Questions tagged [quant-trading-strategies]

Quantitative trading strategies use quantitative signals and a set of predefined systematic rules to make trading decisions. Strategies operate within parameters based on historical analysis (backtesting) and real world market studies (forward testing). Strategies may be executed manually (by a human trader) or automatically (by a computer).

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30 views

How to Manage Large Orders

Forgive me for any violations of posting rules, I’m new to this forum. I’ve written an algorithm that checks the order book for the price point that would completely fill my entire available balance, ...
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How does Intrinsic and Time Premium factor into deep ITM options for leveraged securities

So I'm curious about the downside risk on this trade. Some backstory - I noticed the options chain for TZA had basically no volume or open interest for deep ITM calls about a week ago while also ...
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Which exact interest rate should I use for valuing equity index futures (ie. SPX, MXEA)?

I'm trying to build a model that values futures for equity indicies like SPX. For example, this product link here. I know that the model is simple (please correct me if I'm wrong): $$ S_{T} =S_{0}e^{(...
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34 views

Leakage and bias in XGBoost trading strategy

I apologize for my persistence, i'm on a course of study and doubts increase every day. My goal is "just" to code a profitable forex trading strategy with machine learning. I'm trying to ...
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61 views

Corwin-Schultz estimator of bid-ask spread

I am reading a paper "A Simple Way to Estimate Bid-Ask Spreads from Daily High and Low Prices" cf.A Simple Way to Estimate Bid-Ask Spreads from Daily High and Low Prices The authors proposed ...
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105 views

How is the total return of an alpha strategy being calculated during backtesting?

I am using a quant simulation platform and I have chosen a formulaic alpha to be used. Now the platform is backtesting and displaying the total return of the alpha strategy over 12 years. The trading ...
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3answers
133 views

Backtesting Period Effect

I am backtesting a stock trading strategy. I tested it over two time periods: 2000-2020 and 2015-2020 and compared the results against a buy and hold strategy. To be clear, I only changed backtesting ...
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1answer
102 views

Optimize Bollinger Bands Strategy

I was proving a very simple strategy with Bollinger Bands for a intraday timeframe (1 minute) that buy on lower band and sell in a higher band (Very common strategy), but in backtesting in E-Mini SP ...
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86 views

Machine Learning model forecasting on real time data in python

I’m building a Forex trading system based on machine learning with Python and brokers API. I get price time series data + fundamental data and then i train the model on that. Model means SVM, RF, ...
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90 views

Sharpe Ratio Graphed Over Time

I looked and could not find a suitable answer to my question already, so: What is the best way to calculate the Sharpe Ratio over time, given I have about a decade's worth of 1-minute candlesticks? I ...
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136 views

Factor investing and PCA

I'm struggling to understand how Principal Component Analysis (PCA) is used in Factor Models of returns. For example, in the JPMorgan paper (p.19) the authors write: In a multi asset portfolio, factor ...
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70 views

Quantifying Bollinger Band squeeze

I'm interested in experimenting with Bollinger Band squeezes to see if a strategy can come of it. A simple definition is a narrowing of the bands like the example below. Really, only the standard ...
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55 views

What's the intuition behind factor grouping?

From the book "Finding Alpha", written by a popular quant fund WorldQuant, explains many techniques about quantitative investing but intentionally omits many of the caveats and applications ...
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73 views

Ideas for calculating Accumulation/distribution and buying selling/pressure

With tick level data I'm trying to understand the day's action: Whether the stock was being accumulated or distributed during the day and The buying and Selling pressure throughout the day The first ...
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105 views

Is there a framework to study quantitative model robustness/uncertainty?

Can you point me to any resources about a possible framework to analyse and possibly quantify model uncertainty and -robustness associated with quantitative investment models? As an example, there ...
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105 views

Machine learning algorithms that generate trading models (literature)?

