Multi-cycle market emotion temperature metering method and system

Abstract

The invention relates to the technical field of market metering, in particular to a multi-cycle market emotion temperature metering method and system, and the method comprises the steps: S1, collecting the index data of indexes from a financial terminal; s2, preprocessing the collected index data; s3, calculating the processed data to obtain a medium and long term emotion index and a short term emotion index; and S4, obtaining risk and opportunity early warning signals based on the medium and long term emotion index and the short term emotion index. According to the method, market emotion data is acquired and processed through multiple dimensions, new market emotion features are constructed, and two market temperature emotion indexes, namely the medium-and-long-term market emotion index and the short-term market emotion index, are obtained, the medium-and-long-term market emotion index is used for evaluating the medium-and-long-term evaluation level of the market, and the short-term market emotion index is used for evaluating the medium-and-long-term evaluation level of the market. The short-term market emotion index reflects the fear and greedy emotion of the market in a short term, and finally, a risk and opportunity early warning system is designed based on the two indexes so as to provide more comprehensive market analysis and decision support.

Description

Technical Field

[0001] The present invention relates to the field of market measurement technology, and in particular to a multi-period market sentiment temperature measurement method and system. Background Art

[0002] Financial risk monitoring and early warning have become a global research hotspot. The International Monetary Fund monitors global financial risks and provides early warning recommendations by publishing financial stability reports and financial system stability assessments. Financial regulatory agencies such as the European Central Bank, the Federal Reserve, the People's Bank of China and the China Banking Regulatory Commission are also actively exploring effective methods for financial risk monitoring and early warning. Establishing effective financial risk monitoring and early warning methods will help improve the scientificity and effectiveness of financial risk management and enhance the transparency and stability of financial markets, which is of great significance to promoting financial stability. In the prior art, the number of factors for constructing a market sentiment index is limited, and the current mainstream index construction methods are all unsupervised learning methods, lacking clear target variables, so it is difficult to evaluate and measure the accuracy of the index construction method. In view of the above problems, the present invention proposes a multi-period market sentiment temperature measurement method and system to solve the above problems. Summary of the invention

[0003] The purpose of the present invention is to solve the defects mentioned in the above background technology by proposing a multi-period market sentiment temperature measurement method and system.

[0004] The technical solution adopted by the present invention is as follows:

[0005] A multi-period market sentiment temperature measurement method is provided, comprising the following steps:

[0006] S1: Collect index data from financial terminals;

[0007] S2: preprocessing the collected indicator data;

[0008] S3: Calculate the processed data to obtain the medium- and long-term sentiment index and the short-term sentiment index;

[0009] S4: Obtain risk and opportunity warning signals based on medium- and long-term sentiment indexes and short-term sentiment indexes.

[0010] As a preferred technical solution of the present invention: the indicator data includes first indicator data and second indicator data.

[0011] As a preferred technical solution of the present invention: the first indicator data includes price-earnings ratio, price-to-book ratio, dividend yield, risk premium 1, risk premium 2 and the ratio of stock market value to GDP.

[0012] As a preferred technical solution of the present invention: the second indicator data includes price data, option volatility, annualized premium / discount rate, call-put option ratio, stock-bond return spread, northbound funds and leverage level.

[0013] As a preferred technical solution of the present invention: the preprocessing in S2 includes processing duplicate values, processing missing values, processing abnormal values ​​and processing error values.

[0014] As a preferred technical solution of the present invention: the formula for calculating the medium- and long-term sentiment index in S3 is as follows:

[0015]

[0016] Among them, PE is the price-earnings ratio quantile value; PB is the price-to-book ratio quantile value; GDP is the market capitalization to GDP ratio quantile value; DY is the dividend yield quantile value; RP1 is the risk premium 1 quantile value; RP2 is the risk premium 2 quantile value.

[0017] As a preferred technical solution of the present invention: the step of calculating the short-term sentiment index in S3 is as follows:

[0018] Step 1: Perform logarithmic transformation on the index price data and northbound capital data to obtain the logarithmic transformed index price data and northbound capital data;

[0019] Step 2: Use the moving average to calculate the trend items of the above 7 data. The window length of the moving average is 50 days.

