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1

Xin, Ling, e 辛聆. "The statistical properties and effectiveness of filter trading rule". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2013. http://hdl.handle.net/10722/196092.

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Filter trading rule is a technical trading strategy that was very popular amongst practitioners and has been used a lot for testing market efficiency. It has been shown that the filter trading rule is mathematically equivalent to the CUSUM quality control test as both are based on change point detection theory via sequential probability ratio tests (SPRT). To study the operating characteristics of the filter trading rule, many results from the CUSUM literature can be applied. However, some interesting operating characteristics of a technical trading rule such as expected profit per day may not be relevant when put into a quality control setting. In this thesis, we derive formulae for computing these operating characteristics. It is well known that just like any other technical trading rule, the filter trading rule is not effective when the asset price follows a random walk. In this thesis, we studied the statistical properties and effectiveness of the filter trading rule under different asset price models including Markov regime switching model and conditional heteroskedasticity model. The properties of the filter trading rule considered include the waiting time for the first signal in filter trading, the duration of a long or a short cycle in filter trading, the profit return derived from a long or a short cycle and the unit time return of long term filter trading. Built on the above results, we consider the problem of optimizing the performance of a filter trading rule by choosing a suitable filter size. For filter trading rule under the conditional heteroskedasticity model, the change point detection methods lead to a new technical trading rule called generalized filter trading rule in this thesis. The generalized filter trading rule is shown to have a better performance over the ordinary filter trading rule when it is applied to the trading of the Hang Seng Index futures contract. Finally, we have applied the filter trading rule to intraday trading on high frequency Hang Seng Index futures data.
published_or_final_version
Statistics and Actuarial Science
Doctoral
Doctor of Philosophy
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2

任漢全 e Hon-chuen Yam. "Statistical analysis of some technical trading rules in financial markets". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1996. http://hub.hku.hk/bib/B31213819.

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3

Ma, Po-yee Pauline, e 馬寶兒. "The heteroscedastic structure of some Hong Kong price series". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1989. http://hub.hku.hk/bib/B31976062.

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4

Shen, Rujun, e 沈汝君. "Mining optimal technical trading rules with genetic algorithms". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B47870011.

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In recent years technical trading rules are widely known by more and more people, not only the academics many investors also learn to apply them in financial markets. One approach of constructing technical trading rules is to use technical indicators, such as moving average(MA) and filter rules. These trading rules are widely used possibly because the technical indicators are simple to compute and can be programmed easily. An alternative approach of constructing technical trading rules is to rely on some chart patterns. However, the patterns and signals detected by these rules are often made by the visual inspection through human eyes. As for as I know, there are no universally acceptable methods of constructing the chart patterns. In 2000, Prof. Andrew Lo and his colleagues are the first ones who define five pairs of chart patterns mathematically. They are Head-and-Shoulders(HS) & Inverted Headand- Shoulders(IHS), Broadening tops(BTOP) & bottoms(BBOT), Triangle tops(TTOP) & bottoms(TBOT), Rectangle tops(RTOP) & bottoms( RBOT) and Double tops(DTOP) & bottoms(DBOT). The basic formulation of a chart pattern consists of two steps: detection of (i) extreme points of a price series; and (ii) shape of the pattern. In Lo et al.(2000), the method of kernel smoothing was used to identify the extreme points. It was admitted by Lo et al. (2000) that the optimal bandwidth used in kernel method is not the best choice and the expert judgement is needed in detecting the bandwidth. In addition, their work considered chart pattern detection only but no buy/sell signal detection. It should be noted that it is possible to have a chart pattern formed without a signal detected, but in this case no transaction will be made. In this thesis, I propose a new class of technical trading rules which aims to resolve the above problems. More specifically, each chart pattern is parameterized by a set of parameters which governs the shape of the pattern, the entry and exit signals of trades. Then the optimal set of parameters can be determined by using genetic algorithms (GAs). The advantage of GA is that they can deal with a high-dimensional optimization problems no matter the parameters to be optimized are continuous or discrete. In addition, GA can also be convenient to use in the situation that the fitness function is not differentiable or has a multi-modal surface.
published_or_final_version
Statistics and Actuarial Science
Master
Master of Philosophy
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5

Li, Chun-wah, e 李振華. "Spatial autocorrelation and liquidity in Hong Kong's real estate market". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B47278006.

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Spatial autocorrelation is commonly found in the Hedonic Pricing model for real estate prices, but little attention has been paid to identify the causes behind. The primary objective of this research is to examine the causes of spatial autocorrelation in housing prices. Observed autocorrelation is often attributable to the omission of important location characteristics in the modelling process. Since it is practically impossible to exhaustively include all location characteristics, some variables may eventually be omitted, leaving spatially autocorrelated residuals in the Hedonic Pricing model. This thesis proposes a new source of spatial autocorrelation: real estate market liquidity. We hypothesize that liquidity affects the geographical boundary within which buyers and sellers search for price information. When the “immediate vicinity” of a property has few transactions, buyers and sellers may have to search for price information from more distant locations. Therefore, low liquidity in the vicinity of a property should strengthen the spatial autocorrelation of real estate prices. A Spatial - Liquidity Hedonic Pricing (SLHP) model is proposed to test the above hypothesis. The SLHP model generalizes traditional spatial autoregressive models by making the spatial process liquidity dependent. When applied to the apartment market in Hong Kong, the model is operationalized by defining “immediate vicinity” as the building where the subject unit locates. Furthermore, the SLHP model recognizes that past transactions may affect current transactions, but not vice versa, so the spatial weight matrix is simply lower triangular. Under this condition, we have shown that the Maximum Likelihood Estimation is equivalent to the Ordinary Least Squares Estimation. This greatly simplifies the estimation procedures and reduces the empirical analysis to a feasible scale. Based on 15 500 transactions of residential units in Taikooshing, Hong Kong from 1992 to 2006, we conclude that while positive spatial autocorrelation is present in housing prices, its magnitude decreases when liquidity, as measured by the past transaction volume in the immediate vicinity of a subject unit, is high. In addition, we found that current prices are spatially correlated with transactions occurred up to the last three months only, reflecting the relatively high information efficiency of Hong Kong’s residential market. All these results are generally robust across a variety of distance, liquidity, and time weight specifications. This study establishes liquidity as a determinant of spatial autocorrelation in real estate prices. This is a new finding contributing to the economic literature on liquidity effects and technical literature on spatial estimation. Our results not only reveal the spatially dependent price formation process in the real estate market, but also have practical applications on the hedonic modelling of real estate prices for mass valuation and index construction.
published_or_final_version
Real Estate and Construction
Doctoral
Doctor of Philosophy
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6

