Fall In Prices Research Articles

The Effect of Fundamental Factors and Earnings Growth on Stock Prices in Food and Beverage Subsector Companies on the IDX for the 2019-2023 Period

This study aims to determine and analyze the effect of Fundamental Factors consisting of Earning Per Share (EPS), Price to Book Value (PBV), Price to Earning Ratio (PER) and Earnings Growth on Share Prices in food and beverage subsector companies listed on the Indonesia Stock Exchange for the 2019-2023 period. The sample used in this study is the financial statements of food and beverage subsector companies for the period 2019 to 2023. The method used in determining the sample is by using purposive sampling method, and obtained as many as 13 companies. Data analysis used in research with the Eviews program. The results showed that EPS has a significant effect on stock prices, PBV has a significant effect on stock prices, PER has a significant effect on stock prices, earnings growth has no significant effect on stock prices. While simultaneously EPS, PBV, PER and earnings growth have a significant effect on stock prices. The implication in this study is that the signaling theory of the research results affects the rise and fall of stock prices. In view of the high fundamental factors, it shows a positive signal for the company, especially in stock prices. However, it does not apply to earnings growth because if earnings growth is high, it will have a bad effect on stock prices as well as for investors, but investors can look deeper into financial ratios.

Research on Stock Price Prediction Model Based on Sentiment Factor and Multi-Core Bagging Algorithm

Stock price prediction model is one of the key research points in the quantitative financial field. With the rapid development of data acquisition and storage technology, the data of emotional factors based on nonlinear structure is increasing. How to combine this part of information with common European technology factors to increase the ability of the model is a problem that needs to be solved. Based on this, this paper proposes a method of uncertainty quantification that combines European-and non-European data. Specifically, on the one hand, the Gaussian process regression model is used to capture the unknown relationship between predictive variables and price; on the other hand, the multi-kernel learning technology based on European and non- European kernel functions is used to combine the effective information of European and non- European predictive variables. Moreover, the proposed method can weigh the bias of the prediction model against the variance by using the Bagging algorithm. The simulated data analysis shows that the proposed method not only improves the prediction performance of the European Gaussian process, but also works in the presence of irrelevant predictive variables. Finally, the actual data analysis shows that the proposed method has achieved good prediction results in the task of predicting the rise and fall of stock prices.

As relações econômicas entre Costa do Marfim e França

he present article deals with the economic relations between Ivory Coast and France, analyzing the economic trajectory of the country under the presidency of Félix Houphouët Boigny (1960-1993). We seek to address the process of independence of the country, led by Boigny, dealing with the neocolonialist action of France through the use of the CFA Franc and the maintenance of military bases in the country, among others. In this context, we present a retrospective of Ivory Coast's economic policy, focused on agricultural production, mainly on the coffee-cocoa binomial. Much of the production continued to be exported to France after independence and, after a period of great export growth, in the 1980s the country entered a serious crisis, due to the maintenance of the economic structure of a colonial character. The crisis was marked by the fall in prices of the main export products, the external debt and its moratorium. Although there is a history of adoption of structural adjustment programs (SAP) in the 1980s, conducted by the International Monetary Fund (IMF) and the International Bank for Reconstruction and Development - World Bank (IBRD), the general effects did not lead to overcoming the crisis.

Geopolitical risk and energy price crash risk

This paper explores the link between geopolitical risks and energy prices crash risk. Studying energy price crashes is important given the sharp fall in oil prices in 2008 and 2014. The analysis focuses on three energy markets: natural gas, oil, and coal, while it employs two measures: the negative coefficient of skewness and the down-to-up volatility, to construct proxies for crash risks. The period of examination is January 2000 to December 2023, whereas that for coal is January 2010 to December 2023. The study employs a modified version of the smooth transition autoregressive model. The results show that, within the modelling framework, coal and oil crash risks are driven by the cyclical behavior of geopolitical acts, whereas natural gas crash risks by geopolitical threats. Causality tests confirm the prediction that geopolitical tensions cause crash risks in energy markets. The results also confirm that the “Economic Activity Channel” is only valid for energy markets driven by geopolitical threats. Energy market regulators should be concerned about crash risks, given that the energy supply shows cyclical boom and bust cycles in prices and production. Crash risks could also potentially cause a fall in investments required to enhance energy efficiency.

