金融学术速递[1.10]
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q-fin金融，共计6篇
【1】 Pricing Bermudan options using regression trees/random forests
标题：使用回归树/随机森林为百慕大期权定价
链接：https://arxiv.org/abs/2201.02587
机构：Univ. Grenoble Alpes, CNRS, Grenoble INP, LJK, Grenoble, France, Quantitative analyst at Natixis, Paris, Pierre Henry Labordère, Head of Quantitative Research cross asset, Natixis, quai d’austerlitz, CMAP, Ecole Polytechnique
摘要：美式期权的价值是期权贴现现金流的最大价值。在每个时间步，需要将即时行使值与延续值进行比较，并在行使值严格大于延续值时决定行使。我们可以将这个问题表述为一个动态规划方程，其中主要的困难来自于计算表示每个时间步的连续值的条件期望。在（Longstaff和Schwartz，2001）中，这些条件期望是使用有限维向量空间（通常是多项式基础）上的回归进行估计的。在本文中，我们遵循相同的算法；仅使用回归树或随机林估计条件期望。讨论了用回归树代替标准最小二乘回归时LS算法的收敛性。最后，我们给出了回归树和随机森林的一些数值结果。随机森林算法在高维上给出了很好的结果。
摘要：The value of an American option is the maximized value of the discounted cash
flows from the option. At each time step, one needs to compare the immediate
exercise value with the continuation value and decide to exercise as soon as
the exercise value is strictly greater than the continuation value. We can
formulate this problem as a dynamic programming equation, where the main
difficulty comes from the computation of the conditional expectations
representing the continuation values at each time step. In (Longstaff and
Schwartz, 2001), these conditional expectations were estimated using
regressions on a finite-dimensional vector space (typically a polynomial
basis). In this paper, we follow the same algorithm; only the conditional
expectations are estimated using Regression trees or Random forests. We discuss
the convergence of the LS algorithm when the standard least squares regression
is replaced with regression trees. Finally, we expose some numerical results
with regression trees and random forests. The random forest algorithm gives
excellent results in high dimensions.
【2】 Stationary GE-Process and its Application in Analyzing Gold Price Data
标题：平稳GE过程及其在金价数据分析中的应用
链接：https://arxiv.org/abs/2201.02568
机构：Department of Mathematics and Statistics, Indian Institute of Technology Kanpur
备注：26 pages
摘要：本文介绍了一个新的离散时间连续状态空间平稳过程$\{X_n；n=1,2,ldots\}$，使得$$X_n$服从双参数广义指数分布。研究了这一新过程的联合分布函数、特征和一些相关性质。GE过程有三个未知参数，两个形状参数和一个尺度参数，因此它比现有的指数过程更灵活。在存在尺度参数的情况下，如果两个形状参数相等，则可通过求解一个非线性方程获得未知参数的最大似然估计；如果两个形状参数是任意的，则可通过求解二维优化问题获得最大似然估计。对两个{彩色{黑色}合成}数据集和一个真实黄金价格数据集进行了分析，以了解所提出模型在实践中的性能。最后指出了一些概括。
摘要：In this paper we introduce a new discrete time and continuous state space
stationary process $\{X_n; n = 1, 2, \ldots \}$, such that $X_n$ follows a
two-parameter generalized exponential (GE) distribution. Joint distribution
functions, characterization and some dependency properties of this new process
have been investigated. The GE-process has three unknown parameters, two shape
parameters and one scale parameter, and due to this reason it is more flexible
than the existing exponential process. In presence of the scale parameter, if
the two shape parameters are equal, then the maximum likelihood estimators of
the unknown parameters can be obtained by solving one non-linear equation and
if the two shape parameters are arbitrary, then the maximum likelihood
estimators can be obtained by solving a two dimensional optimization problem.
Two {\color{black} synthetic} data sets, and one real gold-price data set have
been analyzed to see the performance of the proposed model in practice. Finally
some generalizations have been indicated.
【3】 Applications of Signature Methods to Market Anomaly Detection
标题：签名方法在市场异常检测中的应用
链接：https://arxiv.org/abs/2201.02441
机构：Department of Mathematics, ETH, Zurich, Switzerland, Department of Banking and Finance, University of Zurich, Zurich, Switzerland
摘要：异常检测是识别数据集中显著偏离规范的异常实例或事件的过程。在这项研究中，我们提出了一种基于特征码的机器学习算法来检测给定时间序列类型数据集中的罕见或意外项目。我们提出了签名或随机签名作为异常检测算法的特征提取器的应用；此外，我们还为随机签名的构造提供了一个简单的表示理论依据。我们的第一个应用程序基于合成数据，旨在区分真实和虚假的股价轨迹，这些轨迹通过目视检查无法区分。我们还通过使用加密货币市场的交易数据展示了一个真实的应用程序。在这种情况下，通过我们的无监督学习算法，我们能够识别F1分数高达88%的社交网络上组织的抽水和倾倒尝试，从而获得接近基于监督学习领域最先进水平的结果。
摘要：Anomaly detection is the process of identifying abnormal instances or events
in data sets which deviate from the norm significantly. In this study, we
propose a signatures based machine learning algorithm to detect rare or
unexpected items in a given data set of time series type. We present
applications of signature or randomized signature as feature extractors for
anomaly detection algorithms; additionally we provide an easy, representation
theoretic justification for the construction of randomized signatures. Our
first application is based on synthetic data and aims at distinguishing between
real and fake trajectories of stock prices, which are indistinguishable by
visual inspection. We also show a real life application by using transaction
data from the cryptocurrency market. In this case, we are able to identify pump
and dump attempts organized on social networks with F1 scores up to 88% by
means of our unsupervised learning algorithm, thus achieving results that are
close to the state-of-the-art in the field based on supervised learning.
