Yuan Exchange Research Articles

Thai Baht and Chinese Yuan Exchange Rate Forecasting Models: ARIMA and SMA-ARIMA Comparison

This study evaluates the effectiveness of classical Autoregressive Integrated Moving Average (ARIMA) models and kth Simple Moving Average - ARIMA (kth SMA-ARIMA) models in forecasting the exchange rate between the Thai Baht (THB) and the Chinese Yuan (CNY). The analysis uses a dataset of historical monthly exchange rates from January 2011 to November 2022, covering 143 months. The dataset is divided into two segments: the initial 127 months are used as the training dataset for model development, while the subsequent 16 months serve as the testing dataset to evaluate forecast accuracy. The Akaike Information Criterion (AIC) is the decision criterion for model selection during the development phase. The forecasting models' effectiveness is subsequently assessed on the testing dataset using two statistical measures: the Mean Absolute Percentage Error (MAPE) and the Root Mean Square Error (RMSE). The findings indicate that the classical ARIMA (0,1,1) model outperforms the kth SMA-ARIMA models in this study, exhibiting the lowest RMSE and MAPE of 0.1702 and 2.6644, respectively. Additionally, a focused comparison of the kth SMA-ARIMA models for k = 2, 3, and 4 reveals that the 2nd SMA-ARIMA (0,1,2) model demonstrates superior performance compared to the 3rd and 4th SMA-ARIMA models. This superiority is reflected in their respective RMSE values of 0.3202, 0.5146, and 0.6339, and corresponding MAPE values of 5.3533, 8.7531, and 10.4949. These results provide valuable insights for decision-makers in the financial sector, enhancing investment strategy formulation based on anticipated currency movements.

A Study on the Exchange Rate Linkage between Korea and China following the Reform of the Yuan Exchange Rate System

Purpose - This study aims to conduct an empirical analysis of exchange rate volatility and dynamic correlation between Korea and China based on the “8.11” central exchange rate reform in China. Unlike other developed countries’ foreign exchange markets, the Chinese Yuan has not yet achieved complete free circulation, and China has an onshore Yuan exchange rate (CNY) and an offshore Yuan exchange rate (CNH). In this study, we investigated the dynamic correlation between Korea’s won exchange rate and China’s onshore yuan exchange rate and offshore yuan exchange rate around the “8.11” central exchange rate reform in China. Design/Methodology – In this study, we attempted to analyze the average and the volatility spillover effect of the won exchange rate from China’s onshore and offshore yuan exchange rate before and after the 8.11 central parity exchange rate reform. In addition, the relation between the won exchange rate and on- and off-shore yuan exchange rate at various stages were analyzed through the VAR model and the VAR-BEKK-GARCH model. Findings – The results of analyzing the volatility spillovers between the KRW exchange rate and the offshore RMB exchange rate show that there are two-way volatility spillovers between the two markets, both before and after the “8.11” central parity rate reform. The dynamic correlation between the two exchange rates (CNY and KRW, CNH and KRW) is increasing over time. In addition, the two exchange rates are positively correlated with each other, implying that the volatility of the two exchange rate markets is moving in the same direction. The dynamic dependence relations between CNY and KRW become significantly higher after the “8.11” central parity rate reform. Originality/value - As a non-international currency, the won must engage in export trade and capital market transactions with other international reserve currency countries. Therefore, it is important for Korean export-import companies and investors to explore changes in the dynamic correlation between the won and the Chinese yuan through exploration.

Prediction of Changes in the Exchange Rate between the USD and the CNY and Analysis of Influencing Factors

As one of the important indicators of the global financial market, the fluctuation of the US dollar to Chinese yuan exchange rate not only directly affects the economic development of China and the United States, but also has important significance for analyzing the global economic situation. Analyzing the factors influencing the exchange rate between the United States dollar (USD) and the Chinese yuan (CNY) is one of the key research topics today. Researchers have found that exchange rates are influenced by factors such as national policies and the global political situation. However, there is still a certain gap in the comprehensive and objective analysis of these influencing factors. Therefore, the research topic of this article is to predict the trend of the exchange rate between the USD and the CNY and analyze the influencing factors. This study collected exchange rate data from January 2000 to November 2023 and used the ARIMA model to predict exchange rate changes. This study explores the trend of exchange rate changes by visualizing these data. Research has found that significant changes in exchange rates over the past two decades have also occurred during times of global instability and policy adjustments. The economic development level of China and the United States also directly affects the changes in exchange rates. In addition, the model used in this study also predicted the exchange rate between the USD and the CNY in 2024, providing a scientific direction for predicting the economic development trend in 2024.

