{"id":28092,"date":"2021-01-04T08:17:15","date_gmt":"2021-01-03T23:17:15","guid":{"rendered":"https:\/\/smallake.kr\/?p=28092"},"modified":"2021-01-04T10:56:35","modified_gmt":"2021-01-04T01:56:35","slug":"%ed%8a%b8%eb%a0%88%ec%9d%b4%eb%94%a9%ea%b3%bc-%ea%b4%80%eb%a0%a8%ed%95%9c-2020%eb%85%84-%eb%85%bc%eb%ac%b8%eb%93%a4","status":"publish","type":"post","link":"https:\/\/smallake.kr\/?p=28092","title":{"rendered":"\ud2b8\ub808\uc774\ub529\uacfc \uad00\ub828\ud55c 2020\ub144 \ub17c\ubb38\ub4e4…"},"content":{"rendered":"

1.
\n2021\ub144\uc758 \uc2dc\uc791\uc785\ub2c8\ub2e4. \uc62c\ud574 \uc5b4\ub5a4 \uc0ac\uac74\ub4e4\uc774 \uc790\ubcf8\uc2dc\uc7a5\uc744 \ucc44\uc6b8\uae4c\uc694? \ud754\ud788 \ud558\ub294 \ub9d0\ucc98\ub7fc \ub2e4\uc0ac\ub2e4\ub09c\ud560 \ub4ef \ud569\ub2c8\ub2e4. \uadf8\ub7fc\uc5d0\ub3c4 \ubd88\uace0\ud558\uc5ec \uc9c0\ub09c \uc2ed\uc5ec\ub144\uac04 \uc774\uc5b4\uc9c4 \ud750\ub984\uc774 \ubc14\ub00c\uc9c0 \uc54a\uc744 \ub4ef \ud569\ub2c8\ub2e4. \uae30\uacc4\uc640 \uc54c\uace0\ub9ac\uc998\uc744 \uc774\uc6a9\ud55c \ub9e4\ub9e4…<\/p>\n

\uac1c\uc778\uc801\uc73c\ub85c \ubcf4\uba74 2010\ub144 HFT\uac00 \uc2dc\uc791\uc73c\ub85c \ubcf4\uc785\ub2c8\ub2e4. \uac1c\uc778\ud22c\uc790\uc790 – \ubb3c\ub860 \ub113\uc740 \uc758\ubbf8\uc758 \uac1c\uc778\uc785\ub2c8\ub2e4 – \ub4e4\uc774 \ub17c\ubb38\uc744 \uc77d\uace0 \ubd84\uc11d\ud558\uace0 \ud504\ub85c\uadf8\ub798\ubc0d\ud558\uba74\uc11c \ub9e4\ub9e4\ub97c \ud558\uae30 \uc2dc\uc791\ud558\uc600\uc2b5\ub2c8\ub2e4. \uc99d\uad8c\uc0ac\uac00 \uc81c\uacf5\ud558\ub294 \ub370\uc774\ud0c0\uc5d0\uc11c \ubc97\uc5b4\ub098\uc11c \ub098\ub9cc\uc758 \ub370\uc774\ud0c0\uc640 \ub098\ub9cc\uc758 \ubc29\ubc95\uc744 \ucc3e\uae30 \uc2dc\uc791\ud558\uc600\uc2b5\ub2c8\ub2e4. \uadf8\ub9ac\uace0 \uae08\uc735\uacf5\ud559\uc744 \uccb4\uacc4\uc801\uc73c\ub85c \uacf5\ubd80\ud558\ub294 \ubd84\ub4e4\uc774 \ub298\uc5b4\ub0ac\uace0 \uad00\ub828\ud55c \uacfc\uc815\ub3c4 \ub9ce\uc544\uc84c\uc2b5\ub2c8\ub2e4. \uc81c\uac00 \uc624\ub798 \uc804\uc5d0 \uae30\ud68d\ud588\ub358 “\uc54c\uace0\ub9ac\uc998\ud2b8\ub808\uc774\ub529\uad50\uc721”\ub3c4 \uadf8 \uc911 \ud558\ub098\uc785\ub2c8\ub2e4. \ucd5c\uadfc\uc758 \ubaa8\uc2b5\uc744 \ubcf4\uba74 \uc774\uc804\ubcf4\ub2e4 \ub354 \uae4a\uc5b4\uc9c0\uace0 \ub354 \ub113\uc5b4\uc9c4 \ub4ef \ud569\ub2c8\ub2e4. \uba87 \uac00\uc9c0 \uc774\uc720\uac00 \uc788\uc744 \ub4ef \ud569\ub2c8\ub2e4.<\/p>\n

