Price Discovery In Market Research Articles

Determinants of housing rental prices in Seoul: applying explainable AI

ABSTRACT Though previous analyses of housing rental prices rely on hedonic pricing or ordinary least squares models, they cannot fully account for the nonlinearity and complexity inherent in the determination of market prices. We exploit machine-learning techniques to accurately understand the determinants of housing rental prices and emphasise explainable artificial intelligence (XAI) to overcome the limitations of classical machine learning with black-box features. To analyse the determinants of housing rental prices in Seoul, we apply extreme gradient boosting (XGBoost) and Tree Shapley additive explanations (TreeSHAP) models which learn and explain nonlinear features of the rental prices. XGBoost predicts rental prices more accurately than regressions and is robust to multicollinearity. TreeSHAP identifies local and global features affecting the determination of rental prices. Our analyses identify the individual impacts of various determinant variables on rental prices and underscore the multifaceted influences that these variables exert on housing affordability.

From Algorithms to Market Dynamics: A Literature Review on High-Frequency Trading

Abstract: High-frequency trading (HFT) uses advanced technologies and sophisticated algorithms to make transactions at unprecedented speeds, which could significantly impact modern financial markets. This literature review examines the technological foundations, primary trading strategies, market impacts, regulatory environment, risk management practices, and future research directions in HFT. The findings reveal that HFT could increase market liquidity and price discovery but also increase volatility during periods of high market stress. Regulatory frameworks such as the SECs Market Access Rule and MiFID II aim to monitor and control HFT activities, at the same time effective risk management practices are crucial for maintaining market stability. Future research should focus on emerging technologies such as AI, ML, quantum computing, and blockchain, along with a better understanding of market structure and global regulatory coordination. This review provides valuable insights for market participants, regulators and researchers, contributing to a balanced perspective on HFTs role in contemporary financial markets.

“The principles of political economy, though often quoted, are little understood.” Fleeming Jenkin on trade unions and the law of supply and demand

The paper proposes a rational reconstruction of Fleeming Jenkin’s 1868 analysis of wage determination in labour markets characterised by the presence of trade unions. Jenkin intended to show that the supply and demand theory of market price determination did not support the thesis sustained by the opponents of trade unions that the latter are unable to permanently achieve a market-clearing wage higher than that which would be obtained in their absence. Starting with a definition of “demand” and “supply” of a given commodity as functions of a few economic variables, Jenkin elaborated a fresh critique of the wages fund theory and highlighted the impact of trade unions on both supply and demand for labour.

Analyst forecast revision consistency and reversal: Evidence of stock market efficiency

AbstractThis study reexamines the information content and market price discovery associated with individual analysts' earnings forecast revisions. We refine the definition of high‐innovation revisions as high‐innovation consistent forecast revisions and high‐innovation reversal forecast revisions. Cross‐sectional analysis shows that high‐innovation reversal good (bad) news revisions, although having larger forecast changes, cause fewer upward (downward) post‐revision price shifts than high‐innovation consistent good (bad) news revisions. We also find that the market can distinguish which group of analysts provides more useful information about firms’ true value, but it takes some time for the market to digest this useful information.

Smart Agriculture Applications and Data Analysis with Industry 4.0

The world’s food demand is predicted to exceed its food supply significantly in the coming periods. Many physical factors, such as climate change in access to water, change the production amount and food prices. Efficient resource utilization can be achieved by developing smart agricultural applications using the IoT and image processing techniques. For this purpose, in the proposed study, a smart agriculture application was developed using IoT technology with image processing. In the proposed image processing algorithm, the crops’ images were processed, weight estimates were made, and their numbers were taken. The data we collect instantly can be uploaded to the cloud, and the data collected on the cloud side can be analyzed over the mobile application. Thanks to data analysis with the mobile application we have developed, we can see the current status of the crops and make instant decisions, and it also plays a role in determining market prices. With all these studies, it has been seen that agriculture can be digitalized with the technologies we use, and thus, productivity in agriculture can increase significantly.

