Financial Solution

Solution Service

KIS-AMA

inform of KIS-AMA
  • Efficiency Position Management - Bonds(KRW/FCY), Futures, Swap, FX, Derivatives, CD/CP position and trade history
    P/L Analysis - Real Time P/L (Daily/Monthly/Periodically ), RP/Lender Trade, Funding status and cost analysis
  • Investment Decision Simulation - Hedge, Carried Income, Simulation and Bond/Swap/FX, Calculator
    Greek analysis - Position/Sector Delta Analysis, Duration, Hedge Ratio Management
  • Transparency Risk Management - Risk limit settings and management, VaR Calculation and Management
    Performance Analysis - Performance Analysis, Performance factor decomposition, BM Management, Asset Manager performance Analysis

System Functions

inform of System Functions
  • Asset Management Operation status Position and P/L status, Risk Status, P/L, Performance factor decomposition,Asset Manger Performance Analysis
  • Asset Management Strategy Market/corp. Analysis,Simulation / Greek Analysis
  • Asset Management Real-Time Position and Trade Real-Time P/L and Greek Analysis, Real-Time VaR management, Position Management
  • After investment Profit / loss calculation, Automated transfer of operational and market information systems
  • Report P/L Report, Risk Report, Investment Contribution Analysis, Funding Analysis, FX Exposure Analysis, Weekly/Monthly Asset Management Report

Benefits

inform of Increase work efficiency of management personnel, Increase responsiveness to financial market, Transparent and systematic management, System flexibility and convenience
Increase work efficiency of management personnel
  • Simple repetitive processes are automated through the system
  • Systematic management helps prevent manual mistakes and errors
  • Reduce reporting time and establish rapid reporting system
  • Reduces time and convenience of information inquiry
  • Saved Time can be utilized for operational strategy feedback and market analysis
  • Increase the speed and accuracy of investment decisions
Increase responsiveness to financial market
  • Flexible response to the rapidly changing financial market regulations and products
  • Bonds, futures, swaps, foreign currency bonds, foreign futures, FX, CD / CP / flyer bonds, derivatives-linked securities (ELB, DLB), FICC related products
  • Real-time P/L management and VaR limit management when the rapid market rate changes occurs
  • Real-Time trade reflected portfolio Greeks analysis
  • Improving operational efficiency through operational strategy simulations
Transparent and systematic management
  • Transparent Communication on investment performance
  • Improvement of operational effectiveness through integrated total portfolio management
  • Standardization of reporting style and system
  • Standardize and automatized in investment operation
  • Ability to feedback operational strategies through analysis of P/L and Performance factor decomposition
  • Efficient risk management by ensuring transparency in the Investment position
System flexibility and convenience
  • Ensure expendability by providing open and flexible solutions
  • Reduced deployment time by introducing package system, making it possible to customize and provide in-depth analysis tools
  • Reduce risk and operational costs by unifying operations and maintenance
  • Operational stability by utilizing market-validated pricing module

KIS-AMA

inform of KIS-AMA

Risk Types

Market Risk

Any risk associated with market movement(Market Price, Market Interest, FX) against current position

inform of Risk Factor, Related Product
Risk Factor Related Product
Equity Risk Equity, CB, EB, BW, KOSPI200 Futures, Star index Futures, Equity Index Option, Option, Indivisual equity Option, ELS, Warrant
Interest Risk Bonds, Bonds with option, FRN, CD Futures, KTB Futures (3,5YR), MBS, Forward Rate Futures, Swap
Foreign Exchange Risk Foreign equity, Foreign Bonds, FX futures, FX Forward, Swap, USD/WON Option
Market Risk Management