Impact of Oil Price Shocks on Islamic and Conventional Bank Performance: Empirical Evidence from Saudi Arabia

This paper aims to investigate and compare the effect of oil price shocks on the bank performance at the aggregate level as well as the level of conventional and Islamic banks. The Autoregressive Distributed Lag (ARDL) methodology was adopted to analyze a panel of 10 Saudi banks, including 6 conventional and 4 Islamic banks, between 2006 Q1 and 2022 Q4. The results revealed that oil price shocks have a direct impact on banking performance. A rise (fall) in oil prices led to an increase (decrease) in bank performance through the channel of price-induced bank deposits. Additionally, oil price shocks have asymmetric effects, with positive oil shocks having a greater impact on bank performance than negative shocks. The findings highlighted that conventional banks tend to benefit more from oil price shocks, especially during oil price booms, as they experience higher positive impacts. However, during oil price busts, Islamic banks were more adversely impacted by oil shocks.

The Economic Impact of Covid-19 pandemic on Labor Market and Stock Market

The pandemic has caused severe unrest and uncertainty in the labor market. Share prices have fallen sharply. However, the reasons behind it and the related policy effects still lack a unified explanation and summary. Therefore, the topic of this paper is the impact of the epidemic on the labor force and the stock market. The research method of this paper is as follows: firstly, the relevant data such as unemployment rate, hiring ratio and purchasing manager index are collected, and then the data are analyzed. The study found that the main reasons for the decline in labor demand may include business shutdowns, more cautious business investment and the psychological impact on workers. Fears of a potential recession, supply chain disruptions and uncertainty over the duration and severity of the outbreak have driven the rapid fall in share prices. The relevant policy recommendations further encourage local governments to use the surplus funds from unemployment insurance and other sources to support enterprises in maintaining employment stability. This paper will encourage the implementation of policies that delay or partially refund social security contributions. And strengthen the strategy of partially refunding unemployment insurance premiums, promoting local employment opportunities, and providing subsidies to ensure the overall stability of the employment situation. These policies are constantly evaluated and adjusted in light of changing economic conditions and employment trends to help maintain employment levels and support businesses during difficult times.

Examining the Effect of 2023 Cash Crunch on the Poultry Egg Industry in Ogun State, Nigeria

Abstract This study examines the effects of the 2023 cash crunch on the poultry egg industry in Ogun State, Nigeria. Data from 64 poultry egg farmers were collected and analyzed via structured e-questionnaires. Results show 83% of respondents were small-medium scale farmers and 73% used commercial feeds. Total egg production before (12,210 crates) and during the cash crunch (12,391 crates) did not significantly differ. Average feed cost per bag was ₦7,097 before and ₦7,151 during the crunch. However, average sales of 2,213,867 crates before and 199,437 crates during the cash crunch differed. A 36% cumulative decrease in egg price from ₦2,472 (December 2022) to ₦1,587 (March 2023) led to an 83% drop in daily farm revenue. The price fall did not boost egg demand. Coping strategies included increased delivery to customers (18%), gifting eggs (56%), and selling poultry birds (25%). The study recommends government grants and review of loan tenure for farmers while encouraging collaborative egg processing efforts. Additionally, it underscores the need for animal science research to explore methods for temporarily halting egg laying during economic challenges.

Trade war: the steel and aluminum markets and the trade governance

The international institutionalism has been under debate. The World Trade Organization (WTO) has not been immune to strong criticisms that has been exacerbated in recent years. A turning point in this process was the trade war between the United States and China that began in 2018. It was characterized by tariff increases that persist. The contribution of this work is to show how these measures taken by relevant global players (such as the United Sates and China) have significantly affected the international markets and it impacted on third countries, not only in terms of trade flows but also when considering the international trade regulatory framework. The drop in the demand from the United States implied a fall in the global demand that caused a fall in international prices. Moreover, it is shown that Trump's measures were successful given that China was substituted by other suppliers. Finally, his protectionist strategy against China, was accompanied by a broader strategy against the World Trade Organization by blocking not only the negotiations during the Buenos Aires Ministerial Conference but also the Dispute Settlement System.

