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[^1]: [HTML Color Codes](https://html-color.codes)
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## 0) 面试题
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## 面试题
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<s>The sample question for Interview a job in Binary.com. Here I try to write a web application which is automatically gather data, calculate, forecast, place orders, settlement and also P&L report from tip-to-toe. Here I also conducting few research tasks to test the efficiency of some statistical models, and also refer to a [Master Degree level quantitave assignment](https://github.com/englianhu/Quant-Strategies-HFT) as my studies. Hope that I can be shortlisted to be a member of Binary.com.</s>
Kindly refer to [Binary.com Interview Q1](http://rpubs.com/englianhu/binary-Q1) ([Old link](https://englianhu.github.io/2017/09/binary-forex-trading-Q1.html) or [Alternate link](http://rpubs.com/englianhu/binary-forex-trading-Q1) or [Alternate link 2 (Added MSE comparison)](http://rpubs.com/englianhu/binary-Q1-Added)) for more information.
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- 澳美兑换（AUDUSD）
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- 欧美兑换（EURUSD）
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- 英美兑换（GBPUSD）
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- 美加兑换（USDCAD）
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- 美瑞兑换（USDCHF）
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- 美中兑换（USDCNY）
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- 美日兑换（USDJPY）
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Well, dataset for below papers daily OHLCV of 7 currencies from 2013-01-01 to 2017-08-31:
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一）[次元期权面试题一 - 延伸版（英）](http://rpubs.com/englianhu/binary-Q1E) or ([备用网址](http://rpubs.com/englianhu/316133))尝试使用多元计数/机数模型来评估与比较多元货币每日兑换率。
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- AUDUSD
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- EURUSD
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- GBPUSD
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- USDCAD
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- USDCHF
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- USDCNY
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- USDJPY
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二）[广义自回归条件异方差模型中的`ARIMA(p,d,q)`参数最优化](http://rpubs.com/englianhu/binary-Q1FiGJRGARCH)筹算出规律`p,d,q`最优值，并将之应用于广义自回归条件异方差模型提升计数/机数模型的算卜/预测精准度。[次元期权面试试题一 - 广义自回归条件异方差模型中的`ARCH in Mean`](http://rpubs.com/englianhu/binary-Q1-archm)比较ARCHM和非ARCHM的原模型。
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1) Here I wrote another extention page for Q1 which is analyse the multiple currencies and also models <s>from minutes to</s> daily. You are feel free to browse over [Binary.com Interview Q1 (Extention)](http://rpubs.com/englianhu/binary-Q1E) or ([Alternate link](http://rpubs.com/englianhu/316133)).
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2) Here I also find the optimal arma order for GARCH models as you can refer to [GARCH模型中的`ARIMA(p,d,q)`参数最优化](http://rpubs.com/englianhu/binary-Q1FiGJRGARCH). [binary.com 面试试题 I - GARCH模型中的`ARCH in Mean`](http://rpubs.com/englianhu/binary-Q1-archm) compares the ARCHM with previous Non-ARCHM models.
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3) You can also refer to [binary.com Interview Question I - Comparison of Univariate GARCH Models](http://rpubs.com/englianhu/binary-Q1Uni-GARCH) which compares the prediction accuracy of 14 GARCH models (not completed) and 9 models (mostly completed from 2013-01-01 to 2017-08-30).
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三）You can also refer to [次元期权面试题一 - 单变量广义自回归条件异方差模型（英）](http://rpubs.com/englianhu/binary-Q1Uni-GARCH)比较了十四个广义自回归条件异方差模型系列（有缺失值，不够工整数据）和过滤后的九个计数/机数模型如下（从阳历二零一三年一月一日至二零一七年八月卅一日，工整数据）的算卜/预测值的精准度。
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- sGARCH
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- fGARCH.GARCH
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- iGARCH
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- csGARCH
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Besides, I wrote a shinyApp which display the real-time price through API. Kindly refer to [Q1App](https://beta.rstudioconnect.com/content/3073/) where [Q1App2](https://beta.rstudioconnect.com/content/3138/) is another app for financial value betting.
