Sunday, April 4, 2021

Two kinds of people making money in stock market | in Chinese | 中线思维短线技术操作的人 | 长线思维中线操作的人

April 4, 2021

I like to highlight good arguments. 

  1. 尽量避免长期看股票对操作心理产生的影响,没有好的心态,就没有好的操作
  2. 只要有从不被巨大利益所诱惑,知足常乐的心就够了。

 股市里最赚钱的两种人


在股市中,要想生存长久,首先要学会很多知识,积累丰富的经验,总结出一套适合自己的操作方法。


不管是短线客,还是长线投资者,都要经历几年甚至十几年刻苦的学习,痛苦的磨练,才能在股市里总结出适合自己的操作方式。


下面总结了两种成功的人的操作特点,为炒股的朋友参考。

  

(一)中线思维短线技术操作的人的特点:


1.具有较高水平的技术知识和看盘能力。


2.有一颗永远平静的心脏,任何波澜都干扰不了它的节奏。


3.有自己的操盘计划和纪律,并严格遵守。


4.从不相信任何人和消息。


5.习惯实时看盘,对出现的机会和危险反应迅速,处理果断。


6.一定要学习有中国特色的股市心理学,并能分析出庄家的操作心里和习惯!


7.对政策要有敏感的嗅觉和准确的判断的能力。


注:这种操作是的人需要在股市里长期磨练,经过多次的失败和心灵痛苦的折磨,能成功的太少了。对于大部分散户,不要梦想自己是那万分之一的人,还是选另一种吧!


令人遗憾的是,大多散户都选择了做这种人,他们过于相信自己的能力和老天会赐予他的运气,当他们明白时,也亏得差不多了。我不建议散户这么做,所以我介绍的很少,知识太多,一两句说不完。


(二)长线思维中线操作的人的特点:


1.一般要有自己的工作和生活来源,不靠股票来维持生活。最好是非常忙碌的人,没时间和精力看股票,操作股票。(这条的目的是尽量避免长期看股票对操作心理产生的影响,没有好的心态,就没有好的操作。)


2.只要有从不被巨大利益所诱惑,知足常乐的心就够了。他们从不去赌博,不去猜测明天的事,稳健是他们的原则,他们关心的是什么时后买入,什么时后盈利100%以上卖出。

  

3.有一定的股票知识和技术分析能力。(不用像操盘手那么多,把均线知识和中短线买点技术学会了就够了,当然,要是有股票基本面的分析能力和未来政策和市场导向的判断能力就更好了。)

  

4.他的纪律很简单,低买高卖,高卖了再低买。(一般从买到卖再到买,要2-3年以上)

  

5.利用常人的思维来选择市场的位置是高是低。每月只要听听新闻,看看周边炒股的人盈利情况,大盘的历史位置的分析,来决定是否进入市场。


长线思维的操作条件就更简单了:

  

(1)当听到股市暴跌时,他兴奋的心花怒放,他意识到机会快来了。


(2)当80%的人都长期亏损时。


(3)大盘经过长期下跌(一般是9个月以上),处于历史的底部时。


(4)所有的新闻和你周围的人不再谈论股票,大家谈股色变时。国内实体经济并没有明显变弱或已经低估严重。大多数股票已便宜的让人垂涎,股市出现多只2—3元股票。


(5)此时重仓(50%)买入股票,大盘每下跌10%时曾仓10%直至满仓。大盘上涨不加仓,每上涨50%-100%时减仓一半,涨至150%可考虑清仓。(此时大盘已经很低了,如使用黄金分割最后一个支撑0.19位置作为买点,估计满仓的时候少。要真满仓了,那他就等着买宝马7系了。卖出时间是动态的,要根据他的计划预期和市场热度来决定。)


(6)选择1—2只经过长期研究的股票,1只小盘,1只中大盘,要不同行业和板块。(若你买的股票在大盘上涨中期长时间弱于大盘,你就要降低你的获利预期了,最小也要30%。此时换股已来不及了。)


(7)买入股票后,离开股市,每月只看一次自己买的股票价格和大盘点位。来决定下一步的操作计划。


(8)当所有人都谈论股票时,尤其是从不炒股的人也想买股票了,卖掉股票,一般盈利100%—150%之间。


(9)此时离开股市,一年内不看股票。继续忙工作或出去玩,庆祝自己的胜利。(注:股市就是他家的银行,每1-2年取一回分红罢了。)


总结:贪婪和恐惧是人天生的恶习,谁也无法完全控制。意志坚强的人,可选择做第一种人。剩下的人要想克服恶习,做第二种人是你最佳选择! 而且也不累!