Ren, JinJuan, e 任錦娟. "Investigating the role of accounting earnings in explaining increasingidiosyncratic volatility". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B29851051.

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7

Mohammadi, Limaei Soleiman. "Economically optimal values and decisions in Iranian forest management /". Umeå : Dept. of Forest Economics, Swedish University of Agricultural Sciences, 2006. http://epsilon.slu.se/200691.pdf.

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8

Lawrence, Gerald D. "Stumpage price expectations: an empirical analysis of nonindustrial private landowners in the Mid-Atlantic states". Thesis, Virginia Polytechnic Institute and State University, 1985. http://hdl.handle.net/10919/51894.

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Numerous empirical studies outside of forestry have analyzed the role of price expectations in different decision processes. Empirical studies using price expectations in forestry research is a relatively new field of endeavor. Past studies have typically ignored or given cursory treatment to the role of price expectations. This study provides a review of studies in forestry that have attempted to incorporate price expectations into model formulations. Models are then developed to explain the short-run harvest, and long-run regeneration expenditure decisions by the non-industrial private forest owner, incorporating different distributed lag formulations to account for price expectations. The estimated models for the short-run harvest decision, using cross sectional non-aggregated data, indicates that price expectations play a significant role in this decision process. Therefore, price expectations should be incorporated in some form, (i.e. different forms of distributed lags), to properly specify models. Estimated models for the long-run regeneration expenditure decision indicates a weak link between economic variables and the regeneration decision. For both types of models, estimated coefficients for personal characteristics of landowners are in general considered insignificant, indicating the lack of influence that personal characteristics have on these decision processes
Master of Science
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9

Du, Toit Cornel. "Non-parametric volatility measurements and volatility forecasting models". Thesis, Stellenbosch : Stellenbosch University, 2005. http://hdl.handle.net/10019.1/50401.

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Assignment (MComm)--Stellenbosch University, 2005.
ENGLISH ABSTRACT: Volatilty was originally seen to be constant and deterministic, but it was later realised that return series are non-stationary. Owing to this non-stationarity nature of returns, there were no reliable ex-post volatility measurements. Subsequently, researchers focussed on ex-ante volatility models. It was only then realised that before good volatility models can be created, reliable ex-post volatility measuremetns need to be defined. In this study we examine non-parametric ex-post volatility measurements in order to obtain approximations of the variances of non-stationary return series. A detailed mathematical derivation and discussion of the already developed volatility measurements, in particular the realised volatility- and DST measurements, are given In theory, the higher the sample frequency of returns is, the more accurate the measurements are. These volatility measurements referred to above, however, all have short-comings in that the realised volatility fails if the sample frequency becomes to high owing to microstructure effects. On the other hand, the DST measurement cannot handle changing instantaneous volatility. In this study we introduce a new volatility measurement, termed microstructure realised volatility, that overcomes these shortcomings. This measurement, as with realised volatility, is based on quadratic variation theory, but the underlying return model is more realistic.
AFRIKAANSE OPSOMMING: Volatiliteit is oorspronklik as konstant en deterministies beskou, dit was eers later dat besef is dat opbrengste nie-stasionêr is. Betroubare volatiliteits metings was nie beskikbaar nie weens die nie-stasionêre aard van opbrengste. Daarom het navorsers gefokus op vooruitskattingvolatiliteits modelle. Dit was eers op hierdie stadium dat navorsers besef het dat die definieering van betroubare volatiliteit metings 'n voorvereiste is vir die skepping van goeie vooruitskattings modelle. Nie-parametriese volatiliteit metings word in hierdie studie ondersoek om sodoende benaderings van die variansies van die nie-stasionêre opbrengste reeks te beraam. 'n Gedetaileerde wiskundige afleiding en bespreking van bestaande volatiliteits metings, spesifiek gerealiseerde volatiliteit en DST- metings, word gegee. In teorie salopbrengste wat meer dikwels waargeneem word tot beter akkuraatheid lei. Bogenoemde volatilitieits metings het egter tekortkominge aangesien gerealiseerde volatiliteit faal wanneer dit te hoog raak, weens mikrostruktuur effekte. Aan die ander kant kan die DST meting nie veranderlike oombliklike volatilitiet hanteer nie. Ons stel in hierdie studie 'n nuwe volatilitieits meting bekend, naamlik mikro-struktuur gerealiseerde volatiliteit, wat nie hierdie tekortkominge het nie. Net soos met gerealiseerde volatiliteit sal hierdie meting gebaseer wees op kwadratiese variasie teorie, maar die onderliggende opbrengste model is meer realisties.
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10

Lee, Yee-nin, e 李綺年. "On a double smooth transition time series model". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1998. http://hub.hku.hk/bib/B31215555.

