Long-run total real returns of the stock market are approximately equal to long-run real earnings growth plus average dividend yield. However, earnings can be distributed to shareholders not only via dividends, but via buybacks and debt retirement. Thus the total returns minus earnings growth can be considered as implied dividend yield. This quantity must be stable in the long run. If the converse is true: this quantity is abnormally high in the last few years, then the market is overpriced. A measure of such heat is (detrended) cumulative sum of differences. We regress next year's implied dividend yield upon this current heat measure. We simulate future returns, starting from current market conditions. We reject the conventional wisdom that currently the market is overpriced. In our model the current market is undervalued and is likely to grow faster than historically.

The objective is to provide an Al\`os type decomposition formula and an approximate option pricing formula for the Barndorff-Nielsen and Shephard model: an Ornstein-Uhlenbeck type stochastic volatility model driven by a subordinator without drift. Al\`os (2012) introduced a decomposition expression of the call option prices for the Heston model by using Ito's formula. In this paper, we extend it to the Barndorff-Nielsen and Shephard model. As far as we know, this is the first result on the Al\`os type decomposition formula for models with infinite active jumps. Moreover, investigating the rate of convergence as the time to maturity tends to 0 for each term in the obtained decomposition formula, we shall present an approximate option pricing formula, and implement numerical experiments, which show that our approximation formula is effective for in-the-money options.

This paper presents a framework capable of accurately forecasting future sales in the retail industry and classifying the product portfolio according to the expected level of forecasting reliability. The proposed framework, that would be of great use for any company operating in the retail industry, is based on Facebook's Prophet algorithm and backtesting strategy. Real-world sales forecasting benchmark data obtained experimentally in a production environment in one of the biggest retail companies in Bosnia and Herzegovina is used to evaluate the framework and demonstrate its capabilities in a real-world use case scenario.

In our country, majority of agricultural workers (who may include farmers working within a cooperative framework, or those who work individually either as owners or tenants) are shown to be reaping the least amount of profits in the agriculture value chain when compared to the effort they put in. There is a good amount of literature which broadly substantiates this situation in our country. Main objective of this study is to have a broad understanding of the role played by public systems in this value chain, particularly in the segment that interacts with farmers. As a starting point, we first try to get a better understanding of how farmers are placed in a typical agriculture value chain. For this we take the help of recent seminal works on this topic that captured the situation of farmers' within certain types of value chains. Then, we isolate the segment which interacts with farmers and deep-dive into data to understand the role played by public interventions in determining farmers' income from agriculture. NSSO 70th round on Situation Assessment Survey of farmers has data pertaining to the choices of farmers and the type of their interaction with different players in the value chain. Using this data we tried to get a econometric picture of the role played by government interventions and the extent to which they determine the incomes that a typical farming household derives out of agriculture.

China has implemented retrofitting measures in coal-fired power plants (CFPPs) to reduce air pollution through small unit shutdown (SUS), the installation of air pollution control devices (APCDs) and power generation efficiency (PGE) improvement. The reductions in highly toxic Hg emissions and their related health impacts by these measures have not been well studied. To refine mitigation options, we evaluated the health benefits of reduced Hg emissions via retrofitting measures during China's 12th Five-Year Plan by combining plant-level Hg emission inventories with the China Hg Risk Source-Tracking Model. We found that the measures reduced Hg emissions by 23.5 tons (approximately 1/5 of that from CFPPs in 2010), preventing 0.0021 points of per-foetus intelligence quotient (IQ) decrements and 114 deaths from fatal heart attacks. These benefits were dominated by CFPP shutdowns and APCD installations. Provincial health benefits were largely attributable to Hg reductions in other regions. We also demonstrated the necessity of considering human health impacts, rather than just Hg emission reductions, in selecting Hg control devices. This study also suggests that Hg control strategies should consider various factors, such as CFPP locations, population densities and trade-offs between reductions of total Hg (THg) and Hg2+.

Groups of Small and Medium Enterprises (SME) back each other and form guarantee network to obtain loan from banks. The risk over the networked enterprises may cause significant contagious damage. To dissolve such risks, we propose a hybrid feature representation, which is feeded into a gradient boosting model for credit risk assessment of guarantee network. Empirical study is performed on a ten-year guarantee loan record from commercial banks. We find that often hundreds or thousands of enterprises back each other and constitute a sparse complex network. We study the risk of various structures of loan guarantee network, and observe the high correlation between defaults with centrality, and with the communities of the network. In particular, our quantitative risk evaluation model shows promising prediction performance on real-world data, which can be useful to both regulators and stakeholders.