以上分析是大致思路,并不是模式。你要有你的思维和操作习惯。股市千变万化,没有任何一种技术和操作模式是万能的,不同时期要有不同的思维方式。


好的思维方式和操作习惯才是应对股市变化的唯一法宝。

System design: Why I learn Microservice better from Chris Richardson | Hard working | Great teaching techniques

 April 4, 2021

Introduction

It is hard for me to learn system design and be able to compete for a job from Facebook. I am preparing for another onsite in 2021, and I was so excited to learn that I can go to onsite without phone screen this time. I like to learn better this time. 

Being humble 

I came cross the book written by Chris Richardson Microservice pattern, and then I started to read the book, and also watched videos from Chris Richardson. 

I just love to spend time listen his teaching, and then google and find more study material. It is much easy for me to learn this way. 


System design: Chris Richardson | 6.1 The Problem of Microservices and Data Consistency Event Driven Microservices

April 4, 2021

Introduction

It is tough job to learn system design. I do think that it is best option this year to learn Microservice. If I can learn Microservice very well, then I will plan to learn more and learn better. 

6.1 The Problem of Microservices and Data Consistency Event Driven Microservices

Here is the link. 


Saturday, April 3, 2021

System design: Redesigning the Netflix API

 April 3, 2021

Here is the article. 

Decreasing Payload

If we reduce the number of requests to the API to achieve the same user experience, it implies that the payload of each request will need to be larger. While it is possible that this extra payload won’t noticeably impair performance, we still would like to reduce the total number of bits delivered. To do so, we will also be looking at ways to handle partial response through the API. Our goal in this approach will be to conceptualize the API as a database. A database can handle incredible variability in requests through SQL. We want the API to be able to answer questions with the same degree of variability that SQL can for a database. Other implementations, like YQL and OData, offer similar flexibility and we will research them as well. Chattiness and payload size (as well as their impact on the request/response model) are just two examples of the things we are researching in our upcoming API redesign. In the coming weeks, as we get deeper into this work, we will continue to post our thinking to this blog.

System design: Chris richardson: 4.3 Communication Patterns Inter Process Communication Event Driven Microservices | Embracing the Differences : Inside the Netflix API Redesign

April 3, 2021

Here is the link. 

As I discussed in my recent blog post on ProgrammableWeb.com, Netflix has found substantial limitations in the traditional one-size-fits-all (OSFA) REST API approach. As a result, we have moved to a new, fully customizable API. The basis for our decision is that Netflix’s streaming service is available on more than 800 different device types, almost all of which receive their content from our private APIs. In our experience, we have realized that supporting these myriad device types with an OSFA API, while successful, is not optimal for the API team, the UI teams or Netflix streaming customers. And given that the key audiences for the API are a small group of known developers to which the API team is very close (i.e., mostly internal Netflix UI development teams), we have evolved our API into a platform for API development. Supporting this platform are a few key philosophies, each of which is instrumental in the design of our new system. These philosophies are as follows:

  • Embrace the Differences of the Devices
  • Separate Content Gathering from Content Formatting/Delivery
  • Redefine the Border Between “Client” and “Server”
  • Distribute Innovation

I will go into more detail below about each of these, including our implementation and what the benefits (and potential detriments) are of this approach. However, each philosophy reflects our top-level goal: to provide whatever is best for the Netflix customer. If we can improve the interaction between the API and our UIs, we have a better chance of making more of our customers happier.

Embrace the Differences of the Devices

The key driver for this redesigned API is the fact that there are a range of differences across the 800+ device types that we support. Most APIs (including the REST API that Netflix has been using since 2008) treat these devices the same, in a generic way, to make the server-side implementations more efficient. And there is good reason for this approach. Providing an OSFA API allows the API team to maintain a solid contract with a wide range of API consumers because the API team is setting the rules for everyone to follow.

While effective, the problem with the OSFA approach is that its emphasis is to make it convenient for the API provider, not the API consumer. Accordingly, OSFA is ignoring the differences of these devices; the differences that allow us to more optimally take advantage of the rich features offered on each. To give you an idea of these differences, devices may differ on:

  • Memory capacity or processing power, potentially modifying how much content it can manage at a given time
  • Requirements for distinct markup formats and broader device proliferation increases the likelihood of this
  • Document models, some devices may perform better with flatter models, others with more hierarchical
  • Screen real estate which may impact the content elements that are needed
  • Document delivery, some performing better with bits streamed across HTTP rather than delivered as a complete document
  • User interactions, which could influence the metadata fields, delivery method, interaction model, etc.