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11

Dagdelen, Derya. "The Effects Of Exchange Rates, Oil Prices, Global Risk Perceptions And Global Warming On Food Prices". Thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614969/index.pdf.

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This thesis examines the relationship between food prices, oil prices, carbon emission prices, exchange rates and global risk perception. To obtain the effects of these variables on the food prices, Toda and Yamamoto procedure is employed for 5-day week daily time series covering the period February 27, 2008 and March 21, 2011. The empirical results indicate that only volatility index Granger causes food prices. Furthermore, according to results of generalized impulse response plots food prices respond to all variables in the short run.
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12

Hamell, Clara. "Statistical Methods for Analysis of the Homeowner's Impact on Property Valuation and Its Relation to the Mortgage Portfolio". Thesis, KTH, Matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-288498.

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The current method for house valuations in mortgage portfolio models corresponds to applying a residential property price index (RPPI) to the purchasing price (or last known valuation). This thesis introduces an alternative house valuation method, which combines the current one with the bank's customer data. This approach shows that the gap between the actual house value and the current estimated house value can to some extent be explained by customer attributes, especially for houses where the homeowner is a defaulted customer. The inclusion of customer attributes can either reduce false overestimation or predict whether or not the current valuation is an overestimation or underestimation. This particular property is of interest in credit risk, as false overestimations can have negative impacts on the mortgage portfolio. The statistical methods that were used in this thesis were the data mining techniques regression and clustering.
De modeller och tillvägagångssätt som i dagsläget används för husvärdering i bolåneportföljen bygger på husprisindexering och köpesskilling. Denna studie introducerar ett alternativt sätt att uppskattta husvärdet, genom att kombinera dagens metod med bankens egna kunddata. Det här tillvägagångssättet visar på att gapet mellan det faktiska och det uppskattade husvärdet kan i viss mån förklaras av kunddata, framförallt där husägaren är en fallerad kund. Inkluderandet av kunddata kan både minska dagens övervärdering samt predicera huruvida dagens uppskattning är en övervärdering eller undervärdering. För fallerade kunder gav den alternativa husvärderingen ett mer sanningsenligt uppskattat värde av försäljningspriset än den traditionella metoden. Denna egenskap är av intresse inom kreditrisk, då en falsk övervärdering kan ha negativa konsekvenser på bolåneportföljen, framförallt för fallerade kunder. De statistiska verktyg som användes i denna studie var diverse regressionsmetoder samt klusteranalys.
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13

Revend, War. "Predicting House Prices on the Countryside using Boosted Decision Trees". Thesis, KTH, Matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-279849.

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This thesis intends to evaluate the feasibility of supervised learning models for predicting house prices on the countryside of South Sweden. It is essential for mortgage lenders to have accurate housing valuation algorithms and the current model offered by Booli is not accurate enough when evaluating residence prices on the countryside. Different types of boosted decision trees were implemented to address this issue and their performances were compared to traditional machine learning methods. These different types of supervised learning models were implemented in order to find the best model with regards to relevant evaluation metrics such as root-mean-squared error (RMSE) and mean absolute percentage error (MAPE). The implemented models were ridge regression, lasso regression, random forest, AdaBoost, gradient boosting, CatBoost, XGBoost, and LightGBM. All these models were benchmarked against Booli's current housing valuation algorithms which are based on a k-NN model. The results from this thesis indicated that the LightGBM model is the optimal one as it had the best overall performance with respect to the chosen evaluation metrics. When comparing the LightGBM model to the benchmark, the performance was overall better, the LightGBM model had an RMSE score of 0.330 compared to 0.358 for the Booli model, indicating that there is a potential of using boosted decision trees to improve the predictive accuracy of residence prices on the countryside.
Denna uppsats ämnar utvärdera genomförbarheten hos olika övervakade inlärningsmodeller för att förutse huspriser på landsbygden i Södra Sverige. Det är viktigt för bostadslånsgivare att ha noggranna algoritmer när de värderar bostäder, den nuvarande modellen som Booli erbjuder har dålig precision när det gäller värderingar av bostäder på landsbygden. Olika typer av boostade beslutsträd implementerades för att ta itu med denna fråga och deras prestanda jämfördes med traditionella maskininlärningsmetoder. Dessa olika typer av övervakad inlärningsmodeller implementerades för att hitta den bästa modellen med avseende på relevanta prestationsmått som t.ex. root-mean-squared error (RMSE) och mean absolute percentage error (MAPE). De övervakade inlärningsmodellerna var ridge regression, lasso regression, random forest, AdaBoost, gradient boosting, CatBoost, XGBoost, and LightGBM. Samtliga algoritmers prestanda jämförs med Boolis nuvarande bostadsvärderingsalgoritm, som är baserade på en k-NN modell. Resultatet från denna uppsats visar att LightGBM modellen är den optimala modellen för att värdera husen på landsbygden eftersom den hade den bästa totala prestandan med avseende på de utvalda utvärderingsmetoderna. LightGBM modellen jämfördes med Booli modellen där prestandan av LightGBM modellen var i överlag bättre, där LightGBM modellen hade ett RMSE värde på 0.330 jämfört med Booli modellen som hade ett RMSE värde på 0.358. Vilket indikerar att det finns en potential att använda boostade beslutsträd för att förbättra noggrannheten i förutsägelserna av huspriser på landsbygden.
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14

Otunuga, Olusegun Michael. "Stochastic Modeling and Analysis of Energy Commodity Spot Price Processes". Scholar Commons, 2014. https://scholarcommons.usf.edu/etd/5289.

