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To find the Dollar Weighted Return, also known as the IRR (Internal Rate of Return) we need to know the cash inflows and outflows for the portfolio. Let's see: At time 0 there is an inflow of 156,000 (purchased 1300 shares at 120) At time 5 the stock price is 188.90 (=245,570/1300) and there is an inflow of 22,668 (=120*188.90) At time 10 we own ...

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The general explanations quoted by @AK88 are the economic reasons why one observes skew in FX option markets (along with most others). The reason FX has symmetric smiles rather than a consistent pattern of one-sided "smirks" is because any FX price is really a ratio. To expand on that, note first that (vanilla option) skew is basically about the terminal ...

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The first thing to make sure that you have at the front of your mind are the assumptions of the Black-Scholes model, especially lognormal distribution behavior. Meaning that, if the underlying security does have a lognormal distribution, then options are correctly priced using the same volatility at every strike for a given expiry. However, if the ...

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I think Hull does a pretty good job explaining the smile in FX options: In the mid-1980s, a few traders knew about the heavy tails of foreign exchange probability distributions. Everyone else thought that the lognormal assumption of Black–Scholes–Merton was reasonable. The few traders who were well informed followed the strategy we have described [...

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Statmetrics (www.statmetrics.org) is a free Android app for portfolio analytics and supports backtesting for multiple portfolios und calculation of portfolio risk and performance metrics (Sharp Ratio, Maximum Drawdown, Value-at-Risk, Alpha, Beta, etc.).

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You'd use MC-weight calculated on 1/31 applied to the return for Feb (1/31 - 2/28) as these are the weights you'd have at portfolio inception. Ideally, you'd update this throughout the period (as, obviously, composition of portfolio will change with security and portfolio return) and apply each of these to trailing return in a similar manner (either using ...

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VIX futures doesn't always inversely correlated to stock returns. A better approach I can think of is to short stock index futures or index ETF for hedging.

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You can find the complete list on the old NASDAQ website. https://old.nasdaq.com/screening/company-list.aspx

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In principal, nothing stops you from doing both, constructing equally weighted and value weighted portfolios and see how the results differ :) In principal, I'd advice to use value weighted portfolios though. As you say, size can have a significant influence on the cross section of stocks. Look at the RFS paper from Lu Zhang et al. (2018) which tests many ...

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The question is not tricky, FRM just makes it unnecessarily complicated. The answer and hopefully understanding follows from the following steps. Let's assume for simplicity but without loss of generality that risk-free rate is 0. Key idea: under the risk-neutral measure, no matter the shape of the risk-neutral measure, the expected value of the asset is ...

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Yahoo and Google finance have been progressively restricting API access (impacting most bulk-download apps) and forcing users to go directly to their sites which only offer end-of-day data. It is hard to find decent sources of historical intraday data, FirstRateData has some good datasets for 10 years of 1-minute data for most US tickers. If you need tick-...

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I guess the concept you're looking for are martingales. These are stochastic processes which remain on their current level (in expectation!). Ignoring some technical conditions, a stochastic process $(X_t)$ is called a martingale if for all time points $t\geq s$, $$\mathbb{E}[X_t|\mathcal{F}_s]=X_s.$$ Here, $(\mathcal{F}_s)$ refers to a filtration, the ...

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Without detracting from or disagreeing with the many great answers already given, this one is more of an "information systems management" than a "risk model" problem. It's a classic "should I bespoke, outsource, or off-the-shelf?" dilemma. So then the question becomes whether and/or how the risk you want to model differs from that of the modal/median ...

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I can see the following main reasons to create custom risk-models: Universe/Vendor model mismatch: Your universe of assets does not align with those provided by the vendor. For example, Barra provides US and Global models but say your universe has a number of Canadian and US equities then you may need a custom risk model. You want to use a new/different ...

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Nope, you pays your good money to Russell for that one. Else you can find an ETF that does physical replication (eg IWM); and get ready for a LOT of copy-pasting... assuming they are 100% replicated name-by-name all of the time! Your question harks back to something that has bothered me with the Russell for a while. I've told about what "consensus" ...

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Google "MIT a bug's life gambler's ruin" for an exact model for this, albeit in a binomial world. The bug flips a coin every iteration to move left or right; and it might then end up falling off the left cliff or the right one. Which is a perfect metaphor for this challenge. https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-042j-...

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It's market cap based, so if you have market cap data, you should be able to get a pretty good estimate yourself.

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If $H > L$, I can't believe $p_H$ is greater than $p_L$. If we put it in terms of TakeProfit (TP) and StopLoss (SL) concerning the FOREX market, if TP is 20 pips and SL is 10 pips, it will be more likely to hit the ST first than the TP. This is why I suspect the correct equations are $p_H = L/(L+H)$ and $p_L = H/(L+H)$. And now it's time to dive into "S. ...

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If not available via a CSV or other download on the website, you're probably out of luck. Data licensing is obviously the main way they make money after all. You might try MSCI or other providers if you're not married to Russell.

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The rise in yields were not a cause of the crash. Global equity valuations were very high leading up to the crash against a solid macroeconomic backdrop in the years preceding. Eventually, growth began to fade and optimism did as well, feeding into the financial channels leading up to black Monday.

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Another great API is this one : https://www.alphavantage.co/#page-top You can use the API key after having registered and fetch valuable data on equity tickers. There is a comprehensive documentation on the alphavantage's website which will definitely help. I post this url as well, which describes thoroughly the process for a beginner: https://medium....

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You've got the usual suspects. I'd add in Worldscope, now owned by Refinitiv.

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The problem: you do not know the correct ticker that Alpha Vantage can take. The solution: Use the search endpoint to find the ticker. Let's say we want to find the correct ticker for Tsingtao Brewery listed in Hong Kong and Shanghai: Search for the ticker: https://www.alphavantage.co/query?function=SYMBOL_SEARCH&keywords=tsingtao+brewery&apikey=...

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In my opinion the simple answer is supply and demand but this would assume we are rational and never buy when it's too expensive or sell when it's too cheap. Investors, Speculators, all types of different agents have motives to buy and sell the way they do. i'll try to explain it intuitively: People expect a stock to become more valuable in the future and ...

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Let's say the risk free rate is greater than zero. But the argument below can be reversed in the case when risk free rate is negative (as is the case these days): If there is someone silly enough to want to buy a stock at a price of $S_0$ at $t=0$ and then sell it again at time $T>0$ at the same price of $S_0$, then that person is giving money away for ...

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