Fundamental Price Research Articles

Exploring the market resilience of selected stocks in the Johannesburg Stock Exchange

The market resilience of a stock is an integral component of financial market because it supports smooth trading and absorb market shocks. However, the contention has always been to effectively determine the level of resilience in stocks with the application of proper methodology to make informed decisions. Therefore, aim of this study was to examine the level of market resilience in selected stocks in the Johannesburg stock exchange. Using a fixed effect model, the findings of this study indicates that most securities trading on the exchange lack market resilience. This was evident in the significant relationship between the specific independent and dependent variables. A risk coefficient should therefore be assigned to bid and ask to spread to enhance market resilience. These risk coefficients will induce the bid and ask prices to be close to the fundamental price.

Asymmetric Information and Information Assimiliation

The purpose of this research is to determine the impact of information assimilation on equity issuance in the banking sector. The data consists of 384 observations of banking and finance companies listed on the Indonesian Stock Exchange from 2020 to 2023. A univariate analysis was utilized to identify the differences in asymmetry between companies with seasoned equity offerings (SEOs) and non-SEOs to meet capital requirements in the banking sector. The research indicates that SEO and non-SEO banks exhibit significant differences in their spreads. Despite the banking sector's access to deposits and wholesale funding to finance capital shortages or prospective projects, equity issuance by the banking sector has increased. The presence of regulations on information disclosure does not produce asymmetric information; however, the increased spread among companies with SEOs is due to the more complex information assimilation process, which in turn results in a wider spread relative to the fundamental price.

Deep Hawkes process for high-frequency market making

AbstractHigh-frequency market making is a liquidity-providing trading strategy that simultaneously generates many bids and asks for a security at ultra-low latency while maintaining a relatively neutral position. The strategy makes a profit from the bid-ask spread for every buy and sell transaction, against the risk of adverse selection, uncertain execution and inventory risk. We design realistic simulations of limit order markets and develop a high-frequency market making strategy in which agents process order book information to post the optimal price, order type and execution time. By introducing the Deep Hawkes process to the high-frequency market making strategy, we allow a feedback loop to be created between order arrival and the state of the limit order book, together with self- and cross-excitation effects. Our high-frequency market making strategy accounts for the cancellation of orders that influence order queue position, profitability, bid-ask spread and the value of the order. The experimental results show that our trading agent outperforms the baseline strategy, which uses a probability density estimate of the fundamental price. We investigate the effect of cancellations on market quality and the agent’s profitability. We validate how closely the simulation framework approximates reality by reproducing stylised facts from the empirical analysis of the simulated order book data.

Сoordination of fiscal and monetary policy in Ukraine

In the conditions of uncertainty and economic instability, the issue of researching approaches to strengthening the coordination of fiscal and monetary policy is becoming relevant. The aim of the research is to justify directions for strengthening the coordination of fiscal and monetary policy of Ukraine. It is hypothesized that the level of fiscal and monetary policy coordination determines the country’s ability to ensure macroeconomic stability. Special and general scientific methods were used: system approach, theoretical generalization, induction and deduction, statistical, scientific abstraction. Strengthening the coordination of fiscal and monetary policy is an important stabilization tool for ensuring the adaptation of the economy to social and economic conditions, curbing inflation in order to maintain exchange rate stability, reducing fundamental price pressure and directly overcoming inflationary processes. The toolkit of fiscal and monetary policy must be considered in an inseparable unity, taking into account the synergistic effect of ensuring macro­economic stability, which cannot be achieved exclusively by the tools of only one of the policies. The main directions of strengthening the coordination of the fiscal and monetary policy of Ukraine at this stage include: combining the tools inherent in both directions of policies, strengthening its flexibility and adaptability to socio-economic processes; sy­ner­gy of policy instruments in the context of ensuring debt sustainability and reducing fiscal risks; substantiation of the common strategic goals of policies, which will contribute to strengthening their coordination, in particular by developing an appropriate strategy; the development of a financial toolkit for prevention and response, within the framework of which policy instruments are used together, in particular by improving the traditional practice of applying macroprudential measures; streng­thening the independence of state institutions that ensure the formation and implementation of fiscal and monetary policy by continuing institutional and legislative reforms in the relevant areas.

Dividend based risk measures: A Markov chain approach

Computations of risk measures in the context of the dividend valuation model is a crucial aspect to deal with when investors decide to buy a share of common stock. This is achieved by using a Markov chain model of growth-dividend evolution, imposing an assumption that controls the growth of the dividend process and in turn allows for the computation of the moments of the price process and the fulfillment of a set of transversality conditions which allows avoiding the presence of speculative bubbles in the market. The probability distribution of the fundamental value of the stock is recovered by solving a moment problem, based on the solution of a maximum-entropy approach from which it is possible to compute classical risk measures based on these fundamental variables. The methodology is applied to real dividend data from the S&P 500 index. Results show that our model provides complete information about the fundamental price not limited to its expectation.

