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 ...

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18
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3answers
5k views

What types of neural networks are most appropriate for trading?

What types of neural networks are most appropriate for forecasting returns? Can neural networks be the basis for a high-frequency trading strategy? Types of neural networks include: Support Vector ...
1
vote
2answers
565 views

How to incorporate fundamental analysis in quantitative trading algorithm? [closed]

I want to write a quantitative stock trading program based on fundamental analysis. It would crunch through prices, financial reports to look for value stocks. It can support backtesting of strategy ...
3
votes
1answer
256 views

Optimal Executions for Minimizing Slippage

There has been a considerable body of work for finding trading strategies that minimize the slippage wrt arrival price. For instance, the following are on of the most well known papers: [1] Robert ...
0
votes
0answers
32 views

measuring the performance of round-trips on stocks

can you provide me with some ideas to assess the profitability of round-trips? That is when I buy 100 shares of IBM at 10\$ and I resell them two days later at 11\$, how can I measure the profit made? ...
0
votes
1answer
608 views

Asset-or-nothing Option Valuation in the Black and Scholes model

In standard Black-Scholes Model, compute the price of an asset-or-nothing put and asset-or-nothing call options. Write down the put-call parity relation between the asset-or-nothing call and put ...
1
vote
0answers
127 views

Calculating index arbitrage

I have a days-worth of level 2 market data. I am calculating S&P500 index arbitrage. I have a few questions about the calculation: 1) Should I be summing all the bids and asks from the stocks ...
5
votes
4answers
1k views

Usage of Random forests in Quantitative analysis of stocks

I have a question about Random forests and how they could be utilized in trading? I heard Random forests are used for classification, is that accurate? If so, could someone give an example of what ...
1
vote
3answers
807 views

How to trade volatility?

I am analyzing the volatility of financial stock returns and let's say I have a pretty good model to forecast tomorrows volatility of the stock returns. So let's say for simplicity reasons I have a ...
7
votes
3answers
1k views

Optimality of Kelly criterion in non-normal environment

It is a not so well known fact that the Kelly criterion is only optimal in a nice and well-behaved Merton-world. It is far from optimal when things are getting non-(log)normal (i.e. more realistic!). ...
1
vote
2answers
952 views

Calculating true value of a stock given the order-book and recent trades

I'm trying to calculate the 'true value' of a stock listed on an exchange. I have access to the limit order-book (containing all bid/ask quotes) and also all trades which have taken place (which ...
3
votes
3answers
1k views

How much capital do I need to create a competitive automated trading strategy?

I'm a relatively small investor, and I'm interested in building my own fully-automated quantitative trading strategy. I also read about dark pools, and how difficult it is to get good prices on ...
0
votes
1answer
180 views

Quantitative finance mentality for success [closed]

I have a strong statistical background (particularly in Time Series analysis) and previously have spent a lot of time modelling sports, Baseball in particular. After reading "Analysis of Financial ...
2
votes
0answers
744 views

What is the best alternative of Quantlib library

We need to build a Fixed Income Portfolio Risk Analytics solution. Somehow due to administrative reason we can't use Quantlib which is written in C++, even call it through SWIG via JNI. We have tried ...
2
votes
2answers
524 views

Index arbitrage with Options when not all underlyings have options listed?

One arbitrage strategy involves looking at the price of the Index Futures price compared with the prices of the options contracts for the underlyings. My question is, can this arbitrage strategy ...
3
votes
1answer
2k views

Seagull option strategy - clear example

It looks like the subject of seagull option strategy is not as clearly explained as for other strategies (butterly, bull,bear spread). Thus, can someone provide a clear example of what you buy and ...
19
votes
6answers
2k views

Most successful investors using academic-based framework?