Our new model is designed to cut against the OSFA paradigm and embrace the differences across devices while supporting those differences equally. To achieve this, our API development platform allows each UI team to create customized endpoints. So the request/response model can be optimized for each team’s UIs to account for unique or divergent device requirements. To support the variability in our request/response model, we need a different kind of architecture, which takes us to the next philosophy…

...

Of course, one drawback to this is that UI teams are often more skilled in technologies like HTML5, CSS3, JavaScript, etc. In this system, they now need to learn server-side technologies and techniques. So far, however, this has been a relatively small issue, especially since our engineering culture is to hire very strong, senior-level engineers who are adaptable, curious and passionate about learning and implementing these kinds of solutions. Another concern is that because the UI teams are implementing server-side adapters, they have the potential to bring down the servers through infinite loops or other processes that are resource intensive. To offset this, we are working on scrubbing engines that will hopefully minimize the likelihood of such mistakes. That said, in the OSFA world, code on the device can just as easily DDOS the server, it is just potentially a bigger problem if it runs on the server.

Yolanda's Journey To Wellness | Real Housewives of Beverly Hills

 April 3, 2021

Here is the link. 

Yolanda's struggle with Lyme Disease, including having her leaking breast implants removed. Watch All Your Favourite Reality Shows Here: https://www.hayu.com/​ Subscribe to the Official Hayu Channel https://www.youtube.com/c/hayu​ Hayu is the place to watch your favourite reality shows whenever and wherever you want. With loads of shows the same day as the U.S. and thousands of episodes of binge-worthy Box Sets from the start, hayu is the undoubted home of reality TV. And if all that wasn't enough, we've got exclusive clips and snippets you can share and your fave stars' social media all in one place. With hayu, you can literally have it all.

System design: Microservice | 4.2 Communication Patterns API Gateway Event Driven Microservices | Optimizing the Netflix API

 April 3, 2021

Here is the article. 


2.5 Partitioning Strategies Event Driven Microservices

April 3, 2021

Here is the link. 

6:09/ 14:07

How to enforce credit limit? 

Order services - placeOrder()

Customer service - updateCreditLimit()

Order management - Order total 

Customer management - Customer - creditLimit 

Partitioning requires you understand the design

Existing monolith:

  • You understand the dependencies
  • But decomposing is a challenge
Greenfield development:
  • No code => no tangled dependencies
  • But no design either!
  • Therefore, do some upfront design/prototyping to understand what you are partitioning
  • Too few
    • Drawbacks of the monolithic architecture
  • Too many - a.k.a.. Nano-service anti-pattern
    • Runtime overhead
    • Potential risk of excessive network hops
    • Potentially difficult to understand system 

communication pattern - sequential or parallel 

Anti-pattern: Distributed monolith
  • Remember the goal
    • Partition your application so that most changes only impact a single service
  • But if you get it wrong
    • Each change requires you to update and deploy all services
  • Therefore: Common closure principle
    • Components that change for the same reason should be packaged together


System design: Learning Microservice | Scalability | THE SCALE CUBE

 April 3, 2021

Here is the article. 

3 DIMENSIONS OF SCALING

The Scale Cube (sometimes known as the “AKF Scale Cube” or “AKF Cube”) is comprised of 3 axes: 

    • X-Axis: Horizontal Duplication and Cloning of services and data
    • Y-Axis: Functional Decomposition and Segmentation - Microservices (or micro-services)
    • Z-Axis: Service and Data Partitioning along Customer Boundaries - Shards/Pods

Scaling with the X Axis of the Scale Cube

The most commonly used approach of scaling a solution is by running multiple identical copies of the application behind a load balancer also known as X-axis scaling. That’s a great way of improving the capacity and the availability of an application.

When using X-axis scaling each server runs an identical copy of the service (if disaggregated) or monolith. One benefit of the X axis is that it is typically intellectually easy to implement and it scales well from a transaction perspective.  Impediments to implementing the X axis include heavy session related information which is often difficult to distribute or requires persistence to servers – both of which can cause availability and scalability problems.  Comparative drawbacks to the X axis is that while intellectually easy to implement, data sets have to be replicated in their entirety which increases operational costs.  Further, caching tends to degrade at many levels as the size of data increases with transaction volumes.  Finally, the X axis doesn’t engender higher levels of organizational scale.

Figure 3 explains the pros and cons of X axis scalability, and walks through a traditional 3 tier architecture to explain how it is implemented.