The research on factors influencing housing prices-take Beijing as an example

Housing price is not only related to the economic situation of individuals and families, but also has a profound impact on the whole social economy. For many families, their home is their biggest asset. A rise in house prices can increase household net assets. A fall in house prices could lead to a decline in assets. This paper aims to study the influencing factors of housing prices. The data in this paper take Beijing from May to July 2014 as an example. First of all, the article mentions some papers about housing prices, then the author uses scatter plot and linear regression to fix the model. In the results, it can be seen that sqft-living, sqft-above and view have a relatively high correlation with housing prices. Finally, the specific correlation data table is listed. The final conclusion gives the results of the research in this paper and the authors of the articles mentioned. Housing price is not only related to the economic situation of individuals and families, but also has a profound impact on the whole social economy.

Assessment of exchange rate determination in a mono-resource economy: A case of Nigeria

<p style="text-align:justify"><span style="font-size:16px"><span style="font-family:Times New Roman,Times,serif"><span dir="ltr" lang="EN-US"><span style="color:black">This study examined the determinants of the exchange rate in a mono-resource economy, during the period of currency and oil price fall in Nigeria. The aim of the study is to ascertain the potentiality of economic diversification (non-oil export) in saving the falling value of the domestic currency, as well as, its stability. The study employed the use of monthly data from the Central Bank of Nigeria and Nigeria National Petroleum Corporation from January 2008 to December 2020 using the ARDL and NARDL models to achieve the stated objectives. In the literature, several empirical studies analyzed the relationship between exchange rates, oil price, and oil export and came to the logical conclusion that a rise in the price of oil would bring about a rise in the exchange rate, all things being equal while the reverse is the case. To add to the existing body of knowledge this study did not only look at the relationship between the variables but also examined the determinants of the exchange rate in a mono-resource economy and ascertained the potentiality of economic diversification in bringing succor to the falling exchange rate in the midst of falling oil price. The NARDL result corroborates the findings of previous studies on the relationship between exchange rate, oil price, and the performance of non-oil export. It maintains that positive changes in oil prices would lead to the appreciation of domestic currency while negative changes in oil prices would lead to the depreciation of the domestic currency. With this analysis, the study recommends the diversification of the economy and revitalization of the non-oil sector. Since import proves to have a negative impact on the exchange rate, the revitalization of the non-oil sector stimulates domestic consumption and thus reduces import bills which raise the demand for the dollar and weakens the naira.</span></span></span></span></p>

Information Technology and Returns to Scale

What are the implications of the dramatic fall in IT prices for aggregate technology? When firm-level technologies are continuously differentiable, a factor price shock leads to (i) a substitution between factors and/or (ii) an endogenous response of returns to scale. The second channel is governed by the output elasticity of relative factor demand. Using detailed firm-level data from France, we estimate this elasticity to be positive for IT factor demand. A quantitative exercise accounting for both technological channels shows that falling IT prices can explain much of the changes in concentration and the composition of aggregate labor share in France. (JEL D22, D24, D33, E25, L63, L86)

The long term price elastic demand of hydrogen – A multi-model analysis for Germany

Hydrogen and its derivatives are important components to achieve climate policy goals, especially in terms of greenhouse gas neutrality. There is an ongoing controversial debate about the applications in which hydrogen and its derivatives should be used and to what extent. Typically, the estimation of hydrogen demand relies on scenario-based analyses with varying underlying assumptions and targets. This study establishes a new framework consisting of existing energy system simulation and optimisation models in order to assess the long-term price-elastic demand of hydrogen. The aim of this work is to shift towards an analysis of the hydrogen demand that is primarily driven by its price. This is done for the case of Germany because of the expected high hydrogen demand for the years 2025–2045. 15 wholesale price pathways were established, with final prices in 2045 between 56 €/MWh and 182 €/MWh. The results suggest that – if climate targets are to be achieved - even with high hydrogen prices (252 €/MWh in 2030 and 182 €/MWh in 2045) a significant hydrogen demand in the industry sector and the energy conversion sector is expected to emerge (318 TWh). Furthermore, the energy conversion sector has a large share of price sensitive hydrogen demand and therefore its demand strongly increases with lower prices. The road transportation sector will only play a small role in terms of hydrogen demand, if prices are low. In the decentralised heating for buildings no relevant demand will be seen over the considered price ranges, whereas the centralised supply of heat via heat grids increases as prices fall.