What are the most famous/best performing absolute-return funds employing approaches based on mainstream finance theory (i.e., theory presented in Journal of Finance, AER, Econometrica, using typically ...
0
votes
0answers
267 views

Fluid dynamics for order book depth modelling

Would someone be able to give me an idea what type of fluid dynamics I could look at for modelling the order book? My background is more signals-related maths (correlation, covariance, fourier etc). ...
34
votes
8answers
13k views

How useful is the genetic algorithm for financial market forecasting?

There is a large body of literature on the "success" of the application of evolutionary algorithms in general, and the genetic algorithm in particular, to the financial markets. However, I feel ...
3
votes
0answers
454 views

How to determine ratios for mean-reverting basket

Suppose I have a basket of 3 securities A, B, and C. I believe that the basket is cointegrated and I want to create a mean-reverting trade. I fit the model: ...
6
votes
5answers
690 views

Indicators and research for stress-based investment strategies

In reference to this paper: Can risk aversion indicators anticipate ļ¬nancial crises? and the investable UBS Risk Adjusted Dynamic Alpha Strategy: ...
2
votes
2answers
1k views

backtesting options strategies in R

I would like to backtest an options strategy in R. I require the ability to delta hedge and rebalance to options in the portfolio at different frequencies (daily, monthly,etc.) What packages are the ...
-2
votes
1answer
363 views

How to test the efficiency of Exponential Moving Averages as a trading startegy? [closed]

I would like to know how I can test the efficiency of Exponential Moving Averages when it comes to forex trading. Can i have any papers that point to the efficiency of this strategy? Thank you. :)
4
votes
0answers
252 views

Quant/Stat Factor Performance Website/Distribution?

Does anyone know of a decent quant/stat factor website, distribution(public or private) or publication that tracks performance of "many" of traditional quant/stat factors? By that I mean would show ...
15
votes
2answers
1k views

From a high frequency point of view, with a price prediction and assuming infinite leverage, how do you determine optimal trade size?

I have read about something like Kelly criterion for long term expectation maximization assuming a fixed starting bankroll. But if one can assume unlimited leverage, and one has a signal for a price ...
3
votes
3answers
2k views

How to distinguish between different types of algorithmic trading

Algorithmic trading involves the use of algorithms to optimally execute trading instructions. Then there are algorithms which initiate trades, based on various quantitative strategies (e.g. pairs ...
10
votes
3answers
764 views

What is the expected return I should use for the momentum strategy in MV optimization framework?

As all research on the momentum strategies are focused on the indicator, i.e. the entry point, there seems not much discussion on its expected return? Though there are some discussions on the exit ...
3
votes
3answers
582 views

portfolio diversification tester

Are there any online tools (optionally with developer API, to spare me the scraping) that given an existing portfolio, calculate how well a new candidate position would score to increase combined ...
0
votes
1answer
460 views

Selecting timeframe for time series analysis

In technical analysis, we may use confluence of direction for 3 timeframes to roughly gauge bias of market now. Similarly, if we use time series forecasting methods to predict(say daily data-whether ...
14
votes
7answers
9k views

Switching from Matlab to Python for Quant Trading and Research

Has anybody else out there made this switch? I'm considering it right now. What were the negatives and positives of the switch?
-4
votes
1answer
552 views

Target daily ROI for a market-making algorithm

I'm designing a market-making algorithm, I was wondering what a decent ROI / day would be to aim for in such a system?
4
votes
2answers
791 views

Cointegration trading: Ignoring pairs that aren't economically related

Cointegration trading question What's the state of the art when it comes to choosing proper subsets of stocks/assets where cointegrating relationships aren't ignored as (likely to be) spurious? For ...
3
votes
1answer
1k views

Understanding Passive Rebate Arbitrage

I was reading a BMO paper which offered the following example of passive rebate arbitrage: "For example, if BBD.b is trading at $4.71 - ...
9
votes
1answer
869 views

What is the Sugihara Trading System?

I recently heard the term Sugihara Trading System. I guess it might be some trading strategy or a special model to predict trends in market data, but I couldn't find out anything about it. Does anyone ...
7
votes
3answers
624 views

Why is random trading minus transaction costs not zero expected value?