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Supply and demand in the World oil market are balanced through responses to price movement with considerable complexity in the evolution of underlying supply-demand expectation process. In order to be able to understand the price balancing process, it is important to know the economic forces and the behavior of energy commodity spot price processes. The relationship between the different energy sources and its utility together with uncertainty also play a role in many important energy issues. The qualitative and quantitative behavior of energy commodities in which the trend in price of one commodity coincides with the trend in price of other commodities, have always raised the questions regarding their interactions. Moreover, if there is any interaction, then one would like to know the extent of influence on each other. In this work, we undertake the study to shed a light on the above highlighted processes and issues. The presented study systematically deals with the development of stochastic dynamic models and mathematical, statistical and computational analysis of energy commodity spot price and interaction processes. Below we list the main components of the research carried out in this dissertation. (1) Employing basic economic principles, interconnected deterministic and stochastic models of linear log-spot and expected log-spot price processes coupled with non-linear volatility process are initiated. (2) Closed form solutions of the models are analyzed. (3) Introducing a change of probability measure, a risk-neutral interconnected stochastic model is derived. (4) Furthermore, under the risk-neutral measure, expectation of the square of volatility is reduced to a continuous-time deterministic delay differential equation. (5) The by-product of this exhibits the hereditary effects on the mean-square volatility process. (6) Using a numerical scheme, a time-series model is developed and utilized to estimate the state and parameters of the dynamic model. In fact, the developed time-series model includes the extended GARCH model as special case. (7) Using the Henry Hub natural gas data set, the usefulness of the linear interconnected stochastic models is outlined. (8) Using natural and basic economic ideas, interconnected deterministic and stochastic models in (1) are extended to non-linear log-spot price, expected log-spot price and volatility processes. (9) The presented extended models are validated. (10) Closed form solution and risk-neutral models of (8) are outlined. (11) To exhibit the usefulness of the non-linear interconnected stochastic model, to increase the efficiency and to reduce the magnitude of error, it was essential to develop a modified version of extended Kalman filtering approach. The modified approach exhibits the reduction of magnitude of error. Furthermore, Henry Hub natural gas data set is used to show the advantages of the non-linear interconnected stochastic model. (12) Parameter and state estimation problems of continuous time non-linear stochastic dynamic process is motivated to initiate an alternative innovative approach. This led to introduce the concept of statistic processes, namely, local sample mean and sample variance. (13) Then it led to the development of an interconnected discrete-time dynamic system of local statistic processes and (14) its mathematical model. (15) This paved the way for developing an innovative approach referred as Local Lagged adapted Generalized Method of Moments (LLGMM). This approach exhibits the balance between model specification and model prescription of continuous time dynamic processes. (16) In addition, it motivated to initiate conceptual computational state and parameter estimation and simulation schemes that generates a mean square sub-optimal procedure. (17) The usefulness of this approach is illustrated by applying this technique to four energy commodity data sets, the U. S. Treasury Bill Yield Interest Rate and the U.S. Eurocurrency Exchange Rate data sets for state and parameter estimation problems. (18) Moreover, the forecasting and confidence-interval problems are also investigated. (19) The non-linear interconnected stochastic model (8) was further extended to multivariate interconnected energy commodities and sources with and without external random intervention processes. (20) Moreover, it was essential to extend the interconnected discrete-time dynamic system of local sample mean and variance processes to multivariate discrete-time dynamic system. (21) Extending the LLGMM approach in (15) to a multivariate interconnected stochastic dynamic model under intervention process, the parameters in the multivariate interconnected stochastic model are estimated. These estimated parameters help in analyzing the short term and long term relationship between the energy commodities. These developed results are applied to the Henry Hub natural gas, crude oil and coal data sets.
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15

Liu, Xiaodong. "Econometrics on interactions-based models methods and applications /". Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1180283230.

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16

Bunger, R. C. (Robert Charles). "Derivation of Probability Density Functions for the Relative Differences in the Standard and Poor's 100 Stock Index Over Various Intervals of Time". Thesis, University of North Texas, 1988. https://digital.library.unt.edu/ark:/67531/metadc330882/.

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In this study a two-part mixed probability density function was derived which described the relative changes in the Standard and Poor's 100 Stock Index over various intervals of time. The density function is a mixture of two different halves of normal distributions. Optimal values for the standard deviations for the two halves and the mean are given. Also, a general form of the function is given which uses linear regression models to estimate the standard deviations and the means. The density functions allow stock market participants trading index options and futures contracts on the S & P 100 Stock Index to determine probabilities of success or failure of trades involving price movements of certain magnitudes in given lengths of time.
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17

Kiefer, Hua. "Essays on applied spatial econometrics and housing economics". Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1180467420.

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18

Achuo, George. "Partner satisfaction and renewal likelihood in consumer supported agriculture (CSA) : a case study of The Equiterre CSA network". Thesis, McGill University, 2003. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=19555.

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19

Kubheka, Sihle. "Long range dependence in South African Platinum prices under heavy tailed error distributions". Diss., 2016. http://hdl.handle.net/10500/22283.

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South Africa is rich in platinum group metals (PGMs) and these metals are important in providing jobs as well as investments some of which have been seen in the Johannesburg Securities Exchange (JSE). In this country this sector has experienced some setbacks in recent times. The most notable ones are the 2008/2009 global nancial crisis and the 2012 major nationwide labour unrest. Worrisomely, these setbacks keep simmering. These events usually introduce jumps and breaks in data which changes the structure of the underlying information thereby inducing spurious long memory (long range dependence). Thus it is recommended that these two phenomena must be addressed together. Further, it is well-known that nancial returns are dominated by stylized facts. In this thesis we carried out an investigation on distributional properties of platinum returns, structural changes, long memory and stylized facts in platinum returns and volatility series. To understand the distributional properties of the returns, we used two classes of heavy tailed distributions namely the alpha-Stable distributions and generalized hyperbolic distributions. We then investigated structural changes in the platinum return series and changes in long range dependence and volatility. Using Akaike information criterion, the ARFIMA-FIAPARCH under the Student distribution was selected as the best model for platinum although the ARCH e ects were slightly signi cant, while using the Schwarz information criteria the ARFIMA-FIAPARCH under the Normal distribution. Further, ARFIMA-FIEGARCH under the skewed Student distribution and ARFIMA-HYGARCH under the Normal distribution models were able to capture the ARCH effects. The best models with respect to prediction excluded the ARFIMA-FIGARCH model and were dominated by ARFIMA-FIAPARCH model with non-Normal error distributions which indicates the importance of asymmetry and heavy tailed error distributions.
Statistics
M. Sc. (Statistics)
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20