In order to started the high-frequency-trading statistical modelling, I inspect the dataset via [binary.com面试试题 I - 单变量数据缺失值管理](http://rpubs.com/englianhu/handle-missing-value) and also [binary.com 面试试题 I - 多变量数据缺失值管理 II](http://rpubs.com/englianhu/handle-multivariate-missing-value) but the univariate modelling caused some statistical error. The papers compares multi-methods like `interpolatan`, `kalman`, `locf` and `ma`. The [binary.com Interview Question I - Interday High Frequency Trading Models Comparison](http://rpubs.com/englianhu/binary-Q1Inter-HFT) compares ts, msts, SARIMA, mcsGARCH, <s>midasr, midas-garch, Levy process</s> models.
Initially, I wrote a shiny app (as showing in below gif file) but it is heavily budden for loading. Kindly browse over [ShinyApp](https://beta.rstudioconnect.com/content/2367/) (Kindly refer to [binary.com Interview Question I - Lasso, Elastic-Net and Ridge Regression](http://rpubs.com/englianhu/binary-Q1L-EN-R) for more information) which contain the questions and answers of 3 questions. For the staking model, I simply forecast the highest and lowest price, and then :
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Secondly, I wrote another app [testRealTimeTransc](https://beta.rstudioconnect.com/content/3775/) trial version to test the real time trading, and a completed version is [Q1App2](https://beta.rstudioconnect.com/content/3138/).
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Due to the paper [Binary.com Interview Q1 - Tick-Data-HiLo For Daily Trading <spanstyle='color:red'>(Blooper)</span>](http://rpubs.com/englianhu/binary-Q1TD) simulated the data and then only noticed I not yet updated the new function, then I wrote **GARCH模型中的`ARIMA(p,d,q)`参数最优化** to compare the accuracy. However my later paper simulated dataset doesn't save the $fit$ in order to retrieve the $\sigma^2$ and VaR values for stop-loss pips when I got the idea. Here I put it as blooper and start **binary-Q1 Multivariate GARCH Models** and later on will write another **FOREX Day Trade Simulation** which will simulate all tick-data but not only HiLo data.
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Due to the paper [Binary.com Interview Q1 - Tick-Data-HiLo For Daily Trading <spanstyle='color:red'>(Blooper)</span>](http://rpubs.com/englianhu/binary-Q1TD) simulated the data and then only noticed I not yet updated the new function, then I wrote **广义自回归条件异方差模型中的`ARIMA(p,d,q)`参数最优化** to compare the accuracy. However my later paper simulated dataset doesn't save the $fit$ in order to retrieve the $\sigma^2$ and VaR values for stop-loss pips when I got the idea. Here I put it as blooper and start **binary-Q1 Multivariate GARCH Models** and later on will write another **FOREX Day Trade Simulation** which will simulate all tick-data but not only HiLo data.
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### 1.3) 闪霓应用
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### 第一题第三章）闪霓应用
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-**shinyApp** : `shiny::runGitHub('englianhu/binary.com-interview-question')` - Application which compare the accuracy of multiple `lasso`, `ridge` and `elastic net` models (blooper).
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-**Q1App** : `shiny::runGitHub('englianhu/binary.com-interview-question', subdir = 'Q1')` - the application gather, calculate and forecast price. Once the user select currency and the forecast day, the system will auto calculate and plot the graph.
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-**testRealTimeTransc** : `shiny::runGitHub('englianhu/binary.com-interview-question', subdir = 'testRealTimeTransc')` - real time trading system which auto gather, calculate the forecast price, and also place orders, as well as settlement and plot P&L everyday.
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-**Q1App2** : `shiny::runGitHub('englianhu/binary.com-interview-question', subdir = 'Q1App2')` - The application contain the Banker and Punter section which applied aboved statistical modelling.
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## 2) 第二题
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## 第二题
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### 2.1) 解答
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### 第二题第一章）解答
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For question 2, I simply write an app, kindly use [Q2App](https://beta.rstudioconnect.com/content/3089/). The bivariate or trivariate poisson model might useful for analyse the probability of fund-in and fund-out by investors in order to manage whole investment pool. Unfortunately there has no such dataset avaiable for fund pool management modelling.
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### 2.2) 闪霓应用
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### 第二题第二章）闪霓应用
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-**Q2** : `shiny::runGitHub('englianhu/binary.com-interview-question', subdir = 'Q2')` - An application which applied queuing theory.
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## 3) 第三题
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## 第三题
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For question 3, due to the question doesn't states we only bet on the matches which overcame a certain edge, therefore I just simply list the scenario. Kindly refer to [Betting strategy](http://rpubs.com/englianhu/317677) for more informtion.
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