[0020] Step 3: Subtract the trend item from the above 7 data, and calculate the quantile values ​​of the remaining 7 data in the first 50 days, and use these quantile values ​​as new indicators;

[0021] Step 4: Calculate the correlation coefficient between the 6 new indicators in step 3 and the detrended index price;

[0022] Step 5: Take the weighted average of the quantile values ​​of the 7 data processed in step 4, and finally get the market short-term sentiment index.

[0023] As a preferred technical solution of the present invention: the specific steps of S4 are as follows:

[0024] S31: First, divide the value range of the medium- and long-term sentiment index and the short-term index;

[0025] S32: Determine the type of warning signal based on the values ​​of the medium- and long-term sentiment index and the short-term index.

[0026] As a preferred technical solution of the present invention: the value range includes high, medium and low, and the warning signal types include red risk warning, yellow risk warning, blue opportunity warning and green opportunity warning.

[0027] Provide a multi-period market sentiment temperature measurement system, including:

[0028] Financial terminal: used to provide data required for market sentiment index;

[0029] Data collection module: used to collect the first indicator data and the second indicator data from the financial terminal;

[0030] Data processing module: used to pre-process the collected data to ensure the accuracy of the data;

[0031] Data calculation module: used to calculate the first indicator data and the second indicator data to obtain the medium- and long-term sentiment index and the short-term sentiment index respectively;

[0032] Early warning module: used to determine the type and level of early warning based on the range of medium- and long-term sentiment index and short-term sentiment index.

[0033] Compared with the prior art, the multi-period market sentiment temperature measurement method and system provided by the present invention have the following beneficial effects:

[0034] The present invention obtains and processes market sentiment data through multiple dimensions to construct new market sentiment features, aiming to obtain two market temperature sentiment indices, namely the medium- and long-term market sentiment index and the short-term market sentiment index. The medium- and long-term market sentiment index is used to evaluate the medium- and long-term valuation level of the market, while the short-term market sentiment index reflects the fear and greed emotions of the market in the short term. Finally, based on these two indices, a risk and opportunity early warning system is designed to provide more comprehensive market analysis and decision support. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 is a flow chart of the method of the present invention;

[0036] Figure 2 It is the overall system block diagram of the present invention.

[0037] The meaning of each mark in the figure is:

[0038] 1. Financial terminal; 2. Data collection module; 3. Data processing module; 4. Data calculation module; 5. Early warning module. DETAILED DESCRIPTION

[0039] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of this embodiment can be combined with each other. The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0040] Reference Figure 1 , an embodiment of the present invention provides a multi-period market sentiment temperature measurement method, comprising the following steps:

[0041] S1: Collect index data from financial terminal 1;

[0042] S2: preprocessing the collected indicator data;

[0043] S3: Calculate the processed data to obtain the medium- and long-term sentiment index and the short-term sentiment index;

[0044] S4: Obtain risk and opportunity warning signals based on medium- and long-term sentiment indexes and short-term sentiment indexes.

[0045] The indicator data includes first indicator data and second indicator data.

[0046] The first indicator data include price-to-earnings ratio, price-to-book ratio, dividend yield, risk premium 1, risk premium 2 and the ratio of stock market capitalization to GDP.

[0047] The second indicator data includes price data, option volatility, annualized premium / discount rate, call-put option ratio, stock-bond return spread, northbound funds and leverage level.

[0048] The preprocessing in S2 includes processing duplicate values, processing missing values, processing abnormal values ​​and processing error values.

[0049] The formula for calculating the medium- and long-term sentiment index in S3 is as follows:

[0050]

[0051] Among them, PE is the price-earnings ratio quantile value; PB is the price-to-book ratio quantile value; GDP is the market capitalization to GDP ratio quantile value; DY is the dividend yield quantile value; RP1 is the risk premium 1 quantile value; RP2 is the risk premium 2 quantile value.

