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71	Relative or Discounted Cash Flow Valuation on the Fifty Largest US-Based Corporations on Nasdaq : Which of these valuation methods provides the most accurate valuation forecast? Öhrner, Marcus, Öhman, Otto January 2023 (has links) The topic of this Bachelor Thesis is “Which of these valuation methods provides the most accurate valuation forecast”. Assuming that the year is 2020, the goal of this thesis is to forecast the future stock prices of the fifty largest US-based companies on the Nasdaq stock exchange for 2021 and 2022. By using a quantitative method and looking ten years back at historical data. We determine which valuation method provides the most accurate stock price when conducted in a non-sector specific sample by comparing predicted prices to actual stock prices and discussing the results. There are several ways to evaluate a company and the ones being utilized in this thesis are the discounted cash flow valuation method, the price-to-earnings ratio method (equity multiple), and enterprise value to enterprise value before interest, tax, and depreciation (firm multiple). Our results show that when reviewing the valuations of multiple companies in different sectors the relative valuation methods provide better predictions with EV/EBITDA rather than the discounted cash flow method. This thesis provides the reader with a comprehensive overview of these different valuation methods and their effectiveness in providing valuation forecasts. The result of this thesis is beneficial for policymakers, investors, and financial analysts when forecasting future stock prices. Discounted Cash Flow Dividend Discount Model Earnings Before Interest and Taxes Earnings Before Interest Taxes Depreciation and Amortization Depreciation and Amortization ratio Free Cash Flow to Firm Free Cash Flow to Equity Mean Absolute Error Price-to-Earnings Ratio PricewaterhouseCoopers Riskless Rate Root Mean Square Error Return on Capital United States Weighted Average Cost of Capital Business Administration Företagsekonomi
72	The Application of Multiuser Detection to Spectrally Efficient MIMO or Virtual MIMO SC-FDMA Uplinks in LTE Systems. Ben Salem, Aymen 20 December 2013 (has links) Single Carrier Frequency Division Multiple Access (SC-FDMA) is a multiple access transmission scheme that has been adopted in the 4th generation 3GPP Long Term Evolution (LTE) of cellular systems. In fact, its relatively low peak-to-average power ratio (PAPR) makes it ideal for the uplink transmission where the transmit power efficiency is of paramount importance. Multiple access among users is made possible by assigning different users to different sets of non-overlapping subcarriers. With the current LTE specifications, if an SC-FDMA system is operating at its full capacity and a new user requests channel access, the system redistributes the subcarriers in such a way that it can accommodate all of the users. Having less subcarriers for transmission, every user has to increase its modulation order (for example from QPSK to 16QAM) in order to keep the same transmission rate. However, increasing the modulation order is not always possible in practice and may introduce considerable complexity to the system. The technique presented in this thesis report describes a new way of adding more users to an SC-FDMA system by assigning the same sets of subcarriers to different users. The main advantage of this technique is that it allows the system to accommodate more users than conventional SC-FDMA and this corresponds to increasing the spectral efficiency without requiring a higher modulation order or using more bandwidth. During this work, special attentions wee paid to the cases where two and three source signals are being transmitted on the same set of subcarriers, which leads respectively to doubling and tripling the spectral efficiency. Simulation results show that by using the proposed technique, it is possible to add more users to any SC-FDMA system without increasing the bandwidth or the modulation order while keeping the same performance in terms of bit error rate (BER) as the conventional SC-FDMA. This is realized by slightly increasing the energy per bit to noise power spectral density ratio (Eb/N0) at the transmitters. SC-FDMA SC-FDE 3GPP Long Term Evolution Single Carrier Systems Single Carrier Systems Single Carrier FDE Single Carrier FDMA Localized Subcarrier Mapping Distributed Subcarrier Mapping OFDMA MIMO SC-FDMA Spatial Diversity Gain Spatial Multiplexing Gain MIMO Channel SIMO Channel Space Diversity on Receive Techniques Selection Combining Equal-gain Combining Maximal-ratio Combining MRC Channel Equalization Zero-forcing Equalization Minimum Mean-square Error Equalization ZF MMSE SC-FDMA with Multiuser Detection Link Level Simulation V-blast