Liu, Ming-Yeh, e 劉明燁. "A study of the impact of neighboring roads on land prices by statistical methods - Taking Taoyuan District as an example". Thesis, 2017. http://ndltd.ncl.edu.tw/handle/6e27wz.

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碩士
國立臺灣大學
統計碩士學位學程
105
Since August 1, 2012, the Taiwan government announced the implementation of the " national system for registering the actual prices of property transactions ", referred to as the Actual Prices Registration System, expect through the transparent trading information flat the rising house prices, help to improve the buyers and the vast number of housing market in the "information unequal" situation. In recent years, countries around the world tend to open the government information, and this study aims to use the open data to study the possible factor on the impact of land prices, the main interesting factor is that how the neighboring traffic way is named by the “road” or “street” to infect the buyers and impact the land prices. The main factors affecting the real estate transactions in addition to reference to the past information in the Actual Prices Registration System, but also by the government assessed land value, but has been criticized deviated from the market value, the results are much lower than the market value, although the government authorities repeatedly reported that the government assessed land value accounted for the proportion of the normal transaction price has reached 90%, but has not been convinced by the community, this paper also aims to include this important factor. This study examines the single land transactions in Taoyuan District in 2016 from the Actual Prices Registration System, with a semi-logarithmic linear model. We found that the average transaction price was significantly increased by 116.22% when the adjacent traffic way was "street" compare to "road". And the government assessed land value has no significant effect on price.
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21

"Exact simulation of SDE: a closed form approximation approach". 2010. http://library.cuhk.edu.hk/record=b5894499.

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Abstract (sommario):
Chan, Tsz Him.
Thesis (M.Phil.)--Chinese University of Hong Kong, 2010.
Includes bibliographical references (p. 94-96).
Abstracts in English and Chinese.
Abstract --- p.i
Acknowledgement --- p.iii
Chapter 1 --- Introduction --- p.1
Chapter 2 --- Monte Carlo method in Finance --- p.6
Chapter 2.1 --- Principle of MC and pricing theory --- p.6
Chapter 2.2 --- An illustrative example --- p.9
Chapter 3 --- Discretization method --- p.15
Chapter 3.1 --- The Euler scheme and Milstein scheme --- p.16
Chapter 3.2 --- Convergence of Mean Square Error --- p.19
Chapter 4 --- Quasi Monte Carlo method --- p.22
Chapter 4.1 --- Basic idea of QMC --- p.23
Chapter 4.2 --- Application of QMC in Finance --- p.29
Chapter 4.3 --- Another illustrative example --- p.34
Chapter 5 --- Our Methodology --- p.42
Chapter 5.1 --- Measure decomposition --- p.43
Chapter 5.2 --- QMC in SDE simulation --- p.51
Chapter 5.3 --- Towards a workable algorithm --- p.58
Chapter 6 --- Numerical Result --- p.69
Chapter 6.1 --- Case I Generalized Wiener Process --- p.69
Chapter 6.2 --- Case II Geometric Brownian Motion --- p.76
Chapter 6.3 --- Case III Ornstein-Uhlenbeck Process --- p.83
Chapter 7 --- Conclusion --- p.91
Bibliography --- p.96
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22

Ivancic, Lorraine Economics Australian School of Business UNSW. "Scanner data and the construction of price indices". 2007. http://handle.unsw.edu.au/1959.4/40782.

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Abstract (sommario):
This thesis explores whether scanner data can be used to inform Consumer Price Index (CPI) construction, with particular reference to the issues of substitution bias and choice of aggregation dimensions. The potential costs and benefits of using scanner data are reviewed. Existing estimates of substitution bias are found to show considerable variation. An Australian scanner data set is used to estimate substitution bias for six different aggregation methods and for fixed base and superlative indexes. Direct and chained indexes are also calculated. Estimates of substitution bias are found to be highly sensitive to both the method of aggregation used and whether direct or chained indexes were used. The ILO (2004) recommends the use of dissimilarity indexes to determine the issue of when to chain. This thesis provides the first empirical study of dissimilarity indexes in this context. The results indicate that dissimilarity indexes may not be sufficient to resolve the issue. A Constant Elasticity of Substitution (CES) index provides an approximate estimate of substitution-bias-free price change, without the need for current period expenditure weights. However, an elasticity parameter is needed. Two methods, referred to as the algebraic and econometric methods, were used to estimate the elasticity parameter. The econometric approach involved the estimation of a system of equations proposed by Diewert (2002a). This system has not been estimated previously. The results show a relatively high level of substitution at the elementary aggregate level, which supports the use a Jevons index, rather than Carli or Dutot indexes, at this level. Elasticity parameter estimates were found to vary considerably across time, and statistical testing showed that elasticity parameter estimates were significantly different across estimation methods. Aggregation is an extremely important issue in the compilation of the CPI. However, little information exists about 'appropriate' aggregation methods. Aggregation is typically recommended over 'homogenous' units. An hedonic framework is used to test for item homogeneity across four supermarket chains and across all stores within each chain. This is a novel approach. The results show that treating the same good as homogenous across stores which belong to the same chain may be recommended.
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23

Chen, Ko-Shan, e 陳國玄. "The Study of the Classification and the Forecasting of the Stock Prices for the Electronic Industry in Taiwan by Using Artificial Neural Networks and Statistical Methods". Thesis, 2004. http://ndltd.ncl.edu.tw/handle/99785920928232192305.

