Equilibrium reinsurance-investment strategy with a common shock under two kinds of premium principles

This paper investigates the optimal mean-variance reinsurance-investment problem for an insurer with a common shock dependence under two kinds of popular premium principles: the variance premium principle and the expected value premium principle. We formulate the optimization problem within a game theoretic framework and derive the closed-form expressions of the equilibrium reinsurance-investment strategy and equilibrium value function under the two different premium principles by solving the extended Hamilton-Jacobi-Bellman system of equations. We find that under the variance premium principle, the proportional reinsurance is the optimal reinsurance strategy for the optimal reinsurance-investment problem with a common shock, while under the expected value premium principle, the excess-of-loss reinsurance is the optimal reinsurance strategy. In addition, we illustrate the equilibrium reinsurance-investment strategy by numerical examples and discuss the impacts of model parameters on the equilibrium strategy.

The Impact of Business Cycles, Stock Market Phases and Crisis on the Value Premium: The Indian Experience

Purpose :This paper is an attempt to explore the relationship between the value premium and expected stock returns in the Indian stock market and evaluates whether the value premium disappears or not when the different economic conditions (Boom & Recession), market conditions (Bull & Bear) and 2008 Global financial crisis are considered. Methodology: The annual data of 500 companies belonging to BSE-500 from 1999- 2017 was collected and ten portfolios were constructed and sorted using six valuation proxies (P/B, P/E, D/P/, CF/P, S/P and EV/PBDITA). Standard CAPM and Dual beta market model were employed. Findings: The empirical results confirm that irrespective of market conditions, value stock portfolios surpass growth stock portfolios in the Indian stock market by delivering significant abnormal returns. Practical implications: The paper holds important implications for asset pricing literature and investors. The higher returns generated by value stocks during the crisis and recession period imply that investors can put faith in the value stocks during times of adversity. The future value of an investment is a function of its present price. The lower the price, the higher the returns will be. Therefore, value stocks are good investments whether it is boom or recession, bull or bear, crisis or non-crisis periods. Originality: The paper is first of its kind to study the impact of business cycles, stock market phases and crisis on the value premium in the Indian stock market. The paper contributes to portfolio management and asset pricing literature for an emerging market.

Investor Sentiments and Fama–French Five-Factor Premia

This study provides new insights to predict the excess return of a security. As if factor premia are getting influenced by the sentiments that means sentiments are ultimately affecting the excess return of a security. To meet the objective, a composite index developed by Baker and Wurgler is used as sentiment proxy. Monthly data are used from July 1965 to September 2015 in U.S. context. Granger casualty, Vector Autoregression (VAR), and Fama–Macbeth regression are applied to get the results. Results show that investor sentiments significantly drive the Fama factors’ premia: size premium and profitability premium. Sentiments also contain some information to explain the investment premia but fail to explain the market risk premium and value premium. Furthermore, results suggest that sentiments increase the explanatory power of model measured by R square. In short, this study suggests that investor sentiments play a role in explaining the Fama–French five-factor premia.

The County Fair Cyber Loss Distribution

Insurance premiums reflect expectations about the future losses of each insured. Given the dearth of cyber security loss data, market premiums could shed light on the true magnitude of cyber losses despite noise from factors unrelated to losses. To that end, we extract cyber insurance pricing information from the regulatory filings of 26 insurers. We provide empirical observations on how premiums vary by coverage type, amount, and policyholder type and over time. A method using particle swarm optimisation and the expected value premium principle is introduced to iterate through candidate parameterised distributions with the goal of reducing error in predicting observed prices. We then aggregate the inferred loss models across 6,828 observed prices from all 26 insurers to derive the County Fair Cyber Loss Distribution . We demonstrate its value in decision support by applying it to a theoretical retail firm with annual revenue of $50M. The results suggest that the expected cyber liability loss is $428K and that the firm faces a 2.3% chance of experiencing a cyber liability loss between $100K and $10M each year. The method and resulting estimates could help organisations better manage cyber risk, regardless of whether they purchase insurance.

Where to Find Value on the Balance Sheet

Firms with higher book equity relative to market capitalization earn a premium, leading to sorting into value and growth. This sorting implies that any balance sheet additions are risky. This paper provides evidence that what a firm holds on its balance sheet matters, and value occurs with high book-to-market ratios. Each holding relative to firm market capitalization has a risk premium, varying across holdings. Among US firms quarterly for 1980–2016, doubling holdings of cash and receivables relative to market capitalization earn premiums of at least 1%, as does taking on debt. These account for the entire value premium, since physicals, intangibles and payables are not risky. The value premium derives from the composition of the firm’s assets.