词汇:let

vt. 允许,让;出租;假设;妨碍

相关场景

Do not let people think you do not belong, because I promise you once you sit at these tables at these fancy places with folks with fancy titles and they got a big bank account.
>> They just folk
I'll show you how it's done. That's painful. Let's switch.
>> 117-state
To begin with let's plan who to invite.
>> 116-get in shape
首先,让我们计划邀请谁。
11.9:
Uh, today I leave the company. Um they let me go.I have nothing to say. It's the good time,it's the bad time. Sometimes something you don't want,But when they lose you feel sad. Maybe the people Who I worked with. I didn't have new colleagues for a long time. I also feel sorry for them. I could be a good colleague and a good employee for the company. But I can't fit in the team and can't do well with the manager. I always think I'm the manager. I struggle to fit in the group. I'm not comfortable with this type of job. I'm not cut out for this job. This job doesn't suit me. I remain appreciate them.
>> 碎碎念 muttering
11.2:
I'm glad to join the chatting group. When I search the keywords 'English corner' , I found this channel and I followed . First let me introduce myself. I'm in the city of wuhan, I live close to the Yangtze river. In summer I go swimming in the Yangtze River a lot. I can swim a few hundred meters upstream in the river for half an hour. When you swim upstream against the current, you can't stop, if you stop you will flow downstream. It's like if you don't make progress, you will be pushed back. You must hold on and keep swimming . You will feel hot, even through you are swimming in cold river water. After the whole summer exercise I feel healthier.
>> 碎碎念 muttering
Could you let me know If anybody else has gotten a raise in the past five years?
>> 114- Intimidating
Let me just add that the dip tastes great.
>> 113-express opinions
让我补充一点,蘸酱味道很好。
Next time maybe don't Let me run the show. I kind of ruin things when it gets bizarre.
>> 112-retreat
下次也许别让我来主持这个节目。当事情变得奇怪时,我会把事情搞砸。
Suppose we use a decay of 3 in our simulation settings. The final vector of weights in the Alpha would be calculated by combining today’s value with the previous day’s decayed value. In our example, we calculated the normalized weights in the Alpha as of February 2nd. Let’s assume that the normalized weights of stocks in the Alpha vector on February 1st and January 31st are as shown in Columns N and O, respectively.
>> worldquantbrain_4_program
假设我们在模拟设置中使用3的衰减。Alpha中的最终权重向量将通过将今天的值与前一天的衰减值相结合来计算。在我们的示例中,我们计算了截至2月2日的Alpha中的归一化权重。假设2月1日和1月31日Alpha向量中股票的归一化权重分别如N列和O列所示。
我感到非常失望。
Let's talk about the relative clauses!
>> 111-newsletter-relationship-goals
让我们来谈谈相关条款!
Let's begin by identifying stocks with more 'long position advantage' news events. Since nws12_afterhsz_sl has multiple daily values per company, we'll aggregate these into a single representative value using the vec_avg operator.
>> worldquantbrain_2
让我们从识别具有更多“多头头寸优势”新闻事件的股票开始。由于nws12_afterhsz_sl每个公司都有多个每日值,我们将使用vec_avg运算符将这些值聚合为一个代表性值。
This time, let's create an Alpha using the difference in implied volatility between put and call options. Create an Alpha that includes the difference between these two values. You can also assign and use variables like: iv_difference = {comparison_operator}(implied_volatility_call_{expiry},implied_volatility_put_{expiry});
>> worldquantbrain
Options:
Options are contracts within the derivatives market, which give the right, but not the obligation, to buy or sell an underlying security at a specific strike price. Since it's a right and not an obligation, the option holder doesn't have to buy or sell the stock when it expires. The amount paid to have this option is called the option premium, which can be simply understood as the price of the option. Options are good indicators of market participants' psychology and can be useful in exploring Alpha signals. Let's learn some basic knowledge needed to use option data for Alpha exploration.
>> worldquantbrain
期权是衍生品市场中的合约,它赋予以特定执行价格买卖标的证券的权利,但不是义务。由于这是一种权利而不是义务,期权持有人在股票到期时不必买卖股票。为获得此期权而支付的金额称为期权溢价,可以简单地理解为期权的价格。期权是市场参与者心理的良好指标,在探索阿尔法信号方面很有用。让我们学习一些使用阿尔法勘探期权数据所需的基本知识。
Cross-Sectional Operators:
Let's imagine that the student's classmates scored around 90 points on this test. From a comparative perspective, it might be hard to say they achieved an excellent score. Similarly, Cross-Sectional operators resemble this second method of comparing with other students' current test scores.
>> worldquantbrain
