Cost minimization analysis of capecitabine versus 5-fluorouracil-based treatment for gastric cancer patients in Hong Kong

Background: EOX (epirubicin, oxaliplatin, Xeloda; capecitabine) and FOLFOX4 (5-fluorouracil (5-FU), leucovorin, oxaliplatin) are the common chemotherapy regimens used in the treatment of advanced gastric cancer (aGC) in Hong Kong. This study aimed to compare the costs of these therapies for aGC patients from both the healthcare and societal perspectives. It should be noted that, while FOLFOX4 is routinely administered in an outpatient setting in North America and Europe, inpatient setting is adopted in Hong Kong instead, incurring hospitalization cost as a result.

Methods: Fifty-eight patients were identified from the electronic records in two public tertiary hospitals, with 45 and 13 receiving EOX and FOLFOX4 regimens, respectively. Healthcare cost was direct medical costs including drugs, clinic follow-up, hospitalization, diagnostic laboratories, and radiographs. Societal cost refers to indirect costs such as patient time and travel costs. Cost items were further classified as “expected” or “unexpected”. All cost data was expressed in US dollars.

Results: Patients in the EOX and FOLFOX4 arm received an average of 5.3 and 7.8 cycles of treatment, respectively. The capecitabine-based regimen group had a higher expected medication cost per cycle when compared to the 5-FU-based treatment group (US$290.3 vs US$66.9, p?p?p?p?=?.001), respectively, in the capecitabine-based regimen group. Sensitivity analyses based on full cycle regimen costs and net capecitabine or 5-FU/leucovorin costs still showed EOX to be less costly than FOLFOX4.

Conclusion: The capecitabine-based regimen, EOX, was found to generate significant cost saving from both the healthcare and societal perspectives in regions in which FOLFOX4 is given in an inpatient setting.     

Do loan loss reserves behave like capital? Evidence from recent bank failures

Regulatory capital guidelines allow for loan loss reserves to be added back as capital. Our evidence suggests that the influence of loan loss reserves added back as regulatory capital (hereafter referred to as “add-backs”) on bank risk cannot be explained by either economic principles underlying the notion of capital or accounting principles underlying the recording of reserves. Specifically, we observe that, in sharp contrast to the economic notion of capital as a buffer against bank failure risk, add-backs are positively associated with the risk of bank failure during the recent economic crisis. Furthermore, the positive association of add-backs with bank failure risk is concentrated among cases in which the add-backs are highly likely to increase a bank’s total regulatory capital. The evidence cannot thus be fully explained by accounting principles either, since the role of loan loss reserves according to those principles does not depend on whether the reserves generate a regulatory capital increase. Additional analysis suggests that the observed influence of loan loss reserves on bank failure risk may be an unintended consequence of their regulatory treatment as capital.     

Does PIN affect equity prices around the world?

This study examines the empirical controversy over the pricing effect of the Easley, Hvidkjaer, and O?Hara (2002) probability of information-based trading, PIN, on a sample of 30,095 firms from 47 countries worldwide. Contrary to the empirical evidence of Easley, Hvidkjaer, and O?Hara, but consistent with that of Duarte and Young (2009), we do not find that PIN exhibits a positive effect on a cross section of expected stock returns in international markets. Alternative information-based trading measures also display no effect on expected stock returns, corroborating our finding that information risk proxied by PIN, in general, has no pricing effect in world markets.     

Forecasting ATM cash demands using a local learning model of cerebellar associative memory network

Forecasting cash demands at automatic teller machines (ATMs) is challenging, due to the heteroskedastic nature of such time series. Conventional global learning computational intelligence (CI) models, with their generalized learning behaviors, may not capture the complex dynamics and time-varying characteristics of such real-life time series data efficiently. In this paper, we propose to use a novel local learning model of the pseudo self-evolving cerebellar model articulation controller (PSECMAC) associative memory network to produce accurate forecasts of ATM cash demands. As a computational model of the human cerebellum, our model can incorporate local learning to effectively model the complex dynamics of heteroskedastic time series. We evaluated the forecasting performance of our PSECMAC model against the performances of current established CI and regression models using the NN5 competition dataset of 111 empirical daily ATM cash withdrawal series. The evaluation results show that the forecasting capability of our PSECMAC model exceeds that of the benchmark local and global-learning based models.     

Canonical Valuation of Mortality‐Linked Securities

A fundamental question in the study of mortality‐linked securities is how to place a value on them. This is still an open question, partly because there is a lack of liquidly traded longevity indexes or securities from which we can infer the market price of risk. This article develops a framework for pricing mortality‐linked securities on the basis of canonical valuation. This framework is largely nonparametric, helping us avoid parameter and model risk, which may be significant in other pricing methods. The framework is then applied to a mortality‐linked security, and the results are compared against those derived from other methods.     

On investment and exchange-rate movements

We investigate the ways in which permanent exchange-rate changes may affect investment by influencing domestic and foreign revenue, the cost of imported variable inputs and the investment price of imported capital goods. We find that the revenue and investment-price channels have a quantitatively greater effect on investment than the cost channel. The negative effect of the revenue channel, which affects the marginal profitability of capital, outweighs the positive effect of the investment-price channel, which affects the marginal cost of capital, implying that exchange-rate appreciation has a net negative influence on investment. The estimation results are robust to different approaches to extracting the permanent components of exchange rates.     

Market Efficiency and Return Statistics: Evidence from Real Estate and Stock Markets Using a Present-Value Approach

This paper develops a methodology to identify asset price response to news in the framework of the Campbell–Shiller log-linear present-value equation. We further show that a slow price adjustment in real estate markets not only induces a high serial autocorrelation in excess returns, but also dampens the return volatility and the correlation with excess returns in other asset markets. Using Hong Kong real estate and stock market data, we find that the quarterly real estate price assimilates only about half the effect of market news, whereas the quarterly stock price incorporates the news fully. Our analysis identifies a cumulative price adjustment that recovers lost information in real estate returns due to market inefficiency and thereby restores the real estate return volatility and the correlation between real estate and stock markets.