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Abstract (sommario):
碩士
國立成功大學
統計學系碩博士班
92
This paper is to study the application of artificial neural network and statistical method in forecasting tendency of stock market price index and analysis of inner characteristic of stock price trend by using major influence factor of stock price index. According to statistical data that is derived from Taiwan Stock Exchange Corporation, the electronics industry is mainstream industry. For this reason, electronics industry Stock price index is our research target. However, in past research and paper, little is consider about the stock price index by complete variable and approach. Thus, this paper tried to contain effect factor of stock price, including technical variable、macro-economical variable and industry basic variable.   This paper using above variable establish prediction model by regression analysis、time series and back-propagation network forecast tendency of stock market price index in the future. By the same using above variable classify stock price by cluster analysis, and then using discriminate Analysis and probabilistic neural network determine error rate in all groups. Finally, comparing accuracy of all the prediction and classification models.   Experimental result reveal in accuracy of the prediction and classification model. Respectively, the back-propagation network models are best, the second are regression models and the worst are time series models; discriminate Analysis and probabilistic neural network have the same result.
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24

"Barrier option pricing with nonparametric ACE methods". 2013. http://library.cuhk.edu.hk/record=b5549265.

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Abstract (sommario):
有各式各樣的參數與非參數期貨定價模型被廣泛應用於金融領域。其中一些模型的組合能顯著提升期貨定價的準確性。更具體的說,可以先通過參數模型擬合數據,再使用非參數模型學習並修正誤差估價誤差。本論文作為范和Mancini(2009) 結果的延伸,將市場交易的歐式期權價格作為輸入數據,運用「有參數模型指導的非參數定價方法」對障礙期權進行估價。「自動誤差修正估價法」運用非參數方法對由參數估價法產生的誤差進行修正,使得障礙期權的非參數定價模型可以被視為一系列的歐式期權定價的組合。在整個障礙期權的估價過程中,本論文同時提供了一種分數階快速傅裡葉變換的應用,可通過由非參數方法獲得的標的資產對數的存活函數計算標的資產對數最大值分佈的特徵函數。
There are a variety of parametric and nonparametric option pricing models commonly used in Finance. A combination of them can enhance the pricing performance significantly. Specifically, one proposes to fit the data with a parametric method and then correct the pricing errors empirically with a nonparametric learning approach. This thesis extends Fan and Mancini's (2009) model-guided nonparametric method to barrier option pricing using market traded European option data. Adopting automatic correction of errors (ACE) method to estimate the risk neutral conditional survivor function, by which the pricing error of the initial parametric estimates is captured nonparametrically, enables the nonparametric pricing procedure to value a barrier option as a sum of sequence of European options. As a byproduct from the valuation process, this thesis also provides a modified fractional fast Fourier transform technique compute the characteristic function of the running maximum log-price of the underlying asset nonparametrically through the calibrated survivor functions.
Detailed summary in vernacular field only.
Chi, Chengzhan.
Thesis (M.Phil.)--Chinese University of Hong Kong, 2013.
Includes bibliographical references (leaves 38-39).
Abstracts also in Chinese.
Chapter 1 --- Introduction --- p.1
Chapter 2 --- Nonparametric Local Regression Modelling --- p.4
Chapter 2.1 --- Function Estimation by Local Constant --- p.4
Chapter 2.2 --- Function Estimation by Local Linear Regression --- p.5
Chapter 3 --- Nonparametric ACE European Option Pricing --- p.7
Chapter 3.1 --- European Option Prices and Risk Neutral Survivor Functions --- p.7
Chapter 3.2 --- Estimation of Risk Neutral Survivor Functions --- p.10
Chapter 3.2.1 --- Risk Neutral Survivor Functions and Traded Options --- p.10
Chapter 3.2.2 --- Survivor Function Estimation with Nonparametric ACE Method --- p.11
Chapter 3.3 --- Representation of European Option Prices at Log-asset Level and Numerical Example --- p.15
Chapter 4 --- Nonparametric ACE Barrier Option Pricing Framework --- p.20
Chapter 4.1 --- Continuous-time Barrier Option --- p.20
Chapter 4.2 --- Discrete Approximation and Backward Induction --- p.21
Chapter 4.3 --- Decomposed Problems --- p.25
Chapter 5 --- Nonparametric Estimation of Cumulative Distribution Function of M{U+2C7C}(R{U+209C}) --- p.28
Chapter 5.1 --- Survivor Functions and Maxima Probabilities --- p.28
Chapter 5.2 --- Characteristic Functions of Maxima --- p.30
Chapter 5.2.1 --- Algorithm --- p.30
Chapter 5.2.2 --- Preparation --- p.31
Chapter 5.2.3 --- Fast Fourier Transform (FFT) --- p.31
Chapter 5.2.4 --- Fractional Fast Fourier Transform (FRFT) --- p.33
Chapter 5.2.5 --- Derivation of ΦR{U+209C} --- p.34
Chapter 5.3 --- Numerical Experiments --- p.35
Chapter 6 --- Conclusion --- p.37
Bibliography --- p.38
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25

Huang, Wen-ChI, e 黃文奇. "A Research of Housing Market Prices and Court Auction House Prices Applying Spatial Statistics Method-Example Taichung City". Thesis, 2006. http://ndltd.ncl.edu.tw/handle/78601915271822655855.

