J urnal M anajemen (E disi E lektronik )

Volatility is the fluctuation of returns in a certain period, if the fluctuations in returns have a large variation, then the possibility of a risk that will occur is greater, and vice versa if the fluctuation of risk is smaller, the probability that the risk that will occur will be smaller. Analysis of stock price volatility from stock indexes is needed to facilitate investors in making investment decisions. This study aims to provide an overview of the volatility of securities owned by investors towards shares owned in the LQ45 stock index group which have the potential to receive expected returns or have risk potential. Also knowing how much value can be generated from profits and how much risk will be borne by investors. This study uses descriptive comparative and quantitative research methods using secondary data, and the model used to assess stock volatility is the Baskin method (1989). Based on the research results, there is a difference in the volatility of the stock prices of companies that enter and leave LQ45 for the period 1 February – 31 July 2022. The scope of the research is only companies that enter and leave LQ45 for the period 1 February to 31 July 2022, so the number of samples used is limited and the research results cannot be generalized, and. The model used to assess stock volatility is the Baskin method (1989). Novelty is the uniqueness of the research is volatility of stocks leaving LQ 45 during February-July 2022 Keywords: Stock volatility; LQ 45; investors


A B S T R A C T
Volatility is the fluctuation of returns in a certain period, if the fluctuations in returns have a large variation, then the possibility of a risk that will occur is greater, and vice versa if the fluctuation of risk is smaller, the probability that the risk that will occur will be smaller. Analysis of stock price volatility from stock indexes is needed to facilitate investors in making investment decisions. This study aims to provide an overview of the volatility of securities owned by investors towards shares owned in the LQ45 stock index group which have the potential to receive expected returns or have risk potential. Also knowing how much value can be generated from profits and how much risk will be borne by investors. This study uses descriptive comparative and quantitative research methods using secondary data, and the model used to assess stock volatility is the Baskin method (1989). Based on the research results, there is a difference in the volatility of the stock prices of companies that enter and leave LQ45 for the period 1 February -31 July 2022. The scope of the research is only companies that enter and leave LQ45 for the period 1 February to 31 July 2022, so the number of samples used is limited and the research results cannot be generalized, and. The model used to assess stock volatility is the Baskin method (1989). Novelty is the uniqueness of the research is volatility of stocks leaving LQ 45 during February-July 2022

INTRODUCTION
The capital market is a meeting place for investors who have excess funds to invest with issuers (companies) who need funds to develop the company (Tandelilin, 2010). The place where securities are traded in Indonesia is called the Indonesia Stock Exchange (IDX). Investors as one of the capital market players expect returns on the investments they make, because investors have the courage to take risks on these investments. On the IDX various types of securities are traded from various sectors and various types of stock indexes. The stock index that has been around for a long time after the JCI and the sector index is the LQ45 Index. Recently, on 25 January 2022, the IDX announced that five companies had left and five had just entered from LQ45 for the period February -July 2022. The five companies that left the LQ45 group are: a). PT. Ace Hardware Indonesia Tbk (ACES), b With a company leaving the LQ45 group list for the February-July 2022 period, it does mean that the company's liquidity level has decreased, this will affect the desire of investors to invest. Investors will feel insecure about their funds if they keep the portfolio in hand, because for the next 6 months whether the portfolio will provide the expected profit according to investor predictions. To reduce the anxiety experienced by investors, one way that can be done is to analyze the volatility of the stock price (Bodie, Keane, and Marcus, 2011). Volatility is the fluctuation of returns in a certain period, if the fluctuations in returns have a large variation, then the possibility of risks that will occur is greater, and vice versa if the fluctuations in risk are smaller, the probability that risks will occur will be smaller (Carolina, 2016). Thus, it can be seen whether the portfolio owned by the investor has the potential to get the expected profit or the potential risk.
It is necessary to analyze the volatility of the prices of shares that have come out and those that have just joined the LQ45 group for the period February -July 2022, because knowing the level of volatility in stock prices can predict the expected profit potential and risks that will be borne by an investor (Carolina, 2016). So that it can help investors in making stock investment decisions, therefore it is necessary to do this research.

Signaling Theory
Signal theory states that companies will provide signals through actions and communications. Companies will adopt signals that reveal hidden attributes to stakeholders (Malewar, 2008). Meanwhile, Brigham and Houston (2009) revealed that the signaling theory is a theory that investors perceive changes in dividends as a signal of earnings management forecasts. Besley and Brigham (2008), Signals are company management actions that provide investors with evidence about how management views the company's prospects. Signal theory assumes that the information received by the parties is not the same.
This theory is related to information asymmetry, which indicates the existence of asymmetry information between company management and parties with an interest in the information. To do this, managers need to provide information to stakeholders by issuing financial reports. Signaling theory is based on asymmetry information between management information (wellinformed) and shareholder information (well-informed). This theory is based on the idea that when investors or shareholders get good information about a company (such as adding value to the company), management will provide them with information (Ross, 2020). However, investors do not trust this information because managers are interested parties. In this way, high value companies will signal the company's financial policies, which are different from those of low value companies.
Signaling is a process in the form of deadweight costing designed to convince investors about the value of the company. A good signal is one that cannot be imitated by other companies and is of little value due to the cost factor.