A hybrid causal machine learning to reveal driving factors responsible coal market: Case of the Chinese industry

To achieve carbon neutrality, China must grasp the intricate factors driving coal market, as it addresses coal consumption and reduces the carbon footprint. While previous studies have identified certain factors, they have largely overlooked the impact of the overall industry sector on the coal market. In this paper, a hybrid causal machine learning model was proposed that combine with least absolute shrinkage and selection operator (LASSO), multiple linear regression (MLR), peter and clark momentary conditional independence (PCMCI) and interpretable machine learning. The approach employed a complex network perspective to identify 10 key factors in China's coal market from three dimensions: industrial sector, foreign trade and energy market. The hierarchical pattern of these factors is classified into two levels: direct factors, primarily encompassing crude oil futures, exchange rates and architectural decoration, and intermediary factors, mainly including the chemical industry and building material. Interestingly, this paper reaffirms the roles of crude oil futures and exchange rates in the coal market, as identified in prior studies. Additionally, it uncovers new influential factors primarily driven by the chemical industry and architectural decoration, previously unexplored. Furthermore, this paper found a significant contemporaneous relationship between crude oil futures and coal price index (0.151) as well as coal consumption (0.102), and the strong relationship between coal consumption and the Indonesian Rupiah to Chinese Yuan exchange rate (0.063) was also confirmed. Among the emerging dominant factors, the coal price index and the chemical industry (0.145), along with coal consumption and building materials (0.250), also exhibit a strong contemporaneous relationship. These findings highlight the importance of considering the entire industry sector while analyzing the coal market and promoting a cleaner transformation of the industry in China, and the paradigm presented not only applicable to the coal market, but can be extended to other industries.

The Effect of Yuan Exchange Rate to Islamic Banking Credit Risk in Asia Case Study of Indonesia

This study aims to analyze the effect of the yuan exchange rate on non- performing financing in Islamic banking for the period March 2012 to February 2022. The type of data used in this study is quantitative data and the source of data used in this study is secondary data obtained from the official website of the Authority. Financial Services (OJK) and Bank Indonesia (BI) . The data analysis model in this study uses multinomial logit regression analysis, where multinomial logistic regression is a logistic regression used when the dependent variable has a polychotomous or multinomial scale. The results of the analysis show that the yuan exchangeAuthor I ArticleTitle rate has a positive and insignificant effect on non-performing financing of Islamic banking when the NPF ratio is in a Medium Risk condition. In High Risk the yuan exchange rate has a positive and significant effect on non- performing financing of Islamic banking and when in Very High Risk conditions, the yuan exchange rate has a positive and insignificant effect on non-performing financing of Islamic banking. The Pseudo R-Square value is 0.1057 which means that the value of the variation of the dependent variable that can be explained by the independent variable is 10.57% while the remaining 89.43% is explained by other variables.

Chinese yuan interest rate swap yields.

This paper models the dynamics of Chinese yuan-denominated long-term interest rate swap yields. It shows that the short-term interest rate exerts a decisive influence on the long-term swap yield after controlling for various macrofinancial variables, such as core inflation, the growth of industrial production, the percent change in the equity price index, and the percentage change in the Chinese yuan exchange rate. The autoregressive distributed lag approach is applied to model the dynamics of the long-term swap yield. The findings reinforce and extend John Maynard Keynes's conjecture that in advanced countries, as well as emerging market economies such as China, the central bank's actions have a decisive role in setting the long-term interest rate on government bonds and over-the-counter financial instruments, such as swaps.

Volatility, Volume, and FX Policy Uncertainty: Evidence from Seoul and Shanghai Chinese-Korean Direct Exchange Rate Market