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Abstract (sommario):
碩士
國立雲林科技大學
財務金融系碩士班
94
The continuous decline in macro-economic conditions has contributed to a slump in real estate market cycle. As a result, there has been a steady increase in mortgage arrears. A large number of mortgage arrears have been released to the court auction housing market. Spatial parameters of data proposed by Pace and Gilley (1997) are used to improve the Simultaneous Autoregression Model (SAR Model for short) of estimated results and enhance accuracy of appraisals for an empirical study in this research. . Information on court auction houses determined by Taichung District Court from the first quarter of 2004 to the forth quarter of 2005 is collected. There are 423 court auction houses located in Taichung City; however, information from Department of Land Administration, Ministry of the Interior showed there were 1096 house transactions at market prices in the same area. The actual transaction prices of concluded real estate announced by Department of Land Administration, M. O. I. and real prices of court auction houses in the same period are served as dependent variables. Independent variables that may affect court auction houses are selected for regression analysis based on SAR to prove that court auction houses indeed have lower bid prices relatively. In the SAR model, main results are found (1)Prices of court auction houses are lower than those of general real estate transactions at market prices via house agents by about 40.55% on average.(2)Middle district. East district.. South district. prices of court auction houses are lower than those of general real estate transactions at market prices via house agents by about 38.74%.(3)West district. .North district. prices of court auction houses are lower than those of general real estate transactions at market prices via house agents by about 30.23%.(4) Bei-Tewn district. prices of court auction houses are lower than those of general real estate transactions at market prices via house agents by about 47.27% .(5)Cei-Tewn district.. Ann-Tewn district. prices of court auction houses are lower than those of general real estate transactions at market prices via house agents by about 36.87%
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26

"Nonparametric regression-based pattern recognition method for stock price movements". 2011. http://library.cuhk.edu.hk/record=b5896684.

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Abstract (sommario):
Poon, Ka Ho.
Thesis (M.Phil.)--Chinese University of Hong Kong, 2011.
Includes bibliographical references (leaves 62-63).
Abstracts in English and Chinese.
Abstract of the thesis entitled --- p.ii
摘要 --- p.iii
Acknowledgements --- p.iv
Chapter Section 1. --- Introduction --- p.1
Chapter Section 2. --- Review of Useful Concepts --- p.4
Chapter 2.1 --- Terms and Methodologies - Pattern Recognition --- p.4
Chapter 2.1.1 --- Rolling Windows --- p.4
Chapter 2.1.2 --- Smoothing Function - Kernel Regression --- p.5
Chapter 2.1.3 --- Filtering Function ´ؤ Search for Extrema --- p.6
Chapter 2.1.4 --- Filtering Function - The Pattern Detection Algorithm --- p.7
Chapter 2.1.5 --- Risk-adjustment Model --- p.10
Chapter Section 3. --- Data and Methodology --- p.12
Chapter 3.1 --- Data --- p.12
Chapter 3.2 --- Methodology --- p.12
Chapter Section 4. --- Results --- p.17
Chapter Section 5. --- Further Extension --- p.21
Chapter Section 6. --- Discussions and Conclusion --- p.22
APPENDIX 1 --- p.23
References --- p.62
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27

Peterson, David John. "Essays on strategic trading, asymmetric information, and asset pricing". Thesis, 1999. http://hdl.handle.net/2429/9910.

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Abstract (sommario):
This thesis presents three models of asset pricing involving non-competitive behavior and asymmetric information. In the first model, a risk averse investor with private information about dividends trades shares over an infinite time horizon with risk neutral uninformed agents. The informed investor trades strategically in equilibrium. The second model also involves an infinite time horizon, but all agents are risk averse and equally informed about dividends. Non-competitive behavior is exogenously specified; price takers trade shares with a strategic investor who accounts for the effects of her trades on the stock price. In this case, an endogenous information asymmetry arises in equilibrium. Closed form equilibria are derived for both models and implications for price dynamics are explored. While the first model constitutes a new extension of the multiperiod Kyle model of insider trading, the second model generates more interesting price dynamics. If the strategic investor manages a large mutual fund, significant risk premia and price volatility may arise in equilibrium. In fact, if mutual fund participation is sufficiently widespread, multiple equilibria may exist. The third model extends the multiperiod Kyle model to a case where the insider observes a noisy signal of the stock's terminal liquidation value. An equilibrium much like Kyle's is derived. Price tends toward value over time, and stock price volatility depends on both the drift and volatility of the insider's private signal. Like the Kyle model, the insider's trading activity leaves no detectable trace in trading volume, expected returns, or price volatility.
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28

(9160868), Jinho Jung. "ESSAYS ON SPATIAL DIFFERENTIATION AND IMPERFECT COMPETITION IN AGRICULTURAL PROCUREMENT MARKETS". Thesis, 2020.

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Abstract (sommario):

First Essay: We study the effect of entry of ethanol plants on the spatial pattern of corn prices. We use pre- and post-entry data from corn elevators to implement a clean identification strategy that allows us to quantify how price effects vary with the size of the entrant (relative to local corn production) and with distance from the elevator to the entrant. We estimate Difference-In-Difference (DID) and DID-matching models with linear and non-linear distance specifications. We find that the average-sized entrant causes an increase in corn price that ranges from 10 to 15 cents per bushel at the plant’s location, depending on the model specification. We also find that, on average, the price effect dissipates 60 miles away from the plant. Our results indicate that the magnitude of the price effect as well as its spatial pattern vary substantially with the size of the entrant relative to local corn supply. Under our preferred model, the largest entrant in our sample causes an estimated price increase of 15 cents per bushel at the plant’s site and the price effect propagates over 100 miles away. In contrast, the smallest entrant causes a price increase of only 2 cents per bushel at the plant’s site and the price effect dissipates within 15 miles of the plant. Our results are qualitatively robust to the pre-treatment matching strategy, to whether spatial effects are assumed to be linear or nonlinear, and to placebo tests that falsify alternative explanations.


