• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.3
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• pp.211-219
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• 2010

This paper designs the dynamic symbol automatic trading system in Korean option market. This system is based on Multichart program which is convenient and efficient system trading tool. But the Multichart has an important restriction which has only one constant symbol per chart. This restriction causes very useful strategies impossible. The proposed design uses global variables, signal chart selection and position order exchange. So an automatic trading system with dynamic symbol works on Multichart program. To verify the proposed system, BS(Buythensell)-SB(Sellthenbuy) strategies are tested which uses the change of open-interest of stock index futures within a day. These strategies buy both call and put option in ATM at start candle and liquidate all at 12 o'clock and then sell both call and put option in ATM at 12 o'clock and also liquidate all at 14:40. From 23 March 2009 to 31 May 2010, 301-trading days, is adopted for experiment. As a result, the average daily profit rate of this simple strategies riches 1.09%. This profit rate is up to eight times of commision price which is 0.15 % per option trade. If the method which raises the profitable rate of wining trade or lower commission than 0.15% is found, these strategies make fascinated lossless trading system which is based on the proposed dynamic symbol automatic trading system.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.177-192
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• 2016

Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.

• Asia-Pacific Journal of Business
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• v.14 no.2
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• pp.33-49
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• 2023

Purpose - The purpose of this study is to examine the option selection and optimal trading of informed traders in KOSPI 200 options market based on the PIN (probability of informed trading) model of Easley et al.(2002). Design/methodology/approach - This study uses TAQ (trade and quote) data provided by Korean Exchanges (KRX) which contains all the bids and trades recorded during the continuous auction trading hours for the KOSPI 200 options between May 2019 and September 2020. Findings - First, there was no difference in the PIN between call and put options in the 2019 data, but the PIN of put options was slightly higher in 2020. Second, regardless of the type of option, the PIN was higher for in-the-money (ITM) options, and the PIN of out-of-the-money (OTM) options was the same as or slightly higher than that of at-the-money (ATM) options. Third, we found that the PIN decreases as trading liquidity increases, and fourth, the PIN increased sharply as the expiration date approached, especially for OTM options, while ITM and ATM options showed relatively weak effects. Fifth, for foreign and institutional investors, the periodicity of orders was observed in milliseconds, especially for foreign investors, where the periodicity of orders was clear and frequent in OTM options. The results suggest that the purpose of option trading varies depending on the moneyness from the perspective of the informed trader.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.11a
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• pp.489-497
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• 2000

After IMF situation, the money market environment is changing rapidly. Therefore, many companies including financial institutions and many individual investors are concerned about forecasting the money market, and they make an effort to insure the various profit and hedge methods using derivatives like option, futures and swap. In this research, we developed a prototype of forecasting system for KOSPI 200 option, especially call option, trading using artificial neural networks(ANN), To avoid the overfitting problem and the problem involved int the choice of ANN structure and parameters, we employed the ANN ensemble approach. We conducted two types of simulation. One is conducted with the hold signals taken into account, and the other is conducted without hold signals. Even though our models show low accuracy for the sample set extracted from the data collected in the early stage of IMF situation, they perform better in terms of profit and stability than the model that uses only the theoretical price.

• Journal of information and communication convergence engineering
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• v.11 no.3
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• pp.190-198
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• 2013

Recently, one of the most vital advancement in the field of finance is high-performance trading using field-programmable gate array (FPGA). The objective of this paper is to design high-performance Black Scholes option trading system on an FPGA. We implemented an efficient Black Scholes Call Option System IP on an FPGA. The IP may perform 180 million transactions per second after initial latency of 208 clock cycles. The implementation requires the 64-bit IEEE double-precision floatingpoint adder, multiplier, exponent, logarithm, division, and square root IPs. Our experimental results show that the design is highly efficient in terms of frequency and resource utilization, with the maximum frequency of 179 MHz on Altera Stratix V.