\uccab\uc9f8\ub294 \ub9e4\ub9e4\uc640 \uad00\ub828\ud55c \ub17c\ubb38\uc5d0 \uc811\uadfc\ud558\uae30 \uc26c\uc6cc\uc84c\uc2b5\ub2c8\ub2e4. SSRN\uacfc \uac19\uc740 \uc0ac\uc774\ud2b8\ub4e4\uc774\ub098 \ub17c\ubb38\uc744 \uc18c\uac1c\ud558\ub294 \uae00\ub4e4\uc774 \ub298\uc5c8\uae30\ub54c\ubb38\uc785\ub2c8\ub2e4. \ubb3c\ub860 \ub17c\ubb38\uc744 \uc775\ud788\uace0 \ub0b4 \uac83\uc73c\ub85c \ub9cc\ub4e4 \ub2a5\ub825\uc790\ub4e4\uc774 \ub9ce\uc544\uc9c4 \ub4ef \ud569\ub2c8\ub2e4.
\n\ub458\uc9f8\ub294 Python\uc774\ub098 R\uacfc \uac19\uc740 \uc5b8\uc5b4\uac00 \ubcf4\ud3b8\ud654\ud558\uc600\uc2b5\ub2c8\ub2e4. \ub17c\ubb38\uc744 \ucf54\ub4dc\ud654\ud558\uc5ec \ubd84\uc11d\ud558\uac70\ub098 \uc790\uc2e0\uc758 \uc804\ub7b5\ubaa8\ud615\uc744 \ucf54\ub4dc\ud654\ud558\uc5ec \uacf5\uac1c\ud558\ub294 \uacf3\ub4e4\ub54c\ubb38\uc785\ub2c8\ub2e4.<\/p>\n

\uccab\uc9f8\uc640 \uad00\ub828\ud55c \uc815\ubcf4\ub97c \uc81c\uacf5\ud558\ub294 \uc218\ub9ce\uc740 \uacf3\uc774 \uc788\uc2b5\ub2c8\ub2e4. Open Access\ub97c \uc9c0\ud5a5\ud558\ub294 Arxiv\ub97c \uc774\uc6a9\ud558\uba74 \ucda9\ubd84\ud788 \uc811\uadfc\uac00\ub2a5\ud558\uc9c0\ub9cc \ub108\ubb34 \ub9ce\uc740 \ub17c\ubb38\uc774\ub77c \ud558\ub098\ud558\ub098 \uc0b4\ud3b4\ubcf4\uae30 \ud798\ub4ed\ub2c8\ub2e4. \uc81c\uac00 \uac00\ub054\uc529 \uc0b4\ubcbc\ubcf4\ub294 Quantopia\uac00 \ucd94\ucc9c\ud55c Top Ten Blog Posts on Quantpedia in 2020<\/a>\ucc98\ub7fc 2020\ub144 10\ub300 \ub17c\ubb38\uac19\uc774 \uc5c4\uc120\ud55c \uc815\ubcf4\uac00 \uc88b\uc2b5\ub2c8\ub2e4.<\/p>\n