STOCK MARKET REACTIONS TO PUBLIC RELEASE OF ENVIRONMENTAL RANKINGS OF HEAVY POLLUTERS: THE ROLE OF ULTIMATE CONTROLLERS

Adopting the event study method, this paper examines how the stock market reacts to the public release of environmental performance rankings of heavy polluters. Specifically, we explore the impact of the public release of the 100 best and 100 worst companies in terms of environmental performance on the stock prices of companies involved, and the potential moderation of ultimate controllers. We find that the stock prices of the companies on the lists were negatively affected by the event. However, stock price changes are not significantly related to the relative rankings on the list. Furthermore, companies whose ultimate controllers possess a larger control–ownership wedge experienced a less severe fall in stock prices than did their counterparts. This study sheds light on the nuances of the financial implications of negative environmental publicity.

A theory of capital flow retrenchment

During a downturn in the global financial cycle there is a simultaneous retrenchment in gross capital flows and a fall in risky asset prices. The global financial cycle is closely related to fluctuations in risk appetite. We develop a model that can simultaneously produce a fall in gross outflows, inflows, and asset prices following an increase in global risk aversion. There is heterogeneity across investors within a country in the willingness to hold risky assets and to hold foreign assets. The fall in the asset price after a rise in global risk aversion shifts the wealth distribution towards investors that are less willing to hold foreign assets. This leads a drop in gross flows. We calibrate the within country heterogeneity in the model to match heterogeneity observed in micro data of household portfolios. The retrenchment in the calibrated model is quantitatively similar to what we observe in the macro data.

Mobile phones and Mozambique farmers: Less asymmetric information and more trader competition?

We measure how the introduction of mobile phones in Mozambique affected unit values of household maize sales, maize producer prices and traders’ margins. Our estimations are based on both representative household surveys for the years 2002, 2003, 2005, 2006 and 2008, and weekly producer and market prices of white maize grain from July 1997 to December 2009 for 15 major producer markets. We find household sales unit values and producer price decreases, and traders’ margin increases between 14% and 22%, indicating benefits for traders. Next, we investigate heterogeneity of impacts in order to explore underlying mechanisms: impacts on margins decrease with population density and network density, and increase with gains from long-distance trade. Impacts on household selling prices are not significantly correlated with educational attainment, but the fall in prices is less with larger household wealth. Impacts on household selling prices and producer prices also become less negative over time, suggesting delayed adoption by farmers. Our results are robust to various threats.

Wealth inequality and the distributional effects of maximum loan-to-value ratio policy

Macroprudential policy improves economic outcomes by reducing the likelihood and severity of financial crises. Yet, are there unintended long run consequences to the introduction of a macroprudential policy regime, and are they conditional on the level of wealth inequality? I answer these questions by looking at the effect of a reduction in the maximum loan-to-value (LTV) ratio on homeownership rates, house prices and housing wealth inequality across two economies with different initial wealth dispersion. I use a heterogeneous agent model in which households face an endogenous borrowing limit in the form of a collateral constraint. A reduction in the LTV limit tightens the borrowing constraint and changes the levels of wealth at which households rent or become constrained or unconstrained owners. The key finding of this paper is that initial conditions matter; a greater share of households is affected when wealth is distributed more equally. This larger impact on aggregate demand leads to a stronger fall in house prices and a larger rise in the share of constrained homeowners and housing wealth inequality. The effects are also non-linear in the LTV ratio, with progressively stronger effects at lower LTV ratios.