• Management Science and Financial Engineering
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• v.21 no.2
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• pp.13-23
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• 2015

This study addresses the question as to whether the option prices have useful predictive information on the direction of stock markets by investigating a forecasting power of volatility curvatures and skewness premiums implicit in S&P 500 index option prices traded in Chicago Board Options Exchange. We begin by estimating implied volatility functions and risk neutral price densities every minute based on non-parametric method and then calculate volatility curvature and skewness premium using them. The rationale is that high volatility curvature or high skewness premium often leads to strong bullish sentiment among market participants. We found that the rate of return on the signal following trading strategy was significantly higher than that on the intraday buy-and-hold strategy, which indicates that the S&P500 index option prices have a strong forecasting power on the direction of stock index market. Another major finding is that the information contents of S&P 500 index option prices disappear within one minute, and so one minute-delayed signal following trading strategy would not lead to any excess return compared to a simple buy-and-hold strategy.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.13 no.2
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• pp.87-100
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• 2009

Hedging strategy for European option of jump-type semimartingale asset model, which is derived from stochastic differential equation whose driving process is a jump-type semimartingle, is discussed.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.1
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• pp.151-157
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• 2010

This paper proposes the Pyramid strategy which is based on the straddle sell. The Pyamid strategy has multi-entry features with starting date and delta parameters. And It is hedged against a loss by mutual trades and dynamic ripples. This paper analyzes the profit and MDD(maximum draw down) of the Pyramid strategy on system trading. The portfolio tool is used for the experiment which is one of the Multicharts' package. The Multicharts is a good trading system of recent years. For the experiment, three call options and three put options are used at october in 2009. Two parameters are used which are the starting date from first October to twentieth October in 2009 and delta from eight percent to fifty percent. As a result, the profit of composite option is about 3 million won. If the strategy starts before the beginning of option month, investors feel uncomfortable because of a large MDD. If a delta belows 20%, it shows high profit and the ratio of profit and MDD builds up a low value. However a low delta makes frequent trades and results in a loss unless increasing entry levels which mean more amount of investment. This work provides a safer trade system than native option trades. It is important how much levels of multi-entry are acceptable. And an amount of investment with appropriate levels of multi-entry is a subject of a future study.

• International Area Studies Review
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• v.16 no.3
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• pp.239-266
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• 2012

The purpose of this paper is to suggest desirable improvement for KRX derivatives market plagued with many problems in spite of its world level of quantitative growth. In order to try to find desirable improvement for KRX derivatives market which has many problems like that, I suggest various ways of improvement for regulatory system in the future in terms of behavioral regulation for investor protection. First of all, in order to relieve speculative tendency of trading, KOSPI200 option market with ATM-oriented option trading needs to be induced from the market in which OTM-oriented option is now trading. So discount or exemption of brokerage fee for ATM trading and the introduction of market-maker for ATM type can be considered. For the protection of individual investors, we suggest feasible plans such as differential regulation between professional and individual investors, consolidation of basic deposit management, and enlargement of opportunities for risk management education & simulation trading.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.153-153
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• 2018

Water-Energy-Food (WEF) nexus is a new holistic resources management concept that considers the interconnections among resources for sustainable resources planning and management. The current challenge is to fulfill the required demand in the lack of available resources. A traditional way to provide more available resource is by increase in production, but it caused increment of indirect demand of other interlinked resources. Importing resources from other area (where local supply is redundant) is another option to secure local resources with additional economic expenditure. The WEF nexus-trading model adapts the previously developed nationwide nexus simulation model with additional input parameters and functions to simulate trading scenarios. In general, the analysis starts with the quantification of local resources deficit (potential importing amount) and redundancy (potential exporting amount) of each area. Then, a trade module is initiated by determining possible donor area and importation amount. Finally, the nexus simulation for all area is re-run to determine final resources supply-demand results including the trading amount. The trade option provides an opportunity to meet local demands without draining local resources. However, the production capability of donor area may limit the importation amount. The newly developed trade option allows more alternatives for stakeholders to determine resources management plans.