Stick Price Volatility
Volatility is a statistical measure that determines how stock prices fluctuate at any given time (Carolina, 2016). This measurement is designed to see changes in stock price changes from one period to the next. In price volatility, prices move up and down from a certain time. The distance between the lowest price and the highest price at a certain time, and fluctuations in share prices are related to the distance between the highest and lowest prices of a share on the capital market within a certain period (Budiman R, 2021). Greater stock price volatility indicates higher gains and losses in the short term. Stock prices with high volatility can change at any time and are difficult to predict. Stock price volatility is a systemic risk for investors.

Efficient Market Hypothesis (EMH)
The definition of the efficient market hypothesis is the assumption that stock prices perfectly describe information (Bodie et al. 2011). An efficient capital market is a market where the prices of all traded securities reflect all available information (Tandelilin, 2010). A more volatile stock price indicates higher short-term gains and losses. Very volatile stock prices can change at any time and are difficult to predict. Stock price volatility is a systemic risk for investors. This can explain that the greater the volatility, the greater the short-term profit or loss (Bodie et al., 2011). An important characteristic of market efficiency is the random walk of stock market prices. Based on Fama (1970) that the efficient market hypothesis is divided into three forms, namely: This past information is information that happened.
The weak form of market efficiency is related to the random walk theory, which states that past data is irrelevant to present values.
Forms of Market Efficiency Selling Strong, a market is said to be very efficient if the price of a security fully reflects all publicly available information, including information contained in the financial statements of major issuers.
Strong Market Efficiency, a market is said to be very efficient if the price of a security fully reflects all available information, including personal information. Tandelilin (2001) considers the rate of return as a return on investment, either through interest or dividends. Investors invest in companies to earn profits. Keane et.al (1983) suggests that abnormal return is the portion of actual returns that exceeds normal returns. Normal return is the expected return (what investors expect). Thus, the abnormal return is the difference between the actual return that occurs and the expected return.

RESEARCH METHODS
The approach used in this research is descriptive comparative and quantitative research. Descriptive comparative research is a method that explains and compares one event and another, while the quantitative method is a statistical method (Sugiyono 2005:21). This research is used to determine the volatility of the prices of shares leaving and joining the LQ45 group for the period February-July 2022, and to find out the difference in the volatility levels of both.
The population used in this research is all companies that enter and leave the LQ45 group for the period February -July 2022, there are 10 companies. The technique used is the census method, because the number of samples is the same as the number of populations. (Henderson, 2016).
Generally, the variables used in this research model consist of:

Stock Price Volatility
Stock price volatility is the distance between fluctuations or ups and downs of stock prices that are influenced by information in the capital market. Volatility is a statistical measurement of stock price fluctuations over a certain period (Firmansyah in Irma, 2017). Stock price volatility is a concern for market players to determine the right investment strategy. In this study, stock price volatility was measured using the …………………………………. (2) Baskin method (1989)

RESULTS AND DISCUSSION
This study aims to analyze price volatility to be able to find out the returns and risks of securities that investors will buy (Bodie, et al, 2016), for companies that join and leave the LQ45 group for the period 1 February-31 July 2022. Total population is 10 companies the sampling technique used is a saturated sample, namely the entire population is used as a sample (Gajarati, 2019). Where the five companies that left and five companies that are joined the LQ45 group for the period 1 February-31 July 2022. The type of data used in this research is secondary data taken from the yahoofinance.com website, and the IDX. The data used is the daily stock price and JCI at closing time. Descriptive analysis consists of the maximum, minimum, average, and standard deviation values of stock price volatility for companies that enter and leave LQ45 for the period February 1 to July 31, 2022. The results of the descriptive analysis can be seen in Table 3. Based on Table 3, it can be seen that the maximum value for companies leaving LQ45 is 0.2519, the minimum value is 0.2266, the mean value is 0.2419, and the standard deviation is 0.129. Whereas for companies that enter LQ45 the value of the results of the descriptive analysis is greater than that of companies that leave LQ45, with a maximum value of 0.3351, a minimum value of 0.2505, a mean value of 0.3033, and a standard deviation value of 0.0319. The results of the volatility value assessment of companies that enter and leave LQ45 for the period 1 February-31 July 2022 using the Baskin method (1989) which can be seen in Table 4.  The higher the volatility value will show the greater the profit expected by investors, and vice versa, the smaller the volatility value of a security, the smaller the level of profit that investors will get (Tandelilin, 2011). The level of expected profit is directly proportional to the level of risk that will be borne by investors.
Where the higher the volatility value of a security, the risk that will be borne by investors will also be higher, and vice versa, if the volatility value is lower, then the risk that will be borne by investors will also be smaller (Bodie, et al, 2010).

CONCLUSION AND RECOMMENDATION
Based on data analysis, here are a several research conclusions can be made: The volatility value of companies that leave is smaller than companies that join LQ45 for the period 1 February to 31 July 2022. However, compared to the JCI volatility is greater.
The results of this study can be used by investors to determine the level of expected profit and the amount of risk that will be borne by investors in making investment decisions. From the results of the analysis, investors can choose securities that enter LQ45 as a consideration in investment decisions because the volatility value of stocks that join is greater than those that leave LQ45 February 1 to July 31, 2022.
Based on the conclusions, the limitations of the research can be made: a. The scope of the research is only companies that join and leave LQ45 for the period 1 February to 31 July 2022, so the number of samples used is limited and the research results cannot be generalized. It is recommended for future researchers to expand the scope of research. b. The model used to assess stock volatility is the Baskin method (1989), it is recommended for future researchers to use other methods such as the Arch and EGarch methods.