Somebody was telling me that if you buy randomly and assuming no transaction costs in todays market place, you wont make money 50% of the time and lose 50% of the time because of adverse selection. Im ...
2
votes
1answer
619 views

Using alpha to evaluate trading strategy

I have a trading strategy that generates returns $R_{t}$. I want to test the strategy by looking at the alpha: $R_t - R_{f,t} = \alpha + \beta (R_{m,t} - R_{f,t}) + e_t$ I compare my alpha against ...
5
votes
1answer
749 views

Statistical significance of trading systems that use indicators with long lookbacks

Let's say we have a trading system that trades daily, holding for one day, but uses an indicator that looks back over the last 5 years. A simple example could be the percent change in price of an ...
1
vote
2answers
559 views

Evaluating forecasting algorithm

I am trying to evaluate a forecasting algorithm for stock price prediction. However, the performance of the algorithm may be very much tied to the trading strategy. Is there a systematic way for ...
1
vote
0answers
78 views

How to trade risk-adjusted returns?

Why does dividing daily returns by daily range eliminates fat tails and results in an (almost) gaussian distribution? And how could that distribution be exploited to enter trades?
1
vote
1answer
260 views

normalized accumulation distribution

I am looking for a way to take an accumulation/distribution indicator and normalize it so I can compare a bunch of stocks with stock prices that have no relationship with each other. EDIT: This ...
5
votes
4answers
2k views

How should I include the bid-ask spread as a transaction cost in a backtest?

I have two backtesting algorithms: One that uses bid and ask prices for signal generation. For example: Buy when $ask < threshold_1 $ and sell when $bid > threshold_2$. Bid and ask prices are ...
1
vote
3answers
2k views

Appropriate method for calculating negative returns on a trading strategy?

I have a cumulative profit/loss time series below for a trading strategy, what is the appropriate way to calculate the returns in percentage for such a series? My issue is the appropriate ...
5
votes
2answers
1k views

How are momentum and reversion long/short strategies dynamically combined in trading?

I'm trying to understand how to combine two strategies dynamically in trading: one mean-reversion and the other momentum. One way (also the simplest one) of doing this is by scaling/normalizing ...
0
votes
0answers
40 views

Inferring Returns From Minimal Data Points [duplicate]

Possible Duplicate: How much data is needed to validate a short-horizon trading strategy? Suppose I have daily returns for a trading strategy against one month of data. Before starting ...
10
votes
1answer
400 views

How does one measure the effect of latency on potential returns?

I am looking to evaluate the hypothetical advantage one trading system has over another in terms of the possible returns given their latency. Irene Aldridge wrote a piece (How Profitable Are ...
-1
votes
1answer
1k views

Can end-to-day trading be profitable? If not, why? [closed]

Many academics argue that end-to-day trading, where you go long or short before opening and sell your security at the end of the day, is not profitable. Various explanations are given for this ...
13
votes
3answers
4k views

What are the best sources for equity quantitative research?

What are the best sources of quantitative finance research in equities? I will list a couple and note an asterisk if the research is available by request (i.e. non-clients) or online: BAC-Merrill ...
-3
votes
1answer
471 views

Trading Strategies and Portfolio Constructions based on Cross Sectional Regression? [closed]

I often see trading strategies and portfolio construction that are based on cross-sectional regression. For example, I often see regressing some numbers against some factors. I was wondering how ...
12
votes
2answers
2k views

statistical arbitrage option overlay strategies / volatility trading

Here's an interesting trading puzzle that I would love to get the community's input on. Let's say there exists an alpha signal that does a good job of sorting equities expected excess returns over ...
17
votes
7answers
7k views

How are cryptography and speech recognition technology applied to forecasting financial markets?

One of the answers to my previous question regarding the strategy of Renaissance Technologies, there was a reference to The Quants: How a New Breed of Math Whizzes Conquered Wall Street and Nearly ...
-4
votes
1answer
636 views