Scaling with the Y Axis of the Scale Cube
Y-axis scaling (think services oriented architecture, microservices or functional decomposition of a monolith) focuses on separating services and data along noun or verb boundaries.  These splits are “dissimilar” from each other.  Examples in commerce solutions may be splitting search from browse, checkout from add-to-cart, login from account status, etc.  In implementing splits,  Y-axis scaling splits a monolithic application into a set of services. Each service implements a set of related functionalities such as order management, customer management, inventory, etc.  Further, each service should have its own, non-shared data to ensure high availability and fault isolation.  Y axis scaling shares the benefit of increasing transaction scalability with all the axes of the cube.

Further, because the Y axis allows segmentation of teams and ownership of code and data, organizational scalability is increased.  Cache hit ratios should increase as data and the services are appropriately segmented and similarly sized memory spaces can be allocated to smaller data sets accessed by comparatively fewer transactions.  Operational cost often is reduced as systems can be sized down to commodity servers or smaller IaaS instances can be employed.

Figure 4 explains the pros and cons of Y axis scalability and shows a fault-isolated example of services each of which has its own data store for the purposes of fault-isolation.

Scaling with the Z Axis of the Scale Cube

Whereas the Y axis addresses the splitting of dissimilar things (often along noun or verb boundaries), the Z-axis addresses segmentation of “similar” things.  Examples may include splitting customers along an unbiased modulus of customer_id, or along a somewhat biased (but beneficial for response time) geographic boundary.  Product catalogs may be split by SKU, and content may be split by content_id.  Z-axis scaling, like all of the axes, improves the solution’s transactional scalability and if fault isolated it’s availability. Because the software deployed to servers is essentially the same in each Z axis shard (but the data is distinct) there is no increase in organizational scalability.  Cache hit rates often go up with smaller data sets, and operational costs generally go down as commodity servers or smaller IaaS instances can be used.

Figure 5 explains the pros and cons of Z axis scalability and displays a fault-isolated pod structure with 2 unique customer pods in the US, and 2 within the EU.  Note, that an additional benefit of Z axis scale is the ability to segment pods to be consistent with local privacy laws such as the EU’s GDPR.

Summary

Use the Scale Cube to identify opportunities to increase scalability through cloning/replication (X axis), service and resource segmentation (Y axis) and customer/geographical segmentation (Z axis). 
Closely related to the Scale Cube is the Availability Cube.  The two should be considered simultaneously to help architect scalable and available solutions.


Chris Richardson: 2.3 Introduction to the Microservice Architecture Event Driven Microservices

April 3, 2021

Here is the link. 

Sharding - Z-axis scaling, customer ID - data partitioning - scale by splitting 

Function decomposing 

Book - The art of scalability 


Art of Scalability, The: Scalable Web Architecture, Processes, and Organizations for the Modern Enterprise Paperback – Illustrated, June 3 2015

April 3, 2021

I like to spend 30 minutes to look into more about the book. What I can learn quickly from others on this book. 

The Comprehensive, Proven Approach to IT Scalability–Updated with New Strategies, Technologies, and Case Studies

 

In The Art of Scalability, Second Edition, leading scalability consultants Martin L. Abbott and Michael T. Fisher cover everything you need to know to smoothly scale products and services for any requirement. This extensively revised edition reflects new technologies, strategies, and lessons, as well as new case studies from the authors’ pioneering consulting practice, AKF Partners.

 

Writing for technical and nontechnical decision-makers, Abbott and Fisher cover everything that impacts scalability, including architecture, process, people, organization, and technology. Their insights and recommendations reflect more than thirty years of experience at companies ranging from eBay to Visa, and Salesforce.com to Apple.

 

You’ll find updated strategies for structuring organizations to maximize agility and scalability, as well as new insights into the cloud (IaaS/PaaS) transition, NoSQL, DevOps, business metrics, and more. Using this guide’s tools and advice, you can systematically clear away obstacles to scalability–and achieve unprecedented IT and business performance.

 

Coverage includes

• Why scalability problems start with organizations and people, not technology, and what to do about it

• Actionable lessons from real successes and failures

• Staffing, structuring, and leading the agile, scalable organization

• Scaling processes for hyper-growth environments

• Architecting scalability: proprietary models for clarifying needs and making choices–including 15 key success principles

• Emerging technologies and challenges: data cost, datacenter planning, cloud evolution, and customer-aligned monitoring

• Measuring availability, capacity, load, and performance

Microservices Patterns by Chris Richardson

April 3, 2021

Here is the link. 