Nbr. 10:\u00a0What is the Bitcoin\u2019s Risk-Free Interest Rate<\/a>\u00a0\u2013\u00a0<\/strong>cryptocurrency themes are usually popular, so it\u2019s not a surprise, that our analysis of Bitcoin\u2019s risk-free rate made it into the top 10
\nNbr. 9:\u00a0<\/strong>B<\/strong><\/a>acktesting ESG Factor Investing Strategies<\/strong><\/a>\u00a0\u2013 Socially Responsible Investing is more and more popular, so again, no surprise here
\nNbr. 8:\u00a0Trend Breaks in Trend-Following Strategies<\/a><\/strong>\u00a0\u2013 nice paper showing the way how to improve trend-following strategies during unfavourable periods
\nNbr. 7:\u00a0Multi-Asset Skewness Trading Strategy<\/a>\u00a0<\/strong>\u2013 trading strategies based on higher moments of statistical distributions (volatility, skewness, kurtosis) are among our favourite
\nNbr. 6:\u00a0YTD Performance of Crisis-Hedge Strategies<\/a><\/strong>\u00a0\u2013 2020 was a coronavirus crisis year, and a lot of people were interested to see how some of the crisis hedge strategies performed in the middle of the crisis
\nNbr. 5:\u00a0How Do Investment Strategies Perform After Publication<\/a><\/strong>\u00a0\u2013 one of the most common questions we encounter is related to the performance of trading strategies post-publication
\nNbr. 4:\u00a0Trading Index \u2013 TRIN Formula Calculation & Trading Strategy in Python<\/a><\/strong>\u00a0\u2013 a short QuantInsti paper related to TRIN trading indicator
\nNbr. 3:\u00a0Cryptocurrency Volatility Index<\/a><\/strong>\u00a0\u2013 an interesting research paper with a methodology to build \u201cCryptocurrency VIX Index\u201d
\nNbr. 2:\u00a0Hierarchical Risk Parity<\/a><\/strong>\u00a0\u2013 a summary of popular research paper on a risk parity enhancement
\nNbr. 1:\u00a0Working With High-Frequency Tick Data \u2013 Cleaning the Data<\/a><\/strong>\u00a0\u2013 it seems that HFT is and always will be one of the most popular topics<\/p><\/blockquote>\n

Alpha Architect\ub3c4 \uc720\uba85\ud55c \ud68c\uc0ac\uc785\ub2c8\ub2e4.The 2021 Annual Finance Research Geek Fest: Top 5 Most Interesting Papers<\/a><\/p>\n

Forest through the Trees: Building Cross-Sections of Stock Returns:<\/a> I\u2019m still trying to understand what is going on in this paper, but one thing is clear \u2014 their figures\/graphics are incredible!
\nIn Search of the Origins of Financial Fluctuations: The Inelastic Markets Hypothesis<\/a>: Have you ever wondered how fund flows might affect asset prices?
\nWhat Drives the Size and Value Factors?:<\/a> I was convinced that there was nothing left to be said on this topic. I was wrong. Flows matter.
\nDo Women Receive Worse Financial Advice?<\/a> This is a remarkable study that uses undercover agents in Hong Kong. Fascinating.
\nThe Great Divorce Between Investment and Profitability:<\/a> More information on the dynamics and foundations for the profitability factor, which we cover often on this blog.<\/p><\/blockquote>\n

2.
\n \uc880\ub354 \uae08\uc735\uacf5\ud559 \ub17c\ubb38\uc744 \uc798 \uc815\ub9ac\ud574\ub193\uc740 \uacf3\uc740 \uc5c6\uc744\uae4c\uc694? \uc774\ub7f0 \uc758\ubb38\uc5d0 \ub2f5\uc744 \uc18c\uac1c\ud55c \ubd84\uc774 \uacc4\uc2ed\ub2c8\ub2e4. \ud398\uc774\uc2a4\ubd81\uc5d0\uc11c \ubcf4\uc558\uc2b5\ub2c8\ub2e4. <\/p>\n

 <\/p>\n

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\uc62c\ud574 \ub098\uc628 \ud000\ud2b8 \ud398\uc774\ud37c\ub4e4 \uc815\ub9ac. \ud558\ub098\uc529 \uc77d\uc5b4\ubcf4\uc790<\/p>\n

Hyunyul Lee<\/a>\u00a02020\ub144 12\uc6d4 26\uc77c \ud1a0\uc694\uc77c<\/a><\/p><\/blockquote>\n<\/div>\n

Hundreds of quant papers from #QuantLinkADay in 2020<\/a>\ub77c\ub294 \uae00\uc785\ub2c8\ub2e4. Cuemacro\ub294 \uc0dd\uc18c\ud569\ub2c8\ub2e4. \ud68c\uc0ac \uc18c\uac1c\ub97c \ubcf4\ub2c8\uae4c \uc774\ub7f0 \uc9c0\ud5a5\uc744 \uac00\uc9c0\uace0 \uc788\ub124\uc694.<\/p>\n

Seeking the cues in macro markets<\/p><\/blockquote>\n

\uc18c\uac1c\ud55c \ub17c\ubb38\uc911 Trading\uc744 \uc8fc\uc81c\ub85c \ud55c \ub17c\ubb38\ub4e4\uc758 \ubaa9\ub85d\uc785\ub2c8\ub2e4.<\/p>\n

