EVALUASI MODEL SIMULASI HISTORIS VALUE AT RISK PORTFOLIO DENGAN METODE CHRISTOFFERSEN

According to Christoffersen (1998), the property of a good VaR model are correct unconditional coverage, correct independence test and correct conditional coverage. Unconditional coverage test calculate how much violations exceed the VaR. If average of violations exceeded the percentage of VaR value, so it is called bad model. Independence test calculate how much violations clustering. If a model VaR has much violations clustering, so it is called bad model, because the risk of bankruptcy would be much higher than if the violations came scattered randomly through time. Conditional coverage test is simultaneously testing both unconditional coverage and independence test. Backtesting base on Christoffersen method different way with Kupiec method. Kupiec method only test on unconditional coverage, so Christoffersen method more complete than Kupiec method

PENENTUAN HARGA OPSI CALL FLOATING STRIKE LOOKBACK EROPA MENGGUNAKAN MODEL POHON BINOMIAL

This thesis explains about pricing European floating strike lookback call options using a binomial tree model with combinatorial approach. The basic idea is to divide the price paths reaching node terminal into groups by their extreme stock prices. The price paths in the same group have the same payoff. Then the value contributed by grups are evaluated. For evaluating the value contributed by terminal node, two different cases are considered. The value contributed by terminal node is the sum of the value contributed by grups. The value of a floating strike lookback call option is the sum of the values contributed by all the terminal nodes

PENENTUAN HARGA OPSI COMPOUND CALL ON CALL EROPA

In stock and options trading, stock price movements are often up and down. This raises concerns investor to invest in the financial sector. European Call on Call Compound Option is a option on the option. European Call on Call Compound Options will protect and minimize the loss of the option holder if the stock price falls below the market price of the contract. This thesis will discuss the option price calculation Compound Call on Call Europe with the Black-Scholes model approach and the bivariate normal distribution

ANALISIS TEKNIKAL SAHAM MENGGUNAKAN VARIABLE INDEX DYNAMIC AVERAGE (VIDYA)

Our financial and market action change every minute of every day. These markets are dynamic because traders constantly adjust to changing perceptions and participants. Therefore we need dynamic indicators that vary the time periode used in analyzing market action. Variable Index Dynamic Average (VIDYA) is an indicator that adapted Exponential Moving Average (EMA) that can dynamically follow the movements of stock prices. Equal as Exponential Moving Average (EMA), VIDYA also need weight in its calculation methods. In this paper, the weight of EMA is used to determine the weight of VIDYA. VIDYA can be calculated using three different methods, such as standard deviation, Chande Momentum Oscillator (CMO), and coefficient of determination. These calculation method is used to determine the volatility index that worth to predict stock price movements and predict the trend in the future. In addition, VIDYA can be used as trading strategy and determine buy signal or sell signal that using the breakout point. Keyword: technical analysis, volatility index, exponential moving average, standard deviation, coeffitient of determination, momentum indicato

PENENTUAN HARGA OPSI BELI TIPE EROPA DENGAN RETURN ASET BERDISTRIBUSI NORMAL TRUNCATED

In stock and options trading, exchanges often imposed restrictions on the daily price changes of an asset. As a result, the range of asset returns (in logarithmic form) are no longer in the interval (- �, �), but truncated at the bottom and top. Consequently returns no longer normally distributed, but normally truncated distribution. Therefore, in this thesis will be discussed regarding the European option pricing using Normal Truncated Distribution on asset returns. Furthermore, we compare the option price obtained by the normal truncated distribution approach and the Black-Scholes model with option�s market price. As a result, option pricing using normal truncated distribution closer to the market price than the Black-Scholes model.. So we can conclude empirically, the theory of option pricing models with normal truncated distribution approach suitable for the option that has restrictions on its stock price changes

PENDEKATAN HIERARCHICAL LIKELIHOOD UNTUK MODEL LOGNORMAL FRAILTY SATU KOMPONEN DALAM ANALISIS DATA SURVIVAL DUA LEVEL

In survival analysis, it�s known a hazard function. It�s a risk or rate of an individual get an event with one conditional, that individual survives until an event occurs. The hazard function may depend on observed risk variables but usually not all variables are known or measurable. This unknown factor of the hazard function is usually termed the individual heterogeneity or frailty. In its simplest form, a frailty is an unobserved random factor that modifies multiplicatively the hazard function of an individual or group or cluster of individuals. In this thesis will be discussed about lognormal frailty model, an extension of Cox regression. Hierarchical likelihood method will be used to estimate the regression coefficients and to find the effect of frailty in the two level survival data

PENENTUAN HARGA OPSI EROPA MODEL TRINOMIAL DENGAN TEKNIK EKSTRAPOLASI

Research on how option pricing has continued to experienced over time. One of them is by describing stock price movements that follow the trinomial tree model. With this model, it is assumed that the movement of stock prices for the period ahead following three conditions: stock prices will increase, tend to constant, or it will decline. However, the results have a slow convergence so it is required a method to accelerate the convergence with the extrapolation. A frequently used method of extrapolation is the Richardson extrapolation technique which is quite popular extrapolation technique. The initial idea of the use of Richardson extrapolation technique is to do elimination on some early part of the asymptotic expansion from approached function that depends on the stepsize line to get a better approach

PERBANDINGAN MODEL REGRESI NONPARAMETRIK SPLINE DAN REGRESI NONPARAMETRIK KERNEL

Regression analysis is a statistical tool that is widely used to determine the relationship between a pair of variables or more. Regression analysis is divided into two, namely parametric regression and nonparametric regression. Nonparametric regression has several smoothing methods, such as spline and kernel regression. Its main purpose is to compare the two methods for estimating the nonparametric regression model. The data were used to compare the two methods of toddler growth data

APLIKASI GENERALIZED RIDGE REGRESSION UNTUK MENGATASI MASALAH MULTIKOLINEARITAS

Least square method is one of parameter estimation method, it is a method for estimating regression coefficient. If any of classical regression assumption, that is no multicollinearity is not met, parameter estimation using least square method becomes less valid, even if there is perfect multicollinearity then it causes beta parameters can�t be estimated. Linear relationship between the independent variables causes the variance parameter beta becomes large, the error was large. In fact, the estimated value we desired is a small variance and error. For handling this multicollinearity problem, one of the way is using ridge regression. The concept of ridge regression is by adding a k biased constant which is a diagonal matrix, to the correlation matrix ' X X . In this paper we will discuss one of the k parameter estimation methods, namely Generalized Ridge Regression. This method obtain the k ridge parameter that is not a single parameter but multiple k ridge parameters. Those k ridge parameters are different for each independent variables

MANAJEMEN PERSEDIAAN MENGGUNAKAN MODEL Q,r DENGAN TIMEWEIGHTED BACKORDERS

Inventory is one of the most active ingredient in the company's operations are continuously acquired, modified, which then resold. Basically supplies are also a idle resources, which means that if the excess inventory causes wasted investment, but if there is no inventory would be difficult to anticipate fluctuations in demand or other things that cause deficiencies. When faced with stockout, customers react differently, depending upon how it affects their respective businesses. Some are sensitive to the frequency of stockout while others regard number of backorders to be more important. In certain types of businesses such as engines or critical elements, however the duration of stockout is an important element. As such, time - weighted backorders are appropriate measures of stockout in a situation like this. Decisions concerning \" how much and when to place an order \" is a major problem in inventory management. Inventory model Q,r with time - weighted backordes believed to be able to resolve the problem, the system will determine the inventory position of the point of when to order goods (R), and the number of items that should always be booked (Q) when the inventory is right at that point using the method HMMS multi- items