I like to take time to learn from Chris Richardson. There are 29 videos. I like to watch one by one, and also take notes. I think that it is important to learn some patterns and also the concepts related to Microservices. 



Too soon to say if there's an Archegos 'contagion': Author Rickards

 April 3, 2021

Here is the link. 

CNBC's Dom Chu talks about the potential ripple effect of the Archegos fallout with Jim Rickards, author of “The New Great Depression: Post-Pandemic Winners and Losers." For access to live and exclusive video from CNBC subscribe to CNBC PRO: https://cnb.cx/2NGeIvi​


Archegos fallout: The market is trying to figure out if we are having another Lehman moment: PMC

 April 3, 2021

Here is the link. 

Dana D’Auria, PMC Co-Chief Investment Officer of Envestnet, joins Yahoo Finance's Zack Guzman to break down how the Archegos' margin call default is affecting broader markets and investors' portfolios.

GT stock: 4 Value Stocks That Can Double in a Biden Bull Market

 

Goodyear Tire & Rubber

Another deeply discounted value stock that could double in a Biden bull market is Goodyear Tire & Rubber (NASDAQ:GT). Even after its recent surge, shares of the company can be bought for roughly 11 times forward-year earnings.

The macro catalyst for the highly cyclical Goodyear is the expected rebound in the U.S. and global economy. When U.S. and global gross domestic product are increasing, it's common to see businesses and consumers spending more. That means an expected uptick in business and personal vehicle purchases (i.e., more tires sold).

What's more, rubber future have retraced about 20% from their one-year high set in January. For Goodyear, this means lower input costs and potentially higher margins when demand for tires really picks up. 

Wall Street also seems pleased with the company's $2.8 billion cash-and-stock deal to buy rival Cooper Tire & Rubber. Combining these two companies will enhance Goodyear's leading U.S. market share, broaden its product portfolio in the high-margin light truck and SUV segments, nearly double its presence in the fast-growing China tire market, and lead to an estimated $165 million in cost-savings over the next two years. Suffice it to say, Goodyear could be burning rubber for its shareholders for years to come. 

Stock derivative | 股票衍生品

 金融衍生品

什么东西是金融衍生品?

好评回答
  •   互换 swap。亦作:掉期;互换交易;掉汇。名。指交易双方约定在未来某一时间相互交换资产的协议。更确切地说,互换是当事人之间约定在未来某一期间相互交换现金流量的协议。还可以被当作一系列远期合约的组合。由于两个最终用户之间进行互换很困难,通常需要互换交易商作中介。
      最常见的互换交易为利率互换。参见:利率互换 interest rate swap   互换的种类   1.利率互换:是指双方同意在未来的一定期限内根据同种货币的同样的名义本金交换现金流,其中一方的现金根据浮动利率计算出来,而另一方的现金流根据固定利率计算。
         2.货币互换:是指将一种货币的本金和固定利息与另一货币的等价本金和固定利息进行交换。   3.商品互换:是一种特殊类型的金融交易,交易双方为了管理商品价格风险,同意交换与商品价格有关的现金流。它包括固定价格及浮动价格的商品价格互换和商品价格与利率的互换。
         4.其它互换:股权互换、信用互换、气候互换和互换期权等。   互换交易的优缺点   1、 互换与其他衍生工具相比有着自身的优势   首先,互换交易集外汇市场、证券市场、短期货币市场和长期资本市场业务于一身,既是融资的创新工具,有可运用于金融管理。
         其次,互换能满足交易者对非标准化交易的要求,运用面广。第三,用互换套期保值可以省却对其他金融衍生工具所需头寸的日常管理,使用简便且风险转移较快。第四,互换交易期限灵活,长短随意,最长可达几十年。   最后,互换仓库的产生使银行成为互换的主体,所以互换市场的流动性较强。
         2、 互换交易中的缺点   互换交易本身也存在许多风险.信用风险是互换交易所面临的主要风险,也是互换方及中介机构因种种原因发生的违约拒付等不能履行合同的风险.另外,由于互换期限通常多达数年之久,对于买卖双方来说,还存在着互换利率的风险.   互换交易的风险   1.互换交易风险的承担者   互换交易风险的承担者包括:   ①合同当事者双方。
      在互换交易中他们要负担原有债务或新的债务,并实际进行债务交换。   ②中介银行。它在合同当事人双方的资金收付中充当中介角色。   ③交易筹备者。他的职责在于安排互换交易的整体规则,决定各当事者满意的互换条件,调解各种纠纷等。它本身不是合同当事者,一般由投资银行、商人银行或证券公司担任,收取(一次性)一定的互换安排费用,通常为总额的0.125%~0.375%。
         2.互换交易风险的类型   互换交易风险的类型包括:   ①信用风险   ②政府风险   ③市场风险   ④收支不对应风险   ⑤结算风险 金融衍生品是有关互换现金流量或旨在为交易者转移风险的一种双边合约,常见的有远期合约、期货、期权、掉期等,国际上属于金融衍生品品种繁多,在我国现阶段金融衍生品交易主要指以期货为中心的金融业务。
      期货又可分为商品期货和金融期货,后者主要包括货币期货、利率期货和指数期货。
  • 其他答案