Is there any academic literature on machine learning algorithms that are able to generate functioning trading models? Would this even be feasible at all, now or in the future? Could you point me to ...
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104 views

Can I use the Sharpe Ratio as an objective function in algorithmic trading?

I’m experimenting with custom loss functions for different trading rules and have come across a few articles citing success in directly using the (negative) Sharpe Ratio as a loss function, ...
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243 views

What is “signal” in quant investing?

Can somebody explain (and give examples) of "signals" in quant investing? What are those? What does this word mean?
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172 views

Are momentum returns negatively skewed?

In the academic literature, I found that momentum returns are negatively skewed (e.g. Daniel and Moskowitz, 2002). As far as I understand, this usually happens when the "past losers" rebound ...
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40 views

Hedging costs and BS-price

I'm looking at the chapter, "The Greek Letters" in Hull's book (Options and derivatives...) and in particular the paragraph "Dynamic Aspects of Delta Hedging". He demonstrates two ...
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2answers
124 views

What kind of returns should I use for my model?

I'm building a machine learning model with the aim of learning a daily strategy of buy or sell the stock. I was wondering if I should use adjusted close price or something else to calculate returns (I ...
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69 views

Any books on systematic investing in credit securitized products (RMBS, CLO)?

I'm looking for books/research papers that would have information on systematic strategies used in the Credit Securitized products space (specifically RMBS, CLO, etc.), if there are any? I've been ...
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31 views

Combining multiple securities' Net Asset Value time-series into one total NAV series

I have a number of individual securities that each have a Net Asset Value (NAV) time-series. For example: ...
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1answer
137 views

Continuous Percentage Profit and Loss calculation

I need to calculate a profit and loss for an equity timeseries. The position size (column D in the below table) is not binary (not moving from zero position to a position and then back to zero ...
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1answer
59 views

How to combine different strategies in a backtest (and IRL)

I am trying to combine long and short strategies into an L/S strategy in my backtesting program. The way I have my backtester set up is it takes a signals object (...
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1answer
160 views

Can alpha be positive if cumulative returns underperform the benchmark?

According to my portfolio analysis program (pyfolio), the alpha of the following strategy is .17 (I am assuming 17%). [Based on pyfolio documentation, alpha here is the "annualized alpha".] ...
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110 views

Machine learning - assigning a value to each tradable moment

I've been looking at machine learning trading strategies for some time and realized recently that I've been neglecting a very important part of the equation in terms of training an effective model. In ...
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84 views

Forex trailing stops - better alternatives?

I've been pursuing the holy grail of trading, short term FX trading, using machine learning. I've experimented with a ton of strategies but mainly those revolving around holding each trade for a ...
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127 views

Has anyone done the course STATS242: Algorithmic Trading and Quantitative Strategies. Where Can I find the assignments and other resources? [closed]

Basically the title. There's a course STATS 242: Algorithmic Trading and Quantitative Strategies offered in Stanford a few years ago. I searched on google a bit for the course website to see the ...
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27 views

Harvesting Bond Term Premium and Roll Yield using curve plays with Oanda Continuous Contracts

Oanda has their own product pricing and method of rollover that stitches the futures contract prices. I was trying to implement a strategy that accesses the bond term premium and roll over yield for ...
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32 views

Extreme and rare events affecting the market

There are extreme events affecting the high-probability [short-term] market such as lowering interest rates that rocket stock prices, even though such events are rare and the market's response can be ...
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84 views

Is there a scientific significance to Fibonacci numbers in economics?

I am new to the field and have read popular articles on Fibonacci numbers, but I did not find it grounded in academic research and would love to know if there is a research basis for this and whether ...
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1answer
94 views

Predict Log Stock Return Direction and Trading Strategy

The $k$ period log return is defined as $$r_{t}(k)=log(S_{t}/S_{t-k}),$$ Where $S_{t}$ is the stock closing price at time $t$. For argument sake, assume that by time I mean a stock trading day and ...
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2answers
188 views

Decode stock market data from C++

As practice, I have been wanting to parse exchange data and try to build an order book algorithm on my own. I found some sample data from NYSE: ftp://ftp.nyse.com/Real%20Time%20Data%20Samples/NYSE%...
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32 views

Multivariate combinatorial purged cross-validation

Combinatorial purged cross-validation (CPCV) is a technique for backtesting strategies while purging and embargoing observations in a time series. CPCV improves upon classical k-fold and walk-forward ...
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147 views

How do you formulate trading ideas and strategies?