Global uncertainties, geopolitical risks and price exuberance: Evidence from international energy market

AbstractThe interaction of global uncertainty and geopolitical risks with energy price fluctuations has remained a critical global issue. This interaction can impact several regions' macroeconomic performance and welfare by making fundamental energy price forecasting more difficult, which may lead to exuberant behaviour. To help producers, consumers, and regulators make informed decisions in the face of volatile and uncertain energy markets, it is critical to highlight how these uncertainties influence price exuberance. In this light, this study examines the impact of global uncertainty and geopolitical risks on international energy price exuberance using monthly data from January 1990 to October 2022. The study employs supremum augmented Dickey–Fuller (SADF) and generalised augmented Dickey–Fuller (GSADF) tests to identify energy price exuberance. Firstly, consistent with exuberant behaviour, the tests identify seven episodes of explosive behaviour in the international energy prices within the sample. Secondly, this study applies the Logit model to estimate the impact of global uncertainty and geopolitical risks on price exuberance. The estimates suggest that the heightening of global uncertainty may deflate the price exuberance. This study also observes that adverse geopolitical risks (threats and acts) in the world and Ukraine amplify the likelihood of price exuberance in the market. However, adverse geopolitical risk (GPR) in Russia negatively impacted the formation of price exuberance. This finding implies that policymakers can use global uncertainty and geopolitical risks as early warning indicators of probable price exuberance in the international energy market. The findings also indicate the need for a buffer system and safe passage for the flow of energy supply in a geopolitical conflict or a major global event. The study further shows the need for a coordinated effort in innovation, research, and development to enhance energy efficiency and minimise reliance on fossil fuels, which these uncertainties may not significantly influence.

House price bubble detection in Ukraine

PurposeThe purpose of this paper is to present a framework for the assessment of the fundamental value of house prices in the largest Ukrainian cities, as well as to identify the thresholds, the breach of which would signal a bubble.Design/methodology/approachHouse price bubbles are detected using two approaches: ratios and regression analysis. Two variants of each method are considered. The authors calculate the price-to-rent and price-to-income ratios that can identify a possible overvaluation or undervaluation of house prices. Then, the authors perform regression analyses by considering individual multi-factor models for each city and by using a within regression model with one-way (individual) effects on panel data.FindingsThe only pronounced and prolonged period of a house price bubble is the one that coincides with the Global Financial Crisis. The bubble signals produced by these methods are, on average, simultaneous and in accordance with economic sense.Research limitations/implicationsThe framework described in this paper can serve as a model for the implementation of a tool for detecting house price bubbles in other countries with emerging, small and open economies, due to adjustments for high inflation and significant dependence on reserve currencies that it incorporates.Practical implicationsA tool for measuring fundamental house prices and a bubble indicator for housing markets will be used to monitor the systemic risks stemming from the real estate market. Thus, it will help the National Bank of Ukraine maintain financial stability.Social implicationsThe framework presented in this research will contribute to the enhancement of the systemic risk analysis toolkit of the National Bank of Ukraine. Therefore, it will help to prevent or mitigate risks that might originate in the real estate market.Originality/valueThe authors show how to implement an instrument for detecting house price bubbles in Ukraine. This will become important in the context of the after-war reconstruction of Ukraine, with mortgages potentially becoming the main tool for the financing of the rebuilding/renovation of the residential real estate stock.

Managing Bubbles in Experimental Asset Markets with Monetary Policy

AbstractWe study the effect of a “leaning against the wind” monetary policy on asset price bubbles in a learning‐to‐forecast experiment, where prices are driven by the expectations of market participants. We find that a strong interest rate response is successful in preventing or deflating large price bubbles, while a weak response is not. Giving information about the interest rate changes and communicating the goal of the policy increases coordination of expectations and has a stabilizing effect. When the steady‐state fundamental price is unknown and the interest rate rule is based on a proxy instead, the policy is less effective.

Estimating Risk in Illiquid Markets: A Model of Market Friction with Stochastic Volatility

Abstract This article deals with the problem of estimating the volatility of a financial security in a market with frictions. We propose a microstructural model with time-varying fundamental price volatility in which the trading price varies only if the value of the information signal is large enough to guarantee a profit in excess of transaction costs. Using transaction data only, the proposed approach allows to recover: (i) the conditional volatility of the information signal, which is thus cleaned out by market frictions and (ii) an estimate of transaction costs. Our analysis reveals that, after correcting for frictions, the risk of illiquid securities is substantially different from what is predicted by traditional volatility models. Furthermore, using a big dataset of intraday returns, we show that our transaction cost estimate is highly correlated with the main illiquidity measures and that such correlations are significant under different volatility regimes.