Purpose – This paper empirically analyzed the effect of the FX policy uncertainty (FX EPU) of Korea and the trading volume in the direct Korean won/Chinese yuan (KRW-RMB) exchange market agreed on in June 2014 on the volatility of the won/yuan exchange rate. Design/Methodology/Approach – In this paper, we first collected monthly data on the trading volume in the direct Korean won/Chinese yuan (KRW-RMB) exchange market from July 2016 to March 2021. We adopted the linear autoregressive distributed lag (ARDL) approach proposed by Pesaran et al. (2001) to study the impact of the FX EPU of Korea and the trading volume on the volatility of the won/yuan exchange rate. This paper uses direct Korean won/Chinese yuan (KRW-RMB) exchange market data for the first time. Findings – The main findings are as follows. First, the empirical results suggest that an increase in trading volume decreases short-run exchange rate volatility, while an increase in FX EPU increases short-run exchange rate volatility. Second, we also find that the long-run effects of trading volume are negative, while the effects of FX EPU are not. Third, the effects on volatility of trading volume and FX EPU are negative or positive in both simultaneous and dynamic relationships, which is consistent with the mixture distribution hypothesis. Research Implications – The estimation result of the ARDL model shows the long- and short-run effects of volume and FX EPU on volatility. We provide new empirical evidence for the way in which financial markets process information.

Market-Oriented Reform of the Yuan Exchange Rate: Organizational and Analytical Aspects

The article traces the evolution of the market-oriented reform of the exchange rate of the yuan, the national currency of the People's Republic of China. The purpose of the study is to reveal the consistently implemented reform aimed at domestic economic growth on the internationalization of the yuan exchange rate. A hypothesis was formulated according to which, in the conditions of an export-oriented economy, the internationalization of the exchange rate of the national currency without opening financial accounts of the balance of payments is able to remove the limits of economic growth, and thereby allows an adequate response to external and internal negative challenges (global economic crises, pandemic, sanctions, etc.). To test the hypothesis: 1) the specific practical measures are traced that were taken by the People's Bank of China to internationalize the yuan as a tool for attracting external resources for the growth of an export-oriented economy from 1994 to the present; 2) methods of statistical, comparative and step-by-step regression analysis, synthesis, generalization, as well as the logical method were used. The results of the study confirmed the correctness of the formulated hypothesis. Based on them, it is concluded that improving the market-oriented reform of the yuan exchange rate without opening financial accounts of the balance of payments may consist in creating a hidden target zone of the yuan exchange rate together with the reform of the currency system and the mechanism of currency issuance under the influence of the yuan equivalent of foreign exchange reserves. The theoretical significance of the results obtained consists in substantiating the variety of ways of internationalization of the national currency in relatively undeveloped domestic financial markets. The practical significance is connected with the generalization of current measures for further internationalization of the yuan without opening financial accounts of the balance of payments: the abolition of the average parity and the daily floating limit of 2%; the establishment of a hidden target zone for the yuan exchange rate based on the equilibrium exchange rate; the creation of exchange rate equalization funds for operations on the open market; optimization of the structure of reserve assets and increase shares of gold reserves.

PENGARUH NET EKSPOR, KURS YUAN, DAN NET FDI TIONGKOK TERHADAP PEREKONOMIAN INDONESIA

Indonesia is one of the developing countries in the world that is experiencing quite good economic growth. However, the Indonesian economy is not always in a stable condition, from 1997 to 2014 Indonesia has experienced two crises, namely the Asian financial crisis (1997-1999) and the global crisis (2007-2008) which was marked by the emergence of disturbances in macroeconomic indicators. The objectives of this study are (1) to analyze the effect of China's Net Exports, Yuan Exchange Rate, and Net FDI simultaneously on the Indonesian Economy and (2) to analyze the effect of China's Net Exports, Yuan Exchange Rate, and Net FDI partially on the Indonesian Economy. This study observes data over a period of nineteen years (2000 to 2018), the data observed is per semester, so that the total amount of data observed is 38 (thirty eight) data. The analysis technique used in this research is multiple linear regression. The results of this study are (1) Net exports, the yuan exchange rate, and China's net FDI simultaneously have a significant effect on the Indonesian economy and (2) partially Net exports do not have a positive and significant effect on the Indonesian economy while the Chinese yuan exchange rate and Net FDI have an effect. positive and significant impact on the Indonesian economy.
 Keywords: Indonesian Economy, Net Exports, Yuan Exchange Rate, China's Net FDI

Uncertain hypothesis test for uncertain differential equations

Uncertain hypothesis test is a statistical tool that uses uncertainty theory to determine whether some hypotheses are correct or not based on observed data. As an application of uncertain hypothesis test, this paper proposes a method to test whether an uncertain differential equation fits the observed data or not. In order to demonstrate the test method, some numerical examples are provided. Finally, both uncertain currency model and stochastic currency model are used to model US Dollar to Chinese Yuan (USD–CNY) exchange rates. As a result, it is shown that the uncertain currency model fits the exchange rates well, but the stochastic currency model does not.