Portfolio , Rate of Return, Risk analysis to mange against Market Risk

inform of Market Risk Management
  • Portfolio Management Set sectoral Management
    Manage inquiries by fund,, type, manager and whole company
  • Rate of Return Management Classified according to pre-defined rate of return
  • Risk Management Classified by predefined risk indicators
  • Monthly/Quarterly Rate of Return
  • Risk management types of Investment: Equity, Bonds, Derivatives,
    Calculation Criteria: 95% confidence level of fund 1 day VaR
Credit Risk
  • The risk of default on a debt that may arise from a borrower failing to make required payments.
  • Measurement
    • Probability of Default(PD): Probability of Default with in period( usually within a year)
    • Exposure At Default(EAD): the gross exposure under a facility upon default of an obligor
    • Expected Loss: Loss expected within the exposure. Credit Risk is Zero, if the all the loss can be collected after the default
  • Measuring Method
  • inform of Method, Model
    Method Model
    Financial Statement Data Method Altman Z-score regression analysis, Logit, Probit model
    Option Model Method KMV model, Black-Scholes model
    Economic Indicator Method Use of GNP changes, equity Index and etc to calculated Probability of default
    Decision Tree Method Analyze individual companies by categorizing the entire set into similar groups
    Neutral network Method Estimation of default probability using linear, nonlinear, and neural networks
    Mathematical Method Linear Programming, NON-Linear Programming
Risk Factor Management

Manage Risk Factor by rate of return and volatility of the market

inform of Risk Factor, Category, Detail
Risk Factor Category Detail
Rate of Return Equity Use log rate of return
Interest Since the interest rate itself is has the nature of the rate of return, the yield rate of the interest rate is calculated by subtracting the previous day's interest rate from the todays’ interest rate
FX Use log rate of return like equities
Dispersion Covariance SMA A method of estimating the volatility by setting a moving window for a certain period and calculating a simple moving average value during the period
EWMA Assign a high weight to recent data and assign a low weight to older data to estimate volatility
GARCH Risk Factor Model of time-series data on rate of returns in terms of conditional dispersion
Yield Curve Bootstrap Method Generate yield curves sequentially in expiration order based on market data composed of Term Structure
Levenberg Marquardt create curves using the Optimization Method through the entire configured market data
Equity Beta Standard Calculating the equity beta by generating the correlation coefficient from the two same time series data, the beta is calculated based on smaller set amount of data

Interpolation MethodLinear Interpolation) and Cubic Spline Interpolation

Risk Management

Market Risk Management Process

Market risk management consists of processes: data acquisition, data analysis, result data and screen display

inform of Market Risk Management Process
Market Risk Management

Risk associated with Portfolio management and Return is managed though Risk analysis and Pricing

inform of Market Risk Management
  • Exposure Management Position Exposure management by funds or asset management firm
    Exposure limit analysis
  • EAD EAD =Net Replacement Cost + Additional Cost
    Current Exposure
  • Risk Amount/VaR Risk Amount and VaR Limit Management
  • Strengthen monitoring of credit risk system through various credit risk management indicators

VaR

The maximum amount of loss that can occur over a period of time with a given confidence level under normal market conditions
  • For example, if the VaR for a target period of 1 year and a confidence level of 95% is KRW 1 billion, It means 95% chance that the maximum loss can be less than KRW 1 billion with in a year
  • The market risk can be controlled, if there were KRW 1 billion.
  • The higher the confidence level, the larger the VaR..
inform of VaR graph

By implementing VaR,

  • It is possible to objectively quantify the risk instead of based on experience
  • Benefits of managing the risks that occur across various sectors as whole, since financial institutions can calculate the risks that occur in various markets(Bonds Equites and others)
  • Effective allocation of resources using VaR

Portfolio VaR

  • Portfolios risk can be calculated by looking into individual risk elements in the portfolio
  • By disassemble the portfolio, portfolio returns consist of a linear combination of individual asset returns.
  • The weight of individual asset returns given based on the amount of initial investment amount
  • Therefore, VaR in a portfolio can be measured by combining the risks of individual assets with in the portfolio

The portfolio returns from time t to time t + 1 are as follows

inform of The portfolio returns from time t to time t + 1 are as follows

The weights (Wi,t) are given at the beginning of the period and sum to 1. The expected returns of the portfolio are as follows.

inform of The weights (Wi,t) are given at the beginning of the period and sum to 1. The expected returns of the portfolio are as follows.

The variance of the portfolio includes not only the risk of individual assets (securities)(σ12) but also the covariance(σij) between assets.

inform of The variance of the portfolio includes not only the risk of individual assets (securities)(σ12) but also the covariance(σij) between assets.