    • 按金融界的定义,金融衍生品是有关互换现金流量或旨在为交易者转移风险的一种双边合约,常见的有远期合约、期货、期权、掉期等,国际上属于金融衍生品品种繁多,在我国现阶段金融衍生品交易主要指以期货为中心的金融业务。期货又可分为商品期货和金融期货,后者主要包括货币期货、利率期货和指数期货。 
      从金融衍生品的种类和定义来看,其最大特征是依托一种投资机制来规避资金运作的风险,同时又具有在金融市场上炒作交易、吸引投资者的功能。

Stock derivative | 股票衍生品

 股票衍生品都有哪些?

股票衍生品都有哪些?

好评回答
  •   衍生品可做如下分类:(1)根据产品形态,可以分为远期、期货、期权和互换四大类。(2)根据原生资产分类,即股票、利率、汇率和商品。如果再加以细分,股票类中又包括具体的股票(股票期货、股票期权合约)和由股票组合形成的股票指数期货和期权合约等;利率类中又可分为以短期存款利率为代表的短期利率(如利率期货、利率远期、利率期权、利率互换合约)和以长期债券利率为代表的长期利率(如债券期货、债券期权合约);货币类中包括各种不同币种之间的比值;商品类中包括各类大宗实物商品。
      (3)根据交易方法,可分为场内交易和场外交易。场内交易即是通常所指的交易所交易,指所有的供求方集中在交易所进行竞价交易的交易方式。场外交易即是柜台交易,指交易双方直接成为交易对手的交易方式,其参与者仅限于信用度高的客户。3·金融衍生产品是指以货币、债券、股票等传统金融产品为基础,以杠杆性的信用交易为特征的金融产品。
      金融衍生工具,是一种特殊类别买卖的金融工具统称。这种买卖的回报率是根据一些其他金融要素的表现情况衍生出来的。
    收起

其他答案

  • 金融衍生产品是指以货币、债券、股票等传统金融产品为基础,以杠杆性的信用交易为特征的金融产品。如:期货、远期合约。)根据产品形态,可以分为远期、期货、期权和掉期四大类。象原生资产金融衍生产品利率短期存款利率期货、利率远期、利率期权、利率掉期合约等长期债券债券期货、债券期权合约等股票股票股票期货、股票期权合约等股票指数股票指数期货、股票指数期权合约等货币各类现汇货币远期、货币期、货币期权、货币掉期合约等商品各类实物商品商品远期、商品期货,商品期权、商品掉期
    全部
  • 股票衍生产品包括股票期权、股指期货、股指期权、股票期货、认股权证、可转换债券等。金融衍生产品种类繁多,结构复杂,而且不断有新的衍生产品出现,根据金融衍生产品的基础资产,可以划分为货币衍生产品、利率衍生产品和股票衍生产品,其中货币衍生产品包括远期外汇合约、外汇期货、外汇期权、货币互换等;利率衍生产品包括远期利率协议、短期利率期货、债券期货、债券期权、利率互换、互换期权等;。

吉他弹唱 成都 赵雷(松枼婷、松枼潇)

Here is the link. 

I like to listen the song and then enjoy good time. I lived in Shanghai city from 1984 to 1996. I had good time to spend over 12 years in Shanghai city. The song of Chengdu, another city brought back a lot of memory about Shanghai, China. 




Friday, April 2, 2021

System design: AWS | Elastic load balancing user guide | 31 pages | reading challenge

 April 2, 2021

Introduction

I like to challenge myself to spend first one hour to read this user guide, and see how much I can learn compared to lecture from Chris Richardson's video: 

4.4 Communication Patterns Service Discovery Event Driven Microservices


30 minutes reading

Here is the pdf link. 


Here's what we know so far about Friday’s margin call

 April 2, 2021

Here is the link.