让我们想象一下,这个学生的同学在这次考试中得了大约90分。从比较的角度来看,很难说他们取得了优异的成绩。同样,横截面运算符类似于与其他学生当前考试成绩进行比较的第二种方法。
Let's imagine a student who scored 80 points on a test. There are two main ways to evaluate this score: comparing it with their own past scores or comparing it with other students' scores on this test.
>> worldquantbrain
让我们想象一个学生在考试中得了80分。有两种主要的方法来评估这个分数:将其与自己过去的分数进行比较,或者将其与其他学生在这次测试中的成绩进行比较。
enterprise_value / ebitda:
Let's create an Alpha using Enterprise Value (enterprise_value) and EBITDA. Try creating an Alpha using your preferred comparison method. The most straightforward approach is to simply calculate EV/EBITDA for each company and rank them, with lower values potentially indicating more attractive investments.
>> worldquantbrain
让我们使用企业价值(Enterprise_Value)和息税折旧摊销前利润创建一个Alpha。尝试使用您喜欢的比较方法创建Alpha。最直接的方法是简单地计算每家公司的EV/EBITDA并对其进行排名,较低的值可能表明投资更具吸引力。
EBITDA:
You can create more meaningful Alphas by combining PV (Price-Volume) data with fundamental data. Let's examine an Alpha that utilizes company valuation metrics by combining Enterprise Value, a PV-related metric, with EBITDA, a fundamental data point.
>> worldquantbrain
通过将PV(价格-交易量)数据与基本数据相结合,您可以创建更有意义的Alphas。让我们检查一个阿尔法,它通过将企业价值(一个与PV相关的指标)与息税折旧摊销前利润(一个基本数据点)相结合,利用公司估值指标。
Let's create an Alpha using operating income and market capitalization (cap). Try creating an Alpha using your preferred comparison method. Initially, the signal might not be as strong as desired. But don't worry! We'll learn how to improve this in the next steps.
>> worldquantbrain
让我们使用营业收入和市值(cap)创建一个Alpha。尝试使用您喜欢的比较方法创建Alpha。最初,信号可能不如预期的那么强。但别担心!我们将在接下来的步骤中学习如何改进这一点。
PV (Price-Volume):
You can create more meaningful Alphas by combining PV (Price-Volume) data with fundamental data. Let's examine an Alpha that utilizes company profitability rankings by combining market capitalization (cap), one of the PV data points, with operating income, a fundamental data point.
>> worldquantbrain
通过将PV(价格-交易量)数据与基本数据相结合,您可以创建更有意义的Alphas。让我们来研究一个阿尔法,它通过将光伏数据点之一的市值(cap)与基本数据点营业收入相结合,利用公司盈利能力排名。
Assets, equity, and debt:
The most representative fundamental data fields are assets, equity, and debt. Let's get a feel for fundamental data by using one or more of these three data fields. Assets, equity, and debt are basic fundamental data fields from the balance sheet. Come up with alpha ideas related to these three data fields, and simulate an alpha that includes at least one of these data fields.
>> worldquantbrain
最具代表性的基本数据字段是资产、股权和债务。让我们通过使用这三个数据字段中的一个或多个来了解基本数据。资产、权益和债务是资产负债表中的基本数据字段。提出与这三个数据字段相关的alpha想法,并模拟一个包含至少一个数据字段的alpha。
Let's explore fundamental data: Fundamentals capture the underlying business, financial and operational health of a company, usually reported every quarter. This data is typically based on financial statements and plays an important role in investment decision-making.
>> worldquantbrain
让我们探讨一下基本数据:基本面数据反映了公司的基本业务、财务和运营状况,通常每季度报告一次。这些数据通常基于财务报表,在投资决策中起着重要作用。
There are certain criteria to be "submitted" to the BRAIN Alpha Pool, as performance verification is necessary. BRAIN requires passing various tests for Alpha submission. Let's look at the submission criteria for Delay1 Alpha in the USA region. Note that submission criteria vary slightly depending on region and Delay. You can view detailed submission criteria for each region and Delay on the submission criteria explanation page.
>> worldquantbrain
有一些标准需要“提交”给BRAIN阿尔法池,因为性能验证是必要的。BRAIN需要通过各种测试才能提交Alpha。让我们看看美国地区Delay1 Alpha的提交标准。请注意,提交标准因地区和延迟而异。您可以在提交标准说明页面上查看每个地区和延迟的详细提交标准。
trade_when:
Let's set entry conditions. Based on the hypothesis that momentum works when volume surges, we can detect volume increases using these methods: volume > adv20 #adv20: 20-day average volume volume > ts_mean(volume, N_DAYS) volume * vwap > ts_mean(volume * vwap, N_DAYS) You can test different values for N_DAYS. Since momentum is a long-term effect, it's effective to set the exit condition to –1 to keep positions longer once established. Or you can set your own exit condition which you think is effective. Also, since momentum effects tend to occur across industries rather than within them, it's better to set Neutralization options to avoid overly detailed grouping such as Market or Sector.
>> worldquantbrain
VWAP Volume-Weighted Average Price:
VWAP can represent a day's stock price, which is the volume-weighted average price. Since low-volume trades might give a false picture of other price indicators like closing price, VWAP can be a better measure of that day's price. Let's look at this table:
>> worldquantbrain