[0052] The steps for calculating the short-term sentiment index in S3 are as follows:

[0053] Step 1: Perform logarithmic transformation on the index price data and northbound capital data to obtain the logarithmic transformed index price data and northbound capital data;

[0054] Step 2: Use the moving average to calculate the trend items of the above 7 data. The window length of the moving average is 50 days.

[0055] Step 3: Subtract the trend item from the above 7 data, and calculate the quantile values ​​of the remaining 7 data in the first 50 days, and use these quantile values ​​as new indicators;

[0056] Step 4: Calculate the correlation coefficient between the 6 new indicators in step 3 and the detrended index price

[0057] Step 5: Take the weighted average of the quantile values ​​of the 7 data processed in step 4, and finally get the market short-term sentiment index.

[0058] The specific steps of S4 are as follows:

[0059] S31: First, divide the value range of the medium- and long-term sentiment index and the short-term index;

[0060] S32: Determine the type of warning signal based on the values ​​of the medium- and long-term sentiment index and the short-term index.

[0061] The value range includes high, medium and low, and the warning signal types include red risk warning, yellow risk warning, blue opportunity warning and green opportunity warning.

[0062] Reference Figure 2 , providing a multi-period market sentiment temperature measurement system, including:

[0063] Financial terminal 1: used to provide data required for market sentiment index;

[0064] Data collection module 2: used to collect first indicator data and second indicator data from financial terminal 1;

[0065] Data processing module 3: used to pre-process the collected data to ensure the accuracy of the data;

[0066] Data calculation module 4: used to calculate the first indicator data and the second indicator data to obtain a medium- and long-term sentiment index and a short-term sentiment index respectively;

[0067] Early warning module 5: used to determine the type and level of early warning according to the range of medium- and long-term sentiment index and short-term sentiment index.

[0068] In this embodiment, it is first necessary to obtain the first indicator data and the second indicator data from the financial terminal 1. The first indicator data includes the price-earnings ratio, price-to-book ratio, dividend yield and risk premium 1 and risk premium 2 of the CSI 300 Index, and the daily data of the market value-to-GDP ratio of the stock market. Among them, the price-earnings ratio is an indicator that measures the stock price relative to earnings per share. Its calculation formula is market price divided by earnings per share. The higher the price-earnings ratio, the higher the market's expectation of the company's future earnings growth, and the stock price is relatively high; the price-to-book ratio is an indicator that measures the stock price relative to net assets per share. Its calculation formula is market price divided by net assets per share. The higher the price-to-book ratio, the higher the market's valuation of the company's net assets, and the stock price is relatively high; the dividend yield is an indicator that measures the dividend yield relative to the stock price. Its calculation formula is dividend per share divided by stock price. The higher the dividend yield, the higher the dividend yield; the definition of risk premium 1 is the inverse of the index price-earnings ratio minus the yield of China's 10-year treasury bonds; the definition of risk premium 2 is the inverse of the index price-earnings ratio minus the yield of the US 10-year treasury bonds; the definition of the market value of the stock market to GDP is the ratio of the market value of the Chinese stock market to China's gross domestic product (GDP). Then, we calculated the quantile values ​​of the price-earnings ratio, price-to-book ratio, dividend yield, risk premium 1 and risk premium 2, and the market value of the stock market to GDP ratio over the past 10 years. Among them, the higher the percentile values ​​of the price-to-earnings ratio, price-to-book ratio, and the proportion of stock market capitalization to GDP, the higher the valuation of the CSI 300 Index; the higher the percentile values ​​of the dividend yield and risk premium, the lower the valuation of the CSI 300 Index.

