In this paper we investigate the potential of the analysis of noisy non-stationary time series by quantizing it into streams of discrete symbols and applying finite-memory symbolic predictors. The main argument is that careful quantization can reduce the noise in the time series to make model estimation more amenable given limited numbers of samples that can be drawn due to the non-stationarity in the time series. As a main application area we study the use of such an analysis in a realistic setting involving financial forecasting and trading. In particular, using historical data, we simulate the trading of straddles on the financial indexes DAX and FTSE 100 on a daily basis, based on predictions of the daily volatility differences in the underlying indexes. We propose a parametric, data-driven quantization scheme which transforms temporal patterns in the series of daily volatility changes into grammatical and statistical patterns in the corresponding symbolic streams. As symbolic predictors operating on the quantized streams we use the classical fixed-order Markov models, variable memory length Markov models and a novel variation of fractal-based predictors introduced in its original form in (Tino, 2000b). The fractal-based predictors are designed to efficiently use deep memory. We compare the symbolic models with continuous techniques such as time-delay neural networks with continuous and categorical outputs, and GARCH models. Our experiments strongly suggest that the robust information reduction achieved by quantizing the real-valued time series is highly beneficial. To deal with non-stationarity in financial daily time series, we propose two techniques that combine ``sophisticated" models fitted on the training data with a fixed set of simple-minded symbolic predictors not using older (and potentially misleading) data in the training set. Experimental results show that by quantizing the volatility differences and then using symbolic predictive models, market makers can generate a statistically significant excess profit. However, with respect to our prediction and trading techniques, the option market on the DAX does seem to be efficient for traders and non-members of the stock exchange. There is a potential for traders to make an excess profit on the FTSE 100. We also mention some interesting observations regarding the memory structure in the studied series of daily volatility differences. (author's abstract) / Series: Report Series SFB "Adaptive Information Systems and Modelling in Economics and Management Science"

Significant diagonal cracking in reinforced concrete inverted-T (IT) straddle bent caps has been reported throughout the State of Texas. Many of the distressed structures were recently constructed and have generally been in service for less than two decades. The unique nature of the problem prompted a closer look into the design and behavior of such structural components. A preliminary investigation highlighted outdated design requirements and a scarcity of experimental investigations pertaining to inverted-T bent caps. This research project (TxDOT Project 0-6416, Shear Cracking in Inverted-T Straddle Bents) aims to improve current understanding of the behavior of inverted-T caps, while providing updated design provisions. In order to develop strength and serviceability guidelines for inverted-T beams, an extensive experimental program was developed. This series of large scale tests was used to evaluate the strength and serviceability of IT deep beams in relation to the following parameters – shear span-to-depth (a/d) ratio, web reinforcement ratio, ledge height, ledge length, number of point loads, and member depth. This report focuses mainly on results from a first series of tests conducted within this experimental program. / text

Straddles and strangles are common trading strategies introduced in a lot of textbooks and are widely used for option market participants. However, to our knowledge, we might not know how these trades should be designed, which trades are preferable, and how they are constructed in practice. Thus, we want to apply and discuss straddles and strangles as our trading strategies to the practical market. In our research paper, focusing on the time value and finding some profitable strategies are the two important concepts of our straddles and strangles. Being a sell side to earn the time value is our main goal. Although we may take higher risk, time value decay is helpful for us. The research focuses on straddles and strangles by using historical data of TAIEX futures and options. We use the closing price and settlement price as our trading price from data period January 2005 to December 2010. We also compare two different situations, holding positions to maturity and early offset condition, to our straddles and strangles. The findings show that the straddle strategies have positive earnings by holding positions to maturity, and 3 out of 4 strangle strategies have the same results. We can indeed earn the time value as a seller because time value decays quickly for the last seven days of the options contracts. After considering the early offset condition, the profitability of the ATM straddle and strangles become worse. We might easily fall into a trap in which the index futures price fluctuates greatly for a few days and comes back to the normal level on the settlement date. Therefore, we encounter loss due to selling low and buying high so that the trading performance is poor compared with the positions held to the end. Key words: Straddle Strategy, Strangle Strategy, Time Value, Settlement, Early Offset, TAIEX Options, TAIEX Futures