State-owned enterprises as countercyclical instruments: Quasi-experimental evidence from the infrastructure sector

This paper examines the effects of a negative macroeconomic shock on the financial performance of state-owned enterprises (SOEs) in infrastructure. The main aim of the paper is to explore whether SOEs serve as countercyclical instruments or whether they end up generating fiscal costs during a downturn, perhaps amplifying negative shocks. The paper introduces a new measure of fiscal injections that includes subsidies, equityrecapitalizations, and loans from the government, other SOEs, or state-owned financial institutions. The empirical setup uses a quasi-experimental setting that exploits the differential effects of a drastic fall in oil prices (in 2014–15) for SOEs in countries that experience a negative aggregate demand drop as a consequence of this shock versus similar firms in countries that do not suffer a downturn from the shock. The results—based on a balanced sample using coarsened exact matching and a differences-in-differences estimation—show that SOEs in treatment countries received increases in fiscal injections as a percent of average assets of 3.5 percent the year after the shock, equivalent to a significant recapitalization. These fiscal injectionstake the form of equity injections and loans from the government and state-owned financial enterprises. The results also show that capital expenditure as a percent of average assets in fully owned infrastructure SOEs decreased by 3.5 percentage points the year after the negative shock, equivalent to a 40 percent decline relative to its average level. In sum, this paper presents evidence that shows that SOEs do not serve as countercyclical tools and, in fact, may amplify negative shocks by requiring fiscal injections for SOEs while also lowering their capital expenditures.

Spill-over effect of India cotton trade on labour and household income

India is one of the world’s largest producers and exporters of cotton, the major raw material for the textile industry, employing more than 4.5 crore people in the country. The present study aimed to analyse the impact of adverse trade in Indian cotton sector on labor and household income by employing Social Analysis Matrix based multiplier model and partial equilibrium model. Indian textile sector has strong backward linkages with primary input multiplier and household income multiplier of 4.13 and 3.44, respectively and, thus transmitting external impacts to the labour and household income. The sector has a higher multiplier effect of 10.17 on production activities, of which the impact on the cotton sector is 0.126. Fall in export and domestic demand for clothing and apparel in addition to movement restrictions around the world during the period 2020-2021, disrupted cotton supply chain and consequent fall in demand and price of the commodity. Simulations for the increase in carry-over stock and reduction in domestic consumption and cotton exports revealed that limiting the commodity's production and supply would retain the market equilibrium and increase the domestic price to the advantage of the farmers. The study reveals that dynamics in the Indian cotton sector trade significantly impacted labour and household income. Appropriate planning for areas under cotton cultivation and alternate procurement mechanisms during emergency situations would stabilise the Indian cotton economy.

Review of Predicting Stock Prices Based on Machine Learning and Stock Learning

Predicting stocks is to help investors make decisions and help them minimize risks as much as possible, thereby obtaining investment returns. If we can accurately predict the rise and fall of stock market prices, we can buy or sell stocks at higher prices in the market, thereby obtaining higher profits. This article is based on machine learning and deep learning algorithms such as support vector machine (SVM), principal component analysis (PCA), random forest (RF), and recurrent neural network (RNN), long short-term memory network (LSTM), and convolution neural network (CNN). The conclusion is that machine learning requires manual intervention, is faster to train, more interpretable, and usually performs better on data sets with simpler structures and smaller sizes. Deep learning has lower requirements for feature extraction and discovery, has stronger expression and fitting capabilities, and can better capture the correlation between data in larger and more complex data sets.

Impact of China on commodity exporters

AbstractWe compare the effect of a domestic shock in China and the US on the real economy and financial markets of various commodity‐exporting countries. To obtain a reliable indicator for China's macroeconomic conditions, we estimate a Bayesian dynamic factor model using block‐exclusion restrictions to identify a China factor and a US factor from monthly macroeconomic data for China and the US. We, then, assess the implications of a negative shock to both factors on the macroeconomy of a commodity‐exporting nation using Bayesian FAVARs based on recursive identification. A negative China shock leads to output loss and a fall in stock prices in these countries. China shock affects the output of only a subset of countries in our sample compared to the US shock, which affects all countries. China shock has a larger, quicker and more persistent impact on the stock markets of commodity‐exporting countries compared to the US shock. Countries with weaker institutional or business environments experience a larger negative real effect of the China shock, whereas countries with less stable financial systems demonstrate stronger financial effects. Using historical decomposition, we establish a growing role of the China factor over time, in particular for large emerging economies such as Brazil and Russia.