A dataset of egg chick prices within the layer hen breeding industrial chain in China from 2000 to 2019

This dataset is based on the fundamental egg chick market price data sourced from the National Animal Husbandry Station and China Animal Husbandry Association. Rigorous criteria, including considerations for reliability, continuity and authenticity were applied in the selection, processing, and analysis of the data. Through meticulous comparison and validation, we obtained the dataset of egg chick prices within the layer hen breeding industrial chain in China. The time coverage of the dataset ranges from 2000 to 2019, with granularity at monthly, quarterly, and annual intervals. In terms of spatial granularity, the dataset is segmented into two levels of granularity: nationwide and 26 respective provinces (autonomous regions and municipalities directly under the central government). The data elements in each spatiotemporal granularity include the average price of egg chicks, the month-on-month change rate, and the year-on-year change rate. This dataset serves as a foundational resource for the future profit evaluation of the layer hen breeding industry in China, and offers a crucial data basis for the development, policy support and scientific research in the layer hen breeding industry.

A web scraping-based approach for fundamental analysis platform in financial assets

There are two main benefits of using fundamental analysis for investors and portfolio managers. First, investing in a company with good ratios has lower risks. The second reason is that it is possible to evaluate share prices with internal valuation methods based on ratios. These price valuations can be more meaningful when combined with technical analysis data. Many data terminals provide processes such as fundamental analysis data and price valuation on a paid and licensed basis. However, the balance sheet data of publicly traded markets are publicly available and can be obtained and interpreted by web scraping methods. This study presents an approach in which basic analysis and price evaluation are made with balance sheets and ratios using open-source tools and web scraping.

Sieve bootstrap inference for linear time-varying coefficient models

We propose a sieve bootstrap framework to conduct pointwise and simultaneous inference for time-varying coefficient regression models based on a local linear estimator. The asymptotic validity of the sieve bootstrap in the presence of autocorrelation is established. The bootstrap automatically produces a consistent estimate of nuisance parameters, both at the interior and boundary points. In addition, we develop a bootstrap-based test for parameter constancy and examine its asymptotic properties. An extensive simulation study demonstrates a good finite sample performance of our methods. The proposed methods are applied to assess the price development of CO2 certificates in the European Emissions Trading System. We find evidence of time variation in the relationship between allowance prices and their fundamental price drivers. The time variation might offer an explanation for previous contradicting findings using linear regression models with constant coefficients.

Influence of Different Spacing and Organic Manure on the Yield and Economics of Groundnut (Arachis hypogea L.)

Aim: The trail was taken to find out the influence of different spacing and organic manure on the yield and economics of the groundnut (Arachis hypogea L.)
 Study Design: Factorial randomized block design.
 Place and Duration of Study: The experiment was taken during the kharif season of 2021 at G.H. Raisoni University at Agronomy farm, Chhindwara, M.P.
 Methodology: The set of nine treatment combination consist of three different spacing and three different OM which is applied at 12 kg/ha of FYM, at 6 kg/ha VC and at 6 kg/ha of PM. The experiment was carried out in Factorial Randomized Block Design with three replication and the treatment combination is T1: S1O1 (30 cm x 10 cm + FYM), T2: S1O2 (30 cm x 10 cm + VC), T3: S1O3 (30 cm x 10 cm + PM), T4: S2O1 (30 cm x 15 cm + FYM), T5: S2O2 (30 cm x 15 cm +VC), T6: S2O3 (30 cm x 15 cm + PM), T7: S3O1 (45 cm x 10 cm + FYM), T8: S3O2 (45 cm x 10 cm + VC) and T9: S3O3 (45 cm x 10 cm + PM) and total number of plots is 27. At the time of experiment, the maximum mean of temperature was 41.60C whereas the minimum mean temperature was 5.680C. The economics of groundnut crop was calculated as per the fundamental market prices of the input and produced during the kharif season 2021.
 Results: Maximum no. of pods/plant (30.67), length of pod (2.72), no. of kernels/pod (2.07), seed index (43.22 g), shelling percentage (74.76 %), pod weight/plant (18.66 g), pod yield/plot (1.53 kg), pod yield (63.01 kg/ha), kernel yield (23.45 kg/ha), haulm yield (39.56 kg/ha) and harvest index (24.07 %) were recorded with T3–30 cm x 10 cm with Poultry manure at 30, 60 and 90 DAS.
 Conclusion: Based on this experiment, it was said that with spacing 30cm x 10cm in combination with poultry manure gives the maximum and significantly higher kernel yield (23.45 kg/ha), gross return Rs.1,72,022.00/ha) as well as highest net return Rs.99,367.00)/ha).