73	The Application of Multiuser Detection to Spectrally Efficient MIMO or Virtual MIMO SC-FDMA Uplinks in LTE Systems. Ben Salem, Aymen January 2014 (has links) Single Carrier Frequency Division Multiple Access (SC-FDMA) is a multiple access transmission scheme that has been adopted in the 4th generation 3GPP Long Term Evolution (LTE) of cellular systems. In fact, its relatively low peak-to-average power ratio (PAPR) makes it ideal for the uplink transmission where the transmit power efficiency is of paramount importance. Multiple access among users is made possible by assigning different users to different sets of non-overlapping subcarriers. With the current LTE specifications, if an SC-FDMA system is operating at its full capacity and a new user requests channel access, the system redistributes the subcarriers in such a way that it can accommodate all of the users. Having less subcarriers for transmission, every user has to increase its modulation order (for example from QPSK to 16QAM) in order to keep the same transmission rate. However, increasing the modulation order is not always possible in practice and may introduce considerable complexity to the system. The technique presented in this thesis report describes a new way of adding more users to an SC-FDMA system by assigning the same sets of subcarriers to different users. The main advantage of this technique is that it allows the system to accommodate more users than conventional SC-FDMA and this corresponds to increasing the spectral efficiency without requiring a higher modulation order or using more bandwidth. During this work, special attentions wee paid to the cases where two and three source signals are being transmitted on the same set of subcarriers, which leads respectively to doubling and tripling the spectral efficiency. Simulation results show that by using the proposed technique, it is possible to add more users to any SC-FDMA system without increasing the bandwidth or the modulation order while keeping the same performance in terms of bit error rate (BER) as the conventional SC-FDMA. This is realized by slightly increasing the energy per bit to noise power spectral density ratio (Eb/N0) at the transmitters. SC-FDMA SC-FDE 3GPP Long Term Evolution Single Carrier Systems Single Carrier Systems Single Carrier FDE Single Carrier FDMA Localized Subcarrier Mapping Distributed Subcarrier Mapping OFDMA MIMO SC-FDMA Spatial Diversity Gain Spatial Multiplexing Gain MIMO Channel SIMO Channel Space Diversity on Receive Techniques Selection Combining Equal-gain Combining Maximal-ratio Combining MRC Channel Equalization Zero-forcing Equalization Minimum Mean-square Error Equalization ZF MMSE SC-FDMA with Multiuser Detection Link Level Simulation V-blast
74	Statistical Inference Chou, Pei-Hsin 26 June 2008 (has links) In this paper, we will investigate the important properties of three major parts of statistical inference: point estimation, interval estimation and hypothesis testing. For point estimation, we consider the two methods of finding estimators: moment estimators and maximum likelihood estimators, and three methods of evaluating estimators: mean squared error, best unbiased estimators and sufficiency and unbiasedness. For interval estimation, we consider the the general confidence interval, confidence interval in one sample, confidence interval in two samples, sample sizes and finite population correction factors. In hypothesis testing, we consider the theory of testing of hypotheses, testing in one sample, testing in two samples, and the three methods of finding tests: uniformly most powerful test, likelihood ratio test and goodness of fit test. Many examples are used to illustrate their applications. finite population correction factor statistical hypothesis type I error composite hypothesis power Central limit theorem Basu theorem critical value goodness of fit test likelihood ratio test Lehmann-Scheffe theorem complete statistic ancillary statistic P-value type II error Rao-Blackwell theorem simple hypothesis one-sided test two-sided test significance level sufficient statistic alternative hypothesis testing hypothesis null hypothesis rejection region confidence interval confidence level minimum variance unbiased estimator interval estimation uniformly most powerful test Cramer-Rao inequality likelihood function mean square error moment estimator error of estimation point estimation maximum likelihood estimator bias consistent estimator minimal sufficient statistic factorization theorem unbiased estimator statistic most powerful test test statistics Neyman-Pearson lemma decision rule