Efisiensi Perolehan Pendapatan Antara Beban Yang Dikeluarkan Dengan Pendapatan Terhadap Keuntungan Usaha Menggunakan Metode Target Costing (Studi Pada Usaha Kuliner Jajanan Najla Di Purwakarta)

The magnitude of profit obtained is highly dependent on production cost efficiency, thus requiring special attention to achieve the company's target. Cost control must align with the company's objectives, including achieving maximum profit with minimal production costs. This study aims to analyze the relationship between expenses, income, and business profits in UMKM Jajanan Nazla, as well as identify key factors influencing the efficiency of revenue generation and expense expenditure. Based on the analysis of production costs, UMKM Jajanan Nazla faces a deficit in net profit due to the inability to cover production costs. Therefore, this research applies the target costing method to improve its profitability. The steps of implementing target costing involve determining market prices, calculating target profits, and identifying target production costs. By implementing value engineering, such as reducing packaging costs, labor costs, and even eliminating rental costs, UMKM successfully reduces production costs to meet the set target cost. As a result, production costs decreased from Rp. 7,880,000 to Rp. 5,240,000 per month, resulting in savings of Rp. 2,640,000. Thus, the initially deficit net profit increased to Rp. 1,510,000 per month after the application of target costing. In conclusion, it can be inferred that the target costing method is effective in improving the production cost efficiency of UMKM Jajanan Nazla, helping them strengthen their position in the competitive market.

ANALYZING FINANCIAL MARKETS EFFICIENCY: INSIGHTS FROM A BIBLIOMETRIC AND CONTENT REVIEW

The nonlinear nature of financial data series and the intricate incorporation of data into market prices necessitate a comprehensive exploration of key research findings, prevailing trends, intense debates, and subfields in the market behavior realm. Studies exploring the way in which technical analysis can exploit the deviation from market efficiency in stock markets, based on new prediction techniques (machine learning, deep learning, and artificial intelligence), are lacking. This study presents a comprehensive bibliometric assessment of market behavior using the Scopus database from 1972 to 2022. A thorough assessment process, which included keywords, filters, and data cleaning, was employed to narrow down the literature from 30,551 to 8,289 relevant papers. The research framework delineates seven primary themes that underpin this study: market efficiency, behavioral finance, technical analysis, volatility, fractals, asset pricing, and price discovery. For practitioners, investors, and policymakers, our study presents evidence regarding emerging themes, such as technical analysis, adaptive market hypothesis, and machine learning, which diverges from the findings of the proponents of equilibrium models based on investors' rationality. Moreover, an in-depth inquiry into the role of technical analysis in shaping portfolio investment presents a promising future research avenue.

The Path of Empowering Digital Industry with Green Finance for Green and Low Carbon Development

Green and low-carbon development is a consensus among countries around the world on the development of the digital industry. The digital industry, as a pillar industry of China's economy, is a high energy consuming and carbon emitting industry. Therefore, the green and low-carbon transformation of the digital industry is of great significance for China to achieve its "dual carbon" goals. The achievement of the "dual carbon" goal relies on the support of financial services, and green finance plays three roles in guiding resource allocation, market price discovery, and risk management in its development process, mainly including financial products such as green credit, green bonds, green funds, and carbon markets. By building a green financial system that meets the requirements of low-carbon transformation, exploring new growth opportunities in the process of low-carbon transformation, taking precautions, using green finance, enterprise information environment disclosure and other means to guide the rational allocation of funds, using market means for low-carbon investment, reducing investment risks in the process of green transformation, and promoting low-carbon transformation of the digital industry.

Social network mechanisms of price formation in an artisanal fishing community in Chile

Local fish markets play a crucial role in meeting local and regional demand for seafood. However, the underlying social and local processes determining price formation in these markets still need to be clarified. Through ethnographic research of an artisanal fishing community in central Chile focused on the common hake catching (Merluccius gayi gayi), we found that mutual observation and negotiation are the two key social processes of the local economic order. These processes produce two local structures: (a) the fishers’ maritime cliques in the sea and (b) the chain structure in the cove, which combines commercial and community relationships to determine market prices.