[0069] The second indicator data includes the price data of the CSI 300 Index, the option volatility of the CSI 300 Index, the annualized premium / discount rate, the call-put option ratio, the stock-bond return difference, and the northbound funds and leverage level. Among them, the option volatility is a measure of the market's expectation of the price fluctuation of the underlying asset. It is a key parameter in the option pricing model and is used to calculate the theoretical price of the option. According to the price of buying and selling options in the option market, the market's expectation of the volatility of the underlying asset can be inferred; northbound funds refer to the funds invested by overseas investors in the Shanghai and Shenzhen stock markets through the interconnection mechanism with the Hong Kong Stock Exchange and the Shanghai Stock Exchange. The inflow of northbound funds refers to the funds that foreign investors buy into the Shanghai and Shenzhen stock markets, and the outflow refers to the funds that foreign investors sell into the Shanghai and Shenzhen stock markets; the premium rate refers to the percentage difference between the index futures price and the index spot price in the stock market. The premium means that the futures price is higher than the spot price, and the discount means that the futures price is lower than the spot price. The premium rate is an indicator of market liquidity and investment sentiment. The calculation formula of the premium rate is the index futures price minus the index spot price and then divided by the index spot price; the stock-bond return spread refers to the difference between the yields of stocks and bonds. The stock yield represents the investment return of the stock market, and the bond yield represents the investment return of the bond market. The stock-bond return spread is an indicator of market risk preference and capital flow; the leverage level refers to the proportion of market participants using borrowed funds for investment. When the leverage level is high, investors may bear higher risks, but they may also get higher returns. The leverage level is an indicator of market risk and market participant confidence; the call-put ratio refers to the ratio between the number of call option contracts and the number of put option contracts in the market. It is an indicator of market investors' expected sentiment towards the future trend of the underlying asset. When the number of call option contracts is large, the market expects the price of the underlying asset to rise; when the number of put option contracts is large, the market expects the price of the underlying asset to fall.

[0070] Furthermore, in order to ensure the accuracy of the data, it is necessary to pre-process the data, process duplicate values, missing values, abnormal values ​​and error values, and then calculate the medium- and long-term sentiment index and short-term sentiment index of the market. The formula for calculating the medium- and long-term sentiment index is as follows:

[0071]

[0072] Among them, PE is the price-earnings ratio quantile value; PB is the price-to-book ratio quantile value; GDP is the market capitalization to GDP ratio quantile value; DY is the dividend yield quantile value; RP1 is the risk premium 1 quantile value; RP2 is the risk premium 2 quantile value.

[0073] The steps to calculate the short-term sentiment index are as follows:

[0074] Step 1: Perform logarithmic transformation on the price data of the CSI 300 Index and the northbound capital data to obtain the logarithmic transformed price data of the CSI 300 Index and the northbound capital data for use in subsequent steps 2 and 3.

[0075] Step 2: Use the moving average to calculate the trend items of the above 7 data (1 price data and 6 indicator data), and the window length of the moving average is 50 days.

[0076] Step 3: Subtract the trend item from the above 7 data, and calculate the quantile values ​​of the remaining 7 data in the first 50 days. These quantile values ​​will be used as new indicators for subsequent steps 4 and 5.

[0077] Step 4: Calculate the correlation coefficients between the six new indicators in step 3 and the detrended CSI 300 index price. If the correlation coefficient of an indicator is negative, change the quantile value in step 3 to (100-original quantile value) and change the sign of the correlation coefficient to positive.

[0078] Step 5: Take the weighted average of the quantile values ​​of the 7 data processed in step 4, and finally get the market short-term sentiment index. Among them, the weight of the CSI 300 Index price is 1, and the weight coefficients of other indicators are the absolute values ​​of the correlation coefficients in step 4.

[0079] Finally, the value ranges of the medium- and long-term sentiment index and the short-term index are divided first, and the warning signal type is determined according to the values ​​of the medium- and long-term sentiment index and the short-term index. The value range includes high, medium and low, and the warning signal types include red risk warning, yellow risk warning, blue opportunity warning and green opportunity warning. Among them, the value range of the medium- and long-term sentiment index and the short-term sentiment index is 0-100 points. When the medium- and long-term sentiment index and the short-term sentiment index are both greater than 75 points, the red risk warning signal will be triggered, indicating that the risk is extremely high, and it is recommended to significantly reduce the investment proportion of equity assets; when the medium- and long-term sentiment index and the short-term sentiment index are both less than 25 points, the green opportunity warning signal will be triggered, indicating that the opportunity is huge, and it is recommended to significantly increase the investment proportion of equity assets; when the medium- and long-term sentiment index is within the range of 25-75 points, and the short-term sentiment index is greater than 75 points, the yellow risk warning signal will be triggered, indicating that the short-term risk is high, and it is recommended to appropriately reduce the investment proportion of equity assets; when the medium- and long-term sentiment index is within the range of 25-75 points, and the short-term sentiment index is less than 25 points, the blue opportunity warning signal will be triggered, indicating that the short-term opportunity is large, and the investment proportion of equity assets can be appropriately increased. Based on the multi-period market sentiment index, a market risk and opportunity early warning system is built to better monitor financial market indices to provide more comprehensive market analysis and decision support.

