculations, there is no clear termination criterion for the number of points to use. We address this issue here and consider a partial randomization of Owen's technique for overcoming this problem. The proposed method can be applied to much higher dimensions where it would be computationally infeasible for Owen's technique. The efficiency of these procedures is compared using a particular derivative security. The exact price of this security can be calculated very simply and so we have a benchmark against which to test our calculations. We find that our procedures give promising results even for very high dimensions. Statistical tests are also conducted to support the confidence statement drawn from these procedures.     

Blockchain as the Database Engine in the Accounting System

This paper examines the prediction that blockchain technology will transform accounting and the profession because transactions recorded on a blockchain can be aggregated into financial statements and confirmed as true and accurate. We argue that blockchain technology affects the database engine of the accounting information system (AIS) through digitisation of the current paper‐based validation process. In a blockchain‐based AIS, accountants will no longer be the central authority but will remain the preparer of financial reports required by regulations; they will continue to influence policies such as the choice and accreditation of validators and serve as validators of last resort. Audit evidence still needs to be gathered for rendering of an audit opinion in a blockchain‐based AIS. While digitisation of the validation process reduces the error rate and lowers the cost of vouching and tracing, and immutability of blockchain data reduces the incentive and opportunities for fraud, a blockchain‐based AIS alone does not guarantee that financial reports are true and fair. Lower error rates and reduced incentives for accounting fraud in a blockchain‐based AIS are expected to improve audit quality. This prediction will need to be empirically tested when blockchain‐based AIS become available. Using the three‐tier architecture of the AIS, this paper addresses the gap in the literature that misses how characteristics of blockchain technology can influence the implementation of a blockchain‐based AIS with related implications for the accounting profession.     

Dynamic capabilities in the context of Brexit and international wine business: An exploratory two‐country study

This exploratory study proposes a conceptual framework based on the dynamic capabilities approach (DCA) to advance the understanding of firms' responses to turbulence, illustrated by the Brexit phenomenon. The case of wine producers is examined, with a particular focus on perceived impacts of and responses to Brexit among wineries predominantly involved in exports. Data from 281 mainly micro and small exporting Italian and Spanish winery firms were gathered. Various differences emerged in how both groups of businesses perceived Brexit's impacts, and how they planned to respond. Some of these ways revealed principles associated with the DCA, such as possessing critical organizational resources, notably, tangible, intangible, and human to create capabilities. Furthermore, while various comments denoted indecisiveness and uncertainty, others underscored the vital need to exploit opportunities through engaging with new international consumer markets. Overall, the proposed framework facilitates an in‐depth understanding of winery entrepreneurs' strategic behavior in response to turbulent situations.     

The Political Economy of Volatility Dynamics in the Hong Kong Stock Market

Despite its obvious importance, little empirical research has examined the impact of political risk on stock market volatility. This paper uses data on the Hong Kong stock market over a long sample period to investigate whether political risk has induced regime shifts in stock market volatility. Regime shifts are modelled via a Markov switching EGARCH model that allows for regime-dependent volatility asymmetry. We find strong evidence of regime shifts in conditional volatility as well as significant volatility asymmetry in high volatility periods. Major political uncertainties were reflected in a switch to the high-volatility regime. However, contrary to popular perceptions, we find no evidence that the Hong Kong stock market has become persistently more volatile since the start of Sino-British political negotiations in 1982.     

How relevant is the MBA: A revisit

The master of business administration (MBA) is the centerpiece of management education and holds the promise of systematically preparing its graduates for their managerial roles. However, there is escalating criticism that MBA programs are losing their relevance based on empirical evidence that competencies indicated by managers to be most critical are least represented in core MBA curricula. The authors re-examine the evidence and argue that the misalignment appears to be overstated. Consideration for relevance in preparing graduates for managerial roles needs to consider not only curricula, but also actual learning, social capital from the alumni network, and the signaling effect of graduating from an MBA program.     

The impact of medical insurance coverage and molecular monitoring frequency on outcomes in chronic myeloid leukemia: real-world evidence in China

Objectives: Imatinib (Glivec) has been covered by critical disease insurance for treatment of chronic myeloid leukemia (CML) in Jiangsu province of China since 2013. Further, free molecular monitoring has been provided to patients at top clinical centers as part of a pilot study that has changed the local treatment pattern and outcomes of patients with CML. This study evaluates the impact of medical insurance coverage and the molecular monitoring frequency on outcomes of patients with CML treated at a central hospital in Jiangsu, China, according to patient-level data.

Methods: The study investigated 335 CML patients receiving medical treatment in a central hospital between January 1, 2011 and December 31, 2014. Demographic and clinical characteristics were extracted from the patients’ clinical records. Univariate and multivariate analyses using the logistic regression model were performed to identify the differences in outcomes of major molecular response (MMR) or complete cytogenetic response (CCyR) between patients who were insured vs uninsured, or between patients with frequency of PCR monitoring ≤2 times vs ≥3 times per year.

Results: Both the achievement of MMR (BCR-ABL^IS ≤0.1%) (50.4% vs 37.5%) and CCyR (80.7% vs 62.8%) at 12 months have shown significant differences that favored patients with insurance coverage of imatinib, while there was no significant difference in the outcome of BCR-ABL^IS ≤1% between insured and non-insured groups (56.0% vs 51.3%) at 6 months. The long-term results at 24 months demonstrated that there was a statistically significant difference in MMR rates between the group with 3 or more PCR monitoring tests per year and the group of patients with 2 or less PCR tests per year (76.9% vs 52.2%).

Conclusions: The study findings suggest that CML patients benefit from insurance coverage of imatinib and higher frequency (≥3) of regularly scheduled molecular monitoring PCR in China.