Price discovery and volatility spillovers in the interest rate derivatives market

The interest rate derivatives market is an important force in promoting the development of the bond market and is an effective tool to manage interest rate risk. The research on price discovery and volatility spillover of the market can help provide valuable reference information for investors. Based on treasury bond futures and interest rate swaps, the paper aims to discuss the price discovery function and spillover structure of the interest rate derivatives market. The paper establishes the information share model and spillover index model for empirical analysis. The results show that: First, the calculation results of the information share model show that the price discovery of treasury bond futures and interest rate swap markets is stronger than that of the spot market. Second, based on structural break analysis, treasury bond futures and interest rate swaps do not have breakpoints, while the treasury bond spot has three breakpoints. The paper divides the entire sample into four stages based on structural breakpoints and finds that the price discovery ability of the interest rate derivative market dynamically changed. Third, as a net spillover in the market, treasury bond futures have developed relatively stable. Both treasury bond futures and interest rate swaps have spillover effects on the spot market, indicating that China’s interest rate derivatives market can impact the treasury bond spot market.

Market price determination: Interpreting quote order imbalance under zero-profit equilibrium

We address the challenge of accurately determining market prices in order-driven markets, where the granularity of price adjustments is set by exchange rules, such as minimum increments of 0.01. Our approach advances traditional pricing models in accuracy by interpreting the dynamics of quote order imbalance, defined as the difference in volume between buy and sell orders at the best available prices, within a zero-profit equilibrium framework. This framework assumes that market competition leads to a state where no additional profit can be made from these imbalances. Analyzing high-frequency data from China's A-share market, we demonstrate the variable impact of order imbalances on price formation, influenced by the depth and liquidity of the market. We also uncover a potential threshold effect of order flow autocorrelation on pricing. Our findings enhance market microstructure research and high-frequency trading strategies by offering a valuable tool for understanding price formation's complex dynamics.

Pemikiran Tokoh-Tokoh Ekonomi Islam Mengenai Konsep Penetapan Harga Pasar

This journal discusses the thoughts of Islamic economic figures regarding the concept of market price determination. The figures discussed include Ibn Taymiyyah, Al-Mawardi, Abu Yusuf, Al-Ghazali, and Ibnu Khaldun. The methodology used is literature study. The results show that according to these figures, prices should be determined by market mechanisms and the interaction between demand and supply. However, under certain conditions, for example market distortion, the government is allowed to intervene in price fixing to protect public interests. In conclusion, Islamic economic figures agree that basically prices must be determined by competitive market mechanisms, but government intervention is permitted under certain conditions to protect community interests and restore market balance.

Price discovery and volatility connectedness in Indian gold market: a study of ETFs, spot and futures

Price discovery and volatility connectedness in Indian gold market: a study of ETFs, spot and futures

Price discovery and volatility connectedness in Indian gold market: a study of ETFs, spot and futures

Price discovery and volatility connectedness in Indian gold market: a study of ETFs, spot and futures

Comparison of U.S.-China Futures and Spot Market Price Conduction: Based on the Study of Wheat Market

In-depth exploration of the difference of price transmission capacity between Chinese and world agricultural futures market is beneficial to understand the efficiency of Chinese futures market. Studying its transmission mechanism can deepen the understanding of the characteristics of wheat market price fluctuations, which is important to further guide the development of China's futures market and ensure China's wheat industry to develop healthily. This paper uses the VAR model and ARMA-GARCHX model to analyze and compare the prices of futures and spot market in China and the United States from the perspective of yield and volatility transmission. The results show that futures and spot market prices of China and the United States have a mutual guiding relationship, and the price guidance role of the United States in both markets is stronger than China. Then, compared with the spot price, the transmission of futures prices is more comprehensive and significant. Considering the results, China needs to deepen the reform of the futures market and implement precise policies to enhance the ability of market price discovery.