The influence of world oil prices on the Chinese Yuan exchange rate

The influence of world oil prices on the Chinese Yuan exchange rate

Analysis of Determinants of Stock Transaction Volume and its Effect on the IDX Composite in IDX 2010-2020 Period

This study analyzes the impact of cash supply, dollar exchange rate, yuan exchange rate, Shanghai composite index (SSE composite index) on the IDX composite with transaction volume as a mediating variable (Case Study on Companies Listed on the Indonesia Stock Exchange in 2010 - 2020). The review was led utilizing 121 examples comprising of month to month information for all factors from 2010 to 2020. The information handling strategy utilized various straight relapse investigation procedures. The outcomes showed that to some extent cash supply, dollar exchange rate, SSE composite index had a critical constructive outcome on the IDX composite. To some degree, just the yuan exchange rate has no huge impact on the IDX composite. At the same time, cash supply, dollar exchange rate, yuan exchange rate and the SSE composite index simultaneously affected the IDX composite. The cash supply and the SSE composite index record have a critical constructive outcome on transaction volume. To some extent, exchange rate and yuan exchange rate have no critical impact on transaction volume. The cash supply, exchange rate, yuan exchange rate and SSE composite index simultaneously significantly affect on transaction volume. Simultaneously, cash supply, exchange rate, yuan exchange rate and SSE composite index significantly affect the IDX composite with exchange volume as an interceding variable.

Purchasing Power Parity Approach to Exchange Rate Misalignment in Nigeria

This study examines the purchasing power parity (PPP) approach to the determination of exchange rate misalignment in Nigeria by using two variants of the PPP: the absolute PPP (aPPP) and the relative PPP (rPPP). Data on the Nigerian Naira to US Dollar ( N/$), British Pound ( N/£) and Chinese Yuan (N /¥) interbank exchange rates, Nigeria consumer price index and Inflation as well as the US, UK and China consumer price indices and inflation rates spanning 2008:M1 to 2018:M12 were utilized. A recently modified fractional cointegration framework was employed, taking care of smooth structural breaks and nonlinearity, while the unit root tests employed the fractional alternatives. The results confirmed that the aPPP approach to exchange rate determination is unrealistic but revealed empirical support for the rPPP approach. Furthermore, the exchange rates computed with the rPPP approach show that the interbank Naira to US Dollar, UK Pounds and Chinese Yuan exchange rates were overvalued in most of the period of this study. The period of undervaluation observed in June 2016 and April 2017 coincided with the periods when CBN introduced the investors and exporters window. The study recommends the use of rPPP for gauging the level of exchange rate misalignment in Nigeria and suggests the need to diversify the export base to appreciate the exchange rate.

On resolving exchange rate exposure puzzle: evidence from Chinese stock market

PurposeIt has been increasingly recognized that exchange rate changes affect the cash flow and the value of firms. Existing studies on exchange rate exposure do not have much success in finding significant exposure, and the failure to find this relationship empirically has been termed “exposure puzzle”. Motivated by the limited success in detecting significant exchange rate exposure in the extant literature, China's exchange rate regime reform in 2005, the increasing role of China's stock market played in the global financial market and its attractiveness in international portfolio diversification, the purpose of this paper is to resolve the so-called “exposure puzzle” and thus make a contribution to the literature by investigating whether the renminbi (RMB) exchange rate movements have any significant impact on China's stock market from the perspective of US investors who may want to diversify their portfolios with Chinese stocks.Design/methodology/approachSince previous studies which rely heavily on the standard Ordinary Least Squares (OLS) or seemingly unrelated regression (SUR) method of estimation with the assumption of constant variance of firm's or industry's returns do not have much success in detecting significant exchange rate exposure, in this study, we apply an asymmetric GARCH(1,1) with generalized error distribution (GED) model which takes conditional heteroscedasticity and leptokurtosis of asset returns into account in the estimation of first- and second-moment exchange rate exposure.FindingsUsing weekly data over the period August 10, 2005–January 1, 2020 on 40 Chinese sector stock returns, the authors find strong evidence of first-moment exchange rate exposure. In particular, 65% (26 out of 40) of sectors examined have significant first-moment exposures and 73.08% (19 out of 26) of these significant first-moment exposures are asymmetric. For the second-moment exchange rate exposures, they are less frequently detected with 20% (8 out of 40) significant cases. These results are robust to whether an unorthogonalized or orthogonalized bilateral US dollar (USD)/Chinese Yuan (CNY) exchange rate is used in the estimation.Research limitations/implicationsBecause this study concerns only with whether exchange rate movements affect ex post returns as opposed to expected (ex ante) returns, and given the significant exposures with respect to different risk factors found in the study, it is interesting to see if any of these risk factors commands a risk premium. In other words, a natural extension of this study is to test whether any of these risk factors is priced in China's stock market.Practical implicationsThe findings of the study have interesting implications for US investors who would like to diversify their portfolios with Chinese stocks and are concerned about whether the unexpected movements in CNY will affect their portfolio returns in addition to its local and world market risk exposures.Originality/valueThe study extends previous research on the first- and second-moment exchange rate exposure of Chinese stock returns by utilizing an asymmetric GARCH(1,1) with generalized error distribution (GED) model, which has not been fully exploited in the literature.