75	Evaluation of Target Tracking Using Multiple Sensors and Non-Causal Algorithms Vestin, Albin, Strandberg, Gustav January 2019 (has links) Today, the main research field for the automotive industry is to find solutions for active safety. In order to perceive the surrounding environment, tracking nearby traffic objects plays an important role. Validation of the tracking performance is often done in staged traffic scenarios, where additional sensors, mounted on the vehicles, are used to obtain their true positions and velocities. The difficulty of evaluating the tracking performance complicates its development. An alternative approach studied in this thesis, is to record sequences and use non-causal algorithms, such as smoothing, instead of filtering to estimate the true target states. With this method, validation data for online, causal, target tracking algorithms can be obtained for all traffic scenarios without the need of extra sensors. We investigate how non-causal algorithms affects the target tracking performance using multiple sensors and dynamic models of different complexity. This is done to evaluate real-time methods against estimates obtained from non-causal filtering. Two different measurement units, a monocular camera and a LIDAR sensor, and two dynamic models are evaluated and compared using both causal and non-causal methods. The system is tested in two single object scenarios where ground truth is available and in three multi object scenarios without ground truth. Results from the two single object scenarios shows that tracking using only a monocular camera performs poorly since it is unable to measure the distance to objects. Here, a complementary LIDAR sensor improves the tracking performance significantly. The dynamic models are shown to have a small impact on the tracking performance, while the non-causal application gives a distinct improvement when tracking objects at large distances. Since the sequence can be reversed, the non-causal estimates are propagated from more certain states when the target is closer to the ego vehicle. For multiple object tracking, we find that correct associations between measurements and tracks are crucial for improving the tracking performance with non-causal algorithms. evaluation target tracking multiple sensors non-causal smoother smoothing tracking vehicle tracking camera lidar estimate estimation prediction vehicle dynamics sensor fusion real-time tracking extended kalman filter filter validation validation position estimation velocity estimation dynamic model model complexity multi object tracking multiple object tracking single object tracking data association tracking fundamentals iterated kalman filter track management gnn global nearest neighbour mahalanobis mahalanobis distance performance evaluation differential gps dgps roi ego several sensors sensors rmse root mean square error invertible motion anti-causal motion anti-causal tracking constant velocity gnn imu tfs two filter smoother ekf rts radar inertial measurement unit nonlinear nonlinear systems mono camera monocular camera noise model tracking performance fixed interval smoothing m/n logic centralized fusion non-causal object tracker car tracking car dynamics automotive active safety object tracking automotive industry thesis master reverse dynamics reverse tracking reverse sequence sequence tracking data propagation ground truth estimating ground truth additional sensors mounted sensors true estimates environment comparison algorithm independent targets overlapping measurements occluded track switch improve lower uncertainty more certain state process noise covariance sampling image sprt adas cnn cv pdf track target ego tracker tentative track observatiom online tracking offline tracking online offline recorded sequences robust self driving self-driving car traffic trajectory true state scenario scenarios future accurate output advanced driver assistance systems non-linear complex noise pedestrian truck bus maneuvering vehicles processed measurement frame state correction probability density function tuning likelihood transition measurement motion model recursion gaussian approximation distribution linear jacobian multiplicative noise ratio ad hoc ad hoc state space approach backward auction euclidean distance statistical threshold gating association margin normalize covariance matrix fusion confirmed rejected tentative history absolute error modular ego motion parameters variables logg hardware specification fused causal factorization independent uncorrelated transform moving rotation translation oncoming overtaking Control Engineering Reglerteknik

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