Shares of ViacomCBS and Discovery both rebounded after coming under intense selling pressure last week. The two companies were believed to be hit by forced liquidation of positions held by the multibillion dollar family office Archegos Capital Management, a source familiar with the situation told CNBC. CNBC's Jim Cramer, Carl Quintanilla and David Faber discuss.

Richardson Maturity Model

 I like to spend 30 minutes to go over the link. 

Here is the link. 


Linkedin.com | Ray Yang | Connections | 2018 August

April 2, 2021

Introduction

It is hard for me to find something interesting to entertain myself. I like to explore Linkedin.com better this time. One idea is to go over those first connections and then go over hundreds of connections. 

One idea 

I like to go over those connections - Ray Yang, Guo Linfeng, Mengyan, Tracy song, and go over their connections. 

I like to find pictures taken in August 2018 with those friends in the city of San Mateo, and post here. 




Facebook virtual onsite invitation: Bravo!

 April 2, 2021

Introduction

It is tough year for all of us. We all try to find better opportunities to help us go through those pandemic challenges. I was so surprised to hear from a Facebook recruiter, and then after less than 30 minutes phone call, I got invited for another virtual onsite interviews. 

Best opportunity

I just could not believe that Facebook provided 100% remote job opportunities in Canada. I already knew the news from wechat friends. I just could not believe that I could be invited again for another round of onsite interviews. 

Learning 

I just could not believe that system design is such challenge for me through so many years, from 2016 to 2021. I was so happy today to spend a few hours today to read the book called Microservice patterns, and then I spent over two hours to watch videos from Chris Richardson. 



Chris Richardson: 4.4 Communication Patterns Service Discovery Event Driven Microservices

April 1, 2021

Here is the link. 

Agenda

  • Why a pattern language for microservices?
  • Core patterns
  • Partitioning strategies
  • Deployment patterns
  • Communication patterns
  • Microservices chassis 
Communication patterns
  • Overview
  • API Gateway
  • Inter-process communication
  • Service discovery
  • Service registration
Pattern: Client-side discovery 

Service client 

Example: Netflix Eureka and Ribbon 

Benefits and drawbacks

Benefits
  • Flexible, application-specific load balancing
  • Fewer network hops and moving parts compared to Server-side discovery
Drawbacks
  • Couples the client to the Service Registry
  • Need implement client-side discovery and load balancing logic in multiple languages/ frameworks
  • Service Registry is yet another moving part to setup and operate - highly available     


Thursday, April 1, 2021

Chris Richardson: 4.2 Communication Patterns API Gateway Event Driven Microservices

 April 1, 2021

Here is the link. 

Forces

  • Mismatch between the fine-grained microservices and needs of the clients
  • Different clients need different data
  • LAN vs. WAN vs. Mobile network performance 
  • The number of service instances and their locations (host + port) changes dynamically 
  • Partitioning into services can change over time and should be hidden from clients
Directly connecting the front-end to the backend 

API gateway pattern vs directly talk to Microservice 

Pattern: API gateway 

Single entry point - API Gateway 

Client specific APIs 
REST catalog service
REST Recommendation service
Thrift Review service 

Protocol translation 

Example: Netflix API 
thousand streaming clients - Device specific end points 


Benefits of the API gateway
  • Insulates the clients from the partitioning
  • Insulates the clients from the problem of discovery
  • Provides the optimal API for each client
  • Reduces the number of requests/ roundtrips
  • Simplifies the client by moving logic for calling multiple services from the client to API gateway
  • Gateway translates between web-unfriendly protocols and HTTP/WebSockets




Chris Richardson: 4.3 Communication Patterns Inter Process Communication Event Driven Microservices

 April 1, 2021

Here is the link. 

The teaching is so good to remind me good days when I was a student in Florida Atlantic University and Shanghai Jiaotong university. 

Thank Facebook to give me another virtual onsite in 2021. 

Interaction styles

Synchronous/ Asynchronous

I always find myself get distract in 20 minutes video. I just like to remind myself to learn one screen, and take notes from the lecture. 