January 2020<\/b><\/p>\n

01-Jan \/ Trading \/ Design of High-Frequency Trading Algorithm Based on Machine Learning<\/a>
\n15-Jan \/ Trading \/ Path-dependent volatility models<\/a>
\n16-Jan \/ Trading \/ A Higher-Order Correct Fast Moving-Average Bootstrap for Dependent Data<\/a>
\n18-Jan \/ Trading \/ Exponential moving average versus moving exponential average<\/a>
\n27-Jan \/ Trading \/ Trading on the Floor after Sweeping the Book<\/a>
\n28-Jan \/ Trading \/ Corporate Governance, Noise Trading and Liquidity of Stocks<\/a><\/p>\n

February 2020<\/b><\/p>\n

09-Feb \/ Trading \/ PCA for Implied Volatility Surfaces<\/a>
\n11-Feb \/ Trading \/ NAPLES;Mining the lead-lag Relationship from Non-synchronous and High-frequency Data<\/a><\/p>\n

March 2020<\/b><\/p>\n

02-Mar \/ Trading \/ SHIFT: A Highly Realistic Financial Market Simulation Platform<\/a>
\n03-Mar \/ Trading \/ G-Learner and GIRL: Goal Based Wealth Management with Reinforcement Learning<\/a>
\n04-Mar \/ Trading \/ Predictive intraday correlations in stable and volatile market environments: Evidence from deep learning<\/a>
\n06-Mar \/ Trading \/ Optimal Signal-Adaptive Trading with Temporary and Transient Price Impact<\/a>
\n18-Mar \/ Trading \/ Optimal market making with persistent order flow<\/a>
\n21-Mar \/ Trading \/ Informed trading, limit order book and implementation shortfall: equilibrium and asymptotics<\/a>
\n22-Mar \/ Trading \/ Application of Deep Q-Network in Portfolio Management<\/a><\/p>\n

April 2020<\/b><\/p>\n

01-Apr \/ Trading \/ Optimal Execution of Foreign Securities: A Double-Execution Problem with Signatures and Machine Learning<\/a>
\n03-Apr \/ Trading \/ Market structure dynamics during COVID-19 outbreak<\/a>
\n12-Apr \/ Trading \/ How to build a cross-impact model from first principles: Theoretical requirements and empirical results<\/a>
\n13-Apr \/ Trading \/ Industrial Forecasting with Exponentially Smoothed Recurrent Neural Networks<\/a>
\n14-Apr \/ Trading \/ Slow-Moving Capital and Execution Costs: Evidence from a Major Trading Glitch<\/a>
\n16-Apr \/ Trading \/ Effects of MiFID II on Stock Price Formation<\/a>
\n18-Apr \/ Trading \/ Financial Markets and News about the Coronavirus<\/a><\/p>\n

May 2020<\/b><\/p>\n

03-May \/ Coding \/ Springer has released 65 Machine Learning and Data books for free<\/a>
\n08-May \/ Trading \/ Investment Factor Timing: Harvesting The Low-Risk Anomaly Using Arti\ufb01cial Neural Networks<\/a><\/p>\n

June 2020<\/b><\/p>\n

20-Jun \/ Trading \/ Learning a functional control for high-frequency finance<\/a><\/p>\n

July 2020<\/b><\/p>\n

19-Jul \/ Trading \/ Price Discovery in Two-Tier Markets<\/a>
\n20-Jul \/ Trading \/ Transaction Costs in Execution Trading<\/a>
\n21-Jul \/ Trading \/ Deep Learning modeling of Limit Order Book: a comparative perspective<\/a><\/p>\n

August 2020<\/b><\/p>\n

05-Aug \/ Trading \/ Investment sizing with deep learning prediction uncertainties for high-frequency Eurodollar futures trading<\/a>
\n08-Aug \/ Trading \/ Insider Trading with Temporary Price Impact<\/a>
\n09-Aug \/ Trading \/ Detecting bearish and bullish markets in financial time series using hierarchical hidden Markov models<\/a>
\n24-Aug \/ Trading \/ Integrating Alternative Data (Also Known as ESG Data) in Investment Decision Making<\/a><\/p>\n