I have access to some tick data and Bloomberg data. Outside of data mining and hoping to find an economic rationale after the fact, what do you usually do to generate ideas before you look at the ...
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49 views

The discontinuity when applying the combinatorial purged cross-validation

In Marcos Lopez de Prado's book, Advances in financial machine learning, he recommends using the combinatorial purged cross-validation(CPCV) for backtesting. His motivation is sensible. Through the ...
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1answer
205 views

Backtesting with Level 2 depth of book

I'm new to automated trading. I'm in the process of coding the methodology I've been using manually for a few weeks into a quantitative algorithm using IBKR and Python. I read everywhere I should ...
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53 views

Looking for references on reinforcement learning in finance

I plan on using reinforcement learning for a research project. To be specific, I plan to define learning environments using market microstructure models whose solutions are well known and see if I can ...
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1answer
103 views

Why would the market systematically underestimate the probability of unlikely events?

(I'm not in finance, so pardon my ignorance) In The Big Short (2015), there is a little story about Cornwall Capital's early trading strategy: Their strategy was simple and brilliant. Jamie and ...
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2answers
226 views

Would C++'s speed over Python make it a more applicable language for scalping arbitrage opportunities?

I am using the Bittrex exchange API to ping markets to poll whether there are triangular arbitrage opportunities available for USD/BTC/LTC/USD. Note that I am not trading but rather synthesising them ...
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1answer
88 views

What market conditions are attributable to prolonged instances of triangular arbitrage opportunities?

I am investigating the potential for intra-exchange triangular arbitrage opportunities for the Cryptocurrency market. I believe that due its immaturity, relatively low volume and high volatility that ...
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1answer
104 views

How can I combine traditional trading patterns and machine learning algorithms to produce a trading system?

Traditionally, retail traders have leveraged on price patterns discovered by applying graphical tools such as flags, fractals, pennants, heads, shoulders, etc. However, while this method has been ...
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70 views

What are the best metrics to evaluate an ML algo backtest, other than the nominal returns?

I have designed an algorithm that uses Support Vector Machines to classify the next day's price movement for several prominent cryptocurrencies on a ...
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1answer
206 views

How to propertly change time horizon in Avellaneda-Stoikov model?

I'm working in the Avellaneda-Stoikov implementation using Python. My implementation reproduces the authors' results, but I don't know how to properly adapt the algorithm in order to consider a larger ...
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4answers
2k views

Algorithmic Trading: Python vs SQL

I am new to algo trading. But I have bit of coding experience in SQL. Now I am planning to develop a Algorithmic Trading system. In here I am storing all the historical data in Database (PostgreSQL DB)...
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1answer
60 views

Hedge ratio with future contract [closed]

I want to buy some stocks and short future contract instead. I wonder whether I can calculate the hedge ratio?
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81 views

How to monetize ability to predict small stock movements smaller than spread?

For a relatively small subset of stock symbols I have been able to build a model that is able to 20-100 times per day consistently predict whether a stock is going up within the next 2 minutes, being ...
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3answers
430 views

Basics of trading strategy development

I am Computer engineer and I know programming in python, go-lang, C++, I am interested in trading, I know how to make system to get data, send orders, back-test, fault-tolerance system, etc I have ...
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71 views

USING HIDDEN MARKOV MODEL TO DETECT MARKET REGIMES IN R

How can I use a hidden Markov model to detect different regimes within AAPL's returns using the R programming language . If anyone can point me to any papers or links which can help me out that would ...

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