[0080] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

[0081] In addition, it should be understood that although the present specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

Claims

1. A multi-period market sentiment temperature measurement method, characterized by: The steps include: S1: Collect index data from the financial terminal (1); S2: preprocessing the collected indicator data; S3: Calculate the processed data to obtain the medium- and long-term sentiment index and the short-term sentiment index; S4: Obtain risk and opportunity warning signals based on medium- and long-term sentiment indexes and short-term sentiment indexes.

2. The multi-period market sentiment temperature measurement method according to claim 1 is characterized by: The indicator data includes first indicator data and second indicator data.

3. The multi-period market sentiment temperature measurement method according to claim 2 is characterized by: The first indicator data include price-to-earnings ratio, price-to-book ratio, dividend yield, risk premium 1, risk premium 2 and the ratio of stock market capitalization to GDP.

4. The multi-period market sentiment temperature measurement method according to claim 2 is characterized by: The second indicator data includes price data, option volatility, annualized premium / discount rate, call-put option ratio, stock-bond return spread, northbound funds and leverage level.

5. The multi-period market sentiment temperature measurement method according to claim 4 is characterized by: The preprocessing in S2 includes processing duplicate values, processing missing values, processing abnormal values ​​and processing error values.

6. The multi-period market sentiment temperature measurement method according to claim 4, characterized in that: The formula for calculating the medium- and long-term sentiment index in S3 is as follows: Among them, PE is the price-earnings ratio quantile value; PB is the price-to-book ratio quantile value; GDP is the market capitalization to GDP ratio quantile value; DY is the dividend yield quantile value; RP1 is the risk premium 1 quantile value; RP2 is the risk premium 2 quantile value.

7. The multi-period market sentiment temperature measurement method according to claim 5, characterized in that: The steps for calculating the short-term sentiment index in S3 are as follows: Step 1: Perform logarithmic transformation on the index price data and northbound capital data to obtain the logarithmic transformed index price data and northbound capital data; Step 2: Use the moving average to calculate the trend items of the above 7 data. The window length of the moving average is 50 days. Step 3: Subtract the trend item from the above 7 data, and calculate the quantile values ​​of the remaining 7 data in the first 50 days, and use these quantile values ​​as new indicators; Step 4: Calculate the correlation coefficient between the 6 new indicators in step 3 and the detrended index price; Step 5: Take the weighted average of the quantile values ​​of the 7 data processed in step 4, and finally get the market short-term sentiment index.

8. The multi-period market sentiment temperature measurement method according to claim 1, characterized in that: The specific steps of S4 are as follows: S31: First, divide the value range of the medium- and long-term sentiment index and the short-term index; S32: Determine the type of warning signal based on the values ​​of the medium- and long-term sentiment index and the short-term index.

9. The multi-period market sentiment temperature measurement method according to claim 8, characterized in that: The value range includes high, medium and low, and the warning signal types include red risk warning, yellow risk warning, blue opportunity warning and green opportunity warning.

10. A multi-period market sentiment temperature measurement system, based on a multi-period market sentiment temperature measurement method according to claims 1-9, characterized in that: include: Financial terminal (1): used to provide data required for market sentiment index; A data collection module (2): used for collecting first indicator data and second indicator data from the financial terminal (1); Data processing module (3): used to pre-process the collected data to ensure the accuracy of the data; Data calculation module (4): used to calculate the first indicator data and the second indicator data to obtain a medium- and long-term sentiment index and a short-term sentiment index respectively; Early warning module (5): used to determine the type and level of early warning according to the range of the medium- and long-term sentiment index and the short-term sentiment index.

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