【4】 Strategic Storage Investment in Electricity Markets
标题：电力市场中的战略储能投资
链接：https://arxiv.org/abs/2201.02290
机构：∗MIT Energy Initiative, Massachusetts Institute of Technology, Cambridge, USA, †Laboratory for Information and Decision Systems (LIDS), Massachusetts Institute of Technology, Cambridge, USA
摘要：套利是电力市场中储能的一个重要收入来源。然而，市场上的大量储存将影响能源价格并减少潜在收入。这可能导致寻求利润的存储投资者的战略行为。为了研究投资者的战略储备投资，我们在相互竞争的投资者之间建立了一个非合作博弈。每个投资者在长期投资期内决定存储投资，并在日常电力市场中运营存储以获得套利收入。不同的投资者可以部署具有不同特征的存储。由于市场价格由所有投资者的决策决定，他们的决策是相互关联的。我们使用来自加利福尼亚ISO的市场数据来描述存储对市场价格的影响，在此基础上，我们建立了一个集中优化问题来计算市场均衡。我们发现，越来越多的投资者将增加市场竞争，这降低了投资者的利润，但增加了总投资存储容量。此外，我们发现存储效率的轻微提高（例如，充电和放电效率的提高）可以显著提高投资者在市场中的利润份额。
摘要：Arbitrage is one important revenue source for energy storage in electricity
markets. However, a large amount of storage in the market will impact the
energy price and reduce potential revenues. This can lead to strategic
behaviors of profit-seeking storage investors. To study the investors'
strategic storage investments, we formulate a non-cooperative game between
competing investors. Each investor decides the storage investment over a long
investment horizon, and operates the storage for arbitrage revenues in the
daily electricity market. Different investors can deploy storage with different
characteristics. Their decisions are coupled due to the market price that is
determined by all the investors' decisions. We use market data from California
ISO to characterize the storage impact on the market price, based on which we
establish a centralized optimization problem to compute the market equilibrium.
We show that an increasing number of investors will increase the market
competition, which reduces investors' profits but increases the total invested
storage capacity. Furthermore, we find that a slight increase in the storage
efficiency (e.g., increased charge and discharge efficiency) can significantly
improve an investor's profit share in the market.
【5】 Neural calibration of hidden inhomogeneous Markov chains -- Information decompression in life insurance
标题：隐含非齐次马氏链的神经标定--人寿保险中的信息解压缩
链接：https://arxiv.org/abs/2201.02397
机构：University of Applied Sciences Ruhr West, Department of Natural Sciences
摘要：马尔可夫链在包括人寿保险数学在内的许多领域发挥着关键作用。作为保费价值的标准精算量可以解释为关于潜在马尔可夫过程的压缩、有损信息。我们介绍了一种方法来重建潜在的马尔可夫链给定的集体信息的合同组合。我们的神经结构通过明确提供一步转移概率来解释该过程的特征。此外，我们提供了一个内在的、经济的模型验证来检验信息解压的质量。最后，我们的方法在德国定期人寿保险合同的实际数据集上得到了成功验证。
摘要：Markov chains play a key role in a vast number of areas, including life
insurance mathematics. Standard actuarial quantities as the premium value can
be interpreted as compressed, lossy information about the underlying Markov
process. We introduce a method to reconstruct the underlying Markov chain given
collective information of a portfolio of contracts. Our neural architecture
explainably characterizes the process by explicitly providing one-step
transition probabilities. Further, we provide an intrinsic, economic model
validation to inspect the quality of the information decompression. Lastly, our
methodology is successfully tested for a realistic data set of German term life
insurance contracts.
【6】 Surveying 5G Techno-Economic Research to Inform the Evaluation of 6G Wireless Technologies
标题：调查5G技术-经济研究为6G无线技术评估提供信息
链接：https://arxiv.org/abs/2201.02272
摘要：技术经济评估是工程师用来评估新通信技术的一项基本技术。然而，尽管第五代蜂窝网络（5G）的技术经济学是一个活跃的研究领域，但令人惊讶的是，对这一不断增长的文献很少有全面的评估。随着移动网络运营商在其网络上部署5G，因此现在是评估当前成就和回顾最新技术的适当时机。这些洞察可以为目前正在进行的6G研究论文提供信息，并帮助工程师在全球范围内提供负担得起的高容量、低延迟宽带连接。该调查讨论了5G技术经济文献中的新兴趋势，并为下一代6G无线技术的设计和标准化提出了六项关键建议。
摘要：Techno-economic assessment is a fundamental technique engineers use for
evaluating new communications technologies. However, despite the
techno-economics of the fifth cellular generation (5G) being an active research
area, it is surprising there are few comprehensive evaluations of this growing
literature. With mobile network operators deploying 5G across their networks,
it is therefore an opportune time to appraise current accomplishments and
review the state-of-the-art. Such insight can inform the flurry of 6G research
papers currently underway and help engineers in their mission to provide
affordable high-capacity, low-latency broadband connectivity, globally. The
survey discusses emerging trends from the 5G techno-economic literature and
makes six key recommendations for the design and standardization of Next
Generation 6G wireless technologies.
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