Price Discovery and Market Efficiency in India's Financial Futures Market within the Derivatives Landscape: An Empirical Analysis

This study offers a robust, long-term analysis of price discovery and the persisting lead-lag relationship between India’s equity futures and spot markets. Utilising monthly data from April 2005 to December 2022, it filters transient noise typically associated with high-frequency data. Information Share and Common Factor Weight methodologies within the Vector Error Correction (VEC) framework consistently reveal the dominance of futures markets in the price discovery process. The insights remain consistent across three distinct periods spanning the global financial crisis and the COVID-19 pandemic. The volatility dynamics and asymmetry effects in the Indian equity futures and spot markets using the Vector Error Correction - Exponential General Autoregressive Conditional Heteroskedastic (VEC-EGARCH) approach uncover notable asymmetry effects, signifying a strong market sensitivity to negative news. This highlights the necessity for comprehensive risk management strategies and stringent regulatory supervision, especially in light of the significant growth and systemic risks in the Indian derivatives market.

Does high-frequency trading cause stock prices to deviate from fundamental values?

We examine whether high-frequency trading (HFT) is associated with greater deviations of stock prices from firms’ fundamental, intrinsic values. Prior studies show that HFT can improve market liquidity and price discovery in the short-term, but countervailing effects can discourage new information acquisition, reduce the amount of fundamental news reflected in stock prices, and reduce institutional investors’ desire to invest and trade in stocks subject to high levels of HFT. We find that greater HFT leads to a greater deviation of stock prices from accounting-based valuation estimates. The results hold across univariate, multivariate, and cross-sectional tests, as well as a natural experiment that induces an exogenous shock to HFT for a small sample of firms. Our findings contribute to the understanding of the longer-term valuation implications of HFT, as well as the traditional valuation role of accounting variables.

A tale of two contracts: Was the SHFE copper futures market disrupted by the listing of INE bonded copper futures?

AbstractLeveraging tick‐by‐tick data, this study provides the first analysis of Shanghai International Energy Exchange (INE) bonded copper futures' performance in market quality and price discovery. In particular, we investigate the effects of the market opening (listing of INE bonded copper futures) on Shanghai Futures Exchange (SHFE) copper futures' market quality and price discovery. Our results show that the market quality and price discovery of INE bonded copper futures in the first year of the listing is not promising. Our synthetic control method results suggest that market openness does not significantly reduce SHFE copper futures' market quality in terms of activity, liquidity, and volatility. Moreover, market openness does not significantly reduce the SHFE copper futures' price discovery effectiveness. Overall, the performance of new INE bonded copper futures needs improvement, while its listing did not disrupt SHFE copper futures. Our results suggest that a dual‐contract mode is an alternative option for internationalization in China's commodity futures markets.

Analisis Etika Bisnis Islam dalam Penetapan Harga Keseimbangan Pasar Berdasarkan Pemikiran Ibnu Khaldun

This research aims to analyze Islamic business ethics in determining market equilibrium prices based on Ibn Khaldun's thoughts. This research uses qualitative methods with data collection techniques through documentation techniques, observation and interviews with informants. Based on the research results, it can be concluded that at different levels, traders with small capital tend to have poor moral values such as cheating, playing with the scales, and playing with prices. Buyers tend to suffer losses and experience fraud in buying and selling. Meanwhile, the current market price determination is not based on the theory of demand and supply, but the price is high because the price is taken from the agent where the trader takes the merchandise, the seller only adjusts the price and on the other hand the high demand is caused by the behavior of certain individuals or middlemen who cheat by hoarding goods with the aim of taking advantage of the scarcity of supply by raising the price of goods above the normal price when many goods are needed.

Learning About Market Microstructure and Price Discovery Using Experimental Markets

This study introduces the use of an instructor-developed trading simulation to teach intrinsic value estimation, price discovery,and market mechanics. It provides the reader with a cost efficient solution to deepen students’ understanding of financial markets and the price discovery process. By using a multi-week time frame we allow students to analyze the financial information of the companies in the simulation as well as to develop strategies to exploit the market structure and price discovery process. Thus, this simulation combines the importance of financial analysis with the awareness of the impact of liquidity and market organization on price discovery.