If the correlation is low or the number of assets increases, the risk of the portfolio decreases, but the VaR of the portfolio that does not consider the dispersion effect is the sum of the individual VaRs.

Types of VaR

Incremental VaR
  • The incremental VaR of a stock i represents the change in total VaR when the stock is excluded from the current portfolio.
  • To obtain the incremental VaR, we set the holding position of i to 0, calculate VaR of the portfolio again, and subtract it from the VaR of the portfolio that includes the position of i.
  • Incremental VaR equation
  • inform of Incremental VaR equation
  • Incremental VaR can be used to minimize VaR for investments when the amount of investment is limited or when the amount of investment must be reduced.
  • If we reduce the amount of investment by KRW 500,000 and reduce VaR to the maximum, we can reduce the amount of investment in the stocks that have the largest incremental VaR
  • In order to obtain the incremental VaR for individual items, it takes some time to calculate the matrix as above
Marginal VaR
  • Marginal VaR represents the changes in total VaR when the value i in one of item in the current portfolio changes.
  • Expressing this in a formula Marginal VaR
  • inform of Marginal VaR
  • Marginal VaR of i item is proportional to the correlation coefficient between the return of i item and the return of the portfolio
  • The smaller the correlation with the portfolio, the smaller the change in portfolio VaR given the same amount is added, when there is negative correlation the portfolio VaR will decrease.
  • Marginal VaR is defined as movement of the VaR related with movement of the one unit of investment. Therefore, to obtain an accurate marginal VaR, comparison between two different portfolio VaR is required
  • To obtain the Marginal VaR, increase one unit of investment amount in the current portfolio and calculate differences between the previous and the existing portfolio.
Component VaR
  • Component VaR is the contribution of a specific item to the entire portfolio’s VaR
  • Component VaR is useful for analyzing how much the VaR value of a portfolio can be reduced when a specific items or asset group is removed from the current portfolio.
  • However, if the constituent items of the portfolio are changed, the VaR value changes due to the correlation between the constituent items changes
  • Therefore, Component VaR is the ratio of the VaR value of the current portfolio, it is an approximated value.
  • Incremental VaR is when items is removed from the portfolio. Component VaR is an approximation of Incremental VaR.
  • Therefore, in general, the value of Incremental VaR or Component VaR is similar.
  • Jorion defines the Component VaR as follows.
  • inform of Component VaR

VaR Analysis

Back-Testing

The back test for verifying the model is to verify the conformity through comparison of the P/L generated under the confidence level, and to extract the P/L data, back test, documentation and report to the supervisory authority.

VaR Model Analysis
  • Back Test through P/L calculation
  • By comparing calculated the VaR with the actual rate of return on the portfolio on the next day
  • Back Test should be done on a regular basis
  • Modification of the VaR model or analysis of the cause due to an exception events
inform of VaR Model Analysis graph
VaR Model Analysis(Regular)
inform of VaR Model Analysis(Regular)

KIS-VaR

Market Risk Analysis Screen

By basic input information for VaR calculation, the market VaR screen is able to provide position information, market risk information and VaR information by risk factor.

inform of Market Risk Analysis Screen
  • 01 Market Risk Setting
    • Setting the information required for VaR calculation
    • Analysis Method - Parmetric, Historical
    • Holding Period - User-defined value
    • Confidence Level – User-Defined Value
    • Method of Volatility Estimation - MA, EWMA
    • Sample Period – User-Defined Value
  • 02 Market Risk Management and Summery
    • Position information: Market price, Exposure, Book value and risk rate information
    • Market risk: The results of VaR calculated by user defined conditions and the VaR Ratio analysis function
    • By calculating each risk factor able to decompose analysis of VaR
  • 03 Summery Information Graph

    Comparative graphic analysis of different asset management companies, position information by fund, market risk and risk factors

Market Risk Analysis Summery Screen

Market risk analysis summary screen provides position information, market risk information, and VaR information by risk factor through basic input information required for VaR calculation.