September 2020<\/b><\/p>\n

03-Sep \/ Trading \/ Market-making with reinforcement-learning (SAC)<\/a>
\n04-Sep \/ Trading \/ DeepFolio: Convolutional Neural Networks for Portfolios with Limit Order Book Data<\/a>
\n21-Sep \/ Trading \/ How to build a cross-impact model from first principles: Theoretical requirements and empirical results<\/a>
\n22-Sep \/ Trading \/ Machine Learning for Temporal Data in Finance: Challenges and Opportunities <\/a>
\n24-Sep \/ Trading \/ Optimal Order Execution in Intraday Markets: Minimizing Costs in Trade Trajectories <\/a>
\n29-Sep \/ Trading \/ CoVaR with volatility clustering, heavy tails and non-linear dependence <\/a><\/p>\n

October 2020<\/b><\/p>\n

01-Oct \/ Code library \/ PyTorch Forcasting \u2013 Python library for time series forecasting<\/a>
\n02-Oct \/ Code library \/ FinancePy \u2013 Python based option pricing library (inc FX options)<\/a>
\n10-Oct \/ Trading \/ On Detecting Spoofing Strategies in High Frequency Trading<\/a>
\n12-Oct \/ Trading \/ Qlib: An AI-oriented Quantitative Investment Platform<\/a>
\n13-Oct \/ Trading \/ Tail-risk protection: Machine Learning meets modern Econometrics<\/a>
\n15-Oct \/ Trading \/ Hierarchical PCA and Modeling Asset Correlations<\/a>
\n29-Oct \/ Trading \/ Robust Optimization Approaches for Portfolio Selection: A Computational and Comparative Analysis<\/a>
\n30-Oct \/ Trading \/ Analysis of the Impact of High-Frequency Trading on Artificial Market Liquidity<\/a>
\n31-Oct \/ Trading \/ On the impact of publicly available news and information transfer to financial markets<\/a><\/p>\n

November 2020<\/b><\/p>\n

03-Nov \/ Trading \/ Machine Learning Treasury Yields<\/a>
\n07-Nov \/ Trading \/ Excursion Risk<\/a>
\n14-Nov \/ Trading \/ Greedy Online Classification of Persistent Market States Using Realized Intraday Volatility Features<\/a>
\n21-Nov \/ Trading \/ Gamma Fragility<\/a>
\n25-Nov \/ Trading \/ Price Impact on Term Structure<\/a>
\n26-Nov \/ Trading \/ FinRL: A Deep Reinforcement Learning Library for Automated Stock Trading in Quantitative Finance<\/a>
\n29-Nov \/ Trading \/ Tail Risk and Expectations<\/a><\/p>\n

December 2020<\/b><\/p>\n

01-Dec \/ Trading \/ A False Discovery Rate Approach to Optimal Volatility Forecasting Model Selection<\/a>
\n04-Dec \/ Trading \/ Information and the Arrival Rate of Option Trading Volume<\/a>
\n05-Dec \/ Trading \/ A Frequency-Specific Factorization to Identify Commonalities with an Application to the European Bond Markets<\/a>
\n10-Dec \/ Trading \/ Learning (Not) to Trade: Lindy\u2019s Law in Retail Traders<\/a>
\n11-Dec \/ Trading \/ News Shocks Under Financial Frictions<\/a>
\n12-Dec \/ Trading \/ The Impact of Trustees\u2019 Age and Representation on Strategic Asset Allocations<\/a>
\n16-Dec \/ Trading \/ Deep Portfolio Optimization via Distributional Prediction of Residual Factors<\/a>
\n17-Dec \/ Trading \/ Building Cross-Sectional Systematic Strategies By Learning to Rank<\/a><\/p><\/blockquote>\n

\uc704\uc5d0\uc11c \uc18c\uac1c\ud55c \ub17c\ubb38\ub4e4\uc740 Cuemacro\uc758 \uc124\ub9bd\uc790\uc778 Saeed\uac00 \ud2b8\uc704\ud130\uc5d0 #QuantLinkADay\ub85c \ud574\uc2dc\ud0dc\uadf8\ub97c \ubd99\uc5ec\uc11c \uc18c\uac1c\ud55c \ub17c\ubb38\ub4e4\uc785\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uba74 \uc544\ub798\uc640 \uac19\uc2b5\ub2c8\ub2e4.<\/p>\n

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Redrawing the Map of Global Capital Flows: The Role of Cross-Border Financing and Tax Havens https:\/\/t.co\/vOsleNpWOZ<\/a> #QuantLinkADay<\/a> pic.twitter.com\/NFfGXSHWKY<\/a><\/p>\n

— Saeed (@saeedamenfx) January 3, 2021<\/a><\/p><\/blockquote>\n