The Effect of Share Transaction Determinants and its Impact on JCI on IDX 2010-2020

The purpose of this study was to determine the effect of inflation, the dollar exchange rate, the yuan exchange rate and the Chinese index partially and simultaneously on the JCI. To determine the effect of inflation, the dollar exchange rate, the yuan exchange rate and the Chinese index partially and simultaneously on the volume of transactions. To determine the effect of inflation, the dollar exchange rate, the yuan exchange rate and the Chinese index on the JCI with transaction volume as an intervening variable. The results of the JCI data analysis show that the dollar exchange rate, inflation and the Chinese index have an effect on the JCI and the yuan exchange rate does not affect the JCI, but simultaneously inflation, dollar exchange rate, yuan exchange rate and the Chinese index have an effect on the JCI. The results of the transaction volume data analysis show that the dollar exchange rate, the yuan exchange rate and the Chinese index have an effect on the volume of transactions, while inflation has no effect on the volume of transactions. Simultaneously, inflation, dollar exchange rate, yuan exchange rate and Chinese index have an effect on transaction volume. The results of the transaction volume data analysis as an intervening variable indicate an influence.

Analysis of Determinants of Stock Transaction Volume and Its Effect on the LQ45 Stock Price Index on IDX 2010-2020 Period

The LQ45 stock index is a stock index that concerns investors in monitoring the development of company performance that is included in the LQ45 index calculation. Several factors that can cause the movement of the LQ45 stock index include BI interest rates, exchange rates, and global stock exchanges such as the Shanghai Composite Index. The study was conducted to determine the effect of the BI interest rate, dollar exchange rate, yuan exchange rate and the Shanghai Composite Index (SSE) on the LQ45 stock index. The study was conducted using 121 samples consisting of monthly data for all variables from 2010 to 2020. Data analysis was performed using multiple linear regression analysis techniques. The results show the BI interest rate, dollar exchange rate, yuan exchange rate and Shanghai Composite index simultaneously have a significant effect on the LQ45 stock index. BI interest rate and yuan exchange rate partially have a significant effect on the LQ45 stock index. The dollar exchange rate and Shanghai Composite index have no significant effect on the LQ45 stock index. The BI interest rate, dollar exchange rate, yuan exchange rate and Shanghai Composite index simultaneously affect volume of transactions. Partially, BI interest rate, dollar exchange rate, yuan exchange rate have a significant effect on transaction volume, while Shanghai Composite index has no significant effect on transaction volume. Simultaneously, BI interest rate, dollar exchange rate, yuan exchange rate, and Shanghai Composite index have a significant effect on the LQ45 stock index with transaction volume as an intervening variable.

The South Korea–China trade and the bilateral real exchange rate: Asymmetric evidence from 33 industries

The present article contributes to the existing literature by applying the NARDL approach of Shin et al. (2014) to investigate the asymmetric impacts of exchange rates on the bilateral exports and imports of 33 industries between South Korea and China. We demonstrate that there is evidence that fluctuations of the real South Korean won (KRW) to Chinese yuan (CNY) exchange rate have asymmetric impacts on some, though not all, types of South Korea’s exporting and importing industries in both the long- and short-run. Additionally, the asymmetric impacts appear to be an industrial-specific phenomenon.

