Iterated filtering methods for Markov process epidemic models

Dynamic epidemic models have proven valuable for public health decision makers as they provide useful insights into the understanding and prevention of infectious diseases. However, inference for these types of models can be difficult because the disease spread is typically only partially observed e.g. in form of reported incidences in given time periods. This chapter discusses how to perform likelihood-based inference for partially observed Markov epidemic models when it is relatively easy to generate samples from the Markov transmission model while the likelihood function is intractable. The first part of the chapter reviews the theoretical background of inference for partially observed Markov processes (POMP) via iterated filtering. In the second part of the chapter the performance of the method and associated practical difficulties are illustrated on two examples. In the first example a simulated outbreak data set consisting of the number of newly reported cases aggregated by week is fitted to a POMP where the underlying disease transmission model is assumed to be a simple Markovian SIR model. The second example illustrates possible model extensions such as seasonal forcing and over-dispersion in both, the transmission and observation model, which can be used, e.g., when analysing routinely collected rotavirus surveillance data. Both examples are implemented using the R-package pomp (King et al., 2016) and the code is made available online.Comment: This manuscript is a preprint of a chapter to appear in the Handbook of Infectious Disease Data Analysis, Held, L., Hens, N., O'Neill, P.D. and Wallinga, J. (Eds.). Chapman \& Hall/CRC, 2018. Please use the book for possible citations. Corrected typo in the references and modified second exampl

Point singularities and suprathreshold stochastic resonance in optimal coding

Motivated by recent studies of population coding in theoretical neuroscience, we examine the optimality of a recently described form of stochastic resonance known as suprathreshold stochastic resonance, which occurs in populations of noisy threshold devices such as models of sensory neurons. Using the mutual information measure, it is shown numerically that for a random input signal, the optimal threshold distribution contains singularities. For large enough noise, this distribution consists of a single point and hence the optimal encoding is realized by the suprathreshold stochastic resonance effect. Furthermore, it is shown that a bifurcational pattern appears in the optimal threshold settings as the noise intensity increases. Fisher information is used to examine the behavior of the optimal threshold distribution as the population size approaches infinity.Comment: 11 pages, 3 figures, RevTe

Why Are Stocks So Risky?

With the decline in privately and publicly guaranteed benefits for pensions and health care, people increasingly must finance a greater share of their retirement expenses through their own savings. The relatively high long-term return on equity makes investments in stocks seem both an attractive and suitable means of accumulating the substantial wealth that savers will require. Yet, the 50 percent drop in the Standard & Poor’s 500 Index from May 2008 to March 2009 is only the latest reminder that stocks pose considerable risk for investors. In the past, equity returns over periods as long as 10 or 20 years have diverged substantially from their long-term averages, tarnishing the appeal of stocks even as investments for the long run...

The effect of helper virus on Abelson virus-induced transformation of lymphoid cells

Abelson murine leukemia virus (A-MuLV)-transformed fibroblast nonproducer cells were used to prepare A-MuLV stocks containing a number of different helper viruses. The oncogenicity of the A-MuLV stocks was tested by animal inoculation and their ability to transform normal mouse bone marrow cells was measured in vitro. All of the A-MuLV stocks transformed fibroblast cells efficiently. However, only A-MuLV stocks prepared with helper viruses that are highly oncogenic were efficient in vivo and in vitro in hematopoietic cell transformation. In addition, inefficient helpers did not establish a stable infection in lymphoid nonproducer cells. Thus, helper virus has a more central role in lymphoid cell transformation than in fibroblast cell transformation

Information, Trading and Stock Returns: Lessons from Dually-Listed Securities

This paper compares the intra-day patterns on the NYSE and AMEX of volatility, trading volume and bid-ask spreads for European dually- listed stocks, Japanese dually-listed stocks also listed in London, and Japanese dually-listed stocks not listed in London with American stocks of comparable average trading volume and volatility. It is shown that the intra-day patterns for these stocks are remarkably similar even though the public information flows differ markedly across these stocks during the trading day. In the morning, Japanese stocks have the greatest volatility and volume, followed by European stocks and American stocks. These rankings are reversed in the afternoon. We argue that these patterns are consistent with markets reacting to the overnight accumulation of public information which is greatest for Japanese stock and smallest for American stocks and inconsistent with the view that early morning volatility can be attributed to monopolistic specialist behavior.

PENERAPAN METODE CAPM SEBAGAI DASAR PENGAMBILAN KEPUTUSAN INVESTASI SAHAM PADA PERUSAHAAN YANG LISTING DI BURSA EFEK JAKARTA

This research is a case study in shares listed on the Jakarta Stock Exchange between June 2006 under the title "Application of CAPM method as the basis for Investment Decision Making Companies Listing of Shares on the Jakarta Stock Exchange. The purpose of this research is to assist investors in the framework of investment decision. By applying CAPM investors can find stocks which are included in the optimal portfolio of stocks that have examined the period from June 2006. In this study the sample used is a listing of stocks on the Jakarta Stock Exchange accounted for 36 shares were 10% of the total number of shares in the JSE period from June 2006. The analytical tool used in this study were CAPM to determine which stocks are included in the optimal portfolio. By following these steps count (RI), namely the return of individuals, rate of return on the market (Rm), determine the beta of each stock ), Erb determine the difference between the rate of expected return( with risk-free return divided by beta, determine cut off point (C *), after that combines stocks in optimal portfolio with a certain proportion to obtain the optimal rate of return. The results computed by the CAPM it can be seen there are 4 stocks that are included in the optimal portfolio of Hotel Sahid Jaya Tbk, Davomas Abadi, Tbk, Telkom, Tbk and Astra Internatinal, Tbk. Based on the analysis above, the investor can take stock of investment decisions by knowing the stocks in optimal portfolio because it can provide a maximum rate of return

Gold, Oil, and Stocks

We employ a wavelet approach and conduct a time-frequency analysis of dynamic correlations between pairs of key traded assets (gold, oil, and stocks) covering the period from 1987 to 2012. The analysis is performed on both intra-day and daily data. We show that heterogeneity in correlations across a number of investment horizons between pairs of assets is a dominant feature during times of economic downturn and financial turbulence for all three pairs of the assets under research. Heterogeneity prevails in correlations between gold and stocks. After the 2008 crisis, correlations among all three assets increase and become homogenous: the timing differs for the three pairs but coincides with the structural breaks that are identified in specific correlation dynamics. A strong implication emerges: during the period under research, and from a different-investment-horizons perspective, all three assets could be used in a well-diversified portfolio only during relatively short periods