A Discounted View

“A trade is nothing more and nothing less than a datum point in a series of data points subject to probability theory” – Peter Brandt Conducting post trade analysis is imperative for understanding the actual trading results of a system. Using a simple quadrant can help categorize trades in order to glean information on yourself as a trader which will help eliminate flaws. Every trade can be categorized in one of four quadrants as follows.  First, “good trade, good result” implies that a trade was taken based on a pre-defined trading signal in your business plan and resulted in a profit.  These trades will create the right side of the return distribution.  Second, “good trade, bad result” occurs when a trader takes a pre-determined trading signal but is stopped out at a loss.  For particular strategies, like Trend Following, these trades will make up the bulk of a return distribution but the losses (even in aggregate) are minimal when compared to the total value of the gains. When

Despite the title of this post, the curious development of animal anatomy will not be the topic of discussion. Instead, readers will have an opportunity to observe a potential reversal move underway in equity markets and crude oil delineated by this distinctive price action. No trend can last indefinitely and being able to spot signs of a reversal will help a trader better manage a position. One such method is identification of price action through what Dr. Alexander Elder describes as Kangaroo Tails. This sort of price behavior has a unique pattern. Elder states, “A Kangaroo Tail consists of a single, very tall bar, flanked by two regular bars, that protrudes from a tight weave of prices” (How to Trade for a Living, 65). Kangaroo tails that close down indicate a potential market top whereas when it closes up a possible reversal higher is developing. As with most patterns, price action on a long term basis usually carries more weight as it represents a general shift in the market

In trading, controlling the risk in a portfolio is determined by position sizing.  Most trading firms employ a fixed fractional contract position sizing method.  Under this methodology, positions are determined using the following formula: Fixed fractional bet sizing: Amount risked per trade = closing equity * fixed percentage risked per trade (e.g. 25bps) Once the Fixed-Fractional Contract Position Sizing Formula has been used to calculate the amount of risk to put on with a trade (in dollar terms), the Risk-Basis Position Sizing method is employed to determine how many shares or contracts of an instrument to buy or sell.  The Risk-Basis Position Sizing method considers the risk for each security, where risk per share is the entry price minus the stop-loss point.  It divides the total risk allowance (e.g. 25bps in dollar terms) by the risk per share to determine the number of shares to trade.  Legendary systems and Trend Following trader Ed Seykota offers the following insi

Alexander Elder lays out the background and blueprint for the Triple Screen Trading System (Triple Screen) in his book The New Trading for a Living. Elder has been using this system since 1985 with a few minor adjustments along the way. However, the basic premise remains. He states that the Triple Screen makes “trading decisions using a sequence of timeframes and indicators” (The New Trading for a Living, pg. 154). Specifically, there are three screens applied to each trade and only the best trading opportunities pass these tests. In practice, Triple Screen uses trend-following indicators on longer term charts while the intermediate and short-term charts use oscillators for analysis. Trend-following indicators work well for identifying the existence of a trend, but fall short during a range bound market. Conversely, oscillators demarcate overbought and oversold levels which are useful in a trendless market, but will be consistently overbought or oversold when a trend is emerging. As s

In Mebane Faber’s paper, “Quantitative Approach to Tactical Asset Allocation,” he builds a quantitative market-timing model that employs a trend-following strategy with built-in risk management. Specifically, he utilizes a moving-average-based trading system which is the most commonly used trend-following method. The system rules are simple and are as follows: Buy Rule: Buy when monthly closing price > 10-month Simple Moving Average (SMA) Sell Rule: Sell and move to cash when monthly closing price is < 10-month SMA At most, this system will rebalance monthly if a market is range-bound. However, when using the 10-month SMA (near equivalent to the 200-day SMA) as a trading signal, systems generally have a propensity for less turnover than other actively managed strategies. The converse, and one basis for comparison, of an actively managed strategy is a passively managed system. Faber’s research compares the model against a buy-and-hold (i.e. long) allocation to the S&a

After the August 2015 sell-off the broad-based indexes found support and pivoted higher before month-end. However, by the latter half of September 2015 more selling pressure came into the market pushing the price of the S&P 500 Index (SPX) down to a near retest of its August 2015 lows while moving the value of the Russell 2000 Index (RUT) to new lows.  Even though the price action of these two indexes differed, the behavior of each respective Moving Average Convergence Divergence (MACD) Indicator was the same. Specifically, both MACD’s formed a higher low in late September 2015 after the August 2015 low was formed. Given the aforementioned similarities, MACD conveyed a powerful underlying message. In the case of RUT we observe that divergence formed between the lows of the price and the lows of the MACD lines. That is, as RUT formed a lower-low by the end of September 2015 its MACD was making a higher-low which is indicative of future price strength. MACD is categorized as a tren