지역별 주택의 시장근본가격(market fundamental price)추정에 관한 실증연구

In this study, the market fundamental price of house price was estimated from August 2001 to April 2022 in based on the present value model and compared with the actual house sale price.
 As a result, First, the pattern of the difference between the actual housing sale price and the market fundamental price of each model was similar in other regions except Incheon, and although it was not exactly the same, it was divided into four periods. Second, The market fundamental price of houses estimated according to the three models showed different volatility by period and region. Third, the estimate of the third model showed less volatility compared to the estimates of other models and closely followed the actual apartment sale price. Fourth, Factors the interest rate and rent growth rate which are factors constituting the market fundamental price had different effects depending on the period.

Misalignments in house prices and economic growth in Europe

ABSTRACT In this paper we investigate house price misalignments and how they affect the real economy. We estimate the long-term relationship between house prices and the fundamentals that determine long-term house prices for a panel of European countries with dynamic OLS, using data from 2005–2018. We find that income has been the main driver of fundamental house prices in all countries, while the supply of dwellings has calmed the rise in house prices in some of them. We calculate house price misalignments, which are deviations of house prices from the fundamental value, and we employ them in the growth model. The results of the growth regression indicate that house price imbalances amplify business cycles in the short term, but in the long term house price overvaluations slow economic growth down. The findings imply that it is crucial to take measures to stabilize housing cycles.

The Paradoxical Prices of Options

The synchronized relationship between financial and fundamental prices has been topical for years now. It seems that option pricing theory has not been used to disentangle that relationship between two prices during merger and acquisition (M&A) activities. This paper uses Put-Call parity theorem to explore the divergence of financial and fundamental prices in any firm during the acquisition process. The results illustrate that price differentials are persistent; moreover, the differentials are caused by the exponential factor. Despite the fact that some principles are drawn from the real estate investment trust (REIT) literature, the results have wider implications for industries with similar traits to REITs.

Fundamental momentum and enhanced fundamental momentum: Evidence from the Chinese stock market

We use fundamental information to select stocks and construct fundamental momentum in this paper. We use LASSO to select eight fundamental variables from 27 fundamental characteristics mentioned in the previous literature. Then, we integrate these 8 variables into a proxy named FIR (fundamental implies return) as the sorting variable of fundamental momentum. Fundamental momentum generates a monthly return of 1.100%, and it outperforms other single factor fundamental strategies. Furthermore, we show that the abnormal returns of fundamental momentum are due to investors’ limited attention. Moreover, we find that fundamental factors and price factors are complementary in forecasting future returns, and combining price reversal and fundamental momentum into enhanced fundamental momentum earns a 2.107% monthly return.

The impact of Brazil on global grain dynamics: A study on cross‐market volatility spillovers

AbstractBrazil's rise as a global powerhouse producer of soybeans and corn over the past 15 years has fundamentally changed global markets in these commodities. Brazil's rise is arguably due to the development of varieties of soybean and corn adapted to climates within Brazil, allowing farmers to double‐crop corn after soybeans in the same year. Corn and soybean market participants increasingly look to Brazil for fundamental price information, and studies have shown that the two markets have become cointegrated. However little is known about how much volatility from each market spills over to the other. In this article, we measure volatility spillover ratios between U.S. and Brazilian first crop corn, second‐crop corn, and soybeans. We find that linkages between the two countries increased after double‐cropping corn after soybeans expanded, volatility spillover magnitudes expanded, and the direction of volatility spillovers flipped from U.S. volatility spilling over to Brazil before double cropping, to Brazil spilling over to U.S. after double cropping.

Market making and electricity price formation in Japan

Market-making, a common trading practice, is often directed by regulators to improve the liquidity in new products, to make their prices more reliable as markers and to encourage new entrants. Establishing its effectiveness is sometimes elusive, however, as market participation and behaviour can be confounded by many special circumstances, especially in energy. We develop an unusual model-based approach in order to establish if a market-making intervention improved the fundamental price formation dynamics. In the context of the Japanese wholesale electricity auction, we develop a dynamic regime switching formulation to account for the distinct effects of buy-side and sell-side volumes on price formation, using temperature as a regime switching driver. The model has a nonlinear functionality that allows it to fit the spiky time series very effectively. The result is clarity that after a market-making intervention in 2017, the buy and sell volumes had more intuitive and distinct effects upon price formation, compared to previously. In addition, temperature information has been more coherently embedded in price and volatility fundamental modelling since the intervention. We argue that the model indicated a more balanced market with buy and sell side regime drivers behaving more consistently with improved market efficiency.

Fundamental Characteristics, Machine Learning and Stock Price Crash Risk

Fundamental Characteristics, Machine Learning and Stock Price Crash Risk