Hierarchical Axiomatic Fuzzy Set Granulation for Financial Time Series Clustering

Financial time series are generally high-dimensional, nonstationary, and exhibit heteroscedasticity. To derive a suitable way to cluster financial time series, these characteristics have to be taken into consideration. With this aim, in this article, the financial time series is firstly modeled using generalized autoregressive conditional heteroscedasticity (GARCH) models, where the parameters of GARCH models can represent the dynamic feature of the volatility in each time series. Therefore, the following clustering is realized based on the GARCH model parameters, which can help reduce the dimensionality of the original time series at the same time. Then, to produce semantically sound clustering results, we granulate the parameters based on the axiomatic fuzzy set (AFS) theory and structure them into a collection of meaningful and semantically sound entities, i.e., AFS information granules. Furthermore, the hierarchical structure of AFS information granules is built to realize time series clustering under the framework of granular computing. In the proposed approach, the characteristics of financial time series is fully considered to proceed dimensionality reduction, and the semantic clustering results obtained for different numbers of clusters are guaranteed to be the most informative. In the experiments, an application for clustering the time series coming from Chinese Yuan exchange rates against international currencies is presented to demonstrate the performance of the proposed clustering method. The results of clustering of the proposed method are the same as those of the fuzzy C-means algorithm and the hierarchical clustering with ward linkage, where the clustering results produced by the AFS hierarchical clustering exhibit well-articulated semantics at each level of the hierarchy.

A Prediction Model of CNN-TLSTM for USD/CNY Exchange Rate Prediction

The Exchange rate affects the economic development of various countries. To grasp the information of the changeable exchange rate in time, it is necessary to predict the exchange rate price. This paper proposes the CNN-TLSTM model to predict the United States Dollar/Chinese yuan (USD/CNY) exchange rate closing price of the next trading day. The model consists of two parts, namely convolutional neural networks(CNN)and tanh long short-term memory (TLSTM). The function of CNN is to extract feature factors from the input data. TLSTM is used to receive the output data of CNN for prediction, and finally obtain the prediction result. TLSTM is a new model proposed in this paper to improve the internal structure of the long short-term memory (LSTM). Its advantage is to change the range of the output value of the input gate, retain more data features, and prevent the output value of the input gate in LSTM from being overfitting. This paper selects the exchange rate of USD/CNY data and some stock data for each trading day from January 2, 2006, to October 30, 2020, as the experimental data. To prove the effectiveness of the CNN-TLSTM prediction model, the model is compared with multilayer perceptron (MLP), CNN, recurrent neural network (RNN), LSTM, and CNN-LSTM models. mean absolute percentage error (MAPE), mean square error (MSE), and R-squared (R2) are used for comparative analysis. The experimental results show that the CNN-TLSTM model has the best predictive effect on the USD/CNY exchange rate closing price of the next trading day.

КИТАЙСКИЙ ФАКТОР В РАЗВИТИИ СЕЛЬСКОГО ХОЗЯЙСТВА ПРИГРАНИЧНОГО РЕГИОНА ДАЛЬНЕГО ВОСТОКА РОССИИ: ИТОГИ 2000-2020 ГГ.

Attracting foreign capital entails the use of foreign labor. External labor resources have been one of the factors in the development of agriculture in the Far Eastern regions over the past 20 years. Attraction of foreign labor and investment in the agriculture of the regions has ambiguous consequences for the development of these regions. The current situation in the spring of 2020, associated with the closure of the borders of the Russian Federation, revealed the role of the Chinese factor for the regions of the Russian Far East. The peculiarities of attracting Chinese workers to the agriculture of the Russian regions are well traced in the example of the Jewish Autonomous Region, which is located on the border with Heilongjiang Province (PRC). The peculiarities of the region's geographical location influenced the formation of stable Russian-Chinese relations in agriculture. The paper examines the processes of Russian-Chinese interaction in agriculture on the example of the Jewish Autonomous Region. The change in the role of Chinese citizens in the development of agriculture and rural areas of the border region of the Russian Far East is shown. Two periods of Russian-Chinese interaction in agriculture of the Jewish Autonomous Region are highlighted and characterized. The first period (early 2000s - late 2000s) is characterized by a decrease in the area of arable land in the region, attracting cheaper Chinese migrants by local and Chinese agricultural producers. The second period of 2010-2020, this time, a system of lending to local farmers by Chinese partners for the future harvest, an increase in the area of arable land, an increase in the yuan exchange rate led to a higher level of wages of Chinese workers. Chinese farmers are hiring local people. It is concluded that the peculiarity of the development of agriculture with the participation of the Chinese factor in the Russian Far East is that the Chinese were present and are present as investors, producers, workers, and farmers. In addition, most of the soybeans produced in the region are exported to China.