10:20/ 20:20 

Benefits and drawbacks of messaging 

Benefits

  • Decouples client from services
  • Message broker buffers messages
  • Supports a variety of communication patterns
Drawbacks
  • Additional complexity of message broker
  • Request/ reply-style communication is more complex
  • Client needs to discover location of message broker 
Example messaging systems
RabbitMQ, ActiveMQ, Apache Kafka, NSQ

Remote procedure invocation 
REST,
Benefits 
  • Simple and familiar
  • Request/ reply is easy
  • No intermediate broker 
Drawbacks
  • Only supports request/ reply
  • Service must be available
  • Client needs to discover locations of service 
Example RPI mechanisms

REST
  • HTTP-based - super familiar protocol of the web
  • Firewall and human friendly
  • You pick the message format
  • See https://martinfowler.com/articles/richardsonMaturityModel.html
Thrift
  • RPC framework
  • Define services using IDL and generate stubs and skeletons
  • Message formats: Binary, and JSON
  • Transport protocols: TCP, HTTP

How to run out of threads
HTTP -> Tread  -> RPC client code -> Recommendation service

Finite number of threads -> Eventually all threads will be blocked  -> Cannot process any request 

The Netflix approach
  • Network timeouts
  • Invoke remote services via a bounded thread pool -> impose upbound of ... -> fail fast -> tie up any thread 
  • Use the Circuit break pattern 
  • On failure: 
    • return default/ cached data
    • return error to caller


Actionable Items:

Take 30 minutes to review Richardson Maturity model

Richardson Maturity Model

Here is the link. 

6.3 Overview of Event Sourcing Event Driven Microservices

April 1, 2021

Here is the link. 

I like to watch again and take some notes as well. 


Archegos | 中天財經頻道

 April 1, 2021

Here is the link. 

【錢線煉金術】Archegos效應"金融存股?" "隱形護國神山"它待爆發!@中天財經頻道​ 精華版

Archegos | 中天財經頻道

 April 1, 2021

Here is the link. 

錢線煉金術】Archegos讓"銀行損百億?" "美債息.美元"強升隱憂 @中天財經頻道​ 精華版

Mohamed El-Erian on Archegos: It will not cause a massive deleveraging of the financial system

April 1, 2021

Here is the link. 

Yahoo Finance's Seana Smith and Adam Shapiro spoke with Queens' College President, and Allianz Chief Economic Adviser, Mohamed El-Erian about the Archegos blowup and the impact on the financial system.

Archegos fallout: The SWAPs market should have better protection for investors: Heritage Capital

 April 1, 2021

Here is the link. 

#Archegos​ #swaps​ #hedgefund​ Paul Schatz, Heritage Capital President, joins Yahoo Finance’s Alexis Christoforous and Kristin Myers to discuss the Archegos fallout. Subscribe to Yahoo Finance: https://yhoo.it/2fGu5Bb

Credit Suisse and Nomura warn of losses after Archegos fails to meet margin calls

April 1, 2021

Here is the link. 

#Archegos​ #Nomura​ # Yahoo Finance's Julie Hyman and Steve Sosnick, Interactive Brokers chief market strategist, joins Yahoo Finance to discuss the market impact of Archegos defaulting on margin calls. Hedge fund blowup sends shockwaves through Wall Street and the City Oscar Williams-Grut·Senior City Correspondent, Yahoo Finance UK A little known hedge fund that blew up last week has sent shockwaves through the world of investment banking. Shares in Credit Suisse (CSGN.SW) and Nomura (8604.T) sunk over 10% on Monday after both warned they faced potentially billions in losses linked to hedge fund Archegos Capital. Banks that worked with Archegos and lent it money to buy shares were scrambling to offload Archegos' investments after a handful of risky bets made by the hedge fund went bad. The rush to exit these positions hit public shares prices, leaving banks with huge losses. Hedge funds typically borrow money from banks to invest, a process known as margin trading. This allows funds to leverage up the cash they hold and increase their positions — potentially earning far greater returns if their bets come good. However, it also means hedge funds can theoretically lose more money than they hold in client funds. If trades made on margin turn sour, banks will ask a client to put up more money as collateral to limit potential losses. This process is known as a margin call. Archegos faced margin calls on its positions last week but failed to provide extra cash. As a result, banks began selling off stocks held on the hedge fund's behalf — a fire sale known in the City as liquidating positions. The business press reported on Friday that Goldman Sachs (GS) and Morgan Stanley (MS) were selling huge chunks of shares in businesses including ViacomCBS (VIAC), Discovery (DISCA) and Chinese stocks Baidu (BIDU) and Tencent Music (TME). The block sales are estimated to be worth around $20bn (£14.5bn), according to the Financial Times. "Things started going wrong for Archegos when shares of companies such as Viacom started to slide mid-last week," said Michael Brown, a senior market analyst at Caxton Business. "It was at that point that margins were called, and couldn’t be provided, hence the block sales seen Friday." For more on this article please visit: https://uk.finance.yahoo.com/news/arc...