Second Essay: We estimate the cost of transporting corn and the resulting degree of spatial differentiation among downstream firms that buy corn from upstream farmers and examine whether such differentiation softens competition enabling buyers to exert market power (defined as the ability to pay a price for corn that is below its marginal value product net of processing cost). We estimate a structural model of spatial competition using corn procurement data from the US state of Indiana from 2004 to 2014. We adopt a strategy that allows us to estimate firm-level structural parameters while using aggregate data. Our results return a transportation cost of 0.12 cents per bushel per mile (3% of the corn price under average conditions), which provides evidence of spatial differentiation among buyers. The estimated average markdown is $0.80 per bushel (16% of the average corn price in the sample), of which $0.34 is explained by spatial differentiation and the rest by the fact that firms operated under binding capacity constraints. We also find that corn prices paid to farmers at the mill gate are independent of distance between the plant and the farm, providing evidence that firms do not engage in spatial price discrimination. Finally, we evaluate the effect of hypothetical mergers on input markets and farm surplus. A merger between nearby ethanol producers eases competition, increases markdowns by 20%, and triggers a sizable reduction in farm surplus. In contrast, a merger between distant buyers has little effect on competition and markdowns.


Third Essay: We study the dynamic response of local corn prices to entry of ethanol plants. We use spatially explicit panel data on elevator-level corn prices and ethanol plant entry and capacity to estimate an autoregressive distributed lag model with instrumental variables. We find that the average-sized entrant has no impact on local corn prices the year of entry. However, the price subsequently rises and stabilizes after two years at a level that is about 10 cents per bushel higher than the pre-entry level. This price effect dissipates as the distance between elevators and plants increase. Our results imply that long-run (2 years) supply elasticity is smaller than short-run (year of entry) supply elasticity. This may be due to rotation benefits that induce farmers to revert back to soybeans, after switching to corn due to price signals the year the plant enters. Furthermore, our results, in combination with findings in essay 2 of this dissertation, indicate that ethanol plants are likely to use pricing strategies consistent with a static rather than dynamic oligopsony competition.
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29

Ferrero, Eduardo Ezequiel. "Dinámica de relajación del modelo de Potts de q estados bidimensional: una contribución a la descripción de propiedades de no-equilibrio en transiciones de fase de primer orden". Doctoral thesis, 2011. http://hdl.handle.net/11086/163.

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Abstract (sommario):
Tesis (Doctor en Física)--Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física, 2011.
Estudiamos el modelo de Potts de q estados bidimensional, que presenta transiciones de fase magnéticas con temperatura de primer (q > 4) y segundo orden (q = 4). Trabajamos con simulaciones tipo Monte Carlo para las cuales implementamos distintas técnicas algorítmicas, incluyendo una implementación en GPUs. No obstante, presentamos también algunos resultados analíticos. Analizamos la Dinámica de Tiempos Cortos en la aproximación de Campo Medio del modelo de Potts con q=2 resolviendo exactamente la ecuación de Fokker-Planck asociada a la dinámica de Glauber. Confirmamos la validez de la hipótesis de escala de la Dinámica de Tiempos Cortos tanto cerca del punto crítico como de puntos spinodales. Mostramos que es posible definir el punto spinodal a partir del comportamiento dinámico del sistema a tiempos cortos. Estudiamos la metaestabilidad asociada a la transición de fase de primer orden para el modelo de Potts de q estados con q > 4. Realizamos un estudio sistemático de la dinámica del modelo de Potts luego de un enfriamiento brusco a temperaturas subcríticas. Para q > 4 advertimos la existencia de diferentes regímenes dinámicos, de acuerdo al rango de temperaturas. Caracterizamos estos regímenes y los correspondientes estados del sistema.
We analyze the bidimensional q-state Potts model, a paradigmatic model in the study of Statistical Mechanics of Critical Phenomena and Phase Transitions, which presents first (q > 4) and second order (q ≤ 4) temperature driven magnetic phase transitions and has shown a very rich dynamic phenomenology. We mostly work on Monte Carlo numerical simulations, for which we have implemented different algorithm techniques, both traditional and original, including an implementation to run code on graphics cards. Nevertheless, we also present analytic results for some cases where this approach was possible. We study the Short Time Dynamics in the Mean-Field approximation for the 2-states Potts model (the Curie-Weiss model) solving the Fockker-Planck equation associated to the Glauber dynamics for this model. We obtain closed-form expressions for the first moments of the order parameter, near to both the critical and spinodal points, starting from different initial conditions. We confirm the validity of the short-time dynamical scaling hypothesis in both cases. We show that it is possible to define the spinodal point through the short time dynamical behaviour of the system; our definition works both for meanfield and short-range interactions systems. We study the the first order phase transition associated metastability for the q-state Potts model with q >4. We show that the spinodal point is clearly separated from the transition point for all q > 4, delimiting an interval of temperatures capable to hold metastable states. We provide numerical evidence for the existence of metastable states associated to the first order phase transition. We analyze the relaxation mechanism from these states to equilibrium. We perform a systematic study about the nonequilibrium dynamics of the Potts model on the square lattice after a quench from infinite to subcritical temperatures. We analyze the long term behaviour of the energy and relaxation time for a wide range of quench temperatures and system sizes. For q > 4 we found the existence of different dynamical regimes, according to quench temperature range. We characterize those regimes and the system’s corresponding states. We analyze in detail the finite size scaling properties of different relaxation times involved, as well as their temperature dependency.
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