Principals of Quantitative Trading

Hi! I'm just a college kid who loves programming and finance trying to teach some quantitative trading to myself. Coming Soon..

1. Strategy Identification - Finding a strategy, exploiting an edge and deciding on trading frequency

• A mean-reverting strategy is one that attempts to exploit the fact that a long-term mean on a "price series" (such as the spread between two correlated assets) exists and that short term deviations from this mean will eventually revert.
• A momentum strategy attempts to exploit both investor psychology and big fund structure by "hitching a ride" on a market trend, which can gather momentum in one direction, and follow the trend until it reverses.
• Low frequency trading (LFT) generally refers to any strategy which holds assets longer than a trading day.
• High frequency trading (HFT) generally refers to a strategy which holds assets intraday.
• Ultra-high frequency trading (UHFT) refers to strategies that hold assets on the order of seconds and milliseconds.

2. Strategy Backtesting - Obtaining data, analysing strategy performance and removing biases

• The goal of backtesting is to provide evidence that the strategy identified via the above process is profitable when applied to both historical and out-of-sample data.
• Once a strategy has been identified, it is necessary to obtain the historical data through which to carry out testing and, perhaps, refinement.
• free data set from Yahoo Finance
• Possible Errors
  - Accuracy: overall quality of the data - whether it contains any errors. It is often necessary to have two or more providers and then check all of their data against each other.
  - Survivorship bias is when it does not contain assets which are no longer trading. In the case of equities this means delisted/bankrupt stocks.
  - Corporate actions include "logistical" activities carried out by the company that usually cause a step-function change in the raw price such as dividends adjustments and stock splits. This should not be included in the calculation of returns of the price.
• The "industry standard" metrics for quantitative strategies are the maximum drawdown and the Sharpe Ratio.
• Maximum drawdon (%): the largest peak-to-trough drop in the account equity curve over a particular time period (usually annual)
• Sharpe Ratio: the average of the excess returns divided by the standard deviation of those excess returns. Excess returns refers to the return of the strategy above a pre-determined benchmark, such as the S&P500 or a 3-month Treasury Bill.
  - Generally, the greater the value of the Sharpe ratio, the more attractive the risk-adjusted return.
  - A high Sharpe ratio is good when compared to similar portfolios or funds with lower returns.

3. Execution System - Linking to a brokerage, automating the trading and minimising transaction costs

• Interface to the brokerage
• Minimisation of transaction costs (including commission, slippage and the spread)
• Divergence of performance of the live system from backtested performance.

4. Risk Management - Optimal capital allocation, "bet size"/Kelly criterion and trading psychology

• It covers nearly everything that could possibly interfere with the trading implementation,
• A common bias is that of loss aversion where a losing position will not be closed out due to the pain of having to realise a loss.
• Recency bias manifests itself when traders put too much emphasis on recent events and not on the longer term.

How I'm going to write my own strategy.

• I've always interested in stock investmentsand have been doing it for more than a year with 15% return, but this is my very first time creating my own strategy.
• I'm gonna be making two different strategies - one for long term investment and one for short term investment, specifically for NKLA.