inform of Market Risk Analysis Summery  Screen
  • 01 Market Risk Setting
    • Setting the information required for VaR calculationVaR
    • Analysis Method - Parmetric, Historical
    • Holding Period - User-defined value
    • Confidence Level – User-Defined Value
    • Method of Volatility Estimation - MA, EWMA
    • Sample Period – User-Defined Value
  • 02 Market Risk Analysis Details
    • Position Information: Information about book value, market price, and exposure
    • Market Risk: Risk ratio and VaR information
    • VaR calculation type: Incermental VaR, Marginal VaR, Component VaR

Pricing Coverage

inform of KIS-Module
  • Equity Hi-Five,Barrier,Basic,Cliquet,TRS
  • Interest Rate Range Accrual,Spread Range Accrual,Reverse Convertible,Basic,FRN
  • FX Basic,Barrier,Hi-Five,Forward
  • Credit CLO,CLN,CDO,Callable CDS/CLN,TRS,KTB Swap

Special Feature

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  • Accurate/ Defensible Module Complex financial instruments, A fast-changing financial market, The need for accurate and fast pricing of the product and the calculation of risk indicators, Continuous Leading Research, Reliability of module development through vast expericence
  • Transparency in procedure Strengthening of market regulation, Investor's curiosity about module creation principle, The frustration of existing investors who are not familiar with programming languages, Transparent disclosure of the creation process, An easy-to-understand coding description, Continuous contact with customers
  • Customizable KISP Module Others use pre-developed modules to fit the customer, Tailored to customer needs are require due to complexity and various investment products, Development and installation of modules optimized for clients through consulting, Maintains and optimizes for future system changes
  • Distinctiveness(Complexity) Increase in financial market size, Strengthening financial supervision standards, Increase the importance of calculation and management of risk indicators, Collaborate with overseas companies to introduce new solutions, Introduced CUDA system for the first time in the industry, Continuous research to obtain the latest technologies

Applicable Pricing Models

  • Discovering new models and improving existing models through continuous research
  • Various models can be applied according to user's needs
Equity
  • Black-Scholes Model
  • Dupire Model (Local Volatility)
  • SABR Model (Stochastic Volatility)
  • BS-HW Model (Stochastic Interest Rate)
Interest Rate
  • Hull-White 1-Factor Model & Hull-White 2-Factor Model (G2++ Model)
  • Black Model (Log-Normal Model) & Bachelier Model (Normal Model)
  • SABR Model
  • Linear Gauss-Markov 1-Factor Model & Linear Gauss-Markov 2-Factor Model
  • Market Model (Log-Normal Forward Rate Model & Log-Normal Swap Rate Model)
  • Terminal Swap Rate Model
Foreign Exchange
  • Black-Scholes Model (Sticky Delta)
  • HW-BS-HW 3-Factor Model (IR-FX-IR)
  • Local Volatility Model
  • Vanna-Volga Approach
Other Underlying Asset Class
  • Credit : Cox-Ingersoll-Ross++ Model
  • Inflation(CPI) : Jarrow-Yildirim Model
  • Commodity : Black-Scholes Model, Local Volatility Model
  • Hybrid
Applicable Pricing Models
  • KISP’s unique Technique to each Pricing Method
  • Optimal method is applied according to individual product class
inform of Pricing Method, Detail, Application
Pricing Method Detail Application
Closed-Form Solution

Various Closed-Form Solution Secured

  • Forward, IRS, CRS
  • Vanilla Option, Digital Option
  • Barrier Option, Window Barrier Option
Monte-Carlo Simulation
  • Various Discretization Scheme
  • Variance Reduction Technique
  • Brownian Bridge Technique
  • Lizard Hi-Five, Lizard Reverse Convertible
  • Callable Range Accrual
  • Other Strongly Path-Dependent Product
Finite-Difference Method
  • Alternating Direction Implicit Method
  • Operator Splitting Method
  • Adaptive Mesh Refinement
  • Callable Hi-Five
  • Barrier Option, Cliquet Option
  • Other Weakly Path-Dependent Product

Reference

Main Clients
inform of MireaAssetDaewoo Securities, Kiwoom Securities, Hana Securities, KoreaInvestment Securities, Hana Bank, BNP PARIBAS, KB Bank, DB Insurance, KEB Bank, K SURE, KOFIA
KIS-Module Market Share(Securities Only)
inform of other 7%, KISP 93%
KIS-Module data